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PMC Case Study | Industrial Engineering Study for a Major Discount Retailer

June 9, 2021

PMC Case Study | Industrial Engineering Study for a Major Discount Retailer


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Stephanie Sobieski |

Project Summary

A large discount retailer was preparing to incorporate a demand-driven scheduling system.  A key parameter required for this system was accurate workload content by task for each individual department.  This is a classic Industrial Engineering function and the retailer employed PMC to propose a methodology and to execute the study.  While collecting this data, it was important to use Lean principles to identify opportunities to reduce waste and suggest process improvements.

System Description

Six stores across two states were studied.  Within each store, three departments were studied.  The departments studied were Lawn and Garden, Stationery, and Toys.  The toy department consisted of the retail floor as well as an assembly area for bicycles.  There was one common set of tasks which was applicable to all retail departments and a separate list of tasks for the assembly area.

Opportunity

The demand-driven scheduling system is highly desirable for the retail industry because it is crucial to provide customers with the desired service level, while avoiding overstaffing.  Lean principles are currently finding their way into industries outside of manufacturing and the retail industry is no different.  By identifying waste within a store, processes can be streamlined and process times can be minimized; thus improving the customer’s shopping experience and minimizing the associated costs to the retailer.

Approach

PMC utilized random sampling to measure the workload within each store.  The study encompassed one business cycle across six different stores.  A business cycle was defined as a seven day period, all hours of operation, as well as the opening and closing activities of associates.

Solution

Random sampling data was used to develop standard times for tasks.  The number of items sold was used as the workload driver for each department.  This data was used to develop demand-driven schedules.  Several additional analyses were performed using this data including:

  1. Analyzing the impact of government regulations for applying price tags to items versus shelves
  2. Investigating the results of scheduling department managers during peak hours
  3. Comparing task proportions between department managers and retail associates
  4. The work content developed was compared between Old and New store structure

Benefit

PMC provided the data required to support a demand-driven scheduling system based on workload and performed several detailed analyses on this data.  This data can be used to ensure the appropriate service level is achieved, without overstaffing.  Several process improvements were suggested based on lean principles which will enable the retailer to improve productivity of staff and to improve the customer’s shopping experience.

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Stephanie Sobieski

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