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Rice University research uses data to spot your best sales team members

By accounting for both known and unknowable factors, managers can identify salespeople with traits that work best in different types of sales. Getty Images

When you're a manager, decisions barrage you each day. What product works? Which store layout entices? How will you balance the budget? Many of these decisions ultimately hinge on one factor: the skills of your sales force.

Often, when managers evaluate their salespeople they contend with invisible factors that may not show up in commissions or name-tagged sales rosters — intangibles such as product placement, season or simply a store's surrounding population. This makes it hard to fully evaluate a salesperson, or to spot which workers can teach valuable skills to their peers and improve the whole team.

But what if you could plug a few variables into a statistical model to spot your best sellers? You could then ask the star salespeople to teach coworkers some of their secrets. New research by Rice Business professor Wagner A. Kamakura and colleague Danny P. Claro of Brazil's Insper Education and Research Institute offers a technique for doing this. Blending statistical methods that incorporate both known and unknown factors, Kamakura and Claro developed a practical tool that, for the first time, allows managers to identify staffers with key hidden skills.

To test their model, the researchers analyzed store data from 35 cosmetic and healthcare retail franchises in four South American markets. These particular stores were ideal to test the model because their salespeople were individually responsible for each transaction from the moment a customer entered a store to the time of purchase. The salespeople were also required to have detailed knowledge of products throughout each store.

Breaking down the product lines into 11 specific categories, and accounting for predictors such as commission, product display, time of year and market potential, Kamakura and Claro documented and compared each salesperson's performance across products and over time.

They then organized members of the salesforce by strengths and weaknesses, spotlighting those workers who used best practices in a certain area and those who might benefit from that savvy. The resulting insight allowed managers to name team members as either growth advisors or learners. Thanks to the model's detail, Kamakura and Claro note, managers can spot a salesperson who excels in one category but has room to learn, rather than seeing that worker averaged into a single, middle-of-the-pack ranking.

If a salesperson is, for example, a sales savant but lags in customer service, managers can use that insight to help the worker improve individually, while at the same time strategizing for the store's overall success. Put into practice, the model also allows managers to identify team members who excel at selling one specific product category — and encourage them to share their secrets and methods with coworkers.

It might seem that teaching one employee to sell one more set of earbuds or one more lawn chair makes little difference. But applied consistently over time, such personalized product-specific improvement can change the face of a salesforce — and in the end, a whole business. A good manager uses all the tools available. Kamakura and Claro's model makes it possible for every employee on a sales team to be a potential coach for the rest.

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This story originally ran on Rice Business Wisdom.

Based on research from Wagner A. Kamakura, the Jesse H. Jones Professor of Marketing at Jones Graduate School of Business at Rice University.

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Self-driving pizza delivery goes live in Houston

Domino's and Nuro announced their partnership in 2019 — and now the robots are hitting the roads. Photo courtesy of Nuro

After announcing their partnership to work on pizza deliveries via self-driving robots in 2019, Dominos and Nuro have officially rolled out their technology to one part of town.

Beginning this week, if you place a prepaid order from Domino's in Woodland Heights (3209 Houston Ave.), you might have the option to have one of Nuro's R2 robot come to your door. This vehicle is the first do deliver completely autonomously without occupants with a regulatory approval by the U.S. Department of Transportation, according to a news release.

"We're excited to continue innovating the delivery experience for Domino's customers by testing autonomous delivery with Nuro in Houston," says Dennis Maloney, Domino's senior vice president and chief innovation officer, in the release. "There is still so much for our brand to learn about the autonomous delivery space. This program will allow us to better understand how customers respond to the deliveries, how they interact with the robot and how it affects store operations."

Orders placed at select dates and times will have the option to be delivered autonomously. Photo courtesy of Nuro

The Nuro deliveries will be available on select days and times, and users will be able to opt for the autonomous deliveries when they make their prepaid orders online. They will then receive a code via text message to use on the robot to open the hatch to retrieve their order.

"Nuro's mission is to better everyday life through robotics. Now, for the first time, we're launching real world, autonomous deliveries with R2 and Domino's," says Dave Ferguson, Nuro co-founder and president, in the release. "We're excited to introduce our autonomous delivery bots to a select set of Domino's customers in Houston. We can't wait to see what they think."

California-based Nuro has launched a few delivery pilots in Houston over the past few years, including the first Nuro pilot program with Kroger in March 2019, grocery delivery from Walmart that was revealed in December 2019, and pharmacy delivery that launched last summer.

From being located in a state open to rolling out new AV regulations to Houston's diversity — both in its inhabitants to its roadways, the Bayou City stood out to Nuro, says Sola Lawal, product operations manager at Nuro.

"As a company, we tried to find a city that would allow us to test a number of different things to figure out what really works and who it works for," Lawal says on an episode of the Houston Innovators Podcast. "It's hard to find cities that are better than Houston at enabling that level of testing."

Steam the episode here.

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