Why a ‘Single Version of Truth’ is Key to a Great Supply Chain

The journey from ‘good’ to ‘great’ is well underway across many global supply networks.

While comprehensive benchmarks are still being normalized for comparative purposes, recent results that have been experienced by various customers of the new cloud-based platforms include reductions of 40% in inventory requirements for cycle and safety stock when compared to traditional ERP batch type processing, 5% decreases in lost sales, 99% customer service levels at retail, 5% reductions in material costs, and 30% reductions in premium transportation costs.

In order to operate a ‘great’ supply network, we must adhere to 2 immutable truths….namely there is a single statistical sales forecast driving all related actions across the supply network, and this therefore drives a single version of the truth.

In order to operate a ‘great’ supply network, we must adhere to 2 immutable truths….namely there is a single statistical sales forecast driving all related actions across the supply network, and this therefore drives a single version of the truth.

But how do we calculate and measure this single version of the truth?

We shouldn’t view measurement as an overlay on the business or the process. Excellence in process execution is the driver, and measurement is a capability that converts real time data at the process level and aggregates measures at different levels based on which types of measures at which levels will help drive actions that result in improved outcomes.

Consumer Price Index Categories

Measurement can take on a number of different forms including numbers, indexes, percentages, ratings, ratios, and rankings. Numbers are the simplest to understand, but are only as good as the strategic objectives the numbers are measuring.

An index, like the Consumer Price Index (CPI), has the advantage of combining lots of numbers, but it’s hard to understand what is really happening.

Percentages can be good when measuring blocks of time, but can be used incorrectly depending on segments and causals. Ratings are good when comparing qualitative information, but is subjective and can be manipulated based on derivation. Ratios are good for measuring critical relationships, but typically require addition analysis to understand the meaning and reach the correct conclusion.

And finally rankings are a feel good measure for highly ranked companies, but don’t provide any actionable insight for lower ranked companies.