Simplification and growth decisions made with data-driven analyses in store network optimization.
With changing consumer habits, increasing costs, and digitalized service structures, businesses are now re-evaluating their physical branch numbers. However, deciding whether to close a branch or move it to a more suitable location requires looking not only at performance charts but also at location data.
In this article, we examine how branch closure and relocation decisions can be made more accurate with data support, which analyses can be used, and how this process contributes to business strategy.
Closure or Location Change?
A branch’s poor performance does not always mean it should be closed. Often the problem is being located in the wrong place, being in an environment that does not match the target audience, or being under high competition. Therefore, the relocation option is a serious opportunity for branches that have the potential to operate more efficiently at alternative points.
How Does the Data-Driven Decision Process Work?
- Analysis of Performance Data
- The operational data of the relevant branch, such as sales, visits, and transaction volume, are analyzed.
- It is evaluated whether the weakness is temporary, environmental, or structural.
- Location-Based Comparative Review
- Data such as demographics, competition, pedestrian traffic, and accessibility of the branch’s location are analyzed.
- It is investigated whether there are more suitable alternative points in the same region.
- Developing Relocation Scenarios
- Alternative scenarios are created by identifying regions with higher pedestrian flow, where the target audience is concentrated, or that offer rent/cost advantages.
- Feasibility analysis is performed for each alternative.
- Estimated Performance Modeling
- Revenue forecasting is done for new location scenarios.
- The potential return on the relocation decision is calculated by comparing it with past performance data.
- Result-Oriented Decision Matrix
- All alternatives are scored according to cost, revenue, access, and competition criteria.
- It is clearly seen whether closing or moving is more advantageous.
What Kind of Data is Used?
- Store sales and visit data
- Regional demographic and economic indicators
- Competition density maps
- Pedestrian and vehicle traffic measurements
- Access and transportation analyses
- Rental values and property cost data
- Socioeconomic segmentation maps
- Customer profile in new potential regions
Who Should Use This Analysis?
- Retail store chains
- Banks and financial branch structures
- Fast delivery and logistics companies
- Fuel and energy stations
- Health, pharmacy, and private education institutions
- Brands that want to grow their franchise network
The decision to close a branch is a difficult and impactful step. Therefore, it should be based on data, not intuition; it should be understood why the current point performs poorly, and the potential of alternatives should be measured. Thanks to data-driven location analyses, not only closing but also restarting becomes a strategy. Every branch is not unsuccessful — it cannot make a difference if it is not in the right place.
