Berna Bulbul | Product Manager
The past two years and the next couple of years with the pandemic have caused significant changes in customer demand. Spending more time at home due to the compulsory changes in working and education conditions affected consumption habits. We have seen people making their own bread, yoghurt at home, and coffee/tea consumption increased.
Consumers will shop wherever they can find the product they want — and from whoever can get it to them the fastest and without considerable shipping costs. That’s why the importance of product availability has increased by 58 percent since before the pandemic, and quality of service has increased by more than 46 percent during the same period. Consumers are looking to incorporate brands into their lives that give them flexibility, whether they’re working, shopping or looking for entertainment, and are willing to forego loyalty to brands that aren’t able to meet their demands.
These changes also confronted retailers with new challenges. The effect of the pandemic on the consumption data of the past 2 years made retailers ask, “Which ones were permanent effects, which ones were temporary?” to themselves since it is very difficult to examine these situations manually. “Which product, when and how much should I order?” made the answers to these kinds of questions even more critical.
Retailers need to use analytical solutions to answer these questions correctly. Forecasting customer demand with high accuracy can be achieved with data cleaning, data enrichment, and multiple algorithms. In this way, customer demands can be estimated location/time basis in line with customer needs.
So which product, when and how much should I order? If your portfolio is determined correctly; replenishment helps you to feed your stores at optimum stock levels. After detecting the customer demand, optimum stock levels can be determined with the optimization model that is suitable for the customer’s needs. At this stage, especially for products with a short shelf life, the product life cycle should be used as a variable when determining minimum stock levels and creating a recommendation. In short, the changing customer demand should be read from the data and interpreted correctly.
Another question is; “How should the portfolio of my stores be?“. You determined a store-based portfolio with assortment planning. If your portfolio is wrong, it is not possible to feed correctly. No matter how right you feed, you cannot prevent the creation and destruction of overstocks. While determining the portfolio of the stores, it is needed to proceed with a solution that increases profitability, where the effects of different scenario results on profitability can be examined, and which responds to customer expectations. In this solution; store size, store location, seasonality, product shelf life, the effect of complementary and substitute products on demand should be taken into account. For example, with the warming of the weather in seasonal regions, it is important to increase the front surface of products such as cold drinks and ice cream in order to meet the demand. On the other hand, as the weather starts to get colder, these values should be reduced by looking at the historical data. The risk of waste, especially for fresh products, increases if progress is made by looking at the recent time. Therefore, at this point, the importance of data literacy emerges.
The admin panels developed with all these valuable analytical outputs, helps to examine the answers to the following questions: “Do I have overstock? If yes, at what levels? What are my potential products to create overstock? What are my waste rates? Which of my products are wasted the most? In every store or in some stores?”
Even though you have an excellent replenishment product as a retailer, if your portfolio is wrong, you will not get the desired output.
If your portfolio is right, replenishment comes into the picture.
What the retailer should do; examining results, pondering over the finer details, and making actionable decisions.
* EY US Future Consumer Index