Parkinson’s law is the adage that says “work expands so as to fill the time available for its completion.” While sometimes applied to the growth of bureaucracy in organizations, we believe it can be the root of lower productivity in ecommerce operations as well as other business functions.
Cyril Northcote Parkinson, British naval officer, historian and author of over 60 books, first published his law in a satirical article in The Economist in 1955. It was a critique of the inefficiency of civil service bureaucracy, including continually rising headcount and costs.
Decades later, the principle still holds: If we aren’t diligent in planning workloads, measuring productivity and publishing results to employees, work will expand to fill the time available for its completion. If you don’t have productivity measurement in place, here’s how you can experiment with measuring and improving productivity.
An ecommerce client asked us for advice on how to achieve a higher, consistent rate of order picking. The company’s ecommerce operations management:
- Was not measuring the number of orders, lines and units picked per hour throughout the day, so there was no history for planning the workload and measuring productivity
- Used the same number of pickers throughout the five-day work week. Monday had the greatest demand based on weekend web orders, then it was successively smaller through the week
- Had severe concerns that with increasing order volumes they were going to fall behind on larger volume days, possibly missing carrier pickup by 500 to 600 orders. Their service level standard is to clear all orders by 2 p.m. each day
- Had installed a very functional order management system, but has no labor management or productivity measurement software
We set out to see if the order picking pace could be increased without any loss in quality or accuracy. Their accuracy rate was 99.97% for the previous month. As discussed above, if you don’t collect, analyze and use this data for planning it will be very difficult to clear orders daily and handle increasing volume.
So, the next steps were:
Understand the order profiles: What percentage of open orders are single line vs. more complex multi-line? How many had the top-selling product?
At a high level, sample the productivity (orders, lines, units per hour): This needs to be a broad enough order sample, such as during half of an eight-hour shift. We recorded picking productivity and hours worked for the morning and afternoon, with the same team of 10 associates. The overall average was 1.77 minutes per order; the morning averaged 2 minutes per order – when workers didn’t know they were being timed – vs. 1.42 minutes per order in the afternoon when they did.
The improvement overall was significant, especially considering the order makeup and workforce were the same. Of course, the true test comes when the customer receives the order. Barcoding in pick and pack confirmation provides a much higher degree of accuracy.
A couple of employees were very interested in what we were trying to achieve. for the two timeframes, with the same staff and order profiles. The workers said they understood our concerns. Then ecommerce operations management gave them a pep talk, praised them and pumped them up saying they could achieve higher levels without adding people.
Management is going to increase the goals for picking by 8%-10% to see if it’s achievable without quality slipping and increased errors. Once you’re confident of collecting data and measuring productivity, consider taking the reporting to a more granular level such as by employee. Set up ways to communicate productivity reports to the workforce daily and weekly to reinforce the importance of the program.
A natural progression is to consider the facility layout, and how reworking your slotting can improve the pick rate; you can find out more in this blog post.
We want to emphasize that this methodology is in no way comparable to engineered time and motion studies. This involves a much greater degree of data sampling and design as well as a labor management system, testing and an experimental model and a cost/benefit analysis to justify the implementation. Engineered studies must then be updated regularly to raise the productivity bar after reviewing individual work and performance. They are necessary when employees are paid on piecework.
Seeing the immediate increase in productivity and the positive reaction from employees reminded us of another industrial engineering principle: The Hawthorne effect. This holds that people will modify their behavior simply because they’re being observed. The name comes from one of the most famous industrial experiments at Western Electric’s factory in Hawthorne, IL outside Chicago in the late 1920s and early 1930s.
Since December 2017, the unemployment rate in the U.S. has ranged from 4.1% 8. If your company is growing fast and you’re adding people, make measuring productivity in your ecommerce operations a priority.
Brian Barry is President of F. Curtis Barry & Company