Assortment dominance matrix (ADM)
The traditional BCG matrix is suitable for retail applications, but with some adjustments needed.
The “spread in market size” between large and small submarkets is
a measure of the attractiveness of the submarket in terms of revenue potential.
In a large market, small market shares can still represent considerable sales.
The “spread in market share” has to do with
the top of mind awareness among consumers (i.e. the dominance of the assortment): higher than average market share means that, in the opinion of consumers, this group is better covered than the average assortment. Is a measure of the reputation of the sub assortment in the perception of the customers.
The ADM thus leads to a classification of the assortment in 4 categories, the axis:
small or large market (horizontal)
high or low market share (vertical)
small market recognition, high market share
important for reputation not for sales
large market, high market share
cherish: customers recognize it, basis for sales
small market, low market share
question marks - really need them? often involves service assortments
large market, low market share
opportunities - find reason for low market share
The information required for drawing up the ADM:
The ADM can be used to..
In the online world, one can make use of the so-called longtail
This longtail means that in the online world one can offer any product one can imagine, because store space or shelf space is not a limiting factor. However, we believe that the proper handling (gestione) of the ADM can lead to higher profitability.
Also because for increasingly more online players, keeping products in stock is becoming important in order to guarantee the speed that the customer wants. At the same time, this means that the costs of stock will start to count.
Return on stock will also become an important indicator. Retailers who know how to make the right pre-selection for consumers by offering the right assortment will be more attractive.
To arrive at an overall picture of development, it is convenient to construct a dynamic ADM.
We divide all the outcomes of the second ADM by the outcomes of the first ADM and we place the numbers found per department in a matrix, whose cross-axis is 100/100. If all market shares would have remained exactly the same in both years and if all markets would have remained constant in size, all numbers found would end up exactly in the point 100/100.
Using this overview matrix (dynamic ADM), it is possible to see at a glance what and by which departments the change in the average market position was caused.
Sometimes it is not possible in practice to obtain the data needed to draw up an ADM. This may be because the market data is not available or does not appear to be reliable. In such cases, we can still use an analytical model that is very similar to the ADM, based on the company’s own data: the goldmine analysis (GM)
Goldmine analysis (GM analysis)
Partly similar to the ADM, but rather than the analysis of market position, it focuses on the analysis of the contribution of assortment groups to the profitability of the firm.
The ‘large / small market’ input in the ADM is replaced here by the ‘high sales share / low sales share’ input.
The ‘high market share / low market share’ input in the ADM is replaced here by the ‘high / low gross margin’ or ‘contribution margin’ input.
The goldmine matrix thus describes how, in terms of the formula Return = Sales * Margin - Costs, the assortment contributes to R.
Can’t find all the relevant data for the ADM?
Use the goldmine analysis
- No external data is needed
- Not focused on market position, but on:
o Contribution of assortment groups (high/low market share)
o Profitability (high/low gross margin)
In the GM-analysis, by analogy with the prioritisation in the ADM, we can develop a sequence of desired approaches.
Suppose we want to improve profitability from the assortment mix:
Goldmine matrix
Link between goldmine and ADM analyses
Goldmine analysis –> profit portfolio analyses
ADM Analysis –> Sales-portfolio analyses
By comparing the desired prioritisation of approach from both analyses, we gain insight into which groups are of great importance for both improving profitability and improving market position (attack). In one single action, we improve profitability and strengthen the assortment concept at the same time. We also see groups that will not contribute much to sales improvement and not to profitability (reorganize).
Fair share analyzes
In those cases where the market size is stable over time and there are no great dynamics in the market development, we use a simpler method:
We measure where we compare our own performance with a predetermined standard (a benchmark). The result is an index compared to the norm. If the index…
Fair share > 100% or 1: performing above the predetermined benchmark
Fair share < 100% or 1: performing below the predetermined benchmark
The benchmark (index) itself can take different forms
It’s impossible that everyone perform above → means that the benchmark should be higher