Case Study · Operations & Analytics
DC Turnaround
Taking a multi-million-dollar distribution center from the bottom quartile of the company standings to the top — with dashboards, tooling, and a 30-person team.
- Bottom → top company-wide DC standings
- +54.5% standings improvement
- −15% overtime expense
- +7.3% delivery-window success
The situation
I took over a multi-million-dollar distribution center sitting in the bottom quartile of its company-wide performance standings. Overtime was high, inventory variance was unexplained, and delivery windows were missed often enough that customers noticed. Nobody could see the problem in time to act on it — performance was something you learned about after the month closed.
What I did
Made the day visible
I stood up Power BI dashboards for daily order monitoring, so disruptions surfaced the morning they happened instead of in a month-end report. The metrics that mattered — fill, on-time windows, labor hours against volume — became something the team could look at and steer by.
Built the tooling
Custom Excel tooling replaced the manual spreadsheets the operation had been running on, lifting warehouse efficiency roughly 10% and giving supervisors a repeatable way to plan a shift rather than react to one.
Attacked the cost line
Targeted scheduling and process changes cut overtime expense 15% while inventory variance improved — the two numbers that usually move in opposite directions when a DC is under pressure.
Fixed delivery reliability
Driver training, manifest analysis, and tighter DOT compliance raised route-delivery window success 7.3%. Analysis pointed at which routes and which handoffs were failing; the training closed them.
Built the team
Thirty people — hiring, mentoring, and data-driven training programs. This is the part that doesn't show up in a dashboard screenshot: overtime doesn't drop 15% because a report says it should. It drops because supervisors trust the numbers, the crew trusts the supervisors, and problems get raised on shift instead of discovered at month-end. The coaching and the analytics were the same project.
The result
The center climbed from the bottom quartile to the top of the company-wide standings — a 54.5% improvement in ranked performance — while costing less to run and delivering more reliably than it had at the bottom.
Why it's here
This is the same instinct behind everything else on this site: find the measurement that doesn't exist yet, build the thing that produces it, then let the numbers drive the decisions. The tools were Power BI and Excel instead of Python and SQL. The method was identical.
Figures are the relative performance improvements reported on my résumé. No employer-internal data, reporting, or systems are reproduced here.