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Inertia in the Supply Chain
Thursday 24th May 2018
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First Example

Synopsis

Using some remarkable tools to illustrate the case, consultant and researcher Bill Brockbank examines and quantifies the impacts of inertia & momentum in the supply chain before drawing some general conclusions.

Originally published by Cranfield in 2003

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Inertia and Momentum in Supply Chains

Introduction

The notion that supply chains have 'inertia' is perhaps half understood. That is to say, it's well accepted that when sales are high it takes time for the supply chain to catch up. However, there's another side to this coin, that when sales slow down the supply chain 'keeps coming'. In the short term this overfills store shelves, robbing the store of space it could perhaps use to sell something else. In the medium term it leads to warehouses with unwanted product yet out-of-stock of crucial (other) products. In the long term, say a season, it leads to stock markdowns and write-offs.

For this paper we have used a retail supply chain, although the lessons apply to all ex stock chains. Retail, characterised by low rates of sale (per SKU, per store) and the universal need to 'push' some stock in anticipation of sales is the clearest illustration of inertia. It's also the area with the biggest profit potential, much of it unrecognised. To distinguish between 'speed up' and 'slow down' inertia, we'll call the latter momentum.

We'll examine the micro chain, between the store and its local Distribution Centre (DC). The lessons are the same for the supplier >> DC echelon, for the manufacturer >> importer, for the manufacturer's supplier to the factory and so on.

In one sense the momentum at these upper echelons is greater because the lead time is longer. On the other hand, the impact of momentum is less clearcut. That's because the sole purpose of a retail chain is to have something in each shop. Everything else is, broadly, a step along the way. We shouldn't care about out-of-stock in the DC providing we lose no shop sales. Yet too many firms measure line fill (the converse of out-of-stock) in the DC because they can; for all sorts of reasons they don't measure out-of-stock in the stores, or they report something easy to measure which purports to represent OOS[1]

Our retail store also has 'a place for everything and everything in its place'. Corn Flakes can't overflow into the Rice Krispies shelf space or vice versa. Typically, mid priced goods with fixed shelf allocations work like this, while hanging goods do not. In essence the micro chain contains:-

  1. A number of retail outlets each with a target stock for each ranged SKU. We'll examine only one shop[2], from which the lessons are scaleable.
  2. A DC (or factory, or agent, or importer or wholesaler) who supply, on demand, SKU's to replenish the shop.
  3. A control mechanism with 'triggers' and 'rules' to make this happen.

  1. A leading high street chain thought its store out-of-stock was 11% when the customers saw 28%. The differences? Inaccurate store stock records; and counting backroom and in transit stock as 'on display'.
  2. It's a pretty busy shop! We ran over 2,000 combinations of BTL, rate of sale and lead time, each 10,000 times. Our 'one store' not only worked extremely hard, it experienced every possible combination of circumstances.

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