In this article, we will discuss the best software development trends to follow in 2024. Staying updated on the latest software development trends allows industry players and developers to maintain a competitive edge and deliver fresh and cutting-edge solutions every time.

The Evolving Landscape of Software Development

An interesting shift happened globally post-pandemic in 2021, during which the IT sector reentered a growth trajectory after having suffered numerous project delays, cutbacks, and retrenchments during the pandemic. The post-pandemic world saw enterprises big and small recognizing the need to adopt a digital culture. After being caught unprepared when the world went into lockdown, businesses now know better than to stick to the old ways in order to keep the lights on, come what may.

Gartner reports that 91% of businesses have now launched digital transformation initiatives, with 87% of more senior business leaders highlighting that digitalization is a top priority for them. Additionally, 89% of companies have also reportedly adopted a digital-first business strategy moving forward. 

In terms of software development, Statista projects that the market is likely to garner revenues reaching $738.96 billion by 2025. Enterprise software is set to dominate the market with a projected market volume of $312.80 billion in 2025, followed by application development software ($193.30 billion), system infrastructure software ($151.20 billion), and productivity software ($81.66 billion).

Statista also predicts that the global software developer population will hit 28.7 million this year. In terms of working arrangements, it appears that 41% of developers have continued to work remotely despite the IT industry prioritizing a return to office culture overall. 

What’s Trending in the Software Development Industry in 2024?

Among the top software industry trends in 2024 are technologies like artificial intelligence, machine learning, and cloud computing. Development, Security, and Operations (DevSecOps) practices, as well as microservices architecture are also among the latest trends in software development.

Overall, the current trends in software development are driven by previous changes in the IT sector. As mentioned, the shift to digital has catalyzed a lot of change within the industry and has since transformed the way software is developed, deployed, and maintained.

Additionally, Agile development methodologies have gained wider acceptance, allowing for shorter development cycles amid hybrid and remote work. Just a decade ago, much of this would not have been possible without the increased collaboration among teams and departments facilitated by modern technology today.

As such, many of these software engineering trends are tied to the drive toward increasingly optimized current workflows, facilitating the shift to digital, and continuing to adopt and develop emerging technologies in software development. 

Let’s take a closer look at some trending technologies in software development.

1. Increased AI and ML Integration

On top of the list of the latest trends in software development is the recent uptick in the adoption and integration of artificial intelligence (AI) and machine learning (ML) across industries. Both technologies are now widely used by software development companies across the globe to enable data-driven decision-making in businesses as well as to build predictive analytics algorithms.

Regardless of business size, we’ve seen a surge in AI and ML integration all the way from small digital marketplaces to tech giants. This integration is projected to stay on a steady growth course in the coming years. AI, in particular, is expected to surpass half a trillion dollars this year. With a CAGR of 38.1% from 2022 to 2030, the AI market is projected to become a $1.87 trillion-dollar industry by 2030.

In addition to ML, among the top AI development software technology trends include:

• Automated Machine Learning: AutoML will be incredibly useful in simplifying incredibly complex data sets across industries
• Generative AI: Data generated by businesses will soon be used to create original content, including videos, images, and sounds
• Natural Language Processing (NLP): NLP is set to enrich communication between algorithms and users with more advanced natural language understanding
• Ethical AI: Designed to bridge the gap in trust between users and technology  by reinforcing cybersecurity measures, boosting confidence in automated systems
• AI-as-a-Service (AIaaS): Companies will begin leveraging cloud-based platforms for a variety of AI services.

2. Application of Blockchain Technology Beyond FinTech

Blockchain technology itself is not new — but this time, tech experts see blockchain disrupting the software development sector in 2024 as it goes beyond fintech.

Businesses from various industries are beginning to understand the usability and value of the technology and are starting to implement it — especially since blockchain offers incredible security thanks to decentralization. 

The rise of decentralized systems in different software development sectors like the media, publishing, supply chain tracking, and healthcare is expected to continue on its trajectory moving forward. This is because blockchain’s decentralized nature makes it transparent, virtually unhackable, and incorruptible.

Developers are continuously finding new ways to create custom software development around blockchain technology, driving the blockchain market toward a CAGR of 58.90% with a projected value of $20 billion by the end of 2024.

3. Increased Investment in Progressive Web Apps

Like blockchain technology, progressive Web Apps (PWAs) are also not new — they’ve been around since their introduction in 2015. However, it is now gaining widespread adoption and acceptance, with a CAGR of 31.9% and a projected market value of up to $10.44 billion by 2027.

It also seems that the tech industry has caught up to PWA technology, especially given the exponential increase in mobile usage over the past decade. PWAs offer an opportunity for website owners to improve their website’s user experience and aesthetics by giving them a more app-like feel.

The development scene is seeing more site owners investing in PWAs. Previously, converting to PWAs wasn’t so common, which is why Pinterest made headlines for converting. Following an analysis of areas that caused poor site performance and retention, Pinterest went through an overhaul by rebuilding the website using React and converting it into a PWA. As a result, the site enjoyed a 40% increase in time spent on the platform and 44% more revenue. This was back in 2017.

4. More Companies are Embracing Low-Code/No-Code Development

It’s no secret that developing software can be a lengthy and tedious process. Low-code and no-code development offer developers a much faster and easier way to create apps with minimum coding, allowing teams to ship in record time.

Gartner has previously projected that companies of all sizes will begin to embrace low-code development, with the adoption rate set to exceed 50% through 2026. Experts suggest that the key drivers that will accelerate the adoption of low-code and no-code development are:

• Increase in the number of business technologists
• Growing levels of enterprise-level hyper automation
• Composable business initiatives

“Organizations are increasingly turning to low-code development technologies to fulfill growing demands for speed application delivery and highly customized automation workflows,” shares Varsha Mehta, Senior Market Research Specialist at Gartner. 

Basically, these development types allow teams to develop apps with a limited budget and much shorter timeframes. Low code platforms function similarly to purpose-built Integrated Development Environments (IDEs) or platforms that are specifically designed to address varying needs and challenges. Some popular low-code platforms include Mendix, Appian, and Visual LANSA.

Some examples of low-code use cases are:

• Leveraging an existing SaaS infrastructure with customized features according to what a specific business needs
• Transitioning to a cloud-based relational database from traditional spreadsheets
• Converting legacy applications into modern versions

5. The Emergence of FinOps and GreenOps

The cloud computing landscape is currently ushering in the emergence of the FinOps and GreenOps movements, counting them among the latest software development trends. Given the fairly recent upheavals with regard to the way things work, more companies are recognizing how important it is to streamline operations and processes across the board.

After the pandemic, no one wants to get caught unprepared to adapt and keep up with customers’ and the market’s changing demands. Businesses are also putting more effort into sustainability while driving savings and efficiency at the core of business efforts.

In a nutshell, FinOps seeks to drive efficiency across various financial processes, whereas GreenOps focuses on implementing eco-friendly practices in line with long-term value creation. By integrating FinOps and GreenOps, businesses can work to increase their bottom line, comply with regulations, support sustainability efforts, and improve their brand reputation.

6. Serverless Computing

Serverless computing, also called Function as a Service (FaaS), allows developers to create applications and services without having to manage infrastructure, leading to better efficiency and cost savings. 

Among the leading providers are Azure Functions, AWS Lambda, and Google Cloud Functions. For example, streaming provider Netflix has started using AWS Lambda for certain functions within the platform. 

Lambda takes care of tasks such as user authentication,  encoding videos, and backend processes. This allows Netflix to scale its resources based on demand without needing to manage servers while providing a smooth user experience and cutting costs.

Spotify, on the other hand, uses Google Cloud Functions to handle tasks such as user authentication, processing user-generated content, and backend tasks for music recommendation algorithms.

7. Greater Reliance on Distributed Computing

Distributed computing is another software development trend that is gaining more popularity in 2024. Distributed computing is a way of data sharing by way of different computer servers connected as a group. 

As such, large volumes of data that may be too much work for just one server can be spread across multiple servers and thus be processed much more quickly. Distributed computing allows applications to scale accordingly by just adding servers as needed. 

Overall, distributed computing improves performance while minimizing costs. Best of all, a system failure in one server will not affect others — allowing for continuity of operations should something arise.

8. Increased Focus on Cybersecurity with DevSecOps

Development + Security + Operations is DevSecOps. In a nutshell, it’s an automation, platform design, and culture approach. It also integrates security as a crucial and shared responsibility throughout the IT lifecycle. 

Many more companies are beefing up their cybersecurity programs with DevSecOps, as it focuses on built-in security over security measures built around data and apps. DevSecOps prioritizes early detection of potential risks and fixing these vulnerabilities before they become more significant issues.

DevSecOps breaks down silos between different teams and puts security at the forefront of all commit and pull requests. Compliance is also of utmost importance in the DevSecOps pipeline, and as such, compliance and security checks are always integrated.

9. Ushering the AR/VR Era

AR and VR are no longer confined to just video games and entertainment. For clarity, whereas AR uses real-life elements supplemented with computer-generated content to create an interactive and dynamic user experience, VR is entirely a virtual, immersive simulation. 

More and more businesses are seeing the value of these technologies in 2024 and are using them to create real-world simulations for customers and stakeholders, as well as interactive training programs for employees. 

For example, large pieces of tech or machinery that cannot realistically be brought into a trade show fair can be rendered via VR or AR, allowing customers and stakeholders to “experience” what it’s like. The same applies to prototypes that may not yet be ready but already have a defined blueprint.

Also, training programs can be enriched with demonstrative and hands-on training through VR and AR, allowing staff to perfect muscle memory without even having to operate the real thing right away (like heavy machinery and other equipment).

10. Microservice Architecture

Microservices architecture in software development refers to a different approach to software development. Microservices focus on creating single-function modules with specifically defined interfaces and operations.

This is in line with Agile and DevOps and has really picked up in recent years. Microservice architecture is small in scale and independent, allowing smaller development teams to write and maintain services much quicker and more efficiently. 

In such an architecture, each layer of service is separated from the codebase, making it easy to manage. This allows developers to update and manage an app or service without needing to rebuild or redeploy the whole thing.

11. AI in Healthcare

AI offers to the medical sector what a Deloitte study revealed to be among the top three goals of AI in healthcare: Improved efficiency, lower costs, and enhanced products and services.

One of the practical ways AI can help support these goals is by developing AI software that can improve symptom analysis through patient data, automatically detect medication errors, and automate administrative tasks overall. 

Venture capitalists have also reportedly invested over $8.5 billion in the top 50 healthcare AI firms, highlighting the current importance of AI in healthcare.

12. NFT Tokens in Cryptocurrency

NFTs, or Non-Fungible Tokens, are digital elements connected to the Blockchain. They are called such because they are non-fungible, meaning that they’re completely unique and not interchangeable. 

No two NFTs are similar, and this concept has pushed it to become a significant trend, especially concerning Blockchain-based payments in recent times. It is already one of the most common payment methods in software development outsourcing, possibly because it allows for fast, secure, reliable, and transparent payment between people. 

NFTs are projected to grow exponentially and reach $211.7 billion by 2030, with a growth rate of 34.2%. NFTs are built on smart contracts or self-executing lines of code, allowing for speedy and secure transactions.

13. React Native Continues to Thrive

The programming React Native has emerged at the top of the hybrid development market. This is because it allows developers to create high-quality cross-platform applications using a single codebase.

This allows teams to work much faster and more efficiently, cementing its status as an important tool for businesses looking to maximize their reach and streamline workflows. 

14. The Switch to 5G Technology

Alongside the rapid 5G rollout — experts predict that over 1.4 billion devices, or 15% of the global total, will be connected to this network by 2025. 

This is because 5G is more efficient than 4G. It is a new network architecture that seeks to redefine how people communicate and connect digitally, leading to enhanced user experiences. The 5G architecture is also expected to accelerate the growth of innovative technologies like the Internet of things and Artificial Intelligence (AI).

15. The Popularity of IoT is on the Rise

The widespread adoption and growth of smart devices calls for more IoT solutions, ushering in an era of more connectivity — allowing people to bridge the gap between the physical and digital. 

According to research, the global IoT market is projected to grow to $650.5 billion by 2026 and at a CAGR of 16.7%. This is because IoT has found several applications due to the rise of related technologies like AI, ML, automation through edge computing, and more.

City governments exhibit another welcome use of IoT solutions — from enhancing security to traffic congestion reduction, the goal is to streamline urban living and optimize city infrastructure with technology. Healthcare IoT gadgets are also facilitating early disease detection, providing people with better chances of recovery and healing.

16. Python Developer Demand Expected to Rise

Machine learning and data science continue to dominate several industries, causing an increased demand for experienced Python app developers. Python is often considered the ultimate Swiss knife of programming languages, as it is capable of performing numerous tasks and handling complex jobs.

Python also continues to remain versatile and relevant. From web design and app development to machine learning models, the programming language allows developers to complete projects efficiently. Among the key areas in which Python may experience an uptick in usage are game development, AI and ML applications, IoT, web and mobile apps, and automation and robotization. 

17. Web 3.0 Continues to Evolve

It is said that Web 3.0 holds the future of the Internet, as it is continuously being propelled by the latest technologies and software development processes. 

The three basic IT architecture tiers of Web 3.0 are:

• Interaction: This refers to the content, hardware, and software that users communicate with
• Computation: This makes up the logic to enable the interaction between users and the above elements
• Information: Refers to the data and structure required for computing functions to be done accurately and efficiently.

