Productivity is a popular measure of process performance. It can be misleading if too much attention is paid just to it. The Agile and Lean Glossary defines productivity as a ratio of the customer value produced per unit of labor. When labor productivity is the primary focus information effectiveness suffers and the result is higher costs, poorer quality, and lower customer satisfaction.
The emphasis on productivity causes too much attention to be placed on the labor cost denominator of the productivity calculation rather than the customer value numerator. Reducing the number of hours or cost per hour to produce customer value increases productivity. This then becomes the goal.
For example, investments in information technologies are typically justified by increasing labor productivity. If it takes 8 labor hours to create a unit of customer value and a tool can be created to reduce this to 4 hours; the result is a 50% increase in productivity.
Productivity in our Blood
The use of a tool to increase productivity is something people understand. It is in our DNA. We have been prodigious tool users for a very long time. But too much of a good thing leads to an unbalance.
To say that the only measure for process improvement is productivity is the same as saying the only tool needed to build a house is a hammer. Certainly conceivable to do, but add a few more tools to the tool box and the power of possibilities increase.
Lada’s Laws define Service Time and the Lean Ratio as two additional measures that help identify new possibilities for process improvement.
The calculation of service time is divided into two components:
- work time
- wait time
Productivity measures the effectiveness of work time. Reduce work time and productivity increases. But reducing work times may not have an impact on wait time. In fact increasing productivity by reducing work times could cause wait times to stay the same or even increase. Longer wait times lead to increased cost, more errors, and lower customer satisfaction.
Information Effectiveness
If work time is an indicator of labor productivity, wait time is an indicator of information effectiveness. What is waiting during that wait time is information. People are busy. At any point in time they are applying their labor somewhere.
In the typical process information is lazy. It spends a lot of time waiting around for someone to pay attention. And if information is waiting then so is a customer.
Two Perspectives of Improvement
Take the case of customers waiting for their service requests to be completed. Let’s say that the average service time for those requests is 4 weeks and that the total work time to complete the service request is 16 hours.
If we were able to increase the labor productivity associated with the service request by 50% our work time would be reduced to 8 hours from 16. Most organizations would consider a 50% increase in productivity a huge win and a significant cost savings.
From the customer point of view, what used to take 4 weeks would now only take 3 weeks and 4 days. Would the customer even notice the difference? An organization focusing only on productivity may not even notice the problem, but their customers would. Under this scenario you could conceivably reduce the work time to zero and still take 3 weeks and 3 days.
This is a hard lesson to learn. Time after time, organizations attempt to reduce service times by solely measuring and increasing productivity. Paying attention to the wait time component of service time, in addition to the work time, provides a more balanced view that leads to increases in both labor productivity and information effectiveness.
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