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 startup lands $10M to power up electrician staffing platform

money moves

Houston-based Buildforce, which provides a tech-enabled staff platform geared toward electricians and electrical contractors, has raised a $10 million Series A round led by Houston’s Saepio Capital.

Other investors in the round include Blue Heron Capital, Revolution’s Rise of the Rest Seed Fund, S3 Ventures and Chicago Ventures.

Buildforce says the funding will help fuel its national expansion and further development of its technology.

The startup, founded in 2019, connects electricians with electrical contractors for commercial and industrial construction projects. Buildforce’s mobile app helps electricians find and carry out work, and a web app helps electrical contractors find and manage electricians.

“This financing is a major milestone in furthering our mission to help people dedicated to a career in the construction trades lead more secure and fulfilling lives,” co-founder and CEO Moody Heard said in a news release.

Buildforce focuses solely on the electrical trade within the construction sector.

Nick Graziano, principal at Blue Heron, says the shortage of electricians is intensifying as demand for electricians accelerates, driven by data center construction, infrastructure development and energy transition initiatives.

The U.S. Bureau of Labor Statistics estimates the U.S. will need to hire about 80,000 new electricians per year through 2032 to catch up with demand. According to the National Electrical Contractors Association, the U.S. is grappling with a current shortage of 50,000 electricians.

A 2026 economic report from asset manager BlackRock says the electrical trade is expected to be the single fastest-growing employment category in the U.S. labor market over the next 10 years.

“Buildforce is capitalizing on a clear opportunity in America’s generational infrastructure buildout. We believe their mission to use technology to improve lives in the construction space will allow them to make a positive long-term impact on a large and important labor market,” added Jaan Bains, managing partner at Saepio Capital.

Venus Aerospace adds government, C-suite leaders following $91M raise​

new leaders

Fresh off its $91 million Series B, Houston-based Venus Aerospace has made several key additions and promotions to its leadership team.

The company says its expanded team will help it deploy its high-thrust rotating detonation rocket engine (RDRE), which completed its first U.S. flight test last summer.

"We flew the world's first high-thrust RDRE in just over four years on $80 million. We believe that makes it the fastest, most capital-efficient rocket engine program in history," Sassie Duggleby, co-founder and CEO of Venus Aerospace, said in a news release. "Adding this talent to our leadership team is how we bring that same discipline to the company itself, as we scale to meet the technical needs of defense and space customers who need range and speed legacy systems can't deliver."

The key hires include:

Lane Bodian, Vice President of Public Policy

Bodian previously served as the Principal Deputy Assistant Secretary of Defense for Legislative Affairs at the Pentagon.

Dan Rebnord, Director of Federal Government Relations

Rebnord most recently served as Senior Policy Advisor to a member of the Senate Armed Services Committee and previously worked in the Office of Legislative Affairs at the Department of Defense and as Staff Director for a national security subcommittee in the House of Representatives. Rebnord and Bodian will lead Venus' work with government stakeholders.

Tom Barron, Chief Operating Officer

Barron was promoted from his role as vice president of operations for Venus Aerospace. Before his time at Venus, he served as Special Assistant to the Secretary of Defense and consulted aerospace clients at McKinsey & Company. He also served as a U.S. Army Infantry and Special Forces officer.

Nick Cardwell, Chief Product Officer

Cardwell was promoted from his role as vice president of research and development. He previously held product and technology leadership roles at VC-backed tech companies in the San Francisco Bay Area and Austin.

Venus also named Cameron Taylor as its new vice president of operations, Sarah Boland Heine as its head of communications, Matt Stohr as its head of business development, and Sheila Menz as general counsel.

The company also announced a joint technology development agreement to advance the RDRE with defense giant Lockheed Martin last week. Through the partnership, Venus and Lockheed will focus on evaluating the RDRE's propulsion architecture in defense systems, specifically for precision fires applications where weapons are designed to accurately strike targets at long distances.

Lockheed Martin Ventures, the investment arm of the aerospace and defense contractor, is an investor in Venus Aerospace.

"Lockheed Martin is focused on rapidly delivering advanced capabilities that strengthen deterrence and provide decisive advantages for the warfighter," Tim Cahill, president, Lockheed Martin Missiles and Fire Control, said in a news release. "Our collaboration with Venus Aerospace allows us to evaluate a promising propulsion technology and determine how it can be integrated into future precision fires solutions. Efforts like this help accelerate innovation, reduce risk and shorten the path from emerging technology to operational capability."

Venus' RDRE is expected to enable vehicles to travel four to six times the speed of sound from a conventional runway and is about 15 percent more efficient than traditional alternatives, according to the company.

Venus says the reusable, affordable and scalable RDRE is designed with a "common propulsion architecture" that can work for multiple industries and mission types. The company has previously estimated that the hypersonic market is projected to surpass $12 billion by 2030.