Web 3.0 apps are characterized by complexity and interactivity and go a step beyond the static pages we got used to in previous web versions. JavaScript development is used to create Web 3.0 apps, making them both dynamic and responsive. 

Currently, Web 3.0 applications are already available on desktop browsers and some high-end mobile devices like smartphones with OLED panels. However, tech experts anticipated a much higher volume of Web 3.0 apps and compatible devices moving forward.

18. Cloud-Native Technologies Continue to Evolve

Cloud-native technologies and cloud-based architectures allow one to design, construct, and operate cloud-developed workloads, taking full advantage of the cloud computing model. Cloud-native prioritizes agility and better speed, allowing organizations to create strategic solutions that can support their business growth.

In 2024, cloud-native technologies will continue to evolve and increase in usage as cloud-native implementation allows developers to develop and execute scalable applications. Cloud-native apps work across modern and dynamic work environments, such as private, public, and hybrid clouds. This also covers microservices, containers,  immutable infrastructure, service meshes, and declarative APIs.

Additionally, with cloud-native stacks like DevOps and GitOps, developers can easily use continuous innovation and continuous delivery (CI/CD) to test applications while simultaneously pushing new code into production.

By leveraging cloud-native development, organizations can bank on built-in scalability and match any demand profile without investing in added infrastructure design or provisioning. Cloud-native development also allows developers to choose from various tools instead of being limited to in-the-box options.

19. The Advent of IoB (Internet of Behavior)

Personalization is an important driver of success in any business. The more effective your service is, the more your users will adapt their approach to your infrastructure. The Internet of Behavior (IoB) brings to the table important data like user behaviors, interests, and preferences from Big Data,  BI (Business Intelligence), and CDPs. 

Pulling from wearable devices, smart household electrical gadgets, and individual internet activity, IoB reveals valuable information on user behavior and their interests. IoB facilitates easier tracking, merging, and evaluating large volumes of data from various online activities and personal behaviors.

This includes things like social media habits and even commercial transactions. IoB is a little behind IoT in terms of momentum and adaptation. However, as consumers continue to gravitate toward personalization and businesses seek ways to give users a customized (yet still on-brand experience), it is highly likely that IoB will gain greater momentum. 

IoB is already being used by companies and startups. YouTube, for example, has begun to provide viewers with a more customized feed, much like Facebook and other social media platforms. Overall, IoB can help businesses resolve challenges that may hinder them from closing sales and acts much like consumer surveys without needing to expressly ask consumers about their preferences.

20. Edge Computing

Edge computing is called such because it processes data closer to the “edge” of the network or where it’s created—in an effort to greatly reduce latency and bandwidth use. According to research, the global edge computing market is expected to grow at a CAGR of 37.4% by 2027.  Fortune Business Insights projects that the global edge computing market will grow from $15.96 billion in 2023 to $139.58 billion by 2030. 

Edge computing is particularly crucial for IoT devices because they generate huge amounts of data. It can also improve privacy and security as data is kept locally. This is in opposition to centralized cloud platforms, which are not the closest to data sources. 

An increasing number of businesses have started to shift their analytics and decision-making from centralized cloud platforms to the edge.

This trend is largely driven by the observation that data captured at the edge often requires processing, storage, and analysis on-site, and it can’t always be done via cloud-based applications due to cost implications, uptime constraints, and latency issues.

Edge computing is an evolution of on-premise computing. It is technically an IT architecture that processes client data at the network’s edge, closest to the site of capture. By bringing computing closer to such data sources, edge computing is able to reduce latency and enhance real-time data processing capabilities.

Edge computing is particularly useful for applications that require immediate data analysis, such as autonomous vehicles and smart city technologies. In the field of healthcare, edge computing also ensures utmost data privacy and allows for AI-based real-time monitoring and close analysis of the patient’s condition. 

When applied in practice, this technology can transform traffic management by regulating traffic lanes, optimizing bus schedules, and even guiding autonomous vehicle flows.

21. Quantum Computing

The principles of superposition and entanglement are among the most fundamental quantum-mechanical phenomena used in quantum computing for data operations. Quantum computing is an even more advanced form of computing that uses quantum bits (called qubits) instead of classical bits.

The capacity to execute specific calculations much faster than classical computers is one of the primary advantages of quantum computing. As such, it has the potential to greatly revolutionize how machines solve intricate computational tasks, including cryptography, optimization, machine learning, and molecular simulation.

Quantum computing can be particularly useful in sectors like energy, finance, healthcare, and logistics, especially to address computational challenges that may be deemed too complex (even insurmountable) for classical computers. This includes simulating complex system behavior, decryption of cryptographic codes, and optimizing logistics networks that are incredibly large in scale.

That said, the development of quantum computing technology is still in its early stages. Researchers are currently actively engaged in building quantum computers and refining quantum algorithms, as well as software tailored for their operation. Leading companies are currently developing software to make quantum computing more accessible to a wider audience. 

These include tech industry leaders like IBM, Google, Microsoft, D-Wave, and Amazon. IBM is ahead of its peers with Quantum System One and Two, which uses powerful processors of up to 127 qubits. Microsoft, on the other hand, is focusing on topological qubits and integrating them into the already-up Azure cloud platform for wider accessibility.

Conclusion

Current software development trends are driven by the massive shift to digital, as well as the convergence between AI and new technologies that seek to improve our ways of working and living. 

Significant leaps are being made in the field of groundbreaking technologies like the Internet of Things, Internet of Behavior, and Web 3.0, as well as quantum computing — all of which can catalyze even more advancements especially when applied to city traffic, healthcare, finance, and other sectors.

Additionally, technologies that have been around for a while are now finding a firmer footing and are enjoying wider adoption. These include blockchain technology, NFTs, and PWAs, as companies see more use cases and security advantages.

Trusty programming languages like Python and JavaScript remain at the forefront of software development despite these trends. Still, newer ways of doing things — like serverless computing, edge computing, DevSecOps, FinOps, and GreenOps — are coming to the fore as workplaces continue to evolve and create new demands that developers need to address.

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Our team of experienced developers can handle projects of any type and difficulty. From simple web and mobile apps to cloud-based enterprise-level products, we’ll take your vision from the idea board and make it a reality. Get in touch with us today to consult with an expert!

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The game development industry even birthed a new movement known as Creative Coding. While some sources define it solely as creating digital art through code, the gaming world expands this concept significantly. Creative Coding is actively practiced at game development conventions and incorporated into the curriculum of software engineering schools. It represents a unique blend of art, design, and scientific principles. This approach transcends conventional thinking, fostering the creation of extraordinary experiences where the physical and digital realms converge.

Game Dev coders endeavor to bridge the gap between the digital and physical worlds by enriching digital elements with the ability to interact with real-world environments. This allows digital information to become “embodied,” responding to the viewer, dynamically altering the context, and establishing intricate forms of interaction and behavior. Let’s see how AI and its disruptive tech counterparts like VR are currently transforming the gaming industry.

So, What is AI in Gaming?

Artificial intelligence (AI) in games extends beyond the boundaries of traditional interactive experiences. These systems learn about players’ behavior during gameplay, going beyond pre-programmed responses, which allows them to dynamically adapt and provide an optimal gaming experience tailored to each individual.

Role of Artificial Intelligence in the Gaming Industry

The likely reason why AI in the gaming industry strives, particularly in gaming, might be attributed not only to the fact that it is a lucrative market worth billions of dollars. The roots of this interest might stem from the deeply human nature of wanting to gain an advantage in a competitive field to achieve goals. Remember the Game Theory? It is a mathematical study that drives strategic decision-making among individuals and bigger entities like companies or even entire societies. 

Despite the games being traditionally related to entertainment, scientists are working on some serious applications of AI by training their models in the gaming setting. Possible real-world scenarios include military training, education, driving training, medical training, and mental health therapy. 

What’s more, game dev is at the forefront of software development innovation at scale. For instance, IEEE’s annual conference is a platform for presenting research papers. The latest findings are highlighted by the gaming giant EA:

A case study [for automated testing] is Battlefield V, which requires testing of 601 different features amounting to around 0.5M hours of testing if done manually. This corresponds to ~300 work years.

In response to these challenges, researchers are training Reinforcement Learning (RL) and other models, thus striving to rise beyond the limitations of scripted bots (while manual testing becomes increasingly obsolete). Additionally, developers spend thousands of hours on routine tasks like programming characters’ gestures, which could be automated with AI, freeing their time for more interesting tasks.

In this light, integrating AI in gaming and testing appears not just desirable but essential.

How is AI Used in Gaming?

Gaming industry seems to be leading the race in AI creation and evolution. The market has flourished with AI algorithms that are actually working in cloud gaming platforms and scaling on an ongoing basis.

Non-Player Character (NPC) Behavior

Older-generation NPCs are known for their unnatural body language, which results from their lack of responsiveness. AI engineers have figured out multiple ways of enhancing NPC behavior to make games more enjoyable. For example, smart NPCs were implemented in Unreal Engine. According to the original paper behind the research, scientists developed an algorithm based on the use of finite state machines and fuzzy state machines. Finite state machines adjust the NPC behavior based on a set of states (patrolling, chasing, etc.) that are triggered by events (seeing the player, hearing a noise). Fuzzy state machines allow for smooth and nuanced transitions between states based on fuzzy logic (spectrum of variables as opposed to binary logic). Additional models observed in smart NPCs are artificial neural networks that let them learn from experiences and genetic algorithms that let the behaviors evolve over time.

Procedural Content Generation

Machine learning algorithms can generate new levels, items, and quests. This can help keep games fresh and interesting for players, who will always encounter new content. Procedural simply means that developers do not let AIs go haywire while only letting them generate new content based on the predetermined set of rules. This helps them avoid unethical content generation and propagation. Generative adversarial networks work as an improvement mechanism where a generator and a discriminator work “against” each other, which results in more realistic and creative content.

Cheating Detection

AI can be used to detect cheating players. This can help to keep games fair for everyone. They do this by employing anomaly detection to identify and isolate deviating patterns. Supervised machine learning algorithms can be trained on cheating data and non-cheating data so that AI can understand the difference.

Dynamic Difficulty Adjustment

Similar to dynamic online exams where the questions adjust to the learner’s knowledge level, AI in the gaming industry can adjust a game’s difficulty based on a player’s skill level. This can help ensure that the game is challenging enough to keep it interesting, yet at the same time not frustrating. First of all, key metrics to track are identified, and tracking mechanisms are activated. For example, these could be time to complete a level, number of enemies killed, weapons used, etc. Then, the model of the player’s skill level is created. This model can then be used to predict how the player will perform on future tasks and adjust the difficulty accordingly.

Personalized Gaming Experience

Content recommendations that are familiar to us from most of the video and music content apps have also been implemented in cloud gaming. When a user logs into a game, they might be recommended items, heroes, and quests that they are more likely to enjoy. Furthermore, the whole game world can adjust based on the user’s preferences, including the landscape, quests, and AI companions. For example, No Man’s Sky introduced the possibility of creating a whopping 18 quintillion open worlds that are modified based on the player’s experiences.

Enhanced Graphics with AI Upscaling

Cloud gaming lets you play high-end games on devices that wouldn’t normally be powerful enough. However, the data stream from the powerful remote servers can be hefty, requiring good internet bandwidth. Here’s where AI upscaling comes in, offering a win-win situation for both cloud gaming services and players. The remote server renders the game at a lower resolution, reducing the data required for transmission, while the AI model analyzes the incoming lower-resolution image and predicts missing details that would be needed to get a high-resolution experience. Finally, the missing details are generated, and the upscaled imagery is delivered right to your laptop or mobile device.

Major Trends in AI Gaming

Below, we will describe in more detail the key AI trends in the gaming industry.

Generative AI

One of the most ubiquitous, this type of AI in gaming is much more than just text-based chatting. Yes, it can elevate dialogues, but it can also adapt gestures and tone of speech to what the character is saying. This can be used to create more realistic and believable game worlds and characters. When developing open worlds and personalized storylines, game creators rely on generative AI in procedural content generation and speech-to-gesture animation, which frees developers from the overwhelming amount of tedious routine jobs.

AR/VR Technology

This can be used to create more immersive gaming experiences. For example, AR could be used to overlay game elements onto the real world, or VR could be used to create a completely virtual world for players to explore. Technology-wise, hardware quality has skyrocketed over the last few years. Major brands are offering truly immersive experiences with photorealistic image quality, eye motion tracking, body motion tracking, spatial audio, and even sensors that enable tactile sensations and feedback. 

BCI-Enabled Games

Speaking of body signal tracking, some EEG headset manufacturers claim that they implemented neural interfaces for AI in gaming that allow users to play with the power of their minds. Big players like Valve (the owner of Steam) are actively researching the niche, but the progress could be faster. Meanwhile, famous Twitch streamers are trying to play games with their DIY BCI headsets, while critics think it’s a joke because EEG headsets can’t tell meditation state from the hustle of a busy convention space. 

Multiplayer Games

Cloud-based gaming revamped the whole industry, allowing users to play multiple games on a single platform regardless of their device’s processing power. Additionally, it responds to a growing trend of multiplayer games. With an estimated 1.86 billion PC gamers worldwide, the ability to come together in a game is what fuels the industry’s growth. To spice it up a little, developers have something more to offer.

AI Opponents

Smart NPCs are fun, but how about smart opponents? Of course, we are all familiar with playing “against the computer,” which has been historically challenging. However, AI in gaming aims to make this experience more adaptive and exciting. For example, case-based reasoning systems store past experiences and use them to make decisions in new situations. In a game, a case-based reasoning system could be used to allow an AI opponent to learn from its mistakes and adapt its behavior accordingly.

