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.

------

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.)

------

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.

Ad Placement 300x100
Ad Placement 300x600

CultureMap Emails are Awesome

NASA signs on latest tenant for new Exploration Park campus, now underway

space hub

Exploration Park, the 240-acre research and commercial institute at NASA's Johnson Space Center, is ready for launch.

Facilities at the property have broken ground, according to a recent episode of NASA's Houston We Have a Podcast, with a completion date targeted for Q4 2026.

The research park has also added Houston-based KBR to its list of tenants. According to a news release from the Greater Houston Partnership, the human spaceflight and aerospace services company will operate a 45,000-square-foot food innovation lab at Exploration Park. KBR will use the facility to focus on customized food systems, packaging and nutrition for the low Earth orbit economy.

“Exploration Park is designed for companies in the space ecosystem, such as KBR, to develop, produce, and deploy innovative new technologies that support space exploration and commerce,” Simon Shewmaker, head of development at ACMI Properties, the developer behind Exploration Park, said in the GHP release. “This project is moving expeditiously, and we’re thrilled to sign such an innovative partner in KBR, reflecting our shared commitment to building the essential infrastructure of tomorrow for the next generation of space innovators and explorers.”

NASA introduced the concept of a collaborative hub for academic, commercial and international partners focused on spaceflight in 2023. It signed leases with the American Center for Manufacturing and Innovation and the Texas A&M University System for the previously unused space at JSC last year.

“For more than 60 years, NASA Johnson has been the hub of human space exploration,” Vanessa Wyche, NASA Johnson Space Center Director, said in a statement at the time. “This Space Systems Campus will be a significant component within our objectives for a robust and durable space economy that will benefit not only the nation’s efforts to explore the Moon, Mars and the asteroids, but all of humanity as the benefits of space exploration research roll home to Earth.”

Texas A&M is developing the $200 million Texas A&M Space Institute, funded by the Texas Space Commission, at the center of the park. The facility broke ground last year and will focus on academic, government and commercial collaboration, as well as workforce training programs. ACMI is developing the facilities at Exploration Park.

Once completed, Exploration Park is expected to feature at least 20 build-to-suit facilities over at least 1.5 million square feet. It will offer research and development space, laboratories, clean rooms, office space and light manufacturing capabilities for the aerospace, robotics, life support systems, advanced manufacturing and artificial intelligence industries.

According to the GHP, Griffin Partners has also been selected to serve as the co-developer of Exploration Park. Gensler is leading the design and Walter P Moore is overseeing civil engineering.

Houston cleantech co. plans first-of-its-kind sustainable aviation fuel facility

coming soon

Houston-based Syzygy Plasmonics announced plans to develop what it calls the world's first electrified facility to convert biogas into sustainable aviation fuel (SAF).

The facility, known as NovaSAF 1, will be located in Durazno, Uruguay. It is expected to produce over 350,000 gallons of SAF annually, which would be considered “a breakthrough in cost-effective, scalable clean fuel,” according to the company.

"This is more than just a SAF plant; it's a new model for biogas economics," Trevor Best, CEO of Syzygy Plasmonics, said in a news release. "We're unlocking a global asset class of underutilized biogas sites and turning them into high-value clean fuel hubs without pipelines, costly gas separation, or subsidy dependence.”

The project is backed by long-term feedstock and site agreements with one of Uruguay's largest dairy and agri-energy operations, Estancias del Lago, while the permitting and equipment sourcing are ongoing alongside front-end engineering work led by Kent.

Syzygy says the project will result in a 50 percent higher SAF yield than conventional thermal biogas reforming pathways and will utilize both methane and CO2 naturally found in biogas as feedstocks, eliminating the need for expensive CO2 separation technologies and infrastructure. Additionally, the modular facility will be designed for easy replication in biogas-rich regions.

The new facility is expected to begin commercial operations in Q1 2027 and produce SAF with at least an 80 percent reduction in carbon intensity compared to Jet A fuel. The company says that once fully commercialized the facility will produce SAF at Jet-A fuel cost parity.

