FInd out how a student from IIM Shillong used data to minutely analyze each aspect during internship

By: Kuljeet Singh

I was required to maximize the efficiency with which trucks can be loaded or unloaded so that the total idle time of truck at the hub can be minimized and the total time of the truck on road can be maximized.

During my PGDM from IIM Shillong, I did my two months internship in Self-express Pvt Ltd. The interview process for Self-express included two rounds after being shortlisted for the Operations Manager position. During the interview, they ask questions related to 3PL, 2PL logistics. Then they gave a real-life case regarding the heavy attrition of loading workers and I was required to explain how I would handle this scenario making sure that the truck leaves for the destination on time. In the second round, the interviewee asked me to explain a unique value proposition given by self-express to its customers.

Self-express has two kinds of offices: corporate office and hub. The hub is where the actual transportation of vehicles takes place.

Fig1: Working of local and central hub

The project that was assigned to me was “Performance Mapping during Loading and Unloading of Vehicles” and I was to provide recommendations to improve it. Therefore, in layman terms, I was required to maximize the efficiency with which trucks can be loaded or unloaded so that the total idle time of truck at the hub can be minimized and the total time of the truck on road can be maximized.

I knew that the building block of any project is data. So, I collected data about every tiny thing involved starting from the time when the truck enters the hub till the point they leave. It included the time truck takes to register at the gate, time taken to unload the truck, age and background of various workers, time taken to load the truck, source and destination of various packages loaded, distance between where the truck is parked to the point where packages are placed. Therefore, a major part of my initial days at Self-express involved running from one truck to another to make sure accurate and precise data is recorded.

Fig2: Snapshot of data collected

After that, I decided to analyze it using SPSS statistical tool. I found out that the standard deviation of unloading per package is not that much but when we look at the standard deviation of unloading per ton, it is coming out to be around 92.7%, which is a large number. It signifies that some workers are taking very less time to unload per ton and some are taking a lot of time to unload per ton.

Therefore, the next phase involved identifying the reasons for lagging performance. We decided to analyze the performance of each of the operation assistants and handlers. These handlers work under the guidance of the operation assistant. One operation assistant handles a team of four handlers who load and unload the package. The handlers are third party workers and operation assistants are Self-express personnel.

I found out that 3.12 % of the handlers got the score in between one and two. This is primarily due to the lack of knowledge, capability, work manners and attentiveness. 71.8% of the handlers got the score in between two and 3. This is primarily due to lack of Knowledge and work manners. About 25% of the handlers got the score in between three and four. This is primarily due to the lack of work manners.

Then I tried to run a regression analysis on the performance of handlers on the above parameters to see if we could find an equation to predict how a handler will perform based on some factors.

About the Author:

Kuljeet Singh is an alumnus of IIM Shillong. He completed his MBA with a specialisation in Finance in 2019. At present, he works with JP Morgan and Chase as a Senior Analyst.