To my surprise, I was greeted by the same sales executive who had met me in the chain's central Delhi branch. On probing, he told me about the company's strategy to rotate staff based on requirements. Simply put, the store makes weekly - and at times even daily - projections of consumer traffic at various stores and moves available staff among them.
The trend seems to be catching on.
In organised retail today, 90 per cent of the employees are deployed at the front end. Now footfalls vary depending on the day of the week, or even the time of the day, leaving many people at the front end without many customers to attend at times or deal with a sudden rush of people at other times. In that sense, an optimum deployment of people starts with an accurate forecast.
That's how Croma is making the most use of its front-end staff. This was done last year as part of a productivity enhancement initiative across its stores. Earlier, if the chain was opening a new store, it would get into the process of hiring afresh to fill the front-end positions. Now, every time a new store opens, the company pulls a certain number of experienced employees placing them alongside freshers. So even at a new Croma store you will see a fresher-to-experienced employee ratio of 60:40. This achieves two purposes: one, customers don't have to deal with absolute novices, and two, it ensures older staff get exposure to newer zones. The company says it has improved its same-store profitability with this initiative.
Of course, managers have always had to make tough scheduling decisions; now, the discerning consumer and the increasingly fierce competition have made things tougher. Mind you, even the best scheduling plan requires adjustments. From employees calling in sick to equipment breakdown - the list of operational glitches could be endless.
Going forward, the real challenge of advanced scheduling in retail lies in slicing and dicing the available data. Let's not get into the potential of big data because not even a handful of companies are there yet. But from the looks of it quite a lot of companies are looking at staff rotation based on traffic data.
And it's not difficult if you narrow down your focus area. Let's take the example of India's biggest retailer Big Bazaar, which has three stores in Gurgaon. All these stores (MG Road, NH8 and Sohna Road) are located within a radius of 10 km. On any given day if there are more footfalls during a particular time window at any of these stores, some employees could be moved in from stores with low footfalls. Text, email and IVR could be some of the ways of approaching employees for shift changes.
Some tools are available for better advanced scheduling already. Kronos Workforce Scheduler is one. The schedule-to-skill feature enables managers to factor employee skills and proficiency levels into scheduling decisions to avoid assigning all inexperienced workers to high-demand shifts or all highly experienced workers to slower shifts. Instead of sorting through employee records to determine which worker has the right skills, managers can automatically align proficiency requirements by job or location for any time span to define the best labour mix based on forecasted demand. This feature can make it easy for managers at stores that have, say, jewellery counters or bank branches with vaults to schedule the right number of key holders per shift. It allows managers in manufacturing schedule employees with a variety of skills and experience to work together on the production line.
If done in the right way, advanced scheduling can control labour costs, minimise compliance risk and improve workforce productivity. The experiment has just begun.
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