External environment analysis for convenience store opening planning

External environment analysis for convenience store opening planning
Project Summary

Analyzed the oversaturated convenience store market based on the changing external factors such as declining population and upcoming Tokyo Olympic Games. With our store opening potential forecast, we assisted our client to develop 10-year store opening policy.

Intricate external environments impacting convenience store business
With increasing number of stores in the entire industry and the declining local population, the population per store is expected to halve in 2023 compared to 2010 in major convenience store business . This raised a new challenge which is to shift away from the “volume” store opening policy. Furthermore, with the changing external environments, such as increasing elderly population, rising number of female workers, decreasing number of people in employment, material price increase due to the Olympics, the change in the “quality” was also called for. We analyzed the influence of these external factors and calculated the store opening potential in this oversaturated market, therewith supported our client to develop their new store opening policy.

Calculating store opening potential based on local segmentation
In calculating the remaining store opening potential in the area, we first narrowed down the factors that could impact store opening policy. Then we classified 47 prefectures nationwide into 4 different groups based on 2 factors: 1) the coverage ratio in densely populated district (the number of existing stores opened per person), and 2) store opening growth rate. Our store opening policy based on the local segmentations enabled to grasp more precise potential for store opening.

Evaluating realistic store opening policy and in-store initiatives
Our by-area store opening potential forecast seemed to assist our client in setting up their store opening target based on the realistic store opening policy. Also with our analysis they were able to foresee the drastic change in the target layer, which allowed them to prepare store accordingly and item stocking based on the change in target mix.

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