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The Spreadsheet Your Branch Manager Is Hiding From You

Login rates and adoption metrics can mask a deeper problem: when recommendations miss the mark, branch teams often create their own workarounds and stop relying on the system for critical decisions.

By Daniel Dinh
Woman standing by her desk with desktop computer, working
Image courtesy of nd3000 / iStock / Getty Images Plus
June 18, 2026

Right now, at least one branch in your network is running a shadow inventory system. Not because your people are difficult. Because your platform got a call badly wrong, nobody addressed it, and the branch drew its own conclusion.

They did not tell you. They just stopped giving the platform the decisions that mattered.

What That Looks Like in Practice

A branch manager at a Southwest PHCP location kept a spreadsheet taped inside his binder. Every morning, he checked the dashboard, noted the recommendation, then ran inventory the way he always had. A counter rep at the same location didn't dress it up: "I check the screen first, mostly so I can document that I did. Then I look at the reorder sheet."

Several weeks in, the platform recommended pulling back on a thermostatic mixing valve. The branch manager had been carrying higher stock on that SKU for years because a regional hospital contractor regularly called in same-day orders for emergency valve replacements. He knew that account cold. The platform had no record of it.

He followed the recommendation. Within a week the contractor called for units' same day. The branch was short. The contractor sourced the rest from a competitor, told the counter rep he'd remember it, and hung up.

That was the moment the branch stopped trusting the platform on calls that mattered. They kept logging in. For decisions that carried real risk, they went with what they knew.

The American Supply Association reports nearly 75% of PHCP-PVF companies are experimenting with AI or operational platforms, with 34% in active pilots. Most are measuring success the same way this distributor did: logins, views, completed process steps. None of it tells you whether the recommendations are changing what actually gets ordered.

The Number You Are Not Pulling

The comparison that cracked this open was simple: take what the platform recommended, put it next to what branches actually ordered, sort by SKU category, and look at the gap.

At this distributor, recommendation-to-action alignment was low in exactly the product categories tied to the mixing-valve problem. Login rates looked fine. Follow-through on the decisions that carried real risk did not.

One analyst ran this. It took a few hours. It was the only output that answered the real question.

If you have rolled out a pricing or inventory platform in the last two years, run this before your next quarterly review. In our experience working with mid-market distributors, when recommendation-to-action alignment falls below 60% in your highest-stakes SKU categories, the branches have already reached their verdict. They just have not said so out loud.

Why Scheduling More Training Makes it Worse

After the adoption numbers softened, leadership scheduled more training. The branch manager who built the parallel workflow attended. He knew exactly how to use the platform. He had simply stopped trusting it for decisions that carried real consequences, and no walkthrough session changes that calculation.

He waited until the presenter finished, then asked one question: "Are we supposed to follow the recommendation that caused the mixing-valve stockout? Or can we override it without getting flagged?"

The room went quiet. The consultant wrote something down and moved to the next slide.

That manager left with the same view he came in with. Branch managers in this industry talk constantly. By the time a regional director hears there is a problem, it has already traveled through half the network. No training calendar touches that.

What Actually Moves the Needle

If your alignment gap is concentrated in specific product categories, you are likely looking at a configuration problem. The platform was not set up to account for local market conditions or the key accounts your experienced people already know by name. Fix the configuration. When the recommendations get more accurate, branch teams follow them more often.

Then go sit down with the branch manager who is most skeptical. Not a survey. Ask directly what the system got wrong. A calibration problem and a trust problem produce completely different answers, and what you do next depends entirely on which one you are dealing with.

When the platform misses on a call that matters, say so. Tell the branch what the gap was. Be honest about what the system cannot see, like a contractor who has been running same-day emergency orders through the same counter for ten years. The branches that came back around did it because someone had a straight conversation with them, not because the onboarding materials got updated.

Your adoption numbers are not lying to you. They are just not telling you the whole story.


KEYWORDS: artificial intelligence (AI) business management software

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Daniel T. Dinh writes on pricing governance and inventory decision systems for U.S. mid-market industrial distributors. Dallas, TX.

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