Executive Briefings

Using Science to Achieve Retail On-Shelf Availability

Achieving forecast accuracy is both an art and a science. Rahul Tyagi, associate director of retail and CPG with TCS, explains how the science part can help companies to solve this thorny problem.

After all these years, on-shelf availability remains a problem for many retailers. There are two primary reasons for this state of affairs, says Tyagi. One is market-driven, based on an explosion of channels, the dominance of the internet, and growth of business-to-business commerce. Together they have resulted in a fragmentation of demand.

The second reason is a continuing demographic shift in buying power from Baby Boomers to Millennials. The latter are more fickle, and less loyal to a particular channel. “Capturing their behavior is not easy,” says Tyagi, adding that merchandisers must employ all possible sources of information. They need to achieve a “perfect marriage” of supply-chain planning and merchandising.

Retailers and suppliers still have a hard time with forecast accuracy. Many don’t know how to harness a “treasure trove” of data. In addition, traditional forecasting systems make it difficult to obtain a coherent answer, based on the wealth of information that is available to sellers today. Solutions require many parameters and significant scientific know-how.

Yet another challenge lies in the difficulty of managing more than a million item and location combinations a week. Retailers need to employ heuristics and come up with approximations. But in many companies, planning is an entry-level job. New hires simply don’t have the experience to manage the process, Tyagi says.

Science offers analytical techniques that can provide a deeper understanding of demand patterns, especially during promotions and seasonal peaks. Data must be deconstructed and incorporated into workable forecast models. “You have to look at a better way of doing this,” says Tyagi. Over the next five years, he expects new statistical models to become ingrained in forecasting tools.

To view the video in its entirety, click here

After all these years, on-shelf availability remains a problem for many retailers. There are two primary reasons for this state of affairs, says Tyagi. One is market-driven, based on an explosion of channels, the dominance of the internet, and growth of business-to-business commerce. Together they have resulted in a fragmentation of demand.

The second reason is a continuing demographic shift in buying power from Baby Boomers to Millennials. The latter are more fickle, and less loyal to a particular channel. “Capturing their behavior is not easy,” says Tyagi, adding that merchandisers must employ all possible sources of information. They need to achieve a “perfect marriage” of supply-chain planning and merchandising.

Retailers and suppliers still have a hard time with forecast accuracy. Many don’t know how to harness a “treasure trove” of data. In addition, traditional forecasting systems make it difficult to obtain a coherent answer, based on the wealth of information that is available to sellers today. Solutions require many parameters and significant scientific know-how.

Yet another challenge lies in the difficulty of managing more than a million item and location combinations a week. Retailers need to employ heuristics and come up with approximations. But in many companies, planning is an entry-level job. New hires simply don’t have the experience to manage the process, Tyagi says.

Science offers analytical techniques that can provide a deeper understanding of demand patterns, especially during promotions and seasonal peaks. Data must be deconstructed and incorporated into workable forecast models. “You have to look at a better way of doing this,” says Tyagi. Over the next five years, he expects new statistical models to become ingrained in forecasting tools.

To view the video in its entirety, click here