I'm a big fan of XKCD.com - described as "a webcomic of romance, sarcasm, math, and language."
Randall Monroe is a fantastic, fun author and his site is hilarious! I can easily go through a full cup of coffee on his site, scrolling and chuckling to myself.
But, this comic in particular stands out as an all time truth:
Can anyone else relate?
If you've ever tried to consolidate all your company’s data into a single system, then you know the frustration captured here.
You think, "We just need to get everything into [insert your system of choice] and we'll be good."
But, what ends up happening is you get some of the data into the chosen system, but still retain the other systems.
The result? A worse situation in the end because you're dealing with those other systems plus this new one.
The reality is your data has momentum, and trying to force it all into one place is a losing battle.
Instead, I believe the focus should be completely different. Forget about trying to move data anywhere. The only thing that matters is, can you find it for the purpose that you need?
Let me show you what I mean in today's post.
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Plain and simple - data has inertia. It wants to stay where it is.
Plus, you add in the fact that users are often resistant to change, legacy systems hold historical records, and no single platform can meet every need.
The impulse to centralise often stems from a desire for control, but the effort required to migrate and maintain data in one system rarely justifies the benefit.
Rather than moving data around for the sake of historical habit or chasing some cloud or feature dream, companies can instead focus on finding and using information for specific purposes.
That purpose could be a productivity purpose, a compliance purpose, or even something as simple as being required to delete it by policy and law.
But, if you can find what you need, you're good. You don't need to move it anywhere.
AI thrives on fast, reliable access to data. Instead of centralising everything, companies should prioritise accessibility in context.
Again, the key isn’t where data lives, it’s how easily AI and employees can access and use it.
Businesses that skipped legacy infrastructure are already ahead, with data primed for AI-driven insights and automation.
Treating data like "digital paper" is limiting.
Instead, businesses should remix and reuse information dynamically, creating flexible, modular systems that work with AI.
Here's a look at this type of AI search in action.
Rather than spending time and resources on consolidating everything into one system, organisations should embrace a decentralised but accessible approach.
Let AI do the heavy lifting, ensuring that data is available when and where it’s needed.
The future of data management isn’t about features and storage locations, it’s about intelligent access, remixing, and reusability.
Did this topic resonate with you? Still have questions? I'd be happy to connect with you. Book a 15-min meeting with me below.