How many SKUs should a Supply Chain Planner manage


00:08 Introduction
00:24 How many SKUs does a supply chain planner tend to manage?
02:38 What drives the amount of SKUs someone is managing?
04:19 Does one product equal one demand planner?
05:25 In an industry with lots of new products, does that mean that planners will manage less SKUs?
07:00 What can a Supply Chain Scientist manage compared to what can be managed with a more traditional approach?
12:16 How is the numerical recipe built?
13:52 Should all companies leverage machine learning techniques?
16:14 Where do the limitations lie?
19:22 How can one person, responsible for many SKUs, be more effective than an entire team responsible for a smaller scope?
22:41 What are the challenges to overcome in order to introduce a capitalistic approach?

Description

With modern companies providing increasingly large catalogues and technology facilitating easier stock management, a modern Supply Chain Planner must spin many plates. That’s why for this episode of LokadTV we’re asking: how many SKUs should a Supply Chain Planner manage? And just how many is too many?

It of course depends on the specific vertical, but a ballpark number of SKUs that Supply Chain Planners manage is typically within a range of 500 - 1000. The classic way that most Planners operate is to iterate through long spreadsheets of elements in a circular fashion.

When it comes to forecasting, there’s an inverse relationship between erraticity and volume. For most FMCG companies you have more quantity and less erraticity, however this doesn’t make forecasting any easier. On the other end of the spectrum, erratic forecasts can be found in the automotive spare parts market for example. Yet despite this erraticity, the quantities and economic weight of the articles in the supply chain are lower.

Lokad takes a different approach from the classical supply chain management perspective, especially when it comes to forecasting. Most planners go through their spreadsheets in a cycle, using an ABC methodology. We can say that in this manner, the planner’s time isn’t fully capitalized. Meanwhile, a Supply Chain Scientist at Lokad aims to have intelligent decisions ready “out of the box”.

We go into more detail about what we consider to be an “intelligent” inventory replenishment choice. For example, a “stupid” decision could be only stocking your handbag store with black and brown bags. Yes they may sell better, but now the display windows look pretty glum. In our methodology, we also aim to avoid many naive yet heavily ingrained supply planning ideas, such as safety stock.

Individually, we have Supply Chain Scientists at Lokad that take care of millions of SKUs and billions of dollars worth of inventory. We explain how this is possible and why some operations should definitely be automated and others shouldn’t.

To conclude, we talk about the various barriers that have previously blocked the development of supply chain science and the importance of seeing supply chain not as a simple cost center, or support function, but as an asset that can generate significant value for a company.