How the Not-Invented-Here Syndrome can slow you down

In the early 2000s, Open Innovation emerged as a response to the Not-Invented-Here(NIH) Syndrome - a mindset particularly prevalent in engineering and IT organisations.Companies often preferred to build their own solutions rather than adopting existing ones, even when viable alternatives were readily available.

The rise of open innovation, open source, and open data has since accelerated technological progress for everyone. Instead of investing heavily in developing proprietary solutions, businesses can now leverage what already exists, saving time, money, and effort.

Why do companies still build their own solutions?

Despite these advancements, some businesses still choose to develop their own versions of existing solutions. The reasons often include:

• A belief that their needs are unique - assuming no existing solution will fully address their challenges.
• A desire for ownership and control - feeling that an in-house solution offers more flexibility or security.

However, these assumptions often lead to inefficiencies and long-term challenges.

Why reinventing the wheel can be a costly mistake

If a solution already exists in the market, trying to replicate it internally is rarely the best approach. Here’s why:

1. Existing solutions are already optimised. Established providers continuously improve their products, meaning businesses benefit from ongoing innovation at a fraction of the cost.
2. It’s more cost-effective. The upfront investment has already been made by others, allowing you to buy into a mature solution rather than funding development from scratch.
3. Avoiding long-term technical debt. When you build your own solution, you’re responsible for maintenance, updates, and troubleshooting, costs that only increase over time. Dependence on internal teams or external consultants can create bottlenecks and slow progress.

The trap of sunk costs

Once a company has invested in a proprietary solution, it becomes difficult to abandon, even when it’s no longer efficient. This is how businesses end up with a giant with feet of clay, a fragile system that limits agility and innovation.

The Smarter Approach

Rather than building something from the ground up, focus on what differentiates your business. If a solution already exists in the market, build on top of it rather than duplicating efforts. The key to staying competitive isn’t in owning every piece of technology, it’s in leveraging the best tools available to drive your core business forward.

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n today’s business world, being data-driven is no longer a question; it is a necessity. Organisations that don’t understand how to work with data and leverage it risk falling behind or even going out of business. However, merely being data-driven is not enough anymore. The rapid growth of access to artificial intelligence (AI) and lowered computing cost has amplified the significance of data, driving a shift towards predictive (and even prescriptive) intelligence to stay ahead of the competition.  

Transitioning from a data-driven to an AI-driven organisation presents immense opportunities, enabling companies to understand the competitive landscape better, and leverage both market predictions to gain an edge, as well as improving operations to lower operating expenses. This transition requires a fundamental change in how we operate and organise the company. Secondly, we need to decide where to start, and whether to build, or buy a solution.

Here we share five, simple, steps to ensure your organisations success in this transition.  

1. Management must clearly state that it is a goal

Achieving success with a transition is a strategic choice and an executional leadership challenge. It is crucial for management, whether top-level executives, business unit leaders, or team managers, to clearly communicate that the goal is to capitalise on the benefits of being data-, AI-, or analytics-driven, and where these benefits will have an impact, and why the transition is imperative for the organisation’s success. Leaders should:

• Clearly state the necessity of this transition for organisational success.
• Be transparent about the potential challenges of the transition.
• Accept that the transition might take longer time than anticipated, especially if immediate benefits are not apparent.
• Repeat the goal, ensure regular follow-ups on the agenda, at least monthly, preferably weekly, and support.

2. Organise the transition

Clarifying responsibility is essential as well as identifying the right person to lead the operational work of the transition. Allocate funding centrally rather than locally to prevent initiatives from being perceived as competing with short-term operational needs. By centralizing funding and clarifying responsibility, organisations can ensure that the transition to an AI-driven approach is viewed as a strategic investment rather than an operational cost.

3. Disseminate the solution broadly

It is unfortunate when initiatives become confined to a single department or individual. The benefits of an AI-driven approach are significant and extend across the entire organisation. Therefore, it is crucial to integrate solutions into as many teams as possible where there is a business case. Engaging more teams in the adoption phase offers several benefits:

• Shared costs across more teams.
• A unified language and collaborative efforts towards success.
• Accelerated transition and higher combined ROI.

Avoid placing the burden on a single individual. Employ the innovative power of the entire organisation to achieve greater success.

4. Embed new solutions in daily routines

For new solutions and strategies to work, they must be integrated into daily operations. Overcoming existing habits and ways of working requires repetition until the new practices become habits. Incorporate the use of data and analytics tools into the organisational rhythm, such as in weekly meetings or daily stand-ups. Measure the impact of these new practices and share the progress with the entire organisation. Highlight how the transition is improving efficiency compared to previous methods.  

5. Embrace an Adaptive Mentality

Fostering an adaptive mindset is crucial for the transition to an AI-driven organisation. This mindset should infiltrate the company culture, regardless of role. Here are three tips for building a stronger adaptive mindset:

• Identify and support superusers who can inspire and motivate others.
• Hire individuals with an innovative mindset, both leaders and employees.
• Promote a supportive culture through promotions, celebrating successes, and sharing positive results.

It might sound simple, but actively working on lifting and promoting the right people is very often overlooked. Make sure it is part of the leaderships action plan so this practice doesn’t fall between two chairs, or is forgotten within a couple of quarters.

Conclusion

Building a data and AI-driven organisation is essential for maintaining competitiveness in today’s business environment. Transitioning from being merely data-driven to embracing AI and predictive intelligence offers significant advantages, including a better understanding of the competitive landscape, leveraging market predictions, and improving operational efficiencies.

To ensure success in this transition, organisations should follow five key steps. First, management must clearly articulate that becoming an AI-driven organisation is a strategic goal. This involves transparent communication about the importance and challenges of the transition, along with regular follow-ups and continuous leadership support.

Second, organising the transition is crucial. This includes clarifying responsibilities and centralizing funding to ensure that AI initiatives are viewed as strategic investments rather than operational costs.

Third, disseminating the solution broadly across the organisation is vital. Integrating AI solutions into multiple teams enhances collaboration, shares costs, and accelerates the transition, leading to a higher overall ROI.

Fourth, embedding new solutions into daily routines ensures that these practices become ingrained in the organisation’s operations. Regular use and measurement of the impact help highlight the efficiency improvements over previous methods.

Finally, fostering an adaptive mentality is essential. This involves supporting superusers, hiring individuals with an innovative mindset, and promoting a culture that celebrates successes. An adaptive mentality ensures the organisation remains agile and responsive to new opportunities.

By following these steps, organisations can effectively leverage data and AI, achieving sustained success in an increasingly AI-driven world.

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