Leading organizations are increasingly using advanced analytics to improve their people management practices. Retailers should be particularly aware of this emerging trend, notably regarding store staff, as it plays a crucial double role: sales and operational fulfillment.
Our client, a large fast-food chain, had long devoted considerable effort to managing its store-based staff. Still, the company lacked the analytical edge to take people planning to the next level. Four key challenges needed to be addressed:
Performance analytics are at the core of people and capacity planning. A statistical analysis of both transactional data and client surveys highlighted two main trends about employees: experience drove productivity, while age drove customer satisfaction. Either way, effective retention policies emerged as a strategic priority.
Forecasting techniques were then applied to understand seasonality trends and other patterns in order to grasp future demand. Insights about productivity helped to translate such demand into workload projections. Subsequently, an optimization-based approach was developed to generate efficient work plans that met both legal restrictions and employee needs.
The work plans obtained according to the proposed approach yielded a reduction of around 10% in total working hours. Efficiency gains arose mostly in larger stores, as economies of scale were captured by promoting uniform standards between stores. These significant savings were reached without breaching service standards (e.g., minimum staff requirements) or harming employee satisfaction.
The model was materialized in an intuitive decision-support tool, allowing for iterative plan refinement. And as the planning process is as important as the intelligence behind it, close usage support was provided to store managers in an initial phase, ensuring the full adoption of the tool.