tylers-blogger-blog

Most "data strategies" are built like a museum: collect everything, label it nicely, and hope someone strolls through and discovers insight. The contrarian view is simpler-and more uncomfortable: your data strategy is not a storage strategy, not a dashboard strategy, and definitely not a "we should track more things" strategy. A better data strategy is a set of deliberate constraints: what you will measure, what you won't, which decisions you want to accelerate, and where you'll tolerate ambiguity. That sounds like less data, not more. And that's the point. The mistake: treating data like an asset you should hoard Here's the common pattern: 1) A leader says, "We need to be data-driven." 2) Teams instrument everything "just in case." 3) A warehouse fills up, a BI tool goes live, dashboards multiply. 4) People still argue in meetings-now with screenshots. The quiet reason this fails: hoarding data doesn't create clarity; it crea...

We didn't call it a "data apocalypse" at the time. We called it "that weird spike," "the numbers are off again," and-my personal favorite-"let's just refresh and see if it fixes itself." Then came the day every metric disagreed with every other metric. Revenue looked down 22%. Signups looked up 40%. Paid CAC doubled. And the CEO asked the sentence that makes analytics teams age ten years instantly: "Which one is right?" The problem wasn't one bug. It was a chain reaction: a tracking change shipped late Friday, a backfill job that silently timed out, a dashboard built on top of a view built on top of a sheet someone "temporarily" edited. We were one Slack message away from deleting something important just to stop the bleeding. The Apocalypse: When Manual Analytics Collapses Here's what the failure looked like in practice: Multiple sources, one metric name: "Leads" meant "form submits" in on...

If you'd asked our leadership team a few years ago whether we were "data-driven," we would have said yes-confidently. We had dashboards. We had reports. We had a BI tool. What we didn't have was alignment. Different teams tracked the same metric three different ways. Operations loved spreadsheets, Sales wanted leaderboards, and Product cared about cohort charts. Meetings turned into debates about whose numbers were "right," and decisions happened late (or not at all). The turning point wasn't buying a new tool. It was building a visualization strategy: a shared, repeatable way to turn questions into visuals that drive action. Below is the blueprint we used, the practical choices we made, and the examples that helped us move from "pretty charts" to industry-changing outcomes. 1) We Started With Decisions, Not Dashboards Our first mistake was building dashboards around available data rather than critical decisions. We fixed this by flipping the w...