There is a version of AI governance that operational leaders are right to be suspicious of. It shows up as a long policy document and a set of rules written by people who have never had to ship a working report on a deadline or an enterprise wide workflow. It restricts without enabling. It produces compliance theater instead of actual confidence. If that is what governance means, I understand why a busy operations or finance leader would want to skip it and just let people us

A few years ago I recorded a short video for Transportation and Construction GIRL. I was a BI Developer at MCG Civil, which is now HEI Civil, trying to explain what business intelligence meant to people who had never heard the term. I talked about data. About collaboration. About how it was okay not to know everything. About how I ended up in construction not because I planned it but because I wanted to help people and the work kept growing. I was not a Director yet. I did no

A few years ago, I started as a BI Developer at MCG Civil (now HEI Civil). Today, I'm the Data and Automation Director and I'm still learning. But the journey between those two roles taught me something that nobody will else will tell you: you don't have to know where you're going to get somewhere amazing. How It Started I came into the construction industry wanting to do one thing: help people and make a positive impact. That sounds simple, right? But in construction, impact

You built it right. The dashboard is clean. The automation works. The data is solid. But nobody uses it. Or worse, people build workarounds around it. So you assume the problem is the tool. Or the people. Or the process. Usually, it's none of those. The Paradox Every Leader Knows You implement controls. You deploy automation. You collect data. You generate reports. Leadership sees all the reporting. But no action is taken. This isn't a technical problem. It's a system problem

Most organizations don’t struggle because they lack access to data. They struggle because their data lives in too many places, shaped by different assumptions, ownership models, and update cycles. Tools like Power BI make it easy to connect to a wide range of sources. That accessibility is useful, but it also creates a quiet risk: the belief that integration is complete once a connection exists. In practice, connection is only the starting point. Consolidation fails when mean

Most reporting systems don’t fail because of bad visuals or missing data. They fail much earlier, in how calculation logic is designed, scoped, and governed. In Power BI environments, this often surfaces through DAX. Not because DAX itself is the problem, but because it exposes whether calculation logic has been treated as part of the system’s architecture or as an afterthought added to make a report “work.” When calculation logic is designed without architectural intent, rep

One of the fastest ways reporting systems lose credibility is not through incorrect numbers, but through uncertainty. When leaders don’t know how current a report is, they hesitate to use it. When hesitation becomes routine, dashboards turn into reference artifacts instead of decision tools. This is why surfacing data freshness is not a cosmetic choice. It is a trust decision. Freshness answers an unspoken question Every report implicitly asks the reader to believe it. Every