Amidst the barrage of industry buzzwords and fleeting trends, the core foundation of most organizations—data strategy—often does not make the headlines. Yet, this vital function is where the real story unfolds. If you are reading this, you might wonder, "Why hasn't data strategy been part of all the hype or news cycle recently?” Let me be candid: I have been in the trenches. I have worked with data for supply chain, enterprise resources, manufacturing, with data-at-rest, with data-in-motion, as an ethical hacker, and in solving data visualization challenges. I have led data transformations that scaled mountains and faced the abyss of our own data disasters.
But here is the thing - I have learned what is at stake and how to minimize disasters. And that is invaluable.
Data is not merely numbers or files; it is the lifeblood of your business. Yet, mishandling it can lead to nightmares. Data protection is not just about avoiding fines or preserving your brand image; it is about keeping your company's heartbeat steady. I have sat in those agonizing meetings with teams facing the grim reality of lost data. It is an experience that etches the weight of data responsibility deep into one's soul.
Automation gone wrong is not just about wasted resources—it can derail entire business strategies. I have witnessed automation projects run off the rails, yielding nothing. But from those failures, I learned to spot the pitfalls in the project lifecycle, to understand the nuances, and to respect the fine balance between human and machine. Now, when I talk automation, it is not from a theoretical standpoint but from a place of well-earned scars and celebrated triumphs.
Change Management that ignores the human factor in change can send shockwaves through an organization. I have seen firsthand the turmoil, the unspoken frustrations, and the quiet departures that occur when change is mismanaged. Raw data does not capture the apprehension of a team facing change or the morale impact when a transition goes awry. But I have been there, leading the charge, feeling the resistance, and eventually guiding teams to the light at the end of the tunnel.
Process Mining is not just a technical task—it is a pulse check for your business's operations. If you misread it, the consequences can be catastrophic. I recall when a misalignment in process mining painted a rosy picture, while the company was on the brink of a collapse. But from the ashes of those missteps, I have built a toolkit of wisdom that ensures we are not just skimming the surface, but diving deep, understanding core issues, and engineering sustainable solutions.
I am not here to give you textbook answers. There is a world of difference between reading about a storm and weathering one. In the landscape of data strategy, I have experienced a wide range of situations. So, when I share advice, know it has been forged in the fires of real-world challenges. Every piece of advice and strategy I suggest is backed by experience, both good and bad.
There is a saying in our industry: "Trust but verify." Well, I am laying my experiences on the table, the good, the bad, and the downright ugly. That is what real-world experience looks like. And that is why, when I talk about data strategy, you should listen.
