For a while I worked on the retail side of a major wireless company. My job was mainly sales with a slight touch of customer service, or at least that is what I thought. We would come in to the store, have our morning meetings, deal with customers, sell headsets and services, and go home. After a while I was starting to get bored and I decided to shadow my manager to experience a different side of retail sales. During my shadowing I learned a lot about how T-Mobile manages input units such as labor, how it handles its inventory, the metrics it uses to identify inventory problems in specific stores, and what T-Mobile does to optimize the process. In this bog I would like to share my encounter with Process Optimization at T-Mobile.
Once I came to work to find a team of people who were standing and looking over what we were doing. We were told to do everything as we usually do from opening the store to closing; they were with us for the entire process. The method was very close to what we had in our first class where we had an assembly line and where we were making puppets out of paper. The people who were monitoring us had timers with them, as we had in our class, and tablets where they recorded everything that we did, including bathroom and lunch breaks. Now as I think about it, it makes more sense, and I understand that they were trying to identify the specific tasks in our workflow that were taking the longest. Later that data was most likely analyzed for purpose of identifying steps that could be eliminated or combined.
The evaluation team was there during the weekend only. They were following us from Friday to Sunday. The only thing that I didn’t understand was why it was done only during the weekend. Fridays and Sundays are the busiest workdays and if the evaluation process were up to me I would have had this done during the weekday. The reasons for this is because if you compare it to a yearly cycle, they were measuring our productivity during the busiest time of the year for any retail location which starts in September and ends in January. Which means that their measurements would not reflect the actual process since it is not seasonally adjusted. The problem is that many important decisions in Operations Management will be made from the data gathered and this data may not show the real picture of stores productivity.
Another important matter that I noticed was the qualification of the team that visited us. T-Mobile hired temporary workers from Craigslist to do that job. Most of them were between 25-35 years old. Do you think they understood the importance of what they were doing and how it could affect the company?