A few related things happened this week which all prompted me to write about retail innovations. First, a startup company I am advising, Objective Logistics, has received a round of funding from Google Ventures and Atlas Ventures.
I had written about what they do in this blog already and, needless to say, securing funding from these widely respected venture capital firms is exciting. Of course, the media picked up the news and you can read details at ReadWriteWeb, Mashable,Boston Herald, Xconomy and many others. Second, I gave a long interview to the Economist where I talked about some retail innovations out there. Of course, what actually appeared in the journal was just one sentence so I figured I can expand upon what I actually said here. Third, Harvard Business Review asked me to contribute to their blog project on the 21st century retail so I thought I can practice here first (update: here is my HBR blog post). Casual glance at this web site makes it evident that many, if not most, retail innovations seem to be around products, store design, technological innovations etc. But here is a different take on retail innovation.
20th century retail was synonymous with treating labor, the largest operating cost component of any retail company, as a nuisance, which is to be minimized. Sam Walton, the founder of the biggest retailer in the world, said it best in his book “Made in America”: “No matter how you slice it in the retail business, payroll is one of the most important parts of overhead, and overhead is one of the most crucial things you have to fight to maintain your profit margins. That was true then, and it is still true today.” Using this guiding principle, most retail companies would simply set targets for store staffing levels at some constant over time level (say 10% of sales) and, at best, they would vary staffing levels based on sales forecasts or not at all.
In the 21st century retailers will finally realize that labor is the key resource that can drive sales and customer satisfaction. From simply scheduling labor according to demand forecast, innovative companies are already moving towards closely tracking customer flow through the store using technological solutions and then adjusting labor in real time to improve conversion rates. Our study has shown that scheduling labor based on store traffic can help retailers identify stores that are overstaffed and understaffed, and reallocate labor among them to achieve significant sales increases, at no or minimal costs.
But the best-of-the-best companies go even further to recognize that all employees are different – these innovative retailers use business analytics to track performance of individual store associates in order to put best people at the most important times and places in the store. Ann Taylor, a clothing retailer, was one of the early pioneers that recognized the value of scheduling retail labor according to past performance of sales associates: best sales people would obtain first choices of times to work at and more schedule flexibility. Other closely related industries are also experimenting with performance-based scheduling of labor. As I mentioned above, Boston-based startup company Objective Logistics has just received a round of funding from Google Ventures and Atlas Ventures to implement performance-based scheduling software for restaurants. The best-performing waiters would be offered best times to work (e.g., Friday and Saturday dinner times) when orders are the biggest and tips are the highest. Call center companies are increasingly using individual sales data to put best people at the most important junctions.
But this is not the limit either. In the end, ensuring that the store employee is there at the right time does not necessarily mean that the employee will know to do the right thing. The only way to be sure is to track customer behavior within the store, while trying to understand the nature and the outcomes of customer-employee interaction. There is a handful of companies in the world that are currently experimenting with analysis of in-store video streams to better understand the impact of customer-employee interaction and the best ways to increase sales. While in the USA strict privacy concerns handicapped these efforts, South American, Asian and European retailers are increasingly using data analytics inferred from in-store videos to help employees improve sales and customer satisfaction. This could be retail 2.0.