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Since our company's inception, we have had the privilege of engaging with a diverse range of customers, all grappling with a common challenge-the management of their data. Whether a small business or a large enterprise, the issue of technical debt, a result of short-term thinking about data, is a consistent theme. Technical debt, in this context, refers to the cost that accumulates when short-term solutions are implemented to address immediate needs, leading to a complex, inefficient, and duplicate data infrastructure over time.
This technical debt spawns from a patchwork of applying technologies one by one, reacting to a current need. A prime example is when companies opt for a do-it-yourself plan because they don't have to engage procurement or IT and currently have resources available. Aside from the expanding technical debt, this strategy ignores the ongoing service support issues that cost 10x what an off-the-shelf product when looking at the total cost of ownership. I have observed extreme examples of this behavior at companies that have been around for many years. The decision to patch things and solve a short-term pain is very tempting. Leaders convince themselves they can do it cheaper and better because it is custom-built for them versus the pain of trying to convince stakeholders to procure a product.
It's clear that addressing and reducing technical debt is not a simple task. It requires a structured methodology for identifying, justifying, and funding new projects. This funding is not just about acquiring technology; it's about generating the emotional momentum needed to overcome the inertia that has built up over many years in replacing outdated technology.