How to Use AI in Game Development?

AI in Game Programming

Sometimes boilerplate code is what you need. If the unit of writing is destined to be reused without any changes to it, then why write it every time by hand? AI can automate the creation of such basic backend code for common functionalities like basic enemy movement or environmental interactions. This frees up developers to focus on more complex backend logic specific to the game.

AI in Game Design

AI in game development is still evolving, but it holds promise for assisting in the development process, not necessarily replacing it entirely. Multiple use cases require continuous optimization and automation. Luckily, AI is specifically good at that kind of stuff.

For example, you want to optimize server performance. You can employ AI algorithms that analyze player behavior and server load to suggest resource allocation and server infrastructure adjustments. This can help maintain smooth gameplay and scalability for a large player base.

Furthermore, AI in gaming can help you monitor server activity and predict potential issues like outages or bottlenecks. This allows developers to take preventative measures and ensure a stable gaming experience.

AI in Game Testing and Debugging

Machine learning algorithms can analyze vast amounts of gameplay data to identify potential bugs and glitches, allowing programmers to address them before release. As discussed above, AI can potentially mitigate the issue of the overwhelming amount of testing scenarios, even in an automated setting.

QA engineers strive to deploy AI that can control virtual testers to explore the game world, identify areas where players might get stuck, and uncover potential balance issues. This reduces the manual effort required for thorough testing.

After AI playtesting, algorithms can employ data-driven analysis to review the collected data and pinpoint problematic areas or unbalanced mechanics, allowing designers to refine the game.

Benefits and Disadvantages of Using AI in Games

AI in gaming offers a double-edged sword. On the bright side, it can create sprawling open worlds, enrich interactions with NPCs, and render stunning visuals. It also proves to be valuable in AI developers’ pipelines, automating simple repetitive tasks and performing QA on massive amounts of gaming material.

However, content generation might need help to rise beyond simple tasks. Procedural content, though vast, can be unpredictable and repetitive. For example, open worlds might offer generic, repetitive patterns, while human characters might have three hands or two heads.

Training AI in game development requires significant computational resources, potentially increasing gaming prices and amplifying the unnecessary carbon footprint. Additionally, ethical concerns linger as AI may struggle to distinguish between intended and unintended actions. For instance, in content moderation, a chat joke might be interpreted as hate, and the user will be banned, while a player who is displaying toxic behavior during the quest will stay in the game.

The Future of AI in the Gaming Industry

Future applications of AI in gaming involve building on new hardware capabilities. With the rise of edge AI devices, this technology is being brought closer to the sources of collected data (like blood pressure, eye motion, etc.). If that is complemented with VR/AR, brain-computer interfaces, and quantum computing, the games will probably become even better than real life. 

The increased opportunities for open worlds and character development in virtual realities will allow for social interactions and creative exploration. However, ethical concerns about such an escape from the real world are rising proportionally to AI gaming’s popularity.

Summing Up

Overall, AI in the gaming industry enables enhanced player experiences and software scalability at an unprecedented pace, so it seems like we will see it becoming mainstream soon. Some applications of AI in gaming are purely practical (like AI testing in QA), while others are quite far-fetched (like BCI). One thing we know for sure is that the implementation of AI requires a lot of research and experimentation. An iterative approach can fuel this technology’s evolution because, as they say, “A journey of a thousand miles begins with a single step.”

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Nowadays, IT teams want to find the right balance between classical and agile software development methodologies. While any of them might sound like a perfect solution theoretically, the practice might show otherwise. Agile projects grow into relentless scope creep without any direction, while heavily documented processes end up being heavily bureaucratic and inefficient.

If you want to find out more about what software development methodologies are out there and how we use them at Intellectsoft, check out our webinar recording from BrightTalk. 

In this article, we explore how the Stage Gate Process is beneficial for IT teams. It emerged as a risk-reducing tactic for product development in other industries and now starts to gain traction in the digital realm.

What is the Stage Gate Process?

Stage Gate process is a project management technique that breaks down projects into distinct stages with decision points (“gates”) between them. Companies can use it in software development, but it’s not the most common approach. 

The Stage Gate methodology has its roots in the 1960s within the New Product Development (NPD) practices of major pharmaceutical and aerospace companies. These industries dealt with complex projects requiring significant resources, risk management, and regulatory hurdles. The Stage Gate process template provided a way to break down these projects into manageable phases with clear instructions for go/no-go decisions.

How is the Stage Gate Process Used in SDLC?

In software development, the Stage Gate Process is reminiscent of hybrid methodologies like the Spiral Model and Rational Unified Process that connect the best of both polar opposites: Waterfall and Agile. 

Stage Gate Process is rather a simplified alternative because the so-called “gates” in the sense of milestones are basically present in every other software development methodology out there. However, it does include ideation and business case creation, which are often left out in common SDLC workflows. In this regard, the Stage Gate Process offers a more holistic approach to product development where the actual production is a logical outcome of the business needs.

So, Which Projects is It Good For?

• Large, complex projects: For major software development initiatives, Stage Gate can provide structure and control.
• Highly regulated industries: Some industries have strict compliance requirements that benefit from the structured approach of Stage Gate.
• Risk-averse companies: For companies prioritizing risk mitigation, the decision points of Stage Gate can offer reassurance.

Alternatives to Stage Gate Process

• Agile methodologies: More iterative and adaptable, better suited for rapid changes and uncertain requirements.
• Lean development: Focuses on minimizing waste and delivering value quickly through feedback loops and continuous improvement.

Ultimately, the best approach depends on the specific project and the company’s needs. Keep in mind that unless you work in a heavily regulated industry, you don’t necessarily have to do everything by the Stage Gate book. Opt for optimizing if you like some parts of this approach and dislike others. Your team can hybridize the Stage Gate Process to have some understandable structure to follow while keeping the flexibility options, for example. It is better to follow what works best for you rather than adopting Scrum and then having robotic stand-ups where people are involved just formally.

5 Phases of the Stage Gate Process

Go! 🏇

You’re good to launch! The tech works, the market wants it, and the numbers add up. Time to hit the gas and execute the plan.

Kill It 🙈

Not every idea wins. Maybe tech hurdles are insurmountable, the market shifted, or costs outweigh benefits. Shutting down saves resources and lets you focus on better bets.

Hold On ✋

Hit a temporary stop sign. Maybe you’re waiting for key partners, the market needs time to evolve, or your team is busy elsewhere. Define clear conditions for restarting when things change.

Rework It 👷

The design needs tweaks, user feedback demands changes, or finances need fixing. Refine your plan, address issues, and re-enter the race with a stronger engine.

Go With Conditions 🚸

Proceed with caution! You get the green light, but specific milestones need hitting, uncertainties resolved, or external approvals secured. Prove you’re on track before going full speed.

Key 6 Gates of the Stage Gate Process

Just like any project milestones, Stage Gates represent some structures that you have to pass. In order to be approved for the passage, you need to study what has been done up until this point and meet some predetermined criteria.

Let’s review those six gates in more detail.

To understand Stage Gates in a less boring way, let’s imagine a software project as your favorite RPG. Think of the code delivery as a grand quest and Stage Gate as a series of key milestones. Each phase brings unique challenges and rewards, shaping your journey to success.

Gate 1: Ideation (The Tavern)

This is where your initial spark ignites! Brainstorm ideas, explore possibilities, and gather your team. Define your quest’s core problem to solve and its value (impact/reward).

Gate 2: Scoping (The Cartographer’s Tent)

Map your journey in detail. What features are essential (main quest)? What can wait (side quests)? Define the tech stack (your tools) and estimate the resources needed (gold and supplies).

Gate 3: Business Case (The New Quest)

Convince the stakeholders(NPCs). Research the market (terrain), identify your target audience (allies), and estimate potential rewards (profit). Show your project is worth the risk (stage gates).

Gate 4: Development (The Forge)

Time to build your software (hero)! Use your chosen tech stack (tools) to craft features and functionalities (armor and weapons). Your team works through sprints (quests) to progress.

Gate 5: Testing & Validation (The Arena)

Put your hero to the test! Users (battle opponents) provide feedback, revealing strengths and weaknesses. Iterate and refine (train and level up) before the final launch (battle).

Gate 6: Launch & Beyond (The Victory Celebration)

Release your hero into the wild! Support users (allies), gather feedback (loot) and address issues (monsters). Remember, the quest never truly ends – adapt and evolve (new quests) to conquer future challenges!

Stage Gate Process Example

Imagine you’re a PO working on a mobile app for one of Intellectsoft’s clients in the construction industry. Key business stakeholders want to upgrade the app to introduce a better UX and enhanced functionality. They give you the task of researching what features to add, what bugs to fix, and how to increase the overall experience. After the validation of the presented ideas, your team will develop all the updates. While the scope is yet to be discovered, one requirement is already crystal clear: you need to use the Stage Gate process for managing this project.

Phase 1: The Brainstorming

Your team gathers in the office kitchen, fueled by coffee from the machine, and discusses the next Stage Gate for the construction app. Ideas fly: “What if we could track materials in real-time, saving time and money?” You define the core problem – inefficient material tracking, and the added value – increased productivity and cost savings.

Phase 2: The Blueprint

The project backlog is enriched with new items. Features like GPS tags, inventory management, and progress reports take shape. You assess the tech stack (cloud platforms, APIs) and estimate resources (development time, budget).

Phase 3: The Investor Pitch

Time to convince the stakeholders. Your BA mates present market research with a beautiful presentation on industry trends and competitor analysis, showcasing how your feature solves real pain points and generates profit in the form of increased subscriptions and reduced project delays.

Phase 4: The Coding

The coding commences! Your development team builds the feature using chosen tools. Sprint after sprint, you see new features like GPS tracking and inventory management come alive.

Phase 5: The Beta Build

Real construction sites become your testing grounds. Beta testers are real sector employees like foremen and site workers. They provide feedback. As a result, bugs are squashed, and features are refined. For example, you decided to add alerts for low material stock. The fresh new features undergo user acceptance testing before launch.

Phase 6: The App Store Celebration

Your features go live! Users download the app upgrade, construction projects run smoother, and positive reviews flow in. But the journey continues. You gather feedback, continue fixing bugs, and plan future enhancements to keep your app at the top of the construction app charts.

So, will your real-time material tracking system revolutionize construction? With well-navigated Stage Gate project management, your app could be the next big thing!

What Are the Benefits of the Stage Gate Process?

Transparency

The defined stages and gate reviews promote clear communication and collaboration among stakeholders, ensuring everyone is aligned with project goals and decisions.

Flexibility

The ability to hold or recycle projects allows teams to adapt to changing market conditions or unexpected challenges, ensuring the project remains relevant and feasible.

Better Outcomes

Early identification and termination of unviable projects minimize wasted resources and financial losses associated with failed projects.

Wrapping Up

Overall, the higher project success rate that is associated with employing Stage Gate is most likely associated with a clear structure and quick elimination of inefficiencies. Streamlined decision-making helps to allocate resources with maximum efficiency while reducing risks and waste.

Intellectsoft offers a variety of project management techniques that are tailored uniquely to the business and technical needs of our customers. For instance, we designed a mobile solution for Ernst & Young that empowered investors with a customizable financial forecast interface.

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According to McKinsey, 45% of IT projects exceed their budget, and 7% exceed planned time constraints. This signifies poor strategy development at the initial stages.

Intellectsoft’s expertise in conducting the Discovery Phase for system engineering and project management helps you avoid costly mistakes and achieve project success. Learn more about the benefits and deliverables in the article below.

What is the Discovery Phase?

Before learning the intricacies of the project Discovery Phase, you need to make sure you know which “neighborhood” you’re in. When looking for answers online, you can come across a range of various definitions that have nothing to do with the Discovery Phase concept that you really need to know. 

Let’s just clarify that, in this article, we are going to talk about the Discovery Phase as part of the system architecture conducted by your software engineering partner, Intellectsoft. We will also look at the alternative definitions from the Project Management perspective so that you know the difference. 

In the first case, the Discovery Phase encompasses the primary step of the Solution Architecture lifecycle (Lovatt, 2021) that creates a foundation for a successful solution. In this context, it typically includes three major types of activities:

• Fact-checking. Thoroughly studying all architectural inputs that are relevant to the problem area.
• Engaging stakeholders. Identifying people relevant to the solution scope and their responsibilities. 
• Establishing Success Criteria. You’ll never know if the solution turned out well if you don’t set expectations, assessments, and success criteria beforehand.

Inputs to these activities: architectural artifacts, stakeholders register, business case. If some critical information is unavailable, the Discovery Phase has to be extended to cover investigation and modeling. Existing artifacts like business requirements are also subject to reformulation and modification if key stakeholders deem those insufficient.

Deliverables: technical approach outline, system design outline, project planning roadmap, wireframes, and prototypes.

Important Differences

In our customers’ internal business processes, the Discovery Phase in project management involves identifying the business value of some idea. Thus, the major deliverable is the business case. More often than not, we cover the system architecture concept of the Discovery Phase because customers prefer to create their business cases internally (since it depends on many organization-specific and sensitive data).

The primary role of the business idea justification is defining a dominant business objective. This could be a market demand, organizational need, customers’ request, technologically competitive edge, social responsibility, or legal requirements. Whatever the purpose, a project needs some rationale to begin with.

Deliverables: Business case/plan, current vs. future state, return on investment; list of prequalified vendors, predetermined clients, preexisting contracts, capital expenses (CapEx), and operational expenses (OpEx) plans.

