RICHMOND, Va. –
In Parts I and II, we uncovered how problem framing is like solving a mystery and how gut instinct – while colorful – is no match for complex data. But what happens when the tools start talking, teams start listening, and data doesn’t just support decisions, but actually drives them?
Welcome to the new normal at DLA Aviation.
Supply Chain Analyst Francisco Bermudez had a challenge: build a dashboard that gave decision-makers real-time access to the facts. But the ultimate goal wasn’t to pull data together for some fancy charts – it was to pull people together for collaboration.
“All stakeholders had a shared understanding of objectives, data requirements, and desired functionalities,” he said of the Unfilled Orders (UFO) dashboard built for the Navy Fleet Readiness Center Southeast in Jacksonville, Fla. “Effective communication streamlined the decision-making processes and minimized delays.”
It worked. The Qlik App that Bermudez helped to create became a command-level tool for transparency, accountability and performance evaluations. It didn’t just display data – it showed everyone the same version of the truth.
That’s not a dashboard. That’s a lie detector.
Supply Chain Analyst Thomas Wright helped develop the Demand Planner Tool, which compares Air Force demand forecasts with actual acquisition data in DLA’s system.
“It provides variances between forecast requirement and projected acquisition levels, allowing planners to do further research to adjust or accept these variances,” Wright said.
Here’s where it gets better: the tool includes a note system that allows demand planners and sustainment specialists to leave breadcrumbs for each other.
“Before the Demand Planner tool, sustainment specialists had no direct link to see what work the planners may have already performed,” Wright said. Now? They’re not working blind. The tools talk. So do the teams.
When a tool and a team are aligned, duplication decreases and support for the warfighter increases dramatically.
Senior Demand and Supply Chain Analyst Bill Huttemann’s data stories are anything but routine. When working on a project to align Army UH-60 helicopter data with DLA supportability, he ran into a snag.
“We discovered that the HUMS [Health and Usage Monitoring System] data does not readily correlate to DLA data,” Huttemann said.
Rather than give up, his team got to work developing a cross-reference system. The goal? Translate maintenance-focused data into insights that improve part supportability. Think of it as a Rosetta Stone for helicopter maintenance and repair data.
Meanwhile, Supply Chain Analyst Andrew Sabatini automated a tedious 7-hour Unliquidated Obligations (ULO) report by using a cloud-based platform like SAS Viya.
“Automation leads to less manual inputs and fewer mistakes. Now I spend a few minutes getting my import files set up,” Sabatini said. “I can get other work done while the report runs.”
He even applied automation to intern assessments, resulting in less manual input, fewer mistakes and faster insights. Basically, the data became a part-time assistant with a full-time work ethic.
Supply Chain Analyst Conor Musselwhite knows that data acumen extends beyond analysis to documentation and training.
“Analysts often deal with intricate workflows involving multiple tools, data sources, and decision points,” he said. That complexity can be a barrier – especially when it changes week to week.
Enter low-code/no-code platforms, MS Visio and a video library created by his team.
“Videos excel at showing processes in action,” Musselwhite said. And written guides? “They are referenceable and searchable.” Together, they make knowledge sticky – and keep institutional memory from walking out the door when people transfer or retire.
If there’s one thing the data detectives at DLA Aviation agree on, it’s this: your analysis is only as strong as your problem statement.
“To refine and finalize a problem statement for maximum clarity and impact, we start by clearly defining the core issue,” said Adam Hardee, chief of Research, Review and Analysis in the DLA Aviation Business Process Support Directorate. “We use techniques like the ‘5 whys’ to avoid addressing only symptoms.”
Supply Chain Analyst Joshua Bradshaw learned this the hard way. An early misstep led stakeholders to chase the wrong problem.
“I intentionally paused to apply intuitive thinking,” Bradshaw said. “By refining the problem statement, our strategic direction shifted … to fundamentally redefining the game we were playing.”
Sometimes, the most challenging part of solving the case is admitting you were chasing the wrong lead.
Hardee says tomorrow’s data analysts will need more than spreadsheets and SQL. They’ll need:
• Programming in Python and R
• Visualization skills in Qlik and Power BI
• Cloud platform fluency
• Business acumen and critical thinking
• Communication chops to tell the story behind the data
It’s not just about finding insights; it’s about delivering them in a way that changes strategy.
From automated reports to predictive dashboards, from Army helicopters to Air Force fill rates, data acumen is no longer a side skill. It’s the playbook.
At DLA Aviation, every contract, part, forecast and fix have one thing in common: someone looked at the data, asked the right questions and followed the clues
Case closed.