In Part 1 of this series, we discussed the perfect order metric and its value in measuring fulfillment effectiveness. Perfect order is a relatively simple metric in principle, but its implementation can be diabolically complex. For example:
- What is the unit of measure? Case level? Item level? Should it really be at the order level, or do you also want it at a line level? Should it be binary or do you want to bake in an equivalent of fill rate?
- Who are you measuring? Just the supplier? How about third-party logistics players who may be involved?
- What are you measuring? Performance to promise date? Or is it the schedule date?
- How tight are the tolerances? Should we include tolerance levels?
- What is the cost of measurement? Is there an ROI? Could it be negative if we have to become slaves to the metric?
- What role does the customer play in setting the bar? How good are the promise dates? Are they constantly changing? How effective is the broader planning process?
- What if you want to extend the measurement into payments? Perfect order requires accurate invoice information, but what if you want purchase-to-pay (P2P) to be perfect rather than just purchase order (PO) fulfillment?
If you're going to implement the perfect order measurement, you should think about broader performance measurement and how robust your processes and systems are. The perfect order is a KPI that can not only be not cascaded down, rolled up and tracked over time but also “mass customized” to support the various uses of this metric to improve performance.
This requires more than just a standard reporting capability. For example, it can include “metadata” of sorts to handle this variation – you can have many different variants of perfect order depending on whether you are using it, say, internally or externally to compare to a particular benchmark – while still providing a common framework. You might also want to have related leading or causal metrics that are tied in.
Gaining clarity around the performance measurement process and the performance metrics themselves is a huge step toward identifying waste and variation that hide underneath the surface and create misalignment between strategy and execution.
Want to tackle it? Stay tuned to Spend Matters for an in-depth Plus post on the subject.