Range Management is about controlling the number of products (or range of services) you stock or are willing to supply compared to what is available across the market as a whole. It is inevitably a trade-off between what level of volume is economic for the company to supply compared to the revenue forgone by not meeting every need in the market, as summarised in Figure 1. This, in a nutshell, is the basis of our Range Management service but our service delivers more profitable outcomes than have been achieved using traditional approaches.
The digital age means new, more insightful sources of data continue to come on-stream which now enable some of the shortcomings of traditional range management techniques to be overcome in very cost-effective ways. Delivering gains in profits and company performance. Not taking advantage of those changes therefore runs the risk of your company having a competitive disadvantage in the market.
The new sources of data (such as loyalty card data, online transactional information, social media feedback, and so on) and much lower costs of data collection (including online panels and surveys, instant surveys via iPads and other tablet devices, and so on) are showing that traditional range management techniques are woefully blunt – and in many cases actually produce wrong conclusions about what to stock.
Traditional range management techniques, with limited data on customer/consumer needs to draw upon, approached the problem in a very straightforward way. Rank all the products sold in order of their value sales and take a judgement on which ones are too small to be economic to continue supplying. Compare where possible with the total market and then decide from this what set of products provide adequate market coverage without volumes being too small to be uneconomic to handle. An example of this approach for a supermarket FMCG category is shown in Figure 2.
The RedRoute Range Management service helps you leverage these new data sources to do your RM evaluations in a way that creates real competitive advantage for all companies along the supply chain – brand owners, retailers, and other intermediaries.
It does so by looking at ranging from the buyer/user perspective and evaluates both the long and short term implications of ranging decisions upon future business performance. The conclusions are sometimes quite different – and often much more beneficial to company profitability – than the traditional methods would deliver. So using our service companies are able to ensure they trim the fat without cutting into the meat or severing an artery they didn’t appreciate was there. So how does it work?
How it works
There are 3 key elements that create these benefits.
Firstly we conduct a Traditional ranging analysis. This is because it is:
- Straightforward and easy for non-specialists to understand
- identifies products that are important to the market which we are not currently providing
- identifies obviously under-performing lines by benchmarking to the market
However, we need to understand more before taking decisions on what to stock and what not to stock.
So the second element is to look at customer purchasing portfolios (or repertoires). Are there secondary products that customers buy from us purely because they bought an initial ‘trigger’ product?
For instance, many products have associated products that either complement or facilitate their usage (e.g. Tea and biscuits; fence posts and nails; paper and ink; etc) and some may be driven by some other common factor coupled with convenience (e.g. Nappies and beer).
If we delist a product purely on the strength of its own relative performance we may underestimate the ‘halo’ effect that product has on our total sales. So we need to ask the question ‘if we delist this product what effect will that have on the rest of our business?’.
Sometimes the answer will be ‘not much’ but sometimes it could well outweigh the direct profit gain we’d get from delisting it. We could lose the whole basket of sales that they may otherwise have made and/or we could lose them as a customer altogether – and that would not be a healthy long term strategy for the business.
Understanding these potential halo effects means considering all of the differing kinds of product associations that may exist – both direct and indirect. We also need to consider their potential switching behaviour. For example, are we stocking two products which are, in essence, equally substitutable (like two brands of digestive biscuit) and would the customer just switch their buying to the alternative one? If they will then the risk from delisting is much less. If they won’t it could be a very high risk move indeed.
We use customer transactional data and/or independent market research to uncover all these associations and potential switching patterns so that you can make a much better informed and much more strategic decision about what your range should include.
The final element is then to put in place a financial spreadsheet model that calculates the long and short term implications of alternative ranging decisions before you make them. We work with you to understand the implications for overhead costs as well as the direct impacts on trading profits. We use a straightforward ‘cost-to-serve’ model to help decide where to draw the line on which customers (or segments of customers) we will be able to satisfy and which we will not – and, if relevant, what arrangements we’d need to put in place to safeguard the retention of specific high value customers who may otherwise be at risk.
Our approach yields both short term and long term benefits to profitability. Traditional approaches often produce short term gains but at the expense of long term company performance. With the RedRoute approach costs are minimised across differing company functions from warehousing to customer service, cash flow to average product profitability whilst long term company profitability is preserved and maximised, cost-to-serve ratios are controlled and buyer/user preferences are underpinned, not undermined.
The scale of these benefits are often substantial. For example, a leading biscuit manufacturer used our analyses to conduct a category range review for one of the UK’s top four supermarkets. Loyalty card data was used to enhance the traditional ranging approach and make the category easier to shop, preserve choice whilst minimising duplication, and grow the category as well as enhance company share. The net result was that although x % of lines were eliminated from the category, fewer stock-outs (due to more on-shelf availability of key lines) and easier shop-ability of the aisle meant that category sales actually increased. Profits from the category grew by…
Using our RM service usually starts with a Feasibility and Scoping Study to agree the terms of reference, category definitions, business connections, stakeholders, influences and working parameters for decision making. From this review, and using samples of relevant data, we estimate the potential ‘size of prize’ and define the appropriate project plan and resources required.
If the potential gains from conducting the range optimisation project are shown to be significant then the second step is to conduct the detailed data analyses. This may, on occasion, require some original market research to be undertaken amongst the buyer/user base in order to understand buyer portfolios & motivations and create or extend the analytical database. The results from the analysis phase then drive the ranging recommendations and the implied profitability gains.
The final step is then validation of the conclusions through in-market testing. Historical transactional and market research data do not always tell the complete picture. But they do give a strong guide to the right strategy. To make sure nothing has been missed however, we work with you to design and implement an in-market test to validate and/or fine-tune the recommendations. This step provides independent and unambiguous verification of the potential gains and irons out any practical implementation constraints that may arise out in the field.