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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Rice Brain Institute awards seed grants for dementia, Alzheimer’s research

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The recently established Rice Brain Institute awarded 12 seed grants last month to support research on dementia, Alzheimer’s disease, Parkinson’s disease and other neurological disorders.

The grants are part of the Rice DPRIT Seed Grant Program, which aims to help faculty members generate preliminary data, test and teams that would be supported under the Dementia Prevention and Research Institute of Texas.

The DPRIT was approved last year to provide $3 billion in state funding over a 10-year span for research on dementia prevention and other neurological conditions. It will be modeled after the Cancer Prevention and Research Institute of Texas (CPRIT), which has awarded nearly $4 billion in grants since 2008.

“DPRIT is a historic initiative with transformative impact potential and at Rice we are very well equipped to contribute to its mission and help make Texas a leader in brain health and innovation,” Behnaam Aazhang, a Rice professor of electrical and computer engineering and director of the Neuroengineering Initiative and the RBI, said in a news release.

The Rice DPRIT Seed Grant Program is supported by the RBI and the Educational and Research Initiative for Collaborative Health (ENRICH) office at Rice. Most of the funding came from Rice's Office of Research, with a contribution from Rice's Amyloid Mechanism and Disease Center, which also launched last year.

A number of the teams include collaborators from Houston's Texas Medical Center, including Baylor College of Medicine, University of Texas Medical Branch and the McGovern Medical School at UTHealth Houston.

The 12 teams are:

  • Keya Ghonasgi, assistant professor of mechanical engineering at Rice. Ghonasgi's research addresses the high risk of falls among people with different types of dementia and aims to develop a personalized, home-based fall-prevention approach using textile-integrated wearable sensors.
  • Luz Garcini, associate professor of psychological sciences at Rice, and Hannah Ballard, associate director of community and public health at the Kinder Institute for Urban Research at Rice. Garcini and Ballard's research looks at barriers and facilitators to early detection of Alzheimer’s disease in diverse, medically underserved urban communities and focuses on populations that experience late diagnosis, including Hispanic/Latino groups.
  • Lei Li, assistant professor of electrical and computer engineering at Rice, and Pablo Valdes, assistant professor of neurosurgery at UTMB. Li and Valdes' project develops a noninvasive, bedside imaging approach to monitor brain blood flow and oxygenation in patients recovering from stroke or brain surgery using photoacoustic imaging through a specialized transparent skull implant.
  • Cameron Glasscock, assistant professor of biosciences at Rice. Glasscock's project addresses repeat expansion disorders, such as Huntington’s disease and myotonic dystrophy, and focuses on stopping DNA instability before repeats reach a disease-causing threshold.
  • Raudel Avila, assistant professor of mechanical engineering at Rice. Avila's project focuses on everyday health factors such as nutrition, hydration and brain blood flow and how they influence brain aging long before symptoms of dementia appear.
  • Isaac Hilton, associate professor of bioengineering at Rice, and Laura Lavery, assistant professor of biosciences at Rice. Hilton and Lavery's project uses precise CRISPR-based gene regulation to target multiple genetic drivers of neuronal damage in Alzheimer’s.
  • Quanbing Mou, assistant professor of chemistry at Rice, and Qing-Long Miao, assistant professor of neurology at Baylor College of Medicine. Mou and Miao's project aims to develop a gene-regulation therapy for childhood absence epilepsy by restoring activity of the CACNA1A gene.
  • Momona Yamagami, assistant professor of electrical and computer engineering at Rice, and Christopher Fagundes, professor of psychological sciences at Rice. Yamagami and Fagundes' project addresses the physical and mental health challenges faced by spouses caring for partners with Alzheimer’s disease and related dementias and aims to develop algorithms to determine the optimal timing and frequency of supportive text messages.
  • Han Xiao, professor of chemistry at Rice. Xiao's project aims to improve the delivery of antibody therapies to the brain using a noninvasive, light-based approach that temporarily opens the blood–brain barrier.
  • Lan Luan, associate professor of electrical and computer engineering at Rice. Luan's project investigates how tiny blood-vessel injuries in the brain, known as microinfarcts, contribute to dementia.
  • Natasha Kirienko, associate professor of biosciences at Rice. Kirienko's project targets a shared cause of neurodegeneration, impaired mitochondrial cleanup, and aims to identify an existing antidepressant that could be repurposed to protect neurons in diseases like Alzheimer’s and Parkinson’s.
  • Harini Iyer, assistant professor of biosciences at Rice. Iyer's project will observe zebrafish to investigate how the brain’s primary immune cells become improperly activated in neurological disorders, leading to the loss of healthy neurons and cognitive impairment.

