The Data Leader's Reset: From Reporting to Decisions (Part 1 of 3)
A few years ago (possibly more, I’m getting old and my memory is going), I was talking with one of the managers on my team and updating our list of deliverables. I asked what I thought was a pretty simple question.
“What does this get used for?”
He sort of stumbled around for an answer before circling back to who had asked for it, the history of why we were updating it, and why no one else could do it. All true, and it answered “why” we did it, but without really explaining why it was important to our stakeholders.
I didn’t realize it at the time, but that conversation was the start of my first reset. At the time, I didn’t think I was doing anything particularly dramatic, but it was the first iteration of a framework I’ve used a few times since. It was a trigger that made me sit back and think we’re doing a lot… But does anyone notice?
If you’ve been in your role for a year or two and you’re starting to feel reactive in a way you didn’t use to, consider your own reset.
Over the next three weeks, I’m going to walk through each phase of a 90-day framework for moving your team from reactive reporting people love but don’t look at to decision products that drive decisions. This is a condensed version of a longer guide in the Penguin Analytics store.
Here’s the first phase.
Get the picture you’ve been avoiding
You suspect a lot of your dashboards go unused. That suspicion is probably well founded - it was for me - but it isn’t evidence. Before you can have a real conversation with your manager about changing how the team operates, you need numbers.
Pull a list of every dashboard, scheduled report, and self-serve artifact in your BI tools. For each one, capture the basics: name, owner, audience, topic, and last-accessed date. Sort them into three rough tiers based on usage. Active means the intended audience is using it regularly. Stale means a handful of people still check it, but not consistently enough to call it part of a workflow. Dead means it’s been 90 days or more, or close enough that nobody would notice if it disappeared.
You don’t need a perfect census. Most teams that run this for the first time find half to two-thirds of their dashboards fall into stale or dead. That number stings. It’s also the single most useful piece of evidence you’ll generate in this whole process, because it converts a vague feeling into hard data.
Spend a few focused hours, not a few weeks. The point is to have something honest enough to anchor a conversation.
Sort the work into three buckets
Once you have the census, classify your team’s current effort into three categories.
The first bucket is critical decisions. Work that directly supports a recurring decision with real economic impact. Pricing reviews, capacity planning, churn mitigation, board reporting. The dashboards and analyses where, if they broke, someone would notice the very next cycle.
The second bucket is nice to see. General visibility that isn’t tied to a specific decision or cadence. Operational views, exploratory analyses, self-serve tools with a handful of casual users. Useful background that sometimes uncovers opportunities, but nobody is choosing differently because of it.
The third bucket is noise. One-off reports that were never retired, dashboards built for a launch and forgotten, ad-hoc requests that became permanent artifacts. This is the graveyard.
The line between bucket one and bucket two is where the hard thinking happens. A dashboard can be well-built and well-liked without being tied to a decision. Remember, popularity isn’t impact.
Create space and stop the bleeding
Now you have a picture, it’s tempting to dive in and start cutting dashboards, but you’re not ready to retire anything yet. What you can do is stop adding more to the pile.
Introduce a soft intake filter. When someone asks for new work, ask three questions:
What decision is this for?
When does that decision need to happen?
Who owns it?
If the requester can’t answer the first one, the request goes to a parking lot rather than into the team’s backlog.
You don’t need to make this a policy announcement. It’s a one-conversation-at-a-time shift in how requests get scoped and accepted. Most stakeholders, when asked what decision their request supports, will either give you a real answer or quietly let the request go. Both outcomes are wins.
One conversation that makes the rest possible
Everything above is preparation for one meeting. You need your manager’s explicit backing before you start retiring anything or saying no to anyone senior.
Book sixty to ninety minutes and walk them through:
What you found in your census.
What you want to change.
What you need from them.
Frame the problem in their language. If they care about ROI, show them how much team capacity is consumed by work disconnected from decisions. If they care about executive trust, show them the usage data alongside the dashboards leadership keeps requesting.
Then ask, specifically, for three things:
Backing when you start saying no to low-value requests,
Help identifying which decisions matter most to leadership,
Ninety days before anyone judges whether this is working.
If your manager won’t back the reset, you have a different problem than the one this guide solves. You may need to run a smaller pilot, prove the value on a single decision, and come back with evidence. That’s slower, but it’s still a path.
A little assignment
This week, pull the usage data for your ten most prominent dashboards. Not all of them. Just the ten you’d name if a peer asked what your team produces.
For each one, write down the last-accessed date and the decision it supports. Be specific. “Operational visibility” doesn’t count. “The Tuesday pricing review chaired by Sarah” does.
Look at the list. How many of the ten have a decision name next to them? How many of those decisions actually happen on the cadence you assumed?
Whatever the answer is, that’s where the reset starts.
This is the first of three posts on running a 90-day reset for a team that’s drifted into reactive mode. The full guide, with the census template, sample language for the harder conversations, and worked examples from real reset scenarios, is available in the Penguin Analytics store.