With better leadership, Sears could’ve been a contender – Sharmila Chatterjee

MIT Sloan Senior Lecturer Sharmila Chatterjee

MIT Sloan Senior Lecturer Sharmila Chatterjee

From The Hill

When I arrived in the U.S. for graduate school in the mid-1980s, I asked my host family in a Philadelphia suburb where to shop to outfit my dorm room. They didn’t skip a beat: “Sears,” they said. “It has everything you need.”

To say that I was in awe of Sears would be an understatement. Having grown up in small cities in India that were dominated by mom and pop stores, I’d never seen anything like it. I bought pillows and bed sheets; a hot pot, microwave, a mini fridge; and also rain boots, socks, and a pair of earrings. I remember thinking, “This is the American store of my dreams.”

So last week’s news that Sears filed for bankruptcy struck a personal chord. The company has been under pressure for years: shuttering stores, jettisoning assets and taking on ever more debt. Finally, facing a $134 million payment that it could not afford, Sears capitulated.

The main culprit, according to media coverage, was the rise of online shopping and Amazon. Amazon, of course, has become the familiar villain in these tales — allegedly responsible for the death of many once-dominant American retailers, from Toys “R” Us to Sports Authority to Radio Shack.

But considering e-commerce accounts for only 9 percent of all retail sales, that explanation rings hollow. The truth is, Sears’s bankruptcy is of its own making. Its management, led by Eddie Lampert — Sears’s chairman and its biggest individual creditor and shareholder, made a series of missteps that ultimately crippled the iconic chain.

These include focusing too narrowly on cutting costs at the expense of investing in the in-store experience, spinning off key brands and competing on price.

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Viewpoint: How can department stores survive in the digital era? – Sharmila C. Chatterjee

MIT Sloan Senior Lecturer Sharmila Chatterjee

MIT Sloan Senior Lecturer Sharmila Chatterjee

From Boston Business Journal

How can a department store survive in the age of digital shopping carts and free home delivery? It’s a question that some of even the most iconic retailers struggle to answer.

As a result, many are closing up shop. Last month, for instance, Macy’s identified seven stores for closure as part of its previously announced plan to shutter 100 locations nationwide. In November, Sears said it would close 63 stores on top of the 350 that it announced would shut earlier in the year. And last summer, J.C. Penney closed about 140 of its stores around the country.

Closing less-profitable locations makes a lot of sense, but that alone is not enough. What’s needed is a reinvention of the traditional bricks-and-mortar model. Stores must rekindle the magic of department store shopping by providing a holistic customer experience, one that’s efficient and satisfying from a purchasing point of view, but also engaging and exciting.

For starters, brick-and-mortar stores need to change how they view their online counterparts: digital stores should be seen as complementary forces rather than competitive ones. Shopping in the future will be a blend of the electronic and physical realms. Read More »

Detecting customer-to-customer trends (without social media data) to optimize promotions – Georgia Perakis

MIT Sloan Prof. Georgia Perakis

From Huffington Post

Every year, there are a few items of clothing that become hot. For example, last fall, a Zara coat seemed to become a “must have” item. The coat even had its own Instagrampage with more than 8,000 followers. Many factors contribute to this phenomenon like celebrities — and people with large social media followings — wearing the “hot” item.

When we have detailed social media data, it is relatively easy to identify patterns of influence to predict these trends. But what happens when we don’t have social media data? After all, social media platforms charge tremendous fees for access to that information. Can we use traditional data to detect underlying trends between groups of consumers and improve demand estimation? If so, can we use that information to optimize personalized promotions to increase profits, and also to present “the right individual with the right item at the right price?”

In a recent study, I looked at these questions with MIT Operations Research Center PhD students Lennart Baardman and Tamar Cohen and collaborators from Oracle Retail. We found that the answer to both questions is: yes. We began our study by building a customer demand model and algorithm that incorporates customer-to-customer trends or influences. We then applied the information about customer demand to make promotion decisions. With this method, profits increased between 5-12%. The model can be used by any retailer of any size for any product.

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Why it’s not the end of America’s brick and mortar retail stores–Sharmila C. Chatterjee

MIT Sloan Senior Lecturer Sharmila Chatterjee

MIT Sloan Senior Lecturer Sharmila Chatterjee

From The Hill

Even in a digital age, brick and mortar retailers have distinct advantages over e-commerce. But the other day, I watched as two stores totally blew those advantages. In a bookstore, the customer waiting in line before me asked for a particular book, only to be told it was out of stock. “We can order it for you,” the customer was told. But she shook her head. “I have books on order. I wanted something to read now.” The second came as I returned an item to a large department store chain, a routine matter — or so I thought. Thirty frustrating minutes later, after being shuttled between employees like a ping-pong ball, I left, wondering why something so simple had taken so long.

Both these incidents demonstrate how the woes facing brick and mortar retailers go far beyond price competition from online shopping. The bookstore I visited had missed its advantage of instant gratification. The department store lost its advantage of convenience and the human touch. An impersonal trip to the post office to mail a return was better by comparison.

My shopping experience underscores three primary factors that underlie the plight of current brick and mortar retailers: retreat from core competence, failure to view online counterparts through a complementary lens, and loss of focus on customer experience. Unfortunately, the results of these missteps are apparent.

Distressed retailers are closing stores at a record pace. According to the Wall Street Journal, more than 2,800 retail locations have closed just this year, including hundreds of locations being shut down by national chains such as Payless ShoeSource and RadioShack. The outlook for major department stores is grim. Macy’s said it will close 68 of its 870 stores nationwide, affecting 10,000 employees, citing changing consumer behavior. Sears Holding Corp. will close 108 Kmarts.

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Retailers are leaving money on the table by understaffing – Rogelio Oliva

MIT Sloan Visiting Professor Rogelio Oliva

From Marketwatch

If you’ve gone shopping this holiday season, you may have had the following experience.

You go into a store looking for a gift but need help from a salesperson. Maybe you need more information on the product, or perhaps you need help finding the right color or size. You look around the store, but you can’t find anyone. Giving up, you leave the store without making a purchase.

If that sounds familiar, you aren’t alone. The proportion of customers who typically leave a store because of poor service is not negligible. Prior research shows that 33% of customers who experienced a problem were not able to locate sales help when they needed assistance, and 6% of all possible sales are lost because of lack of service.

Help wanted

Effective management of store labor is clearly important, as it impacts sales performance. However, labor-related expenses also constitute one of the largest components of retailers’ operating costs. As a result, there is a widespread tendency to understaff to save on those costs.

But what is the right number of employees? This is a complex question, as retail environments are characterized by volatile store traffic, making it hard to determine the correct staffing levels and often leading to inconsistent service.

The traditional method for determining staffing is sales-driven and depends on store budget allocation. A typical sales-based staffing rule is to match a constant ratio of expected store sales to the number of store associates. However, that rule ignores the fact that retail sales are also affected by store traffic and might result in labor-to-traffic mismatches, which can hurt sales revenue. Retailers can’t reach their full potential in sales if they follow that staffing practice.

Another problem is that shopper demand may be different from past sales, as past sales include only customers who purchased and not those who had an intention to purchase but left the store due to lack of service. As noted above, this is a fairly common scenario.

Matching staff to shoppers

To address this challenge, my colleagues and I developed a method to match store labor with incoming customer traffic in an efficient manner to improve sales performance. Our method is unique, as it goes beyond the focus on past sales at individual stores to leverage performance data across different stores within a retail chain. It enables retailers to derive aggregate labor requirements by using traffic data, point-of-sale data and labor data across stores with similar attributes like store format, product mix and market demographics. Read More »