“We believe NovaSAF represents one of the few viable pathways to producing SAF at jet parity and successfully decarbonizing air travel,” Best added in the release.

---

This article originally ran on EnergyCapital.

Houston company ranks No. 13 worldwide on Forbes Global 2000 list

World's Biggest Companies

More than 60 Texas-based companies appear on Forbes’ 2025 list of the world’s 2,000 biggest publicly traded companies, and nearly half come from Houston.

Among Texas companies whose stock is publicly traded, Spring-based ExxonMobil is the highest ranked at No. 13 globally.

Rounding out Texas’ top five are Houston-based Chevron (No. 30), Dallas-based AT&T (No. 35), Austin-based Oracle (No. 66), and Austin-based Tesla (No. 69).

Ranking first in the world is New York City-based J.P. Morgan Chase.

Forbes compiled this year’s Global 2000 list using data from FactSet Research to analyze the biggest public companies based on four metrics: sales, profit, assets, and market value.

“The annual Forbes Global 2000 list features the companies shaping today’s global markets and moving them worldwide,” said Hank Tucker, a staff writer at Forbes. “This year’s list showcases how despite a complex geopolitical landscape, globalization has continued to fuel decades of economic growth, with the world’s largest companies more than tripling in size across multiple measures in the past 20 years.”

The U.S. topped the list with 612 companies, followed by China with 317 and Japan with 180.

Here are the rest of the Texas-based companies in the Forbes 2000, grouped by the location of their headquarters and followed by their global ranking.

Houston area

  • ConocoPhillips (No. 105)
  • Phillips 66 (No. 276)
  • SLB (No. 296)
  • EOG Resources (No. 297)
  • Occidental Petroleum (No. 302)
  • Waste Management (No. 351)
  • Kinder Morgan (No. 370)
  • Hewlett Packard Enterprise (No. 379)
  • Baker Hughes (No. 403)
  • Cheniere Energy (No. 415)
  • Corebridge Financial (No. 424)
  • Sysco (No. 448)
  • Halliburton (No. 641)
  • Targa Resources (No. 651)
  • NRG Energy (No. 667)
  • Quanta Services (No. 722)
  • CenterPoint Energy (No. 783)
  • Coterra Energy (No. 1,138)
  • Crown Castle International (No. 1,146)
  • Westlake Corp. (No. 1,199)
  • APA Corp. (No. 1,467)
  • Comfort Systems USA (No. 1,629)
  • Group 1 Automotive (No. 1,653)
  • Talen Energy (No. 1,854)
  • Prosperity Bancshares (No. 1,855)
  • NOV (No. 1,980)

Austin area

  • Dell Technologies (No. 183)
  • Flex (No. 887)
  • Digital Realty Trust (No. 1,063)
  • CrowdStrike (No. 1,490)

Dallas-Fort Worth

  • Caterpillar (No. 118)
  • Charles Schwab (No. 124)
  • McKesson (No. 195)
  • D.R. Horton (No. 365)
  • Texas Instruments (No. 374)
  • Vistra Energy (No. 437)
  • CBRE (No. 582)
  • Kimberly-Clark (No. 639)
  • Tenet Healthcare (No. 691)
  • American Airlines (No. 834)
  • Southwest Airlines (No. 844)
  • Atmos Energy (No. 1,025)
  • Builders FirstSource (No. 1,039)
  • Copart (No. 1,062)
  • Fluor (No. 1,153)
  • Jacobs Solutions (1,232)
  • Globe Life (1,285)
  • AECOM (No. 1,371)
  • Lennox International (No. 1,486)
  • HF Sinclair (No. 1,532)
  • Invitation Homes (No. 1,603)
  • Celanese (No. 1,845)
  • Tyler Technologies (No. 1,942)

San Antonio

  • Valero Energy (No. 397)
  • Cullen/Frost Bankers (No. 1,560)

Midland

  • Diamondback Energy (No. 471)
  • Permian Resources (No. 1,762)
---

A version of this article originally appeared on CultureMap.com.