Cost-to-Serve Model Gives Leading Food Distributor an Inside Look at Customer Performance

company overview

Since its formation in 2019, this company has become one of the largest independent fresh food distributors in the United States. They have risen to be a category leader in providing food service and retail industries with fruit, vegetables, proteins, fresh-cut produce, fresh grab-n-go offerings, dairy, floral, and specialty products. This company has seen tremendous growth, nearly quintupling in size, through seven acquisitions and strategic operational investments. The company continues to acquire new companies, with the current operations spanning 27 facilities with a fleet of more than 947 trucks and more than 2,000 employees.

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Food & Beverage
Service category
Supply Chain
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The Challenge

As a food service distributor, the customer specific delivery requirements drive a large portion of this organization’s operating expenses. Having the ability to identify the costs for specific customers or customer doors becomes a key tool when negotiating with a customer, and additionally provides leadership with clear line of site to available levers to achieve financial goals. This process is further compounded by data availability, customer door counts greater than 25,000, and computing power. This organization was looking for a solution to provide them with real-time data into their customer costs to streamline their expense planning.

The Results

This distributor now has a powerful Cost-to-Serve tool in Anaplan that can fuel executive decision making, targeted improvements to adjusted EBITDA results in real time. Customers that are delivering negative adjusted EBITDA can be evaluated for a more profitable product mix, or to be dropped all together. They can identify problem customers, such as the customer that is 7th in sales, 10th in gross profit, but 586th in adjusted EBITDA. Negotiations are empowered with an understanding of how the customer is impacting the bottom line, sharing price breaks with process friendly customers, and passing along price increases to process adverse customers. Ability to target promotions to specific profit contributing customers is also an improvement.

Additionally, some customer parents had doors across multiple operating companies, which we were able to combine OpCo sales, COGS and OPEX to create a P&L Statement for a customer that bridges multiple data systems.

The Solution

Develop a Cost-To-Serve (CTS) Application, with the goal of being able to immediately produce a customer door level P&L Statement and be able to aggregate the P&L Statement up the customer hierarchy. Parents of customer doors crossed operating companies due to various acquisitions. This led to the organization having multiple operating companies servicing various chain restaurant locations, and the parent company existing across operating companies.

Our starting point was the operating companies’ Profit & Loss Statement, which was data supplied from another Anaplan Application (benefits of connected planning). Each cost center needed to be evaluated to determine the appropriate cost driver per general ledger account. For some cost centers, particularly related to labor expenses, needed to be disaggregated using department specific drivers, rather than the G/L Account driver. We identified five key cost drivers that could be identified using a sales history and a trip history report: Cases, Pounds, Miles, Deliveries, Invoices and Driver Hours.

With each general ledger or department accounted for based upon shipment/trip history, we could calculate each door’s percentage of total organization it represented. For example, Grocery Store 1 represents 5% of the invoices for the period. Grocery Store 1 would receive 5% of any expenses being disaggregated by Invoices. Using the commercial data files, Accelytics was able to sum sales value and cost of goods sold value, leaving us with a customer door gross profit. The disaggregated expenses represent the Operating Expenses; we have created all data elements needed to calculate adjusted EBITDA. We can place that in context, such as OPEX per Case or rank customer’s against each other. We can now identify unprofitable customer doors, and we can roll those customer doors up to parent customer, and we can roll parent customer up to customer segment, etc.

Some operating companies did not have same cost driver data available to them. With Anaplan, you can create a window into what operating companies were missing data and override the general ledger assignment for that specific operating company, while other operating companies can operate with a full suite of cost drivers.

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