The RBI also named the first four projects to receive research awards through the Rice and TMC Neuro Collaboration Seed Grant Program in January. Read more about those projects here.

Report: These 10 jobs earn the biggest salary premiums in Texas

A move to Texas bolsters earnings for some, and a new SmartAsset study has revealed the top professions where the median annual earnings in the Lone Star State exceed the national median.

The report, "When it Pays to Work in Texas — and When It Doesn’t," published in April, analyzed over 700 occupations to determine which have the biggest "Texas premium" — meaning jobs where the price-adjusted median annual pay in Texas most exceeds the national median for the same occupation — and which jobs have the biggest “Texas penalty,” where the statewide median annual pay falls furthest below the national median. Salaries were sourced from the U.S. Bureau of Labor Statistics (BLS) and adjusted for regional price parity.

According to the report's findings, geoscientists have the biggest "Texas premium" and make a $159,903 median annual salary. Texas' salary for geoscientists is 61 percent higher than the national median for the same position (after adjusting for regional price parity).

"Texas’s large petroleum industry helps explain why employers in the state retain so many geoscientists," the report's author wrote. "In fact, the Lone Star State is home to more geoscientists than any other state except California."

There are more than 3,600 geoscientists working in Texas, SmartAsset said.

These are the remaining top 10 occupations with the biggest "Texas premiums" (salaries are price-adjusted):

  • No. 2 – Commercial pilots: $167,727 median Texas earnings; 37 percent higher than the national median
  • No. 3 – Sailors: $67,614 median Texas earnings; 36 percent higher than the national median
  • No. 4 – Aircraft structure assemblers: $83,519 median Texas earnings; 35 percent higher than the national median
  • No. 5 – Ship captains: $108,905 median Texas earnings; 27 percent higher than the national median
  • No. 6 – Nursing instructors (postsecondary): $100,484 median Texas earnings; 26 percent higher than the national median
  • No. 7 – Tax preparers: $63,321 median Texas earnings; 25 percent higher than the national median
  • No. 8 – Chemists: $104,241 median Texas earnings; 24 percent higher than the national median
  • No. 9 – Health instructors (postsecondary): $128,680 median Texas earnings; 22 percent higher than the national median
  • No. 10 – Engineering instructors (postsecondary): $129,030 median Texas earnings; 22 percent higher than the national media

The careers where Texas workers earn less

SmartAsset said an editor is the Texas profession where workers earn the furthest below the median for the same occupation elsewhere in the U.S. Not to be confused with film and video editors, BLS defines editors as those who "plan, coordinate, revise, or edit written material" and "may review proposals and drafts for possible publication."

The study found editors make a price-adjusted median wage of $29,710, which is 61 percent lower than the national median for the same position, and there are nearly 8,200 editors in Texas.

It's worth noting that the salaries for editors may be skewed by the fact that there are not major publications in rural areas of Texas, and other professions may also have financial deviations for similar reasons.

Several healthcare jobs also appear to have the worst penalties in Texas compared to elsewhere in the country. Home health aides are the second-worst paying professions in the state, making a median wage of $24,161.

