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

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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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Announcing the 2025 Houston Innovation Awards finalists

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InnovationMap is proud to reveal the finalists for the 2025 Houston Innovation Awards.

Taking place on November 13 at Greentown Labs, the fifth annual Houston Innovation Awards will honor the best of Houston's innovation ecosystem, including startups, entrepreneurs, mentors, and more.

This year's finalists were determined by our esteemed panel of judges, comprised of past award winners and InnovationMap editorial leadership.

The panel reviewed nominee applications across 10 prestigious categories to determine our finalists. They will select the winner for each category, except for Startup of the Year, which will be chosen by the public via online voting launching later this month.

We'll announce our 2025 Trailblazer Award recipient in the coming weeks, and then we'll unveil the rest of this year's winners live at our awards ceremony.

Get to know all of our finalists in more detail through editorial spotlights leading up to the big event. Then, join us on November 13 as we unveil the winners and celebrate all things Houston innovation. Tickets are on sale now — secure yours today.

Without further ado, here are the 2025 Houston Innovation Awards finalists:

Minority-founded Business

Honoring an innovative startup founded or co-founded by BIPOC or LGBTQ+ representation:

  • Capwell Services
  • Deep Anchor Solutions
  • Mars Materials
  • Torres Orbital Mining (TOM)
  • Wellysis USA

Female-founded Business

Honoring an innovative startup founded or co-founded by a woman:

  • Anning Corporation
  • Bairitone Health
  • Brain Haven
  • FlowCare
  • March Biosciences
  • TrialClinIQ

Energy Transition Business

Honoring an innovative startup providing a solution within renewables, climatetech, clean energy, alternative materials, circular economy and beyond:

  • Anning Corporation
  • Capwell Services
  • Deep Anchor Solutions
  • Eclipse Energy
  • Loop Bioproducts
  • Mars Materials
  • Solidec

Health Tech Business

Honoring an innovative startup within the health and medical technology sectors:

  • Bairitone Health
  • Corveus Medical
  • FibroBiologics
  • Koda Health
  • NanoEar
  • Wellysis USA

Deep Tech Business

Honoring an innovative startup providing technology solutions based on substantial scientific or engineering challenges, including those in the AI, robotics and space sectors:

  • ARIX Technologies
  • Little Place Labs
  • Newfound Materials
  • Paladin Drones
  • Persona AI
  • Tempest Droneworx

Startup of the Year (People's Choice)

Honoring a startup celebrating a recent milestone or success. The winner will be selected by the community via an online voting experience:

  • Eclipse Energy
  • FlowCare
  • MyoStep
  • Persona AI
  • Rheom Materials
  • Solidec

Scaleup of the Year

Honoring an innovative later-stage startup that's recently reached a significant milestone in company growth:

  • Coya Therapeutics
  • Fervo Energy
  • Koda Health
  • Mati Carbon
  • Molecule
  • Utility Global

Incubator/Accelerator of the Year

Honoring a local incubator or accelerator that is championing and fueling the growth of Houston startups:

  • Activate
  • Energy Tech Nexus
  • Greentown Labs
  • Healthtech Accelerator (TMCi)
  • Impact Hub Houston

Mentor of the Year

Honoring an individual who dedicates their time and expertise to guide and support budding entrepreneurs. Presented by Houston Community College:

  • Anil Shetty, Inform AI
  • Jason Ethier, EnergyTech Nexus
  • Jeremy Pitts, Activate
  • Joe Alapat, Liongard
  • Neal Dikeman, Energy Transition Ventures
  • Nisha Desai, Intention

Trailblazer Recipient

  • To be announced
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Interested in sponsoring the 2025 Houston Innovation Awards? Contact sales@innovationmap.com for details.

Houston scientists earn prestigious geophysics career awards

winner, winner

Two Rice University professors have been recognized by the American Geophysical Union, one of the world’s largest associations for Earth and space science.

Rice climatologist Sylvia Dee was awarded the 2025 Nanne Weber Early Career Award by the AGU’s Paleoceanography and Paleoclimatology Section. Richard Gordon, a Rice professor of geophysics also received the 2025 Walter H. Bucher Medal by the AGU. They will both be recognized at the AGU25 event on Dec.15-19 in New Orleans.

The Nanne Weber Early Career Award recognizes contributions to paleoceanography and paleoclimatology research by scientists within 10 years of receiving their doctorate.

