Almost everybody involved in the retail business is aware of spoiled goods, returns and lost sales leading to decreased profitability. In recent years there is much general awareness in spoiled food and governments have been taking steps to reduce this. Food is not only product group suffering from the phenomenon, however. It is just one which everyone can most relate to and get emotional. Other consumer goods such as clothing, household items &c. suffer from the same phenomenon and sometimes the negative effect of stale inventories is much more global and may have much higher environmental impact.
So why the goods get spoiled or outdated? Dr. Anna-Lena Sachs from University of Cologne, Germany has published an extensive research paper covering the reasons behind losses in the retail business.
It is pointed out that despite large amount of goods in inventories retail businesses frequently experience out-of-stock situations. Some studies have shown that this ration in non-perishable goods categories is close to 10% while in the food products it is even higher due to shorter shelf-life cycles.
The questions have been asked why such phenomenon occurs. It may be evident that this kind of shrinkage is caused by mismatch between supply and demand. Studies show that 50% of customers leave the the store without buying the product while only half of them choose substitution. The latter situation leads to increased sales of other products and does not indicate in any way the actual demand.
The study also points out that customers facing frequently unavailability of preferred products not only result in individual lost sales but they tend not to visit particular stores in the long run.
If the category management decisions are solely based on historical data which often may be skewed due the reasons described above. The historical data-based analysis may suggest certain goods being in demand while they are merely substitutes.
The paper also suggests that this kind of demand switching behaviour is not the only reason of suboptimal decision making. There is also a human factor, the decision makers themselves whose actions are often biased by human behaviour and inadequate metrics such as chase demand or mean demand.
It is pointed out that all retail businesses carry vast amounts of data originating from POS and other in-store systems but often lack tools and skills to process and understand this information. There are specialized retail analytics systems aiming to achieve better alignment of supply and demand whereas decision-making aids and management information systems helping business managers to remain unbiased and base their decisions on facts and thought-out reasoning.
Sachs, A.-L. Retail Analytics; Springer International Publishing Switzerland 2015