"More home health aides work in Texas than in nearly any other state, with only California and New York employing more," the report said. "However, the more than 300,000 Texans in this occupation earn median annual pay that is about 31 percent below the national median, after adjusting for regional price parity.

SmartAsset clarified that pay penalties are not consistent "across the board" for other healthcare occupations in Texas.

"For physical therapy assistants, occupational therapy assistants, and postsecondary nursing instructors, Texas may be an especially strong place to work, with these occupations offering 'Texas premiums' of between 17 percent and 26 percent," the study said.

These are the remaining top 10 occupations where median annual earnings in Texas fall furthest below the national median for the same occupation:

  • No. 3 – Cardiovascular technicians: $49,382 median Texas earnings; 27 percent lower than the national median
  • No. 4 – Semiconductor processing technicians: $38,295 median Texas earnings; 25 percent lower than the national median
  • No. 5 – Tutors: $30,060 median Texas earnings; 25 percent lower than the national median
  • No. 6 – Control and valve installers: $56,496 median Texas earnings; 24 percent lower than the national median
  • No. 7 – Mental health social workers: $46,109 median Texas earnings; 23 percent lower than the national median
  • No. 8 – Clinical psychologists: $74,449 median Texas earnings; 22 percent lower than the national median
  • No. 9 – Producers/directors: $65,267 median Texas earnings; 22 percent lower than the national median
  • No. 10 – Interpreters/translators: $46,953 median Texas earnings; 21 percent lower than the national median

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This article originally appeared on CultureMap.com.

Houston rises in 2026 ranking of best U.S. cities to start a business

Best for Biz

Houston has reaffirmed its commitment to a business-friendly environment and now ranks as the 26th best large U.S. city for starting a business in 2026. The city jumped up eight places after ranking 34th last year.

WalletHub's annual report compared 100 U.S. cities based on 19 relevant metrics across three key dimensions: business environment, access to resources, and costs. Factors that were analyzed include five-year business survival rates, job growth comparisons from 2020 and 2024, population growth of working-age individuals aged 16-64, office space affordability, and more.

Florida cities locked out the top five best places in America for starting a new business: Tampa, Orlando, Jacksonville, Hialeah, and St. Petersburg.

Houston's business environment ranked as the 19th best in the country, and the city ranked 51st in the "business costs" category. However, the city lagged behind in the "access to resources" ranking, coming in at No. 72 overall. This category examined metrics such as Houston's working-age population growth, the share of college-educated individuals, financing accessibility, the prevalence of investors, venture investment amounts per capita, and more.

"From the Gold Rush and the Industrial Revolution to the Internet Age, periods of innovation have shaped our economy and driven major societal progress," the report's author wrote. "However, the past few years have been particularly challenging for business owners in the U.S., due to factors such as the COVID-19 pandemic, the Great Resignation and high inflation."

Earlier this year, WalletHub declared Texas the third-best state for starting a business in 2026, and several Houston-area cities have seen robust growth after being recognized among the best career hotspots in the U.S. Entrepreneurial praise has also been extended to five local companies that were named the most innovative companies in the world, and six powerhouse female innovators that made Inc. Magazine's 2026 Female Founders 500 list.

Texas cities with strong environments for new businesses
Multiple cities in the Dallas-Fort Worth Metroplex can claim bragging rights as the best Texas locales for starting a new business. Dallas ranked highest overall — appearing 11th nationally — and Irving landed a few spots behind in the 16th spot. Arlington (No. 23), Fort Worth (No. 30), Plano, (No. 35), and Garland (No. 65) followed behind.

Only six other Texas cities earned spots in the report: Austin (No. 24), Lubbock (No. 36), Corpus Christi (No. 39), San Antonio (No. 64), El Paso (No. 67), and Laredo (No. 76).

Austin tied with Boise, Idaho and Fresno, California for the highest average growth in the number of small businesses nationally, while Corpus Christi and Laredo topped a separate list of the U.S. cities with the most accessible financing.

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This article originally appeared on CultureMap.com.