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— There are a lot of factors and they are relevant not only for our business, but for the entire retail industry. These are seasonality, local holidays, weather, tourism, consumer preferences, trends, prices and promotions. For example, recently Korean cosmetics have been especially popular throughout Eastern Europe. It is almost impossible for a human being to analyze everything, so help from algorithms is needed. In the past, store managers ordered goods in our company. It was ineffective. The quality of ordering depended on people whose expertise did not really lie in ordering goods. They could see their store's sales, but not the general trends. We were dependent on a person in case of personnel changes. Will the new manager be able to order goods efficiently? And the quality, shall we say, was “average”. Our colleagues from other countries told us that they did tests and the best store manager ordered the goods at the automatic order level. Instead of dealing with an order, store managers can focus on improving store operations by serving customers, preparing the store for work, preparing goods for presentation, etc. This is why we started looking for a solution to automate the ordering process. There were already operational solutions for that within the other chains of A.S. Watson Group. Our shortlist consisted of two vendors: MySales, which is was already used in one of the A.S. Watson businesses that time and another well-known system operating in another retail chain in the group. We spoke to our colleagues from various departments of the company that used MySales. In the end we came to the conclusion to go ahead with MySales sales forecasting module and stay with our present auto-ordering tool. So far we did not decide to move to MySales auto-ordering automated replenishment module due to significant labor costs effort needed for conducting such a migration. We load MySales forecasts into the solution we’ve used before.
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