In this scenario, the main deliverable (business case) outlines the scope, audience, and purpose of the proposed work and establishes the value it could bring. A well-researched business case can show that a project is worth the investment. It is a strategic document.

Consequently, here Intellectsoft steps in on the next phase (which traditionally could be called the Initiation phase), where we define success criteria, preliminary scope and requirements, high-level risks and assumptions, summary milestones, summary budget, and key technical stakeholders, create a stakeholder register, develop a responsibility assignment matrix, establish communication channels, begin records management, review existing artifacts, determine a solution design, define access requirements for project work, obtain charter sign-off, and perform kickoff.

How to Plan a Discovery Phase of a Project?

Discovery Phase planning at Intellectsoft is adjusted to every individual request. Instead of proposing cookie-cutter solutions, we emphasize quality and usefulness, even if it’s a preliminary system design outline. That’s why, after the initial internal discussion, we allocate resources to cover the full-scope Discovery Phase. If we are working with the existing client, the planning phase can be very fast because we already know the artifacts and the current state. However, if we are working with a new customer, the planning process may take up to a few weeks. 

Of course, there is also a standard process at play; for example, our project Discovery Phase normally starts with activities like:

• Preliminary meetings with a customer,
• Interviews with stakeholders,
• Contextual research,
• Documentation study,
• Review of preexisting processes.

Once we have a general understanding of the scope of work, we are ready to dive deeper and work on discovering appropriate technological solutions to the project in question.

Sometimes, when technical stakeholders say planning, they also mean all the activities of the actual, ongoing Discovery Phase of a project. So, just to clarify, all the processes of brainstorming and creating supporting documentation throughout the already initiated phase can be referred to as Planning.

What Are the Discovery Phase Deliverables?

Below are examples of Discovery Phase deliverables that might be associated with software development projects. Note that it greatly depends on the customer and the particular objectives. For larger projects and sometimes for venture series startups, more paperwork is involved.

Existing Artifacts Review

Artifacts are tangible items, like documents or products, that were previously made and are available at the time the project Discovery Phase starts. For example, we might ask to review the business case, current project documentation or previous designs, and so on. Without understanding what you already have, we won’t be able to make informed conclusions and outline of what needs to be done next.

If we are to build a complex system, we might ask to clarify your relationship with current or future clients, vendors, etc. Preexisting contracts might affect how the system needs to be shaped, e.g., what business processes and logic to include. 

You might supply such artifacts as a master service agreement (MSA), statement of work (SOW), or terms of reference (TOR).

Capital Expenses vs. Operational Expenses Assessment

Budget allocation is usually the customer’s call, but when we see room for optimization, we offer guidance. For instance, in heavy equipment facilities, projects often involve both operational expenditure (OpEx) for software, which doesn’t appreciate or depreciate, and capital expenditure (CapEx) for durable assets like equipment, which are taxed and appreciate/depreciate over time. In such cases, we suggest ways to leverage technology to increase the value of those durable assets and lower OpEx, ultimately boosting ROI.

Example

A client needs software for monitoring ice melting that might result in spring flood damage to a city at the foot of the mountain. The problem is that the visualization quality is poor, so the client is considering a multi-million dollar investment into cloud-based data processing architecture that improves quality with AI. We analyze their situation and point out that improving the physical layer (OSI Layer 1) by ensuring a clear line of sight between transceivers, along with minimum loss of local connectivity on Layers 2 and 3, could achieve similar, even better results faster and at a lower cost. 

Therefore, we’d advise enabling VLANs to isolate network traffic throughput and introducing QoS routing. Then, we could suggest lightweight software specifically designed for handling interference, phase delay, and signal loss issues to avoid operational lags. We would also ask questions about how satisfied the client is with the current data processing algorithms because GIS is known to work with huge amounts of data, so before doctoring that with AI, it is necessary to make sure that we do not work with erroneous and poorly pre-processed data in the first place (which can be achieved by well-known mathematical algorithms and quickly done using existing libraries). This software might focus on key data points and visualization techniques optimized for the available bandwidth, delivering clear visuals more reliably.

Note: The low-level software solution will depend on various factors like the facility’s specific needs, the type of wireless system, and the desired data representation. This example aims to illustrate the principle of offering software alternatives that capitalize on improved hardware conditions instead of relying solely on “fashionable” cloud solutions that don’t necessarily address the core problem.

Because capital assets will benefit the organization for years after the project ends, they may be sourced from the organization’s budget, not the project’s. That is often a point that needs to be escalated to a higher level of negotiation.

Current State vs. Future State / Gap Analysis

Here, the analyst will create a contrast-and-comparison table of the current state of project solutions vs. the desired improvement. While these statements should be clear and concise, they should not focus on either the technical or implementation aspects of the issues.

For example, instead of mentioning the future state as “Sales team is migrated to This CRM Brand,” it is better to write “Sales leads are increased by 30%.” Particular solutions to the future state will be designed at a later stage of the project Discovery Phase.

This document can focus on gaps, bottlenecks, and weaknesses in current processes, such as lack of automation or missed revenue caused by outdated software. Growth of business operations might also go here, as it is an opportunity for improvement.

Interface Inventory, IT Asset Inventory

Naturally, any solution has multiple components at different levels of interaction and communication with each other. By creating an interface inventory, we are clarifying our understanding of the solution architecture and, therefore, can refer to it when deciding on the implementation roadmap priorities.

We document details like:

• Name of the interface
• Source
• Destination
• Rules and other events
• items exchanged, including any supporting information
• Workflows, itineraries
• Pre- or post-conditions.

Same goes for IT assets. We want to itemize all the physical and non-physical digital entities such as networks, servers, workstations, databases, and so on.

Project Charter

Usually developed by the PM during the Discovery Phase of project management, this document is the cornerstone of the project and its main point of reference. It defines the reporting structure for decision-making, as well as the project’s purpose, goals, objectives, requirements, high-level assumptions and constraints, high-level risks, success criteria, a summary milestone schedule, key stakeholders, a summary budget, and an initial key stakeholder register. The project success criteria, which serve as a benchmark for the quality of the produced outcome, are also included (Heldman, 2022).

Risk Assessment

Discovery Phase of a project also highlights possible issues and high-level solutions that are possible to suggest based on existing knowledge.

The basic version of the document is usually an executive summary that provides a top-level synopsis of the problem, the proposed solution, the justification, and the expected benefit, but it skips the analysis behind these decisions. That analysis, along with the estimates of financials, would be included in the more in-depth version of the risk assessment. Depending on the size of the project, it could include the following elements:

• Problem statement: Description of the issue.
• Analysis: A root cause analysis or any other analysis that predicts the outcome of the stated issue.
• Recommended solution: The solution that was analyzed as most likely to succeed
• Proposed solutions: Alternative approaches to the recommended solution, their strengths and limitations.

The initial risk assessment documents are typically reviewed, refined, and formalized in the project charter.

Preliminary Scope Statement

Outlines the tasks to be done and specifies what’s not part of the project. It’s often called the big-picture scope.

A PM looks at the charter’s requirements and makes a detailed scope statement during planning. This statement gets added to the scope baseline and lists the individual tasks needed for the project. However, the charter’s scope is preliminary until more analysis is done.

Usually, it describes the project, what needs to be delivered, how it will be accepted, important points in the timeline, and what’s not included in the project.

Solution Design Outline

Solution architecture is often the most anticipated part of the project Discovery Phase. Everyone wants to know the architect’s vision of how to build the solution to estimate what it would take to make it a reality.

Determining which solutions are needed and how they will interact with existing infrastructure is what our architects want to show. We also want to plan for the future, making this solution maintainable and scalable to support the business’s growth.

The solution design process has two main outputs: a high-level conceptual design and a low-level technical roadmap. 

Technical Roadmap

Our tech team, including the architect, developers, UX designers, and more, are the main stakeholders for this document. They want to outline the low-level tech details, such that are specific enough to put into sprints and iterations. 

Importance of the Discovery Phase

The Discovery Phase activities target a primary goal: developing a conceptual design for part or all of the project. The proposed solutions must align with our customer’s business requirements, therefore addressing business needs and opportunities.

It might be one of the most challenging parts of the solution design pipeline because we need to showcase the value of our proposed design without going into too much detail. It is important to keep an open mind and stay away from specifics because doing so might result in focusing on logical conclusions rather than premises. On the flip, more investigation and flexibility down the pipeline typically result in better working systems.

Importantly, the conceptual solution outline ideally holds the core logical reasoning, which can be extended into and connected to all further levels, down to the physical. Due to the nature of modern system architectures, the level of technological volatility might be high, so making a high-level solution outline ensures that we will not make premature decisions that will have to be redone further down the line. It is essential to acknowledge that the solution architecture life cycle exhibits a high degree of parallelism and iterative refinement based on accumulating knowledge.

Discovery Phase Best Practices

Adhering to industry-wide standards such as ISO/IEC/IEEE is considered the best practice in the project Discovery Phase. Some of the activities described in these guidelines include the following.

Gathering Architecture Inputs

A number of factors determine whether useful architecture artifacts are available at the start of the project Discovery Phase:

• Architecture maturity: whether architecture practice is established and working well in the organization or enterprise and if there is an efficient repository of artifacts that can be easily accessed and in which it is easy to find relevant artifacts.
• Overlap with current problem area: if the new problem to be solved is in an area or operational domain that has never been addressed before, there will be fewer relevant artifacts.
• Clarity of understanding of the current problem: if the focus of the problem is too broad or ill-defined, it is harder to distinguish relevant artifacts, and too many irrelevant ones may be included as inputs.

The main product of this activity is a catalog of relevant architecture artifacts for the operational domain of the solution vision. At this stage, it is not necessary to examine the artifacts in detail, but it is important to identify them and know they are available when needed.

If the artifacts are organized in a repository, then more details will be available, such as:

• Date of production and modification
• Version number
• Owner
• Business area
• Related artifacts that would be impacted by change, and any dependencies.

It is also useful to record the reason for selecting this artifact by linking it to an element or concept in the problem domain.

Defining Stakeholder Engagement

According to ISO/IEC 42010:2011 and TOGAF definitions, stakeholders are individuals, groups, or organizations having an interest or concern in a solution. They can be internal or external.

Beyond just listing stakeholders, we can also create a stakeholder communication plan that expands on the level of involvement in the solution architecture process, responsibility matrix, methods of communication, deliverables, etc. Usually, that level of detail is more important in enterprise projects and can be omitted in startups and SMBs or ongoing agile processes.

Refining Business Requirements

Project success criteria are not possible to draw without prior documentation of business requirements. The logic here is simple: if all the requirements are met – the project deliverable is considered successful. Alternatively, the success can also be judged from the perspective of project constraints like time and resources – in this case, their optimization would imply high-quality results.

Further down the line, business requirements also become a basis for us to create a solution design proposal and a roadmap outline. Keep in mind that if we are adopting an Agile methodology, business requirements might come and go as the project evolves.

The documenting process is sometimes more complex than writing something like “Ok so my idea for a project is this…” If we are taking the business value seriously, our business analysts need to go through several stages:

• Capturing: listing requirements, plus simple yet actionable explanations.
• Validating: checking for completeness and correctness.
• Verifying: testing requirements to see if they are the best option, checking for conflicts and overlaps.

The resulting requirements catalog might include:

• Name of the business requirement;
• ID;
• description;
• Justification;
• Category;
• Status;
• Change control details.

The requirements catalog is useful for tracing how business requirements become system or data requirements. It can also be used to check if the business needs to consider additional operational measures such as new SLAs.

To document business requirements, we might interview stakeholders, review existing artifacts, or even make new ones (such as use cases, user stories, data models, etc.)

Creating Solution Proposal

At this stage of the project Discovery Phase, we are approaching the most interesting part – describing and illustrating our vision for the solution. We need to focus on core models without swinging away into specifics that could potentially lead us astray. So here we are showing the essence of the design, not constrained by jumping to conclusions or step-by-step plans yet.

If there are several good alternatives, we might propose more than one solution for a customer to choose from. It is also important to come to an agreement between all the stakeholders at this stage.

Visuals

Complex tech solutions really come alive in stakeholders’ imaginations once they are presented visually. For that, we can use a variety of mediums:

• Diagrams, charts, graphs, maps
• Wireframes
• Design mockups
• And more!

Our objectives here are to abstract high enough from technical buzzwords, convey meaning, and, ultimately, obtain stakeholders’ approval.

Supporting Artifacts

Nice visuals are fun, but stakeholders want to understand how the solution addresses their area of business. For that, we dive deeper into supporting artifacts.

For example, a sample high-level architecture definition:

• Outlines the infrastructure layer that an application will be built on top of
• Depicts main components together and highlights proposed building blocks
• Specifies relations and interactions between subsystems
• Defines security boundaries and considerations
• Declares data types and their storage approaches
• Determines application resiliency and failover processes
• Highlights the insights of the middleware layer
• Illustrates the principles of scaling and load balancing of the system and its components.
• Indicates observability functionalities and toolset
• Marks out external interfaces and integration capabilities and approaches

Project discovery phase might result not only in the collection of information but in the true discovery of requirements that stakeholders didn’t know before. That is why, to clarify our solution ingenuity, it’s useful to maintain artifacts like traceability/cross-reference grids where we show the links between the initial idea and its evolution path, providing explanations for the variations.

Outlining the Step-byStep Plan

At this stage, we collect all the artifacts we obtained or produced before and go down the rabbit hole of the specifics. We are scoping the solution, analyzing interfaces and risks for smaller deliverables (like features), looking at the tech stack options, and offering a high-level step-by-step plan.

