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 maritime startup raises $43M to electrify vessels, opens new HQ

Maritime Mission

A Houston-based maritime technology company that is working to reduce emissions in the cargo and shipping industry has raised VC funding and opened a new Houston headquarters.

Fleetzero announced that it closed a $43 million Series A financing round this month led by Obvious Ventures with participation from Maersk Growth, Breakthrough Energy Ventures, 8090 Industries, Y Combinator, Shorewind, Benson Capital and others. The funding will go toward expanding manufacturing of its Leviathan hybrid and electric marine propulsion system, according to a news release.

The technology is optimized for high-energy and zero-emission operation of large vessels. It uses EV technology but is built for maritime environments and can be used on new or existing ships with hybrid or all-electric functions, according to Fleetzero's website. The propulsion system was retrofitted and tested on Fleetzero’s test ship, the Pacific Joule, and has been deployed globally on commercial vessels.

Fleetzero is also developing unmanned cargo vessel technology.

"Fleetzero is making robotic ships a reality today. The team is moving us from dirty, dangerous, and expensive to clean, safe, and cost-effective. It's like watching the future today," Andrew Beebe, managing director at Obvious Ventures, said in the news release. "We backed the team because they are mariners and engineers, know the industry deeply, and are scaling with real ships and customers, not just renderings."

Fleetzero also announced that it has opened a new manufacturing and research and development facility, which will serve as the company's new headquarters. The facility features a marine robotics and autonomy lab, a marine propulsion R&D center and a production line with a capacity of 300 megawatt-hours per year. The company reports that it plans to increase production to three gigawatt-hours per year over the next five years.

"Houston has the people who know how to build and operate big hardware–ships, rigs, refineries and power systems," Mike Carter, co-founder and COO of Fleetzero, added in the release. "We're pairing that industrial DNA with modern batteries, autonomy, and software to bring back shipbuilding to the U.S."

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This article originally appeared on EnergyCapitalHTX.com.

Innovative Houston-area hardtech startup closes $5M seed round

fresh funding

Conroe-based hardtech startup FluxWorks has closed a $5 million seed round.

The funding was led by Austin-based Scout Ventures, which invests in early-stage startups working to solve national security challenges.

Michigan Capital Network also contributed to the round from its MCN Venture Fund V. The fund is one of 18 selected by the Department of Defense and Small Business Administration to participate in the Small Business Investment Company Critical Technologies Initiative, which will invest $4 billion into over 1,700 portfolio companies.

FluxWorks reports that it will use the funding to drive the commercialization of its flagship Celestial Gear technology.

"At Scout, we invest in 'frontier tech' that is essential to national interest. FluxWorks is doing exactly that by solving critical hardware bottlenecks with its flagship Celestial Gear technology ... This is about more than just gears; it’s about strengthening our industrial infrastructure," Scout Ventures shared in a LinkedIn post.

Fluxworks specializes in making contactless magnetic gears for use in extreme conditions, which can enhance in-space manufacturing. Its contactless design leads to less wear, debris and maintenance. Its technology is particularly suited for space applications because it does not require lubricants, which can be difficult to control at harsh temperatures and in microgravity.

The company received a grant from the Texas Space Commission last year and was one of two startups to receive the Technology in Space Prize, funded by Boeing and the Center for the Advancement of Science in Space (CASIS), in 2024. It also landed $1.2 million through the National Science Foundation's SBIR Phase II grant this fall.

Fluxworks was founded in College Station by CEO Bryton Praslicka in 2021. Praslicka moved the company to Conroe 2024.