I have been working as a Team Leader with Rui Chuang Technologies Pvt Ltd (Vivo Mobile Gujarat) for almost 2 years. My duties include sales team management and retail management. Team management further includes responsibilities such as analysing productivity, improving product knowledge, devising sales strategies, evaluating sales team performance, assigning tasks, achieving sales targets, and providing end-to-end support to enhance sales. Under Retail Management, I’m handling Stock Placement, Inventory Management, WOD placement, scheme rollout, planning sell-out schemes and ensure timely liquidation of stocks before new product launches.
As we all know “Data is the New Oil”, I have experienced this term personally, while working as a Team Leader my job was to extract meaningful insight from raw data so that I could answer the questions starting with ‘How’. While working on data I gradually build up an interest in working on multiple excel sheets, processing them, doing many statistical operations, and running some random regression models. As a result, I decided to complete transit my career in the data domain. The moment I took the charge of a team leader I was supposed to manage a team of 45 executives. My role was to take the best out of them and work on their sales skills. This required daily monitoring of sales data, current stock data, maintaining sales turnover period, and effectively looking for the best ways to boost sales for that particular store.
Using data science, we were confident about predicting sales on festivals, inventory per day, forecasting performances, and sales targets and maintaining each product inventory turnover ratio. Being a retail company every company wants its product should receive a good amount of customer pull power so that its stock gets liquidated easily. Assessing the right amount of stock requirements for each store – zero old model inventory and priority to fast-moving models. Need to place the right executive at the right store – so that more customers get converted into sales. Festival Day prediction: sales numbers – Biggest days for a retail company everything needs to be proper. Cross-selling – boosts revenue, increases customer satisfaction, builds engagement and creates long-lasting relationships. Retailer Management – No. of retailers should increase so that more products get into the market, to maintain higher market penetration. The data collection was done using Google sheets, and forecasting and product launch analysis was done using Excel, Time Series Analysis was used for target prediction, SQL for data retrieval, and finally Power BI for generating reports.
After processing the data I found that almost half of the executives have the capability to achieve assigned tasks (Targets) before the month ends. This helps me push their boundaries and derived more numbers. Working on this aspect helps to decrease the model turnover ratio and the retailers’ cash cycle also increased. Productivity increased by 1.5 times and conducting promotional activities at key accounts helped to achieve the desired result. With the help of these processes, I could track each and every aspect of my assigned area, it helped me to record each and every transition and I could take any decision swiftly.