Scope Definition

After choosing a solution, we formalize its scope by detailing changes in each business area, specifying their nature (new, existing modification/removal/replacement), and linking them to relevant architecture documentation. This ensures clarity and avoids conflicting efforts throughout the solution’s lifecycle.

Building Block Analysis

Building block analysis helps identify reusable components within the organization and assess their suitability for the solution. It creates a solution-building block model detailing each component’s name, category, ownership, current state, and required modifications.

KPI Documentation

Before initiating the project, we need to formalize our acceptance criteria with stakeholders. What is considered successful? What is considered done? What are the key metrics that we are striving for? What is the logic behind deciding what’s good and what isn’t? All that needs to be described at the stage of documenting KPIs.

Most often, the KPI documentation types will depend on methodologies and stakeholders involved.

Examples of KPI documentation:

• Budget (cost performance, cost variance, planned value, etc.) 
• Performance (schedule performance/value, resource capacity/velocity, stories in development, tasks reopened, changes accepted, burndown, cumulative flow, code coverage, etc.)

Wrapping Up

Discovery Phase is one of the most exciting stages in software development. It is the time to be creative and to attempt to save the world by visualizing how your solutions will positively impact the global landscape. Whether you are an aspiring startup or an international enterprise, Intellectsoft offers a variety of Discovery Phase packages to suit your needs.

We’ve built software for train passengers, enabled multilingual communications, streamlined investment decision-making, and even helped to build cities. With a diverse experience under our belt, we confidently scale ambitious businesses that want to embrace digital evolution in all of its beauty and power.

The post Guide to the Project Discovery Phase in 2024 appeared first on Intellectsoft Blog.

Enter FinTech, transforming the landscape with its digital prowess. This article explores how it reshapes the financial world with SME banking software, addressing the businesses’ unique needs and opening up a world of possibilities.

What is SME Banking?

SME banking is a set of financial services custom-fitted for the smaller scale and specific needs of Small and Medium-sized Enterprises (SMEs).

What makes it important? According to the OECD, SMEs account for over 95% of firms and 60%-70% of employment. They also generate a large share of new jobs in the OECD economies.

Traditional banking services like loans, credit lines, and deposit accounts have been gradually sculpted to fit SMEs’ demands and industrious nature. However, the journey wasn’t straightforward. In the not-so-distant past, SMEs faced a banking landscape that was, more often than not, below accommodating. Navigating the traditional banking terrain felt like trying to solve a Rubik’s cube blindfolded. 

SMEs grappled with high fees, rigid credit assessments, and optimized one-size-fits-all solutions that barely fit anyone in practice. Securing funding was akin to a Herculean task, while personalized financial advice was rare and often accessible only to the privileged minority. 

The disconnect between what SMEs needed and what banks offered was glaring. It was this very gap, this misalignment of services, that set the stage for the FinTech revolution that promised to tear down these barriers and usher in a new era of customization.

With the advent of FinTech, the world of SME banking is undergoing a tech-savvy makeover.

Imagine a banking universe where every service, every product, is tailor-made, just like a bespoke suit perfectly cut to fit its wearer. FinTech is adding smart, high-tech accessories to that already well-crafted suit. In other words, with SME banking solutions, their financial needs aren’t just an afterthought—they’re the star of the show. 

As a more plastic illustration, picture a quaint local bakery that once spent hours on billing, now effortlessly managing transactions with a sleek digital payment platform. FinTech’s integration into SME banking is revolutionizing their game, making financial management not just more convenient but also smarter and more intuitive.

In essence, FinTech isn’t just redefining SME banking; it’s reinventing it, making it more inclusive, more accessible, and more aligned with the dreams and realities of small and medium-sized enterprises.

Challenges Faced by SMEs in Banking

• Limited access to capital
• High transaction costs
• Cumbersome payment processing
• Complex financial management
• Inadequate personalized services
• Inflexible banking hours and locations
• Credit scoring challenges
• Lack of financial literacy resources
• Data security concerns
• Regulatory compliance
• International transactions
• Delayed invoice settlements

FinTech’s innovative approach to these challenges improves the position of an SME in banking. It helps the companies operate more efficiently, scale effectively, and focus on their core business activities.

How FinTech Addresses SME Banking Challenges?

So, this is where FinTech starts as the hero. With SME banking solutions, it revolutionizes how these businesses interact and navigate the finance landscape.

Digital lending platforms, among other perks, are streamlining the loan process. It’s like having a financial wizard at your fingertips, turning weeks of paperwork into a few clicks. Take, as an example, a small tech startup that accessed seed funding through a digital platform, catapulting it from a garage to the global stage. Mobile banking and AI-driven financial tools are also part of this FinTech arsenal, empowering SMEs with real-time financial insights and control.

Here is an overview of the most notable FinTech solutions to common challenges. 

Access to Capital

Traditional lending can be a tightrope walk for SMEs, with banks often setting a high bar for loan approval. FinTech dances to a different tune, offering platforms like peer-to-peer lending and online crowdfunding, where SMEs can secure funds without the rigmarole of traditional banking.

Transaction Costs

For SMEs, every penny counts, but banking fees can take a big bite out of their budget. FinTech slashes these costs with sleek, automated processes, turning what was once a financial drain into a manageable trickle.

Payment Processing

Juggling payments with old-school systems can feel like navigating a hedge maze for SMEs. FinTech simplifies this labyrinth with swift, user-friendly payment solutions, ensuring SMEs keep their cash flow as fluid as a running stream.

Financial Management

Economic administration can be full of twists and turns. FinTech brings in a GPS in the form of intuitive digital tools that help SMEs easily chart their financial course, from budgeting to forecasting.

Personalized Services

SMEs often crave banking that understands their unique needs rather than semi-usable cookie-cutter solutions. FinTech tailors its suit to fit every SME, offering specialized products and advice that resonate with their individual business models.

Banking Hours and Locations

Traditional banking hours can be a hassle in the contemporary business landscape, feeling like a square peg in the round hole of an SME’s schedule. With FinTech’s 24/7 online platforms and SME mobile banking, financial management becomes a flexible process suitable to any timeline.

Credit Scoring

Conventional credit scores can unfairly label SMEs, leaving them in the financial cold. FinTech uses a broader lens, considering various data points to paint a fairer picture of an SME in banking, emphasizing their creditworthiness and warming them up to more funding opportunities.

Financial Literacy Resources

Navigating the financial landscape without a map can leave SMEs lost. FinTech provides this map through accessible, easy-to-understand educational resources, guiding SMEs toward better financial health.

Data Security

In a digital world, data leaks are like open floodgates for SMEs. FinTech reinforces the dam with advanced security measures like encryption and blockchain, keeping SMEs’ financial data safe and dry.

Regulatory Compliance

Staying on top of regulations can feel like a high-wire act for SMEs. FinTech acts as a safety net, incorporating compliance features that help SMEs adhere to financial laws and standards, all without the circus act.

International Transactions

Global business can tie SMEs in knots with currency and cross-border payment complexities. FinTech untangles these knots, offering streamlined solutions for international transactions, turning a global headache into a walk in the international park.

Invoice Settlements

Late payments can strangle SMEs’ cash flow. FinTech offers a lifeline with solutions like invoice financing and digital invoicing, ensuring payments flow as smoothly as a serene river, bolstering the SMEs’ financial health.

Through these innovative solutions, FinTech addresses the specific challenges of SME banking, empowering companies to navigate the financial landscape with greater ease, confidence, and success.

Collaboration Between Banks and FinTechs

The evolving tale of banks and FinTech companies relies on partnership and cooperation, where each party brings its strengths to the table. This beneficial fusion thrives on blending the reliability of traditional banking processes with technological innovation. 

Among the bountiful case studies, the best examples here might be the FinTech giants themselves. TransferWise, co-founded by Skype alum Taavet Hinrikus, is a prime illustration of FinTech innovation meeting SME needs. Originating from a personal need to avoid high fees in cross-border transactions, once an SME itself has grown into a leading player in the field, offering efficient, low-cost international payment solutions now widely used by other SMEs. 

The stories of Lending Club and Revolut further epitomize the fusion of tech-driven solutions and traditional financial services, catering effectively to the global business needs of SMEs.

Opportunities for Growth in SME Banking

The business landscape for small and medium-sized enterprises is changing, closely following FinTech innovations as they unlock new growth opportunities. Digital lending platforms use algorithms to assess creditworthiness, providing quicker and more accessible funding options. This is particularly beneficial for businesses previously overlooked by conventional banks. In addition, personalized banking services involve a variety of integration possibilities and a level of customization that was previously out of reach for many.

Example: A boutique coffee shop with a stellar prospect that may struggle with traditional bank loans due to the nature of its business.

In addition, AI and data analytics are revolutionizing SME banking, transforming guesswork into strategic decision-making. SMEs can leverage these tools for cash flow forecasting and customer spending analysis, enhancing their inventory management and marketing strategies in return. To quote Wealth and Finance, “Thanks to the advent of predictive analytics tools such as machine learning algorithms or modeling software, SMEs can now look at historical data and make projections for what may happen in the years ahead.”

Example: Small construction companies can now streamline their financial operations with customized solutions from a single FinTech platform.

FinTech is also paving the way for SMEs to expand into international markets. Simple, efficient handling of international payments and currency risk management opens global opportunities once hindered by complex banking processes. A study conducted by Chinese experts, based on the data of listed small and medium-sized enterprises from 2011 to 2020, proved that FinTech in banking can significantly ease the financing constraints of SMEs. Their results showed a decrease of 0.0767% for every 1% increase in FinTech.

Example: Small artisanal soap makers or chandleries are often confined to local markets. By utilizing a FinTech platform to seamlessly handle international transactions and manage exchange rates, they gain the opportunity to expand their customer base and reach multiple countries with ease.

The Future of SME Banking

It doesn’t take a crystal ball to detect that SME banking’s future sparkles with FinTech innovation. Technologies like AI, blockchain, and open banking evolve day by day, promising to revolutionize this space further. 

SMEs have already begun managing their finances with the help of AI assistants, in addition to using blockchain for secure, transparent transactions. This future is not just a possibility; it’s unfolding before our eyes, reshaping the entire banking landscape into a dynamic, tech-savvy ecosystem.

Wrapping Up

In summary, the marriage of FinTech and SME banking is more than beneficial—it’s transformative. It’s a venture of overcoming challenges and seizing opportunities, where SMEs are no longer bystanders but active players in the banking arena. As FinTech continues to evolve, it’s clear that SME banking will never be the same.

In such an inspiring landscape, companies like Intellectsoft emerge as key players with their tailor-made FinTech solutions. They harness their vast global experience to fuel SME growth, providing bespoke financial technology platforms: innovative, practical, and accessible.

Intellectsoft’s commitment to delivering top-notch services ensures that its software is seamlessly woven into the fabric of SMEs’ business operations, empowering them to navigate the complexness of the global market with confidence and efficiency.

The post SME Banking: FinTech Challenges & Opportunities appeared first on Intellectsoft Blog.

Going digital in the construction world stretches way beyond the convenience of using the latest gadgets. Common data environment and BIM technologies are transforming the entire landscape to make things as clear and streamlined as possible. And let’s not forget about teamwork: construction projects involve a powerful workforce. Architects, engineers, and builders all need to share information with each other. The frequency of exchange, back and forth, creates an ever-evolving dynamic data landscape as the project goes on, requiring an equally powerful system for organizing all the data available.

In simple (also not overenthusiastic) words, the common data environment is a game-changer. It helps construction jobs run more smoothly and accurately, leading to fewer delays and staying on budget. The question is: how? 

We will now dive deep into how a CDE works, what good stuff it brings to the table, and how it’s really making a difference in building stuff today.

What is a Common Data Environment (CDE)?

The name refers to a digital, cloud-based platform designed specifically for construction projects. At its core, it’s a giant database that stores all relevant information, making it accessible and handy to all project participants—but that’s not all. As a central hub for accumulating, managing, and sharing project data, common data environments are sophisticated ecosystems that allow complex interaction while keeping all necessary details at your fingertips, regardless of physical location.

The market demand behind the common data environment’s existence is pretty clear. Taking predictions by Oxford Economics into account, we can expect the need for effective data management in construction to grow in geometric progression. During the next 15 years, global construction work will grow from US$9.7 trillion in 2022 to US$13.9 trillion in 2037. Expectedly, the market is driven by superpower construction markets China, the US, and India.

But How Exactly Does the CDE Fit Into That Picture?

In the old days, construction projects would easily get tangled up in misunderstandings and mix-ups with paperwork. Even though software solutions have been gradually developed since the mid-20th century, until recently, project managers had to rely on the manual processing of fragmented systems, where the results could easily get off track. The deficiency of comprehensive information sometimes induced such negative outcomes as poor data management followed by problematic, intuition-based decisions.

These time-consuming processes also hindered project success in other ways. Difficulties in accurately predicting and managing budgets and timelines led to cost overruns, inconsistent quality, and expensive delays. Communication gaps among multiple stakeholders were unavoidable, resulting in errors, misunderstandings, and inadequate risk management. And challenges in ensuring compliance with various, ever-changing regulations just added to the pile. 

This is where the common data environment excels, taking the role of a superpowered digital meeting room. 

CDE in construction is revolutionizing the industry by tackling its core challenges. It streamlines data management, replacing manual and disjointed processes with quick, efficient systems. It also enhances decision-making by providing accurate, real-time data for informed choices, preventing costly mistakes and project delays. Furthermore, it addresses communication gaps, ensures quality control, manages risks effectively, and aids in maintaining regulatory compliance.

