What Ray-Ban's supply chain tells us about to stock, and how much

Published on: 16th May 2014

That's a key question for small firms that sell or manufacture products.

The costs of getting it wrong are substantial - if your stock ends up a mix of the wrong products, you'll lose sales and risk obsolescence (or a heavy discount on sales, affecting margins). Too high stock levels overall and you can have a major drain on cash.

This article describes some of the best practice used in stock management (by firms like Ray-Ban), particularly focusing on how you can use your knowledge of demand to optimise your stock levels. if you have products with very short life cycles (e.g. fashion items), or high seasonality - like some sunglasses lines! - that gets a bit harder to handle still. (Maybe a post for the future)

A good place to start is the 80/20 principle (also known as Pareto).

You probably recognise the practicalities of this every day - most of your sales come from relatively few products, though that doesn't necessarily mean the same applies to where your profits come from.

Some firms use 80/20 as a corner-stone of their stocking policy - i.e. they focus only on the high-running products which are easier to predict and manage; or, they deliberately offer a 'long tail' of products but price these low-runners at a premium to cover the additional stocking costs.

Clearly articulating the objectives of your business model regarding the range of products you offer is an important pre- requisite for getting your stock management right. Are customers coming to you because they know they can get certain items quickly, or because they can make a choice from a lot of things?

The other critical customer factors that should shape your approach are the level of availability you need to offer and on what lead times? If you think your online retailer needs stock available to despatch off-shelf 99.9% of the time, that will have a considerably higher stock requirement than if it is tolerable for stock to be available to customers off-shelf 95% of the time - with a few days wait otherwise.

Again, it is important to ensure you are aligning your business objectives, the prospective service you communicate, and your stocking policies.

Back to looking at demand. So far, we considered demand volume only ... and some people stop there. However, it is perhaps even more critical to consider how variable your demand is. As an extreme example, if the same person came into your shop every day and bought the same item, and no-one else did at all... you would have low volume demand (1/day) but it would be very stable (always 1/day!). It would be easy to run that with very low stock levels - maybe even near-zero if it was cost effective to have your customer's item delivered daily just before he arrived!

Consider the chart below. This takes the volumes from the 80/20 chart but adds a new dimension - the demand variability.

Each square represents a product. Product D then is a high volume, low variability product, whilst Product A is low volume and high variability. You can see the demand histories for the example products represented on the charts, which just show the demand over time. We've drawn some "policy" groupings on the chart, as follows, and these can help you with stock management:

  1. Runners: these are products with reasonable volumes and stable demand. You should stock these, but - like with the bloke buying the same item a day - you should be able to run them with very low stock levels. The way you'd do that is to have a standard order for a fixed quantity with your supplier and carry a safety stock to cover the variability only. So, for product D, you'd have 70 delivered every week, come what may - the weeks you sell a little less, the stock will increase a bit; the weeks you sell a bit more, you'll eat into your safety stock a little. There is next to no risk of obselescence, and if you run out of stock, it won't be for long, as you already have another order on the way. For product D, your stock is probably going to vary between 30 and 100 most of the time - on average a week of stock.
  2. Repeaters:these are products that are less stable than runners and / or with lower volumes. Again, you should stock these items, but manage them differently by using a re-order point mechanism - using product B as an example, 10 of the product would be re-ordered each time the stock level dips below say 10 units. While the replenishment stock is being delivered, the stock levels continues to reduce, the new stock arriving "just in time". Average stock levels will be a higher than for 'runners' but you have the security of knowing you are only procuring what is selling.
  3. Strangers: in the ideal world, you wouldn't stock these as the demand is so variable - there is a risk of obsolescence, a high carrying cost, and cash tied up (if you buy a lot of something that isn't shifting, you can't buy something that is). But if your business model calls for a product like "A" to be available from stock, your focus should instead be on trying to minimise the stock levels (see below for more on this).

A note on "C" - this is a product with reasonable underlying volume but a big spike. The best way to deal with products with these sort of characteristics is to have a maximum order size that is available ex-stock - with the "spike" balance delivered to order on a longer lead-time.

What is the right stock level?

With all the policies described above, there are quasi-scientific/mathematical ways to calculate theoretical stock levels based on target availability/service levels. The approaches have in common a recognition that - in addition to demand volume - variability of demand and supply lead time are critical factors.

From our experience, the best way to start is to simplify and keep things pragmatic.

Do some analysis of your sales patterns first and see if our classifications make sense for your business. Assuming they do, start with a small group of products and do some testing - for example, if you sell between a half and one and a half boxes of product XYZ every week and product XYZ takes a week to re-order, it's probably a 'Repeater' and you should hold three boxes in stock and re-order three boxes when you open the second to last box. Monitor for a few weeks - if you keep running out, add a box; if you never touch the last box, then reduce your order quantity to two boxes and only order when you open the last box.

Once you have the basic model in place, you can build the spreadsheet, add some science and do some optimisation!

What about reducing stock?

This article is really about understanding the drivers of stock levels - the most important of which are your business objectives (e.g. stock availability targets), the policy you use to 'control' an item, the volume of demand, the variability of the demand, and the lead time for supply.

If your objective is to reduce stock levels- for example on those 'Stranger' items - then you can look at and address those factors. For example, if demand is very variable, can that variability in demand be managed out? Domino's has price reductions on pizzas on Tuesdays (to boost demand on low days).

Or can you reduce your lead times, or order reduced quantities more frequently?

Congratulations on reading this far! I hope the article has at least prompted a few ideas - let me know either way! (I may even be persuaded to put up a downloadable stock calculation spreadsheet if people are nice enough....)


PYXI CRM Team: 16th May 2014 09:00:00