Eastern Fish

Raymond Morrissey

As logistics focuses on driving both reliably supplied and lowest cost per pound to sales regions; there are solutions to improve freight planning and budget alignment. Let’s look at the Food Service Industry to see how to apply basic measures that cross functionally make the connection simple and understandable between the two operational teams.

The transition point is moving from logistics talking cost per mile to sales discussion in a delivery cost per pound. In the example below, the measures of cost per mile and cost per pound exist in the historical level one data, however the bridge in communication is key to devising plans that connect customers, shipment lanes, unit of measures, weight classes and distance to support a firm’s sales and operations planning process that all parties can understand and influence.

"The data becomes the unmassaged raw data for building accurate budgets and forecasts that connect customers to logistical cost estimates."

The measure of cost per pound in delivering products that are scaled by weight class in pounds connect a carrier sourcing class of “less than truck load” (LTL) to a maximum “full truck load” (FTL) demand (see Food Service Net Weight Brackets below). The historical data shipments are attributed into the weight bracket scales at the aggregate sales order level. We can see the price per pound scaling for the carrier network (see Freight Summary 1).

Food Service Net Weight Brackets and Carrier Type:

Freight Summary 1: (PADD Groups)

The logistics team can further benchmark the actual cost structure by decomposing the “cost per pound” into a generic “costs per state shipping lane” to simplify the aggregation of many street address locations. In this example, the cost basis is a per pound within the “MIDATLANTIC” shipping lanes are detailed (see Freight Summary 2).

Further evaluation leads to questions concerning carriers freight pooling options that cause variations between freight brackets, exact distance (reminder that the theory of large numbers has been applied to simplify), seasonality, capacity, lead time (urgency) and choice of carriers in a firm’s core carrier or approved carrier program.

By converting the same data into usage, the data can be trended into the number of shipments. The monthly shipment counts can be time-series and trended. The data becomes the unmassaged raw data for building accurate budgets and forecasts that connect customers to logistical costs estimates. The application of demand planning principles and removing lost distribution, removing one time distress sales, alignment of network changes of customers, new distribution and applying changes for growth and/or contraction the plan becomes a useful tool in predicting freight. Further refinement includes the indexing of fuel surcharges to produce a highly reasonably freight plan without having a full blown TMS system.

Freight Summary 2: (State and Mileage Breakouts)

Partial list of benefits:

Improved budgeting and execution of freight accruals

 Evaluation of costs at aggregate level.

Ability to share information with internal logistics team, sales, customers and logistics carriers.

Customer and product margin improvement planning and hunting.

Sets the stage for the deeper lane analysis and mileagebased shipping lane attributes.

Ability to compare national fuel regions (PADD) to understand the variations for local LTL delivery versus national pricing impacts.

Ability to integrate with demand planning and forecasting.

New product distribution assumption analysis.

Key performance measures and goal setting

 Risk analysis planning.