The Building Blocks of CDE 

According to the ISO 19650 standard, two integral parts of the BIM-based execution of construction projects involve project management and information delivery. Project management comprises all steps necessary to set up a BIM project, from Employer Information Requirements (EIR) to the preparation of the BIM Execution Plan (BEP).
Information delivery, on the other hand, is about model creation, which is heavily related to the Common Data Environment (CDE). 

Data Integration in CDE

Data integration is a key functionality of common data environments, converging diverse sources and formats into a single, coherent system. This synthesis maintains the continuity and integrity of project data, ensuring that all stakeholders work with the most current and accurate information.

Example: An architect’s blueprints combined with an engineer’s technical specs make the design plan as a whole more understandable for everyone.

Collaboration Tools in CDE

A common data environment is equipped with a range of collaborative tools designed to facilitate communication and teamwork. These tools enable document sharing, version control, and real-time chat functions, among others, enhancing the cooperative spirit of construction projects.

Example: A builder spots an issue on-site. They immediately share a photo in the CDE, and the architect can promptly respond with revised plans. Managers and supervisors automatically get informed on the changes and what caused them, all at the same time and within the same system.

Data Security and Access Control In CDE

Data security is a critical component of common data environments in an industry where sensitive and confidential information is frequently exchanged. The system addresses this concern by implementing robust access control mechanisms, ensuring only authorized personnel can access selected project data. Such an approach protects sensitive information and fosters a sense of trust among project participants at the same time.

Example: A construction project for a government building with strict security requirements. In the CDE, access to detailed security system plans and confidential contract documents can be restricted to only a few key personnel, such as the lead architect, the project manager, and the government liaison. At the same time, it still allows a broader construction team access to general timelines or material lists.

Practical Applications of CDE

Streamlining Workflows

One of the primary advantages of a common data environment is its ability to streamline project workflows. By creating a unified data management and communication platform, CDEs diminish redundancy and inefficiency, leading to smoother overall execution in return.

This asset is particularly beneficial in large infrastructure projects, such as the construction of highways or bridges, where a common data environment significantly reduces the time spent on data entry and verification. In addition, the streamlined approach saves time and reduces the likelihood of errors.

Key benefit: The centralized approach of CDE in construction allows for a more coordinated and coherent workflow, reducing the time and effort typically associated with data management.

Enhancing Collaboration Through CDE

Common data environments have been instrumental in enhancing collaboration in construction projects. By providing a common platform for information exchange, they enable seamless coordination among diverse project stakeholders. 

This feature offers a notable advantage in constructing high-rise buildings, where architects, engineers, contractors, and clients need simultaneous access to the project’s data pool. Real-time collaboration leads to a more dynamic, interactive project environment, where changes and updates are communicated instantly, significantly improving the outcomes.

Key benefit: Improved collaboration leads to a more integrated project approach, where decisions are made efficiently and project goals are achieved more effectively.

Informed Decision-Making via CDE

CDEs enable access to real-time, comprehensive data, which is crucial for informed decision-making.

In residential construction projects, for instance, project managers leverage CDEs to monitor progress, resource allocation, and budgetary constraints. The real-time overview enables them to make quick, informed decisions, adjust strategies promptly, and mitigate risks effectively. 

Key benefit: Informed decision-making allows project managers and stakeholders to act on the most current and complete information available, leading to more effective administration and better overall outcomes.

Implementing CDE in Construction Sector

While the benefits of a common data environment are clear, its implementation in the construction industry is not free of challenges. Common obstacles include the technological learning curve, resistance from staff accustomed to traditional methods, and the need for integration with existing systems. To successfully implement a CDE, it’s essential to address these issues head-on.

Discussions at forums like the European BIM Summit have highlighted the importance of standardized implementation methods that can unify the approach. This emphasizes the need for a cohesive strategy to encourage the adoption process in line with the global best practices across the industry.

Overcoming Implementation Challenges

Managing resistance to change is one of the main challenges of implementing CDE in construction. It requires clear communication about the benefits of CDE and how it simplifies tasks, along with highlighting its role in reducing errors and saving time.

Integrating disparate data sources into a common data environment is another common issue. To tackle this, start with a comprehensive audit of existing data and systems. Utilize specialized integration tools or services to streamline this process, ensuring a smooth transition.

Finally, adequate training and support are critical for successful implementation. Offer extensive training sessions and continuous support to ensure all users are comfortable and proficient with the new system.

Best Practices for Data Management in CDE

Effective data management within a CDE involves the quality and accuracy of data, clear governance protocols, and system maintenance that will ensure its ongoing efficacy. 

Key practices include:

• Regular data audits
• Clear documentation of processes
• Training all users on best data management practices

Case Studies and Success Stories

The case study conducted in Checz Republic is a comprehensive example of streamlining workflows with a common data environment in construction. It examines the remodeling of the As-Built documentation into the BIM and GIS environment during the railway construction project, specifically focusing on the Šumice railway station. 

The key aspects of the study include the transformation of documentation into a BIM/GIS-based common data environment, the challenges and solutions associated with this transition, as well as its benefits. The conversion from CAD to BIM CDE is generally found automatable at about 65%, leaving 35% to human decision-making.

Emphasizing the shift from traditional 3D CAD (Computer-Aided Design) documentation to a common BIM (Building Information Modeling) or GIS (Geographic Information Systems) data environment, the authors found that the use of documentation was particularly efficient during the operational phase of the construction, including tasks like maintenance planning.

The study acknowledges that current software systems can still have limitations in capturing geometric shapes with absolute accuracy. Despite these challenges, the authors found satisfactory solutions within the existing applications.

Their conclusion is that converting original CAD documentation into BIM significantly streamlines approval processes during construction preparation and execution. The data generated by BIM-managed software was also beneficial for other miscellaneous engineering and administrative purposes.

Future Trends in CDE

The future of common data environment in construction is shaped by emerging technologies such as artificial intelligence (AI), machine learning, and the Internet of Things (IoT). 

These technologies promise to enhance the capabilities of CDEs, offering more advanced data analytics, predictive modeling, and automation features. As the digital landscape continues to evolve, the role and impact of CDEs in the construction industry are expected to grow, further revolutionizing project management and execution.

Wrapping Up

The common data environment brings compelling digital change to the construction industry. It helps manage data, improve teamwork, and make better decisions, promoting successful outcomes of diverse construction projects. 

Companies like Intellectsoft take great pride in delivering sophisticated common data environment solutions, drawing on the broad international expertise in the field. As a dedicated provider of CDE and BIM platforms, Intellectsoft ensures comprehensive support at every phase, from initial planning and discovery stages to ongoing assistance.

The post What is a Common Data Environment (CDE) in the Construction Industry? appeared first on Intellectsoft Blog.

The need to create digital medical databases first came to light during the early 1990s. Medical workers recognized its capacity as a valuable resource for management and clinical research. However, due to privacy and other concerns, the innovation was adopted by many other industries before finding its way to healthcare.

So, What Is Data Warehousing in Healthcare?

Briefly put, data warehousing in healthcare is the most efficient file management system there is. It allows for storing, organizing, and handling vast amounts of information, from patients’ clinical histories and lab tests to insurance records and financial reports. It also minimizes the risk of human error and keeps the files secure.

If you are new to the world of digital data management, just imagine a giant, fully automated library that operates at light speed. Both comprise endless rows and columns of neatly stacked folders, color-coded and marked by letters, numbers, and signs.

The main difference between a perfectly organized physical library and a digital warehouse is functionality. The latter is capable of searching and integrating data from various sources all at once. Simultaneously, it performs complex analytics, supports administration, and helps identify weak links and areas with potential for improvement. 

Properly designed medical data software can compute and solve tasks within seconds, saving plenty of time you can invest in maintaining and improving the quality of service.

Good to know: Although they might sound synonymous at a glance, a clinical repository and a healthcare data warehouse are not the same thing. The clinical repository holds only clinical data, like patient records. Conversely, the data warehouse is a central repository that keeps, more or less, all kinds of files involved with the clinic’s operation.

Let’s now dive deeper into details and explore the benefits, features, and cost considerations of healthcare data warehouses.

Benefits of Data Warehousing in Healthcare

A healthcare data warehouse can be your most helpful tool for improving your medical business, making the best use of all information available. Centralized files and automated processing allow you to gain quick, sharp insights, optimize resources, and make well-informed decisions. 

Here is an overview of the most important advantages.

Improved Data Accessibility

We have already mentioned that a healthcare data warehouse resembles a giant library, which means all information resides in one place. Thanks to advanced organizing systems, it’s easy to find and use. A patient’s medical history, treatment records, and diagnostic processes, as well as administrative files—you can obtain anything within seconds. Such a rounded, encyclopedic picture allows you and your medical staff to provide the highest level of service in return.

In other words, by analyzing all available data, you can improve the accuracy of diagnosis and chances of therapy success. The ease of access also helps medical researchers to identify trends and develop new treatments.

Enhanced Data Analytics

The fans of Doctor House will remember how much diagnostics sometimes resembles detective work. A healthcare data warehouse is like a box of clues that pave the road to finding a reason why a patient is sick. The database contains details about the patient’s lifestyle, family history, habits and weaknesses, food and exercise info, allergies, and more. What’s best, it’s already completely set, systematized, and ready to use.

Through data analytics, you can track the clues and identify patterns that lead to the correct conclusions about patients’ conditions. 

Scalability and Flexibility

Many clinics and medical businesses start small but grow fast. When the patients become regulars, their files grow with every visit, and so does the clinic’s administration. Healthcare data warehouses can grow (or shrink, if necessary) to follow the development. Many tools can be added or omitted according to the ongoing needs.

The possibility of scaling the digital database means you can always have the product optimized to provide maximum convenience.

Data Security and Privacy

The patient’s privacy is holy to ethical practice. With that in mind, healthcare data warehouses are programmed to provide exceptional levels of data security. It involves applying high levels of protection against system breakdowns as well as hacker attacks.

Data warehousing in healthcare involves advanced and up-to-date security measures that keep all information safe from unauthorized access.

Streamlined Operations

The bigger the clinic gets, the more diverse services it provides, and your need for efficient data administration rises exponentially. A database warehouse in healthcare helps you optimize appointment scheduling, which will reduce waiting times and improve the patients’ experience in return. Moreover, it takes over the hassle of inventory management. Usage tracking makes it possible to alert the staff before a supply runs out and prevent shortages. And in terms of financial planning, the system can analyze the processes and patterns to identify the room for improvement. 

Due to its solution-oriented analytic capabilities, data warehousing pinpoints and optimizes every aspect of medical business. 

Predictive Analytics and Machine Learning

A giant, systematized database assists doctors in tracking down the underlying threats to the patient’s health. It recognizes potentially problematic habits, patterns, and genetic predispositions that might trigger a disease in the future. Knowing the risks helps you advise and take steps to prevent it from happening. On a larger scale, predictive analytics can also anticipate massively contagious outbreaks, such as seasonal flu, and prepare for it in advance. 

By collecting, organizing, and analyzing copious amounts of information, a warehouse database helps you prepare and react before the events occur.

Key Features of Healthcare Data Warehouse

Data Integration

Accumulating and integrating many kinds of data from diverse sources is fundamental for healthcare data warehousing processes. That includes:

• Electronic Medical Records (EMR)
• Electronic Health Records (EHR)
• Enterprise resource planning systems (ERP)
• Lab databases
• Public health databases
• …and much more.

Data integration enables keeping all valuable information in one place, which in return helps with overviews and predictive analytics.

Data Cleansing and Transformation

Just like any large, ongoing database, a healthcare data warehouse also needs occasional cleaning and decluttering in order to remain up to date. This is very important for several reasons, starting from removing duplicates, errors, and inconsistencies in available material that could affect predictions or test results. Moreover, the process identifies information holes and marks them for filling up. 

After cleaning, the data can be augmented, reorganized into a more optimized form, indexed, and sorted. 

Data Governance and Compliance

Data governance is the supervising element of a data warehouse in healthcare, a set of rules determining how to handle the content. It covers the whole information cycle, from creation to the moment it’s archived or destroyed. Moreover, as healthcare heavily relies on accurate, reliable information, data government also implements processes that will keep things relevant and establish through access control.

Data Security and Encryption

Apart from access control, extensive security measures involve:

• Encryption
• Firewalls
• Intrusion detection systems
• Regular security audits
• Staff training
• Regulation compliance
• Physical security 

A combination of advanced technology, robust backup and recovery plans, education, and physical server security creates an all-rounder network with high-security coverage. 

Data Querying and Reporting

Healthcare data warehouse models employ specific tools for querying and presenting information accurately. 

• SQL & Query Builders retrieve data necessary for a specific research
• Business Intelligence tools (BI) assist in visualizing maps of complex data
• Data mining tools are used for discovering patterns and relations in large data sets
• OLAP (Online Analytical Processing) supports data interaction for better analyses 
• Decision support tools integrate with warehouses to provide specific recommendations 
• Reporting software for creating formal tickets on patient’s care
• Self-serving analytics that aid non-technical users
• APIs & Integration tools responsible for real-time data processing and repotting 

These tools make it possible to efficiently retrieve, analyze, and report healthcare data, promoting informed decision-making and effective healthcare management.

Costs of Implementing Healthcare Data Warehouse

A range of small and substantial costs are involved between the initial setup and ongoing maintenance of a fully active healthcare data warehouse system. The final sum depends on many factors, starting from the size of the warehouse and its assets.

