What will make your software product competitive in 2024 and beyond?

Oleg Lola, founder and CEO of MobiDev, a bespoke software engineering and consultancy firm.

Software is an important part of business operations, but software is never static. Every year, C-level executives face new strategic challenges, driven by evolving software development practices, outdated technologies or emerging trends that require companies to adapt. These decisions often involve choosing between extremes: whether to implement DevOps, infrastructure such as code, AI or blockchain, or to completely ignore market changes with all the possible consequences.

While there is no universal advice, I want to provide a strategic look at the software elements you need to look at as a manager to maintain your competitiveness and be future-proof without jumping between trends. This includes understanding the direction you want to go, surviving the transition, and optimizing the modernization pipeline.

Stay ahead of the trend curve

The direction your product moves should never focus on a specific technology as the ultimate problem solver. With the recent rise of generative AI and large language models (LLMs), specific market segments have been bombarded with offers to implement wondrous AI features and improve their business performance. While GenAI is a powerful tool, the value it brings depends on how prepared your product is in terms of data, compliance, and infrastructure.

My company, MobiDev, has received a lot of requests in 2024 to integrate ChatGPT or similar generative model functionality from customers. However, many companies focus solely on the benefits that LLMs can provide, without considering what it takes to maintain a custom model and where it will pull the data from. This situation is reminiscent of the great shift to cloud technologies, where even large companies moved their old monolithic applications to new infrastructures without conducting thorough platform analyses, code audits, or decommissioning legacy technologies before adopting the innovation.

Among other aspects that prevent companies from quickly modernizing and implementing new technologies, there are two central points that I encounter most often:

1. Absence of technical resources

Or, more precisely, the lack of internal development teams that have the required tech stack to meet both platform maintenance and modernization needs. A common approach for a mid-sized company is to retain just enough development staff to support core business activities.

When it comes to upgrading your existing frameworks or implementing data-centric technologies, AI features or AR components, managing the existing workforce to cover the required tech stack can become an issue. An IBM survey on generative AI adoption found that 40% of respondents surveyed plan to hire additional staff, while 53% are already struggling to fill key technology roles. Another part of the market tends to meet their technical needs by outsourcing and sourcing talent from specialist suppliers offering team expansion or special team services.

2. Fear of long transition periods

This is the second factor that affects the entire process of updating existing software. The operational problem with regularly and quickly modernizing software lies in the time it takes to develop a strategic plan while minimizing downtime. As a result, modernizations tend to occur less frequently, usually every few years, and often involve the adoption of new cultural approaches, development practices, or major updates.

How to overcome transition challenges

Transitioning from an old solution to a new one can take quite some time, especially if no updates are made. It is typically the responsibility of the CTO or CIO to find contractors and explore ways to reduce risk, minimize operational downtime, and develop a plan that meets the needs of all stakeholders within the organization.

To prepare for this transition, I recommend taking the following steps, which can help lay a good foundation for adopting new technologies:

Understanding the value of consultancy

Consulting is particularly valuable for organizations that do not want to scale their own engineering teams or do not have the resources to develop in-house expertise. Consulting services offer practical benefits and provide an in-depth analysis of your software solution, along with development plans and time and budget estimates.

Prepare your data

Digitizing, extracting, transforming and synchronizing your business data is the key to becoming a data-driven organization. Master data management (MDM) solutions can ensure that data feeds are synchronized across channels. This creates a fully operational data hub that prepares your organization to adopt AI solutions as part of application modernization.

Resolve regulatory and compliance issues

Creating new data sources or processing methods can lead to serious problems if regulatory compliance and data protection rules are overlooked by the industry. Sensitive data usually needs to be anonymized before being used in AI solutions to avoid legal complications. Additionally, security measures must be implemented during development, including compliance with regulations such as the EU AI Act, GDPR, CCPA, CPRA, or industry-specific standards such as HIPAA.

Ensure test coverage and documentation

During the development phase, it is important to prioritize security. Writing tests for your code shortens the transition period by minimizing the risk of downtime and operational disruptions. In addition, it is important to create clear documentation of the work performed or request it from your software supplier.

Continuous software modernization

Modernization should not be seen as a strategic initiative that happens every now and then. This often results in a large list of changes that you want to implement at once, but that you have difficulty with due to the rapidly changing technology landscape.

Incremental upgrades and continuous modernization ensure better stability and faster response to market needs without losing grip on your competition. Gradual preparations and continuous improvements help companies stay ahead of the trend curve and be ready to adopt the required technology as soon as it is needed.

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