Supply Chain View

This is the second part of a two-part post. Part 1 was posted last week.

6. Optimise stock over the range

The same investment in stock can produce better or worse levels of availability. This is intuitively obvious if we think of some reductio ad absurdum examples: all of our stock invested in a single slow-moving product will yield very little availability, but held against the fastest moving products will satisfy a good proportion of demand. The subtlety is knowing how to exploit the supply, demand and cost characteristics of each product to hold the optimum stock for a given overall availability. This can be quite hard, but a good combination of statistical safety stocks and differentiated policy rules regularly delivers improvements over a simple weeks cover rule of the order of 30% reduction in stock and halving non-availability at the same time.

7. Strangers strategy

Where there is a lot of slow moving product in the range, seriously addressing the fulfilment rules of these items can make a big difference. Integrating closely with suppliers may enable a back-to-back ordering process and remove the need to hold stock altogether, but this requires a good understanding of the customer expectation and an excellent relationship with the supplier. (This is the model that Amazon uses for the bottom end of its range. My own experience with obscure books is that their cataloguing process leaves something to be desired, and the promised product is regularly not in the range of the supplier.)

If general back-to-back ordering is not possible, then optimisation of the small stock quantities (ones, twos, threes) that are required can deliver impressive inventory reductions and service improvements. Often the real holding cost of these products is much higher than that of the faster movers, because it is here that most of the exposure to obsolescence occurs: stock reduction on slow movers will add more to the bottom line pound per pound than on fast movers. Knowing where to draw the stock/non-stock line is vital too.

8. Understand your customers: change your service proposition

An example illustrates this well. Fashion retailers usually run on 2 or 4 seasons a year, at least for their mainline ranges. Due to the high labour content of clothing, most production is now sited in low-cost but remote locations (China, Sri Lanka, Bangladesh). Thus there is a significant transport element to the lead time, which is large compared with the selling season. This means that an underestimate of the popularity of an item (common in fashion-driven markets) can lead to poor availability when we run out of an item and can’t get hold of more supply.

This is how Spanish retailer Zara handles this (among some other clever agile supply chain techniques): Zara runs very, very short seasons. This might seem to make things more difficult, but they use the short seasons to change their customer offer. A Zara customer has been educated to expect a line to be stocked only for a few weeks. She knows that if it is popular it may run out early. But for Zara this isn’t necessarily a lost sale, because the customer knows that next week or the week after there will be a brand new line. Stockouts still happen, but for shorter periods and there is always a pipeline of new lines coming through.

Really understanding the customer like this is hard, and it takes vision and conviction to make these kind of decisions – especially as they cut across marketing and supply chain.

9. For multi-tier operations, change the network configuration

This applies where we have stock in main locations and satellites. The general rule is that the safety stock in the system is proportional to the square root of the number of locations – note that it’s only the safety stock that’s affected in this way, and that the cycle stock should stay the same. It may be worse than that if there are a lot of slow movers because we get rounding up effects on small stock quantities.

For this reason the rule is usually: as few locations as possible, unless there are capacity constraints. As few as possible means that we need to take into account proximity to market and customer fulfilment time requirements (e.g. same day delivery requires a denser net of stocking points than next day). Capacity constraints come into play when there are high volumes that would congest a single distribution point (and in these cases distribution costs also start to dominate).

Apart from this, understanding the relationship between main store availability and satellite availability is also vital. This allows the right balance to be struck between stock in different tiers of the supply chain. Fixing a typical imbalance could reduce stock by up to 10% overall.

10. For short season markets, back winners with stock (and shun losers)

A common problem for retailers with large ranges is that the budget and forecast is spread too evenly across any particular range, not taking adequate accounts of the Pareto distribution of sales. While planning at a high level (range, category) is usually good, devolving this to individual lines is hard and time-consuming. Because seasons are short, the initial estimate and buy is the main determinant of availability and end-of-season stock (mark-downs and disposal).

So, a successful strategy is to make sure that buyers back winners with their initial orders and act much more conservatively for those products in which they have less confidence. I have found that people are generally good at identifying winners and losers before the start of the season. The problem is that they allocate too much budgeted forecast to the losers and not enough to the winners – often because if they were more realistic about the losers they would have some very difficult conversations about why the products were ranged in the first place.

See also

10 ways to reduce inventory and improve service – part 1