Costs of Initial Setup

• Hardware and infrastructure include the cost of physical servers and storage systems (this can be the most significant expense)
• Software licensing is the price you pay for healthcare data warehouse solutions, as they are
• Data integration covers the cost of integrating data from various sources
• Training & development is the price of educating and training your staff to use the new system properly 
• Consulting & expertise mark the cost of hiring external experts for planning and implementing the healthcare data warehouse.

Ongoing Maintenance Costs

Software updates and licensing are continual costs you will pay to your healthcare data warehouse vendors. Then, there is regular maintenance to ensure optimal performance and costs associated with managing, caring for, and updating the data.

Expect also ongoing expenses for data security, including regular audits and subscriptions. And finally, there is always staff training that will ensure the optimal use of all resources.

Return on Investment (ROI)

This is the sweeter art of the cake, which depends on several factors.

• Cost savings: Operational cost reductions
• Improved patient outcome: Adequate healthcare delivery often results in improved patient health, which can enhance the image and reputation of the health provider
• Efficiency gains: Time and resources saved by improved decision-making and streamlined administrative processes
• Revenue operations: New ROI opportunities generated through effective treatments and research opportunities

If you need a more precise estimation, you can compare the benefits to the total costs of installing and maintaining the data warehouse.

Healthcare Data Warehouse Case Studies

Mayo Clinics

Most renowned healthcare institutions worldwide use some kind of healthcare data warehouse model. Take, for example, the Mayo Clinic, which witnessed significant improvement in patient care efficiency, as well as in research capacities. Integrated records and research data streamline all processes, helping them deliver better experiences while boosting research capacities at the same time. 

After a while, the clinic reported notable improvements in treatment outcomes and patient health in general. Over time, thanks to data cleansing and predictive analytics, they also registered cost savings.

Kaiser Permanente Southern California (KSPC)

KSPC is one of the largest healthcare providers in the USA. They developed and maintained a medical research data warehouse for over a quarter of the century, extending it largely in 2006. Data integration greatly enhanced their preventive care measures, improved vaccine strategy, and helped them manage chronic diseases effectively. 

The application of a digital warehouse at KSPC made different study approaches possible by supplying specific data-based material. One such study explores the volume, patient characteristics, and age-adjusted prevalence of selected medical conditions.

The results showed patterns and age-related prevalence in obesity, asthma, atrial fibrillation, diabetes mellitus, hypercholesteremia, and hypertension, also noting the period when they escalated above the average. More detailed results of the study you can find here.  

Best Practices for Implementing Healthcare Data Warehouses

1. Begin with clearly understanding your goals and reasons for installing a data warehouse. 
2. Set the targets in most fields, from improving patient care to streamlining operations. 
3. Ensure data quality—it’s a healthy basis for all functions.
4. Establish strict protocols for data cleansing and validation. 
5. Choose a scalable system suited to your present needs and flexible enough to grow smoothly.
6. Maintain a strong focus on data safety and implement robust security measures.
7. Ensure compliance with healthcare regulations.
8. Involve end users in the process and collect feedback to make the end product more user-friendly.
9. Don’t skimp on training that will help your staff make the most of the software possibilities.
10. Set aside resources and make plans for ongoing maintenance that will keep the system at its best.

Wrapping Up

Implementing a data warehouse helps you centralize and streamline the management of all business and medical data necessary for successfully operating your clinic. Moreover, the long-term cost saving, multi-level efficiency, and broad potential for advanced research make them an invaluable asset for any healthcare organization.

Established companies like Intellectsoft take pride in providing healthcare IT infrastructure based on extensive experience and worldwide expertise. Their approach goes beyond bare software development to strengthen the core of your healthcare services. As a dedicated healthcare IT solutions provider, they offer comprehensive guidance at every step, from discovery workshops to continuous support.

The post Healthcare Data Warehouse: Benefits, Features and Cost appeared first on Intellectsoft Blog.

As a result, many organizations and entrepreneurs are interested in having custom-made websites with tailored sets of features. However, businesses and individuals are usually unaware of the cost of creating and running a website. So, in this article, we will describe the components of the total website development cost and define the price ranges for every step of creating and maintaining a website, depending on its complexity. 

Factors Influencing Website Development Costs

The average cost of building a website is defined by several factors that can be roughly divided into three groups: hosting-related, size-related, and complexity-related. One could compare website development to building a house, where the investments depend on the desired location, design, and materials.

The cost of a website is largely determined by its purpose. A landing page for a promotional campaign and an online store with hundreds of product names require significantly different amounts of effort and resources, so their development prices are wide apart.

Traditionally, the size of a website should match the size of the business. This means that it may be inefficient for a small company to invest in a large, feature-rich website. And vice versa, it may look suspicious if a large enterprise owns a single landing page or a template-based website with a default stock design.

Hosting

As a rule, when a customer asks to build a website from scratch, the developers also handle such aspects as name registration, selection of a hosting service provider and an adequate plan, purchasing an SSL certificate, and so on. A reliable hosting provider that offers scalable services is essential for the uninterrupted operation of a website. A good-looking top-tier domain name that is easy to remember may be expensive, but it is for brand recognition and attracting new customers. 

Size

The size of a website determines its structure, the number of pages, and the amount of content. In turn, these factors determine the volume of storage required to host the website and the corresponding cost.

Size and complexity also determine whether you have to hire a dedicated team or whether it is viable to build a website by yourself with or without the help of freelancers.

Complexity

The complexity of a website refers to a much more diverse set of factors determining the overall cost. Among them, the choice of technologies is the most impactful factor. In other words, the more features are needed, the more expensive and lengthy the website development will become.

If a website requires advanced features and integrations, its cost will increase, often dramatically. Implementing features takes more work hours from web developers and demands additional plugins, modules, and other paid features. 

Complex functionality also demands developers with high skill levels to handle advanced technologies. Their hourly rates are higher, and they are more difficult to find than junior- and middle-level web developers. 

Also, do not forget about the additional costs of website maintenance and promotion. Even though these expenses are technically “post-development,” they should be considered when you estimate a budget for creating a website.

So, How Much Does It Cost to Build a Website?

Different types of websites usually have specific combinations of size and complexity. Here are a few popular types of websites with approximate price ranges provided by Upwork. 

A small business website containing up to 16 pages will cost about $2,000-7,000. 

A large business website of up to 75 pages will cost about $10,000-35,000.

The cost to develop a website for e-commerce starts from $5,000 for an online store with 100 products and may reach $55,000 for a store with 1,000 products.

The total price can be broken down into several groups of expenditures that correspond to the stages of the development process. They include:

• Design and UX/UI expenses.
• Development and coding costs.
• Testing and quality assurance expenditures.
• Maintenance and ongoing support charges.
• Hosting and domain fees.

Ideally, all these activities should be performed by specific experts, which is the case if you hire a dedicated team. So, based on the list above, the team should contain the appropriate number of such specialists: web designer, copywriter, content manager, web developer, QA and testing specialist, and SEO specialist. 

Every phase of website development should have an adequate budget since they all influence the quality of the final product. Here are rough estimations for every stage:

1. UI/UX design. On average, this stage takes one or two weeks and costs from $700 to $4,000.
2. Front-end development. This stage may require various numbers of programmers depending on many factors, so the approximate time and cost may vary from two weeks and $1,000 to six weeks and $12,500.
3. Back-end development. If your website needs a lot of custom coding and third-party service integrations, such as payment processing systems, this stage can easily take up to eight weeks and cost $12,500. Luckily, in most cases, the average numbers are much lower: about three weeks and $4,000.
4. CMS and admin panel development. Every website needs a functional means of administration and content management. Even if your site uses a third-party CMS, such as WordPress or Drupal, it has to be customized according to your business needs. Creating a customized CMS may take from three to eight weeks and will add $3,000-9,000 to the total budget.
5. QA and testing. It is vital to test the website’s usability and security on different platforms, especially on various mobile devices. This process can be done manually and using specialized tools for automated testing. The average rate of a QA engineer is about $25/hour, so the total cost of quality assurance and security testing will be in the range of $500-5,000, depending on the size of the website and the number of tests.

The total website development cost also includes additional expenses on project management, content creation, SEO and promotion, hosting, and other activities.

Industry Trends Shaping Website Development Costs

In order to attract users and offer improved usability, your website should make effective use of current trends, such as:

• Mobile-first design.
• Responsive web development.
• Progressive web apps (PWAs).
• Voice search optimization.
• AI and chatbot integration.

Though implementation of these features will increase the cost of website development, their benefits are well worth it. They improve customer satisfaction, reduce operational costs, and increase efficiency, among other advantages.

Cost of Website Development by a Vendor Type

In most cases, when a company or an individual needs a custom website, there are three common options. The first one is contacting a software development company or a web design agency and hiring a dedicated team. The second one is hiring individual specialists on Upwork or similar freelance platforms. And the last option is to build a website using your own skills. Let’s look at the pros, cons, and approximate costs of these approaches.

Hire a Development Team

This is the most expensive but safe route to getting a custom website. Web development agencies have all the required skills and workforce to deliver projects of various complexity. They are an ideal solution for a busy entrepreneur who needs the result by a specified time. In addition to design and development, such agencies also provide other services, such as maintenance, SEO, marketing, content updates, business analysis, and so on. Often, web development agencies offer their services as all-in-one packages that may include discounts.

However, most agencies do not reveal their rates to a broad audience. Instead, they estimate the costs individually for every project. It is common practice in this industry, so you will have to contact several companies, tell them what kind of website you need, and ask for an estimate. The location of a web design agency also has an influence on the price tag. Nearshore development companies tend to charge more, while offshore companies offer better prices but involve additional drawbacks.

It should be noted that some agencies tend to decline small projects or give them low priority. Overall, the cost of hiring an agency to build a business website starts from about $15,000 and can reach $150,000 or even more. For most startups and small companies, this price is far beyond their budgets, making them look for cheaper options.

Hire an In-House Team

Hiring an in-house team or a department for your business company is not always viable. On one hand, you will have the same specialists as the hired agency as your employees. On the other hand, you will have to ensure effective management and working conditions. Moreover, the search process, interviewing, and other aspects of hiring are time-consuming. Sometimes, there are just no suitable candidates that match your criteria. 

An in-house team is viable if a website is the staple of your business and you do not want to rely on third parties to ensure its operation. For example, it is justified for an online store or a corporate website but may be excessive for a landing page or portfolio. Considering the additional costs of hiring, management, and work environment, an in-house team involves more investments and hustle than hiring a team from an agency.

Hire Freelancers

Even if you need just a small website, it is unlikely that you will find a “jack of all trades” capable of delivering it without extra help. Usually, you need at least three specialists to build a website and fill it with content: a web developer, a UI/UX designer, and a copywriter/content manager. This option usually means that you have settled for using a popular web builder that offers customizable CMS. The most common examples are Squarespace, Wix, Shopify, WordPress.org, and GoDaddy. 

According to Upwork, the average hourly rates of a web designer and web developer are $15-30, while the copywriter’s rate is $20-45 per hour. This means that a small business website built by freelancers will cost you from $1,500 to $5,000, while the price for a complex website that requires 1000 hours of work will be about $20,000-30,000. This sum largely depends on the implemented functionality, the amount of custom programming, the use of paid modules, and so on.

Do It Yourself

If you have free time, you can try to turn your idea into a working website using your skills and tenacity. This is a huge responsibility, so you need to evaluate your skills and available resources carefully. Most probably, you will have to learn a lot while working on your website, so this is a great chance to improve your skills. On the other hand, you will be able to handle only a small and simple project and will face many challenges during this process. That’s why you should think carefully and decide whether you are up for this task.

Currently, many website builders offer intuitive, no-code tools for virtually anyone. The basic functionality is generally free or very cheap, but any advanced features will require one-time payments or subscriptions. This way, you will save money on specialists and can spend it on premium features and paid functionality of a chosen website builder. Generally, this is the slowest way to build a website, even if you have certain experience.

If you resort to a bare minimum, then you will have to pay about $3/month for a combination of website builder and web hosting services at Hostinger, for example. A domain name ending in .com or .net will cost you at least $8 yearly, but you can also choose cheaper domains like .xyz or .shop for $1-2 per year. Many features and services will come free with the hosting plan. They will be basic but acceptable for simple websites.

Strategies for Cost Optimization

If your budget is limited, you will have to find ways to save money with as little decline in quality and functionality as possible. Here are some illustrative steps:

Make a priority list of features and functionalities. Setting up goals and priorities is vital for the development process in terms of product quality and budget efficiency.

Use open-source solutions and frameworks. There are plenty of web development tools for limited budgets. Websites created with web builders, theme templates, and CMS plugins are the common practice for small businesses. 

Employ Agile project management. Agile methodology enables great flexibility and predictability while also focusing on quality and customer engagement. 

Consider outsourcing instead of in-house development. Hiring a dedicated team is more cost-effective in many situations than running an in-house department.

Prepare for long-term expenses in advance. Don’t forget that your website will need maintenance, new content, and other updates and upgrades. Web hosting and other subscription-based services are cheaper in long-term plans.

How to Choose a Trustworthy Web Development Partner?

This mission is not the easiest, yet not impossible. Here, we’ll point out a few things to look at if you want to find not a random development team but trustworthy experts.

Experience and expertise. Check for how many years your selected software development company or freelance specialist has been active in their area of expertise. A veteran company is significantly more reliable than its competitors, who appeared six months ago. 

