As an internal auditor for Alicia’s Accessories, a manufacturer of jewelry and fashion accessories sold at popular chain stores throughout the United States, you are assigned to an advisory engagement for warehouse operations.
The warehouse schedules pickup and delivery times based on data points like order frequency, pickup locations, available employees, and the layout of the warehouse. To support these scheduling decisions, the information system captures data, including demand, stock, layout, and daily operations like hours worked and equipment uptime, which is the time a piece of equipment is operating each day.
Last year, the Internal Audit department partnered with the company’s Process Improvement Six Sigma team to perform an advisory review and identify inefficiencies in warehouse operations. The review resulted in recommendations that the warehouse modify the layout by optimizing rack arrangements and redesigning where the conveyors are located. At the time, Internal Audit predicted that there would be a 35% reduction in distance finished goods traveled and a 70% reduction of workforce hours.
Now that the implementation of these recommendations is complete, the chief operations officer has asked Internal Audit to perform data analytics to assess the actual impact of the modifications. You are given the following sample of historical data and sample of post-implementation data. Identify the actual reduction in average distance traveled and workforce hours and compare your numbers to the predicted impact. Determine if the recommendations have had more or less of an impact on the efficiency of the warehouse or if they have had no effect. Perform this analysis based on individual product types.

Sample of historical data:

 

Product Type		Production Quantity		Travel Distance		Hours Labored
A		189261		620		205
A		189620		695		246
A		189722		645		252
B		189630		456		126
B		190201		485		152
B		190322		501		149
B		190410		492		160

Sample of post-implementation data:

 

Product Type		Production Quantity		Travel Distance		Hours Labored
A		189261		490		70
A		189620		540		55
A		189722		530		62
B		189630		225		32
B		190201		315		55
B		190322		266		43
B		190410		290		48

		Historical average distance traveled		Post-implementation average distance traveled		Distance traveled reduction		Meets/Does not meet predictions
Product A Distance:		enter the average distance traveled		enter the average distance traveled		enter percentages %		select an option                                                           Does not meet predictions.Meets predictions.
Product B Distance:		enter the average distance traveled		enter the average distance traveled		enter percentages %		select an option                                                           Does not meet predictions.Meets predictions.

 

 

		Historical average hours labored		Post-implementation average hours labored		Hours labored reduction		Meets/Does not meet predictions
Product A Labor Hours:		enter a number of hours		enter a number of hours		enter percentages %		select an option                                                           Does not meet predictions/Meets predictions.
Product B Labor Hours:		enter a number of hours		enter a number of hours		enter percentages %		select an option                                                           Does not meet predictions/Meets predictions.