“Paleoclimate research provides essential context for understanding Earth’s climate system and its future under continued greenhouse warming," Dee said in a news release. “By studying how climate has evolved naturally in the past, we can better predict the risks and challenges that lie ahead.”

Dee’s work explores how Earth’s natural modes of variability interact with the changing climate and lead to extreme weather. It shows how these interactions can add to climate risks, like flooding and rainfall patterns all around the world.

The Bucher Medal is awarded to just one scientist for their original contributions to the knowledge of the Earth’s crust and lithosphere.

Gordon’s research has reshaped how scientists understand the movement and interaction of Earth’s tectonic plates. He helped reveal the existence of diffuse plate boundaries—areas where the planet’s crust slowly deforms across broad regions instead of along a single fault line. His work also explored true polar wander, a phenomenon in which Earth gradually shifts its orientation relative to its spin axis.

Gordon introduced the concept of paleomagnetic Euler poles, a method for tracing how tectonic plates have moved over millions of years. He also led the development of major global plate motion models, including NUVEL (Northwestern University Velocity) and MORVEL (Mid-Ocean Ridge Velocity).

“Receiving the Walter Bucher Medal is a profound honor,” Gordon said in a news release. “To be included on a list of past recipients whose work I have long admired makes this recognition especially meaningful. There are still countless mysteries about how our planet works, and I look forward to continuing to explore them alongside the next generation of scientists.”

3 Houston-area companies appear on Fortune’s inaugural AI ranking

eyes on ai

Three companies based in the Houston area appear on Fortune’s inaugural list of the top adopters of AI among Fortune 500 companies.

The three companies are:

  • No. 7 energy company ExxonMobil, based in Spring
  • No. 7 tech company Hewlett Packard Enterprise, based in Spring
  • No. 47 energy company Chevron, based in Houston

All three companies have taken a big dive into the AI pool.

In 2024, ExxonMobil’s executive chairman and CEO, Darren Woods, explained that AI would play a key role in achieving a $15 billion reduction in operating costs by 2027.

“There is a concerted effort to make sure that we're really working hard to apply that new technology to the opportunity set within the company to drive effectiveness and efficiency,” Woods told Wall Street analysts.

Hewlett Packard Enterprise is also employing AI to decrease costs. In March, the company announced a restructuring plan — including the elimination of 3,000 jobs — aimed at cutting about $350 million in annual expenses. The restructuring is scheduled to wrap up by the end of October.

Hewlett Packard Enterprise’s Catalyst cost-cutting program includes a push to use AI across the company to improve efficiency, Marie Myers, the company’s executive vice president and chief financial officer, told Wall Street analysts in June.

“Our ambition is clear: A leaner, faster, and more competitive organization. Nothing is off limits. We are focused on rethinking the business — not just reducing our costs, but transforming the way we operate,” Myers said.

At Chevron, AI tools are being used to quickly analyze data and extract insights from it, according to tech news website VentureBeat. Also, Chevron employs advanced AI systems known as large language models (LLMs) to create engineering standards, specifications and safety alerts. AI is even being put to work in Chevron’s exploration initiatives.

Bill Braun, Chevron’s chief information officer, said at a VentureBeat-sponsored event in 2024 that AI-savvy data scientists, or “digital scholars,” are always embedded within workplace teams “to act as a catalyst for working differently.”

The Fortune AIQ 50 ranking is based on ServiceNow’s Enterprise AI Maturity Index, an annual measurement of how prepared organizations are to adopt and scale AI. To evaluate how Fortune 500 companies are rolling out AI and how much they value AI investments, Fortune teamed up with Enterprise Technology Research. The results went into computing an AIQ score for each company.

At the top of the ranking is Alphabet (owner of Google and YouTube), followed by Visa, JPMorgan Chase, Nvidia and Mastercard.

Aside from ExxonMobil, Hewlett Packard Enterprise, and Chevron, two other Texas companies made the list: Arlington-based homebuilder D.R. Horton (No. 29) and Austin-based software company Oracle (No. 37).

“The Fortune AIQ 50 demonstrates how companies across industry sectors are beginning to find real value from the deployment of AI technology,” Jeremy Kahn, Fortune’s AI editor, said in a news release. “Clearly, some sectors, such as tech and finance, are pulling ahead of others, but even in so-called 'old economy' industries like mining and transport, there are a few companies that are pulling away from their peers in the successful use of AI.”