Case Studies/Portfolio. The first thing you will probably pay attention to when searching for a software development vendor is their portfolio. Trustworthy professionals give enough information about their projects so that their future clients can get a full picture of their expertise. Most importantly, pay attention to whether they mention real clients, at least in some case studies. If not, consider moving to the next candidate for the job.

Testimonials. Customers’ feedback shows the trustworthiness of the development partner. If clients of a web development company or freelancer leave no or mostly negative comments, this is a red flag for you. The best thing in clients’ testimonials is that they commonly specify the client’s name, occupation, and the company they own or work for. Thus, you can contact this person and additionally ask them to what extent their collaboration with the web development partner was efficient and smooth.

Presence in reliable catalogs like Clutch, GoodFirms, Business of Apps, etc. This works only for the companies. These catalogs are highly informative and useful because they also have testimonials taken directly from the clients.

Location. Web development partners that have offices in different countries are way more reliable than the ones with one specified location or not specified at all. Companies with several offices within one country or around the world won’t jeopardize all this hard work and their reputation with bad work and/or poor communication. 

Transparency. Pay attention to how much information your future web development partner shows on their website or profile and in private communication. Also, it wouldn’t hurt to pay attention to how they’re dealing with all the paperwork, like legal documents and agreements. This may tell you a lot about their reliability.

The cost of developing a website or other software. Too low or too high a price on services is always a red flag, showing that something is shady. Of course, if a company has years of experience and has become a globally renowned brand, it can have the website development cost way higher than the average on the market. However, if a company is new and doesn’t offer unique expertise in something, it may only show that this team very likely intends to leave the market soon.

As you see, the company’s website development cost shouldn’t be your only criterion when choosing your software development vendor. Those who choose the wrong one often pay twice, so choose yours wisely.

As a company that has been providing web development and other services for more than 15 years, we’ve worked hard on our reputation and our clients’ business well-being since day one. Today, we have offices in San Francisco, New York, London, and Oslo and an engineering workforce in 21 countries across the Atlantic. We are pleased to tell everyone that we have many Fortune 500 companies among our clients – Harley-Davidson, Melco, Hoosbaa, Clinique, Eurostar, and many more. However, we don’t limit ourselves to working with enterprises only. If you’re a startup, our cost of website development is reasonable for your business as well.

Conclusion

The average cost of website development comprises many factors – size, hosting, and complexity are among the ones that lie on the surface. However, there’s a lot more to mention – the size of the development team and the expertise level of each specialist plays a huge role in the total cost. If you need a website with complex functionality and infrastructure, you’ll need more than one or two specialists to build it. Thus, the website development cost increases. 

The location of development specialists has a significant impact on the average cost of website development. The hourly rate of software engineers from the US or Europe can be twice or three times higher than their colleagues from other regions. Another website development cost factor is expertise. Specialists with solid experience are valuable in the labor market, especially when they’re familiar with the peculiarities of different industries.

If you’re looking for a reliable vendor to build your website from scratch or upgrade the one you have, Intellectsoft is the best one for the job. For over 15 years, we have created and delivered more than 600 digital solutions for businesses of all sizes – from early-stage startups to SMBs and Fortune 500 enterprises. To learn more about our work, please check our most prominent cases for clients in such industries as fintech, healthcare, construction, eCommerce, transportation, and a lot more.

So, how much does it cost to build a website with the help of Intellectsoft’s team? Get in touch with us and tell us your project requirements. Our business development manager will reach out to you with the initial project estimation and recommendations. The cost of developing a website can be calculated only based on the specific information on your project. So, don’t hesitate to contact us to get a custom solution for your business at a reasonable price.

The post Website Development Cost: A Complete Guide in 2024 appeared first on Intellectsoft Blog.

Off the back of increasingly sophisticated automation and financial technologies, core banking is emerging at the forefront of this financial revolution.

As recently as 2022, the global market for core banking software hit an impressive 10.89 billion USD, and there’s no immediate sign the trend is slowing.

Experts predict a growth phase of 9.3% annually through 2030, and the USA, China, and Asian Pacific regions are leading the charge.

These stats are a clear sign of how crucial core banking has become in the day-to-day financial dealings with our banking institutions.

So, what is core banking exactly? Think of it as the powerhouse behind your bank’s operations. 

It is the back-end system that seamlessly connects different branches of a single bank, making facets such as loans and credit processing smoother and faster not just for the bank but for customers too. Read on to find out more.

What is Core Banking?

The term “core” is an acronym for ‘Centralized Online Real-Time Environment’, and represents both the physical and topological structure of core banking. It enables a bank to operate from both the perspective of the instrument itself and its customers as a single entity. 

Customers are provided with consistent and efficient services, regardless of where they live, their country, or even the presence of local bank branches. The core banking system is central to modern online banking, streamlining account management, loans, and transaction processes.

Customers who interact with a core banking system can expect more convenience and independence. Actions such as withdrawals and deposits are processed centrally by back-end servers, which can either be hosted on-premises or cloud-based. 

The servers handle everything from transaction processing to authentication, which ensures speed and security. The centralized servers are robustly protected against cyber threats, safeguarding customer and bank data.

Types of Core Banking Systems

Generally, core banking platforms are divided into two types:

• Traditional
• Digital-first

Traditional systems operate on the basic aspects of banking—the foundational services and processes one would expect from a “traditional bank.” 

Digital-first core banking, on the other hand, is at the forefront of financial technology (fintech). They leverage innovations such as automation, AI, and blockchain, offering advanced functionality and technologies to their customers.

Core Features of IT Core Banking

Typically there are several (information technology) IT features present in banking institutions that have adopted the core banking structure. Each key feature plays a role in shaping how the bank operates and interacts with its customers.

Real-Time Transaction Processing

Transaction processing done in real-time is a hallmark feature of IT banking. It ensures that financial activity conducted within the system, like deposits or transfers, are processed and updated instantly. 

This kind of fast payment system is essential for not only customer satisfaction but also the accurate management of banking records.

Unified Customer Data Management

Unified management of customer data is a vital component of core banking. Systems bring together information from various touchpoints to create a complete customer profile. 

The integrated approach facilitates the rapid delivery of personalized services and enhances risk management strategies. 

Multi-Channel Support

Customers who interact with core banking services will often experience multi-channel support. This enables the customer to engage with their bank through a myriad of different mediums – mobile apps, websites, or in-person visits. This ensures a seamless and consistent banking experience. 

The multi-channel support is particularly important with digital-first core banking systems, where a brick-and-mortar branch is not available.

Automation and Scalability

Automation in core banking software plays a key role in optimizing routine tasks. It reduces manual workload while simultaneously reducing the likelihood of errors. 

Equally important is scalability, which allows banks to expand their offerings and accommodate growing customer bases without sacrificing performance or security.

Multi-Factor Authentication (MFA)

Cyber security is taken seriously within core banking, due largely to both the centralized and mobile of the system. 

Multi-factor authentication adds an extra layer of protection and typically requires a customer to authenticate sessions and transactions with a one-time passcode or token. 

For example, a customer transferring money from an account can expect to authenticate the transaction with a 4-digit code sent to a linked device such as a smartphone. 

The feature is critical for safeguarding transactions and preventing unauthorized account access.

Know Your Customer (KYC) Onboarding

Finally, KYC onboarding is integral to IT core banking systems. KYC stands for ‘Know Your Customer” and ensures the bank thoroughly verifies the identity of new clients.

While traditional banks might have required a customer to bring physical identification such as a passport or residency papers, a core banking service can verify a customer with secure online submission of ID. 

This process is streamlined in modern systems, enhancing efficiency while adhering to regulatory compliance.

The Transformative Benefits of Core Banking Solutions

Core banking solutions, pivotal in the modern financial landscape, offer an array of benefits that not only streamline banking operations but also revolutionize the customer experience. 

From enhancing data security to boosting operational efficiency, these solutions are reshaping how banks function.

Enhanced Customer Experience

One of the most noticeable benefits of core banking systems is the enhanced customer experience. 

These systems allow for more personalized and efficient service, offering customers quicker transaction processing, easier account access, and a range of convenient online services. 

Improved Operational Efficiency

A core banking solution streamlines various banking processes, significantly improving operational efficiency. Automation of routine tasks reduces manual labor and minimizes errors, leading to a more efficient, cost-effective operation.

Enhanced Data Security

With the increasing prevalence of cyber threats, the enhanced data security provided by core banking systems is invaluable. 

These systems employ sophisticated security measures to protect sensitive customer data, ensuring safe and secure banking transactions.

Regulatory Compliance and Risk Management

Core banking platforms are designed to comply with the ever-evolving regulatory landscape, which is crucial for banks to avoid penalties and legal issues. 

These systems help in risk assessment and management, ensuring banks operate within the set regulatory frameworks.

Case Study: NKGSB’s Transformation with Core Banking

A prime example of the benefits of core banking solutions can be seen in the transformation of NKGSB, an Indian bank established in 1917. 

The traditional bank undertook a 17-month process to overhaul its traditional banking infrastructure. This was in collaboration with Modus and the InfoSys Finacle platform, a niche core banking software provider, and Data Systems Group.

This transformation included the implementation of Automated Clearing House (NACH/ECS), Real Time Gross Settlement (RTGS) systems, National Electronic Fund Transfer (NEFT), and Mobile Banking. The outcomes were remarkable:

• Unified Core Banking System: NKGSB moved to a single, integrated core banking system, enhancing coherence across its services.
• Internalization of Processes: Previously outsourced processes were brought in-house, leading to better control and integration.
• Automation and Information Capture: The automation of tasks and improved information capture significantly enhanced operational efficiency.
• Easier Access to Customer Data: Retrieving customer information became more straightforward, aiding in better customer service.
• Increased Readiness for Change: A core banking system means the bank is now better equipped to adapt to future technological advancements and market changes.

This case study of NKGSB not only highlights the multifaceted benefits of core banking rollouts but also demonstrates how traditional banks can successfully transition into the digital age, setting a precedent for others in the industry.

Challenges in Implementing Core Banking Solutions

While the transition to core banking solutions offers numerous benefits, it’s not without its set of challenges. These hurdles can range from technical complexities to human factors, each requiring careful consideration and strategic planning.

• Integration with Legacy Systems: Many banks operate on dated systems that might not seamlessly integrate with a modern core banking solution. 
• Data Migration and Cybersecurity Concerns: Shifting data from legacy systems to new core platforms involves significant risks. The process needs to be secure to protect sensitive financial information. Additionally, ensuring data integrity during migration is a critical challenge.
• Staff Training and Change Management: The shift to a new system necessitates staff training. Employees must be brought up to speed with the new technologies and processes. 
• Cost Implications and ROI Analysis: Implementing a core banking platform often requires substantial investment. Banks need to conduct thorough cost-benefit analyses to ensure that the long-term return on investment (ROI) justifies the initial expenditure.

Pioneers in Core Banking: Fintech Success Stories

SDK Finance: As a veteran fintech software vendor with over 15 years of experience, SDK Finance has carved a niche in enabling various financial services like P2P lending, mobile banking, and e-wallets.

Skaleet: Next-generation platform, scalable and capable of continuous deployment. Skaleet specializes in services like card issuing and banking accounting, underpinned by robust KYC, KYB, and AML-CFT frameworks.

Fintech Lab’s offerings are comprehensive, including PSD2-compliance, SWIFT, neo-banking, and open banking APIs. Their solutions, which also cover e-wallets and currency exchanges, are popular across Europe and Asia.

The Future of Core Banking Platforms

As we peer into the future of banking, it’s clear that the sector is on the cusp of a transformative era propelled by emerging technological trends. 

These advancements promise to redefine the banking experience for both institutions and customers. 

Let’s explore the key trends shaping the future of banking.

• Instant Real-Time Banking: The shift towards real-time banking is accelerating. This trend is about providing immediate transaction processing, account updates, and customer notifications, making banking more responsive and efficient.
• Open Banking: Open banking is revolutionizing the industry by promoting greater financial transparency and data sharing between banks and third-party providers. This fosters a more interconnected and innovative banking ecosystem, offering customers more personalized financial services.
• Artificial Intelligence (AI) and Machine Learning (ML): AI and ML are at the forefront of driving smarter, more predictive banking solutions. From personalized customer service to fraud detection, these technologies are enhancing the efficiency and security of banking operations.
• Blockchain: Blockchain technology is gradually gaining traction for its potential to enhance security, transparency, and efficiency. Its application ranges from secure transactions to streamlined cross-border payments, presenting a new frontier in banking technology.

As these trends continue to evolve, expect core banking deployments to become more agile, secure, and customer-centric. 

The Future of Banking with Intellectsoft

As we conclude our exploration of core banking, it’s evident that this field is about redefining the banking experience. 

From the integration of real-time processing and open banking to the innovative use of AI, ML, and blockchain, the core banking system is set to revolutionize the financial landscape.

At Intellectsoft, we stand at the forefront of this transformation. Our expertise in financial software development propels banking and financial services into the future. We specialize in crafting customized online banking platforms, and mobile apps with a focus on security and user-friendly UI/UX, and systems integration. 

We have implemented cutting-edge solutions in blockchain and cryptocurrencies, digital wallets, and AI & ML technologies to redefine efficiency and customer service in banking. 

Our success stories, including a blockchain wallet app and a banking web portal, demonstrate our commitment to innovation and excellence. 

Join us in this journey to architect new banking experiences and advance your business performance with Intellectsoft’s future-proof solutions. 

Embrace the change, and let’s shape the future of banking together.

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