Is your data ready for AI?

As I catch another Chicago Fire game last night with my good friend, Mark Tack along with my colleagues since the last Messi no-show game, the turnout and quality of the game aren’t what I was expecting. Although not to the level of fair comparison, Messi’s presence (or absence) can cause some impact to crowd turnout and gates revenue but probably never to Taylor Swift’s level. Since the quality game was not capturing much of my attention, my mind started to drift recalling the last meeting where both Mark & I were speaking at a Chief Data Officer conference a few months ago.? Mark was speaking on the growing importance of having a unified Customer data and Organization can get ahead of its competitors by mastering and getting a strong foothold of their first party customer data with a well-established CDP (Customer Data Platform) through Treasure Data who recently became one of the top leaders in Gartner’s Magic Quadrant while I emphasized on 6 core business dimensions that any Organizations must mature fundamentally as they begin to embark on the latest AI, GenAi trail.

?At a recent IDC-CIO round table poll I also found out that ~70% of those who attended does not have a well-articulated data strategy, ~60% struggled defining their single source(s) of truth, ~50% have challenges with their role of leadership in creating a data-aware environments, ~70% also struggled with establishing data governance and security of data and were challenged utilizing data from any source including unstructured data.?

As technologists and data enthusiasts, sometimes we are too eager to experiment with advance and emerging technologies but neglected at times to remind ourselves to associate these efforts with an intended business outcome. It comes back to Value Enabling, Value Creating and Value Realizing. This is necessary if you want to press home as part of your digital AI-led advantage that you’re trying to capture. The “why” is now more important than the “what, when & how” as more than 75,000 AI startups continues to populate the globe today.

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Whether you have Customer or Product as your center of your universe, start developing an Enterprise Data Strategy (EDS) and align all of your core business dimensionality towards it. Seek and build your core foundational Multi-Facet Data Domains while asking “what are the core critical data elements required to produce those Business Outcomes?”? Drill down to the next layer of various work streams, core initiatives or programs checking to see if they are supporting your EDS with the required level of data disciplines - integrity, quality, consistency, and accuracy. And if they aren’t, build all the required Data Governance Pillars and underlying rigors and process to get them some minimal level of maturity to prepare your Organization’s level of readiness. That readiness should also incorporate your AI talent pool. And then begin measuring their progress as we all know, you can’t manage if you can’t measure.

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Wrap all of the above with the warm embrace of Organization Change Management process to address your cultural and mindset shift and you should be on your journey to tackle any AI initiatives in a more prudent manner.

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Quick win is never quick. At least, you’re heading in the right direction!

p.s. Being a former player, referee, coach and mentor, I can't help but share that you check our Mark's lad who at his age is a phenomenal soccer player constantly sharing unselfishly all of his tips and tricks!