Value-driven business process design focuses on business goals and how to optimize them. The business metric is central in this process; it’s how we identify and measure value creation.
Well-designed metrics help us consistently do the right things in the right ways to optimally achieve our goals.
What are the components of a fully-developed business metric? How do these components work together? What is the best-practice methodology for building and maintaining value-driven business metrics?
Three core principles drive world-class business metric design: value maximization, root cause analysis, and corrective action. First, let’s look at value maximization.
Each metric should be designed to drive business role behavior toward optimally achieving business objectives. The behavior monitored by each metric should therefore be understood in a global context where tensions between conflicting metrics are optimized globally rather than locally in order to maximize top-level metrics.
Designing a metric for this purpose requires positioning it within a structured hierarchy where the inter-dependencies between all metrics are clearly understood in relation to each other and the system objectives, measured by the top-level metrics which all other metrics support. It also requires setting the target value for the metric by considering the impact of its behavior on the global system objectives in an integrated context with other metrics rather than attempting to force isolated behaviors to extremes due to disconnected, sub-optimal targets.
For example, Expedited Freight and Inventory Turns are KPIs which help account for fluctuations in Profit, but they are generally conflicting metrics, inversely related to each other when trying to maximize profit: too little inventory of key SKUs tends to increase expedited freight; trying to eliminate expedited freight tends to require significant inventory buffers. In most supply chains, optimal inventory buffer settings allow for a small amount of expediting and/or stockouts; driving either metric to an extreme would reduce total profitability.
In our next post, we’ll look more carefully at how best-practice metrics methodology enables root cause analysis.