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.

Keeping on track with trends is crucial to growing and developing a relationship with your customers, these Rice University researchers found. Getty Images

Rice researcher delves into the importance of trendspotting in consumer behavior

Houston voices

Every business wants to read consumers' minds: what they love, what they hate. Even more, businesses crave to know about mass trends before they're visible to the naked eye.

In the past, analysts searching for trends needed to pore over a vast range of sources for marketplace indicators. The internet and social media have changed that: marketers now have access to an avalanche of real-time indicators, laden with details about the wishes hidden within customers' hearts and minds. With services such as Trendistic (which tracks individual Twitter terms), Google Insights for Search and BlogPulse, modern marketers are even privy to the real-time conversations surrounding consumers' desires.

Now, imagine being able to analyze all this data across large panels of time – then distilling it so well that you could identify marketing trends quickly, accurately and quantitatively.

Rice Business professor Wagner A. Kamakura and Rex Y. Du of the University of Houston set out to create a model that makes this possible. Because both quantitative and qualitative trendspotting are exploratory endeavors, Kamakura notes, both types of research can yield results that are broad but also inaccurate. To remedy this, Kamakura and Du devised a new model for quickly and accurately refining market data into trend patterns.

Kamakura and Du's model entails taking five simple steps to analyze gathered data using a quantitative method. By following this process of refining the data tens or hundreds of times, then isolating the information into specific seasonal and non-seasonal trends or dynamic trends, researchers can generate steady trend patterns across time panels.

Here's the process:

  • First, gather individual indicators by assembling data from different sources, with the understanding that the information is interconnected. It's crucial to select the data methodically, rather than making random choices, in order to avoid subjectively preselecting irrelevant indicators and blocking out relevant ones. Done sloppily, this first step can generate misleading information.
  • Distill the data into a few common factors. The raw data might include inaccuracies, which must be filtered out to lower the risk of overreacting or noting erroneous indicators.
  • Interpret and identify common trends by understanding the causes of spikes or dips in consumer behavior. It's key to separate non-cyclical and cyclical changes, because exterior events such as holidays or weather can alter behavior.
  • Compare your analysis with previously identified trends and other variables to establish their validity and generate insights. Looking at past performance through the filter of new insights can offer managers important guidance.
  • Project the trend lines you've identified using historical tracking data and their modeling framework. These trend lines can then be extrapolated into near-future projections, allowing managers to better position themselves and be proactive trying to reverse unfavorable trends and leverage positive ones.

It's important to bear in mind that the indicators used for quantitative trendspotting are prone to random and systematic errors, Kamakura writes. The model he devised, however, can filter these errors because it keeps them from appearing across different series of time panels. The result: better ability to identify genuine movements and general trends, free from the influence of seasonal events and from random error.

It goes without saying that the information and persuasiveness offered by the internet are inevitably attended by noise. For marketers, this means that without filtering, some trends show spikes for temporary items – mere viral jolts that can skew market research.

Kamakura and Du's model helps sidestep this problem by blending available historical data analysis, large time panels and movements while avoiding errors common to more traditional methods. For managers longing to glimpse the next big thing, this analytical model can reveal emerging consumer movements with clarity – just as they're becoming the future.

(For the mathematically inclined, and those comfortable with Excel macros and Add-Ins, who want to try trendspotting on their own tracking data, Kamakura's Analytical Tools for Excel (KATE) can be downloaded for free at http://wak2.web.rice.edu/bio/Kamakura_Analytic_Tools.html.)

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This article originally appeared on Rice Business Wisdom.

Wagner A. Kamakura is Jesse H. Jones Professor of Marketing at Jones Graduate School of Business at Rice University.

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Houston robotics co. unveils new robot that can handle extreme temperatures

Hot New Robot

Houston- and Boston-based Square Robot Inc.'s newest tank inspection robot is commercially available and certified to operate at extreme temperatures.

The new robot, known as the SR-3HT, can operate from 14°F to 131°F, representing a broader temperature range than previous models in the company's portfolio. According to the company, its previous temperature range reached 32°F to 104°F.

The new robot has received the NEC/CEC Class I Division 2 (C1D2) certification from FM Approvals, allowing it to operate safely in hazardous locations and to perform on-stream inspections of aboveground storage tanks containing products stored at elevated temperatures.

