Persuasion | ETW Digital https://etwdigital.com Get The Help You Need, When You Need It Fri, 03 Oct 2025 20:24:28 +0000 en hourly 1 https://wordpress.org/?v=6.9.4 https://etwdigital.com/wp-content/uploads/2018/01/cropped-ETW-Final-White-Back@2x-32x32.png Persuasion | ETW Digital https://etwdigital.com 32 32 Propane Delivery Company https://etwdigital.com/project/propane-delivery-company/ Mon, 14 Nov 2022 15:48:21 +0000 https://etwdigital.com/?post_type=project&p=768

How can you improve delivery costs per gallon?

Propane Delivery Company 

The Challenge

The company was looking for significant cost savings across the board, and last-mile deliveries carried high costs and the most critical risk to the business’s health. In the fuel delivery business, refilling a customer early is marginally more expensive; getting to a customer late means they are out of fuel and calling your competitors. The goal is to balance under-servicing (losing customers) and over-servicing (losing money).

The Solution

In the fuel delivery business, there are three key metrics:

  1. Out of Gas – The customer is bone dry on refill.
  2. Zero Gallon Delivery – You deliver, but there is no room in the tank.
  3. Early Delivery – Customer on the route that doesn’t need a delivery.

Early deliveries are by far the most common. An 8-hour shift delivering propane costs the same whether you provide 1,000 gallons or 2,500 gallons, although the cost to deliver the propane is significantly higher in the former. Therefore, the goal was to determine the optimal number of drivers to minimize early deliveries.

To quantify the opportunity, we created a monthly driver efficiency score model based on the number of gallons remaining in the truck at the end of the day. A driver efficiency score of 1.0 meant you finished your shift with an empty truck. A driver efficiency score of 2.0 meant you finished your work shift with a truck that was half full. Your delivery expense for both routes was equal. The model allowed us to identify over and under-capacity based on location and seasonality to augment workflow appropriately.

Tools Utilized

  1. MS SQL
  2. Tableau
  3. Data Mining
  4. Field Visits
  5. Driver delivery ride alongs
  6. Excel modeling

Expected Results

The amount of propane sold over a year will be the same regardless of delivery schedule, absent period timing differences that may fluctuate over month end. The only certainty in this business is that minimizing early deliveries with running customers out of gas significantly increases profit margins.

Fuel route planning is very complicated, and factors that contribute to early deliveries are typically the weather in general and the change of season in particular.  Early deliveries were 78%, but out-of-gas deliveries were only 0.4%. The theory was that the squeaky wheel not being quantified contributed to the number of premature deliveries. A 50% reduction in these deliveries was worth approximately $30 million.

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Why doesn’t my CapEx spending fluctuate with changing business dynamics?

Propane Tank Exchange Business

The Challenge

 The lack of propane cylinder inventory control measures led to a consistent annual CapEx budget of $40 million, regardless of sales fluctuations. Management wanted a clear understanding of how inventory was tracked, where it was maintained, and how it could be modeled more efficiently going forward.

The company operates regional production plants that inspect, repair, and refill propane cylinders sold in retail locations across the United States. Consumers buying extra tanks causes inventory control problems as it eliminates a 1:1 exchange.

Decentralization and management silos led to large quantities of inventory stock at regional storage yards utilized for swift last-mile delivery.

The Solution

This is the classic case of the “devil being in the details” and “too close to the forest to see the trees.” The data analyzed across millions of rows identified the course of action, and site visits to a production plant, inventory storage yard, and retail sale location helped confirm the hypothesis. Location and seasonality also played a role in inventory control issues. Observations included:

  1. No one section (Plant/Staging Yard/Retail) in the supply chain owned tank inventory
  2. Operations did not trust the technology that was put in place to track inventory
  3. No disincentive to hoard inventory
  4. Staging yards held peak season capacity year-round in all locations

A modeled-based approach could reduce idle tank inventory from 13 and 27 days to 5 days based on historical delivery schedules between the plants and the storage yards. In addition, a reconfiguration of the staging yards into trailer pallets (Full on one side/Empty on the other side) significantly improved hand inventory counts for management reporting.

Most importantly, management’s #1 concern of retail out of inventory was driven by delivery frequency, not tank inventory.

 

Tools Utilized

  1. Site visits
  2. Cultural persuasion
  3. Departmental management interviews
  4. Supply chain ride alongs
  5. Data mining
  6. MS SQL
  7. Excel modeling

 

 

Results

Reduction of staging yard inventory to 5 days stock on hand resulted in a one-time savings of $20 million in new tank purchases. This was accomplished by managing inventory as a function of retail capacity. When retail capacity hits 110%, new tank purchases were built back up to 125% capacity—this methodology allowed for a systematic inventory scaling as sales secured new business. 

 

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