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Use case Contract intelligenceMidwest fuel wholesaler, 310 dealers

How a Midwest wholesaler closed most of a 1.2 million gallon gap before month-end.

Eight dealers were behind on their volume commitments with eleven days left. The instinct was to lean on the dealers. Cortex showed most of the gap started with the wholesaler’s own trucks.

Cortex · connected to your business

“Which dealer accounts are at risk of missing their volume commitments?”

Cortex

Eight accounts, 1.2 million gallons behind pace with eleven days left in the month.

The difference

Same question. Different results.

The question“Which dealer accounts are at risk of missing their volume commitments, and why?”

Claude / GPT / Public LLMs

Uploaded file

1 sourceThe file you uploadeddealer_volumes.xlsx

Answer

Eight dealers are 1.2 million gallons behind their commitments. Contact them and consider allowances to close the gap.

Just an answer.

Cortex AI

Connected intelligence

Cortex AI
  • Load timing
  • Route changes
  • Road closures
  • Rack prices
  • Rival supply prices
  • Local demand
  • Traffic counts
  • Weather
  • Dealer street prices
  • Contract terms
  • 62% of the gap is supply-side
  • Road closure on 2 routes
  • 3 dealers buying elsewhere

Answer

Most of the gap is on your trucks, not your dealers. Move 41 loads forward and restore the old route order. Give account managers rack data for the 3 dealers buying elsewhere.

A decision.

Eight dealers behind. Eleven days left.

On the 19th, the monthly volume report showed eight dealers well behind their committed gallons. Their shortfall also put the wholesaler’s own supplier minimums at risk.

Account managers called a few dealers, and every one said business was fine. The usual playbook was ready: push the dealers, offer allowances, and buy the gap back with margin.

Before Cortex

What the team saw first

  • Dealer volume8 accounts, 1.2M gallons below commitment
  • Rack pricesNo unusual moves at their terminals
  • Dealer feedback“Sales are normal”
  • InstinctPressure the dealers, offer allowances

Then they kept asking

The follow-up questions, in the team’s own words.

“Why are they behind?”

Cortex

62% of the gap is on your side: late loads, missed delivery windows, a road closure and softer demand. Three dealers are lifting from a cheaper supplier.

“Which dealers were hit hardest?”

Cortex

Two dealers on one route had loads arrive after their morning peak nine times in three weeks. The route was resequenced when a driver left.

What Cortex found

Where the 1.2 million gallons went

1,200,000gallons behind commitment, split by cause
Wholesaler side · 46%Market · 16%Dealer · 38%
  • Late loads and missed delivery windows330,000 gal
  • Loads arriving after the dealer’s peak hours230,000 gal
  • Road closure detouring traffic past two sites110,000 gal
  • Softer local demand80,000 gal
  • Three dealers lifting from a cheaper competing supplier450,000 gal

62% of the gap came from late loads, missed delivery windows, a road closure and demand. Only 38% was the dealers.

“What should we do first?”

Cortex

Move 41 loads forward for the five supply-side dealers, restore the old route order, and give account managers rack data for the three buying elsewhere.

The dealers weren’t short on customers. Their fuel was arriving late.

Cortex joined dealer sales, dealer tank inventory, dispatch records, terminal lifts and contract terms. It added weather, road closures, local events and competitor rack prices, and split the gap by cause in under a minute.

Two dealers on one route had loads arrive after their morning peak nine times in three weeks. A driver had left, and the route was resequenced. Low tanks at peak meant fewer grades available and lost sales. Nobody had connected the late arrivals to the volume report.

The decision

Fix the trucks first. Then talk to the dealers who really were buying elsewhere.

  • Moved 41 loads forward for the five supply-side dealers and restored the old route order.
  • Set an assistant to alert dispatch when any committed dealer’s tank falls below 30%.
  • Gave account managers competitor rack data for the three off-contract dealers. Two came back within their contract price.

What changed.

MeasureBeforeAfter
Projected month-end shortfall1.2M gal560K gal
Loads arriving after a dealer’s peak hours, per month233
Dealers buying off contract31
Time to answer “who’s at risk and why”2–3 days< 60 sec
At-risk reportOn requestEvery Monday
Leadership takeaway

Look at your own trucks before you lean on your dealers.

We were about to have eight hard conversations with dealers. Five of them would have been about our own trucks.

A volume commitment is a promise both sides keep. The team now knows which side slipped before anyone picks up the phone.

Before your next month-end, which dealers would you ask about?Book a demoSee all use cases
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Target implementation2–4 weeks
EnvironmentPrivate enterprise
Timeline depends on data readiness and integrations.

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