Building a Transaction-Level Data Set

The old adage “you can't manage what you don't measure” goes a long way to explaining why companies have struggled to improve their profitability. Companies often find themselves facing a glut of information with little or no underlying structure to make it useful. A wave of enterprise resource planning (ERP) implementations in recent decades has led companies to store massive amounts of data backed by armies of individuals who manage, manipulate, and monitor a variety of metrics, measures, aggregates, and outcomes. The challenge is not simply to measure activities appropriately, but to measure the right data at the right level of detail in the appropriate format.

Effective pricing and profitability management must begin with a solid foundational fact base. The lifecycle of each transaction must be traced in detail as well as the revenues and costs associated with it. This is where profitability-related efforts often go off course. The data in most systems are based on the financial reporting timeline; that is, the date when the transaction is recorded to the general ledger. Unfortunately, this practice biases the information toward the balance sheets because each notation reflects when the transaction was paid or received. For example, a product pallet purchased in January would appear in accounts receivable that same month, while the annual rebate earned on this same pallet will appear as a cost in accounts payable some 12 months later. This ...

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