Honey, I Shrunk The Inventory

Working at T-Mobile I learned a lot about Operations. I learned that T-Mobile’s inventory has more items than just phones. It contains items such as handsets, covers, headphones, chargers, and other accessories. The inventory is counted at least once a month and the process involves manually counting each SKU (Stock Keeping Unit) in the front of the store and in the back of the store where the inventory is locked. After each count the result is compared to the inventory at the beginning of the month plus new-ordered inventory minus the sales and minus all the items that have been returned for various reasons. In theory the manual count should equal to the remaining inventory on file, but in real life it doesn’t happen.

Honey, I shrunk the Inventory

In real life the store manager uses personal judgment when opening large business accounts and he is able to give some SKUs for free. Sometimes when the employees sell or return the SKU they may accidentally scan a different SKU (each color or pattern of the certain cover has its own SKU!). Sometimes the returns are not scanned correctly, and sometimes it happens that a phone cover falls under a closet. In real world there is a certain percentage for which the loss is acceptable.

When the loss of inventory is bigger than a set percentage it becomes an issue. That may indicate that there is theft in the store, or mishandling of inventory or perhaps just plain incompetence. The steps to fight the high “shrink” percentage include a weekly count of the inventory, daily reports, probations and write-offs for the employees who are caught for scanning wrong items at POS or not scanning them at all. The store managers are being judged by the “Shrink” metrics, their salary and performance reviews can be seriously affected by the higher percent of “Shrinkage”.

Another metrics that affects managerial performance is traffic conversion. It is measured on daily and monthly basis and it’s designed to measure sales productivity. Each store has a device mounted inside of the store, just above the door, and it measures the number of people who walk-in. Then the number of sales is divided by number of “walk-ins” and that ratio represents the sales conversion rate. A low conversion rate shows low productivity and it means that the store manager should step up his game.

One of the ways to fight a low conversion rate is to make sure that the sales associates talk about current promotions. That they look at the customer’s account to see if the customer has any type of need and that need has a solution in a form of a product they can offer. That the employees are asking the customer the right questions that may help discover other needs. So next time when you are paying your bill or buying something at your carrier’s store consider whether or not you think of the sales representative’s questions as product pushing or simply discovering customer needs.

Optimize, Don’t Compromise!

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?