“Our engineering team developed the SR-3HT in response to significant client demand in both the U.S. and international markets. We frequently encounter higher temperatures due to both elevated process temperatures and high ambient temperatures, especially in the hotter regions of the world, such as the Middle East," David Lamont, CEO of Square Robot, said in a news release. "The SR-3HT employs both active and passive cooling technology, greatly expanding our operating envelope. A great job done (again) by our engineers delivering world-leading technology in record time.”

The company's SR-3 submersible robot and Side Launcher received certifications earlier this year. They became commercially available in 2023, after completing initial milestone testing in partnership with ExxonMobil, according to Square Robot.

The company closed a $13 million series B round in December, which it said it would put toward international expansion in Europe and the Middle East.

Square Robot launched its Houston office in 2019. Its autonomous, submersible robots are used for storage tank inspections and eliminate the need for humans to enter dangerous and toxic environments.

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This article originally appeared on EnergyCapitalHTX.com.

Houston's Ion District to expand with new research and tech space, The Arc

coming soon

Houston's Ion District is set to expand with the addition of a nearly 200,000-square-foot research and technology facility, The Arc at the Ion District.

Rice Real Estate Company and Lincoln Property Company are expected to break ground on the state-of-the-art facility in Q2 2026 with a completion target set for Q1 2028, according to a news release.

Rice University, the new facility's lead tenant, will occupy almost 30,000 square feet of office and lab space in The Arc, which will share a plaza with the Ion and is intended to "extend the district’s success as a hub for innovative ideas and collaboration." Rice research at The Arc will focus on energy, artificial intelligence, data science, robotics and computational engineering, according to the release.

“The Arc will offer Rice the opportunity to deepen its commitment to fostering world-changing innovation by bringing our leading minds and breakthrough discoveries into direct engagement with Houston’s thriving entrepreneurial ecosystem,” Rice President Reginald DesRoches said in the release. “Working side by side with industry experts and actual end users at the Ion District uniquely positions our faculty and students to form partnerships and collaborations that might not be possible elsewhere.”

Developers of the project are targeting LEED Gold certification by incorporating smart building automation and energy-saving features into The Arc's design. Tenants will have the opportunity to lease flexible floor plans ranging from 28,000 to 31,000 square feet with 15-foot-high ceilings. The property will also feature a gym, an amenity lounge, conference and meeting spaces, outdoor plazas, underground parking and on-site retail and dining.

Preleasing has begun for organizations interested in joining Rice in the building.

“The Arc at the Ion District will be more than a building—it will be a catalyst for the partnerships, innovations and discoveries that will define Houston’s future in science and technology,” Ken Jett, president of Rice Real Estate Company, added in the release. “By expanding our urban innovation ecosystem, The Arc will attract leading organizations and talent to Houston, further strengthening our city’s position as a hub for scientific and entrepreneurial progress.”

Intel Corp. and Rice University sign research access agreement

innovation access

Rice University’s Office of Technology Transfer has signed a subscription agreement with California-based Intel Corp., giving the global company access to Rice’s research portfolio and the opportunity to license select patented innovations.

“By partnering with Intel, we are creating opportunities for our research to make a tangible impact in the technology sector,” Patricia Stepp, assistant vice president for technology transfer, said in a news release.

Intel will pay Rice an annual subscription fee to secure the option to evaluate specified Rice-patented technologies, according to the agreement. If Intel chooses to exercise its option rights, it can obtain a license for each selected technology at a fee.

Rice has been a hub for innovation and technology with initiatives like the Rice Biotech Launch Pad, an accelerator focused on expediting the translation of the university’s health and medical technology; RBL LLC, a biotech venture studio in the Texas Medical Center’s Helix Park dedicated to commercializing lifesaving medical technologies from the Launch Pad; and Rice Nexus, an AI-focused "innovation factory" at the Ion.

The university has also inked partnerships with other tech giants in recent months. Rice's OpenStax, a provider of affordable instructional technologies and one of the world’s largest publishers of open educational resources, partnered with Microsoft this summer. Google Public Sector has also teamed up with Rice to launch the Rice AI Venture Accelerator, or RAVA.

“This agreement exemplifies Rice University’s dedication to fostering innovation and accelerating the commercialization of groundbreaking research,” Stepp added in the news release.