Why relying on intuition can backfire when it comes to crafting a successful business strategy. Photo via Getty Images

When a fast-casual restaurant chain started to see stagnating sales, the company’s CEO came up with a solution: adding new, higher-quality menu items.

To validate his thinking, he informally interviewed a few dozen diners at different locations, asking them how they would feel about more and higher-quality menu items. After getting enthusiastic responses from several customers, he went ahead with his plan. Sales fell further.

So what went wrong? Systematic surveys showed that what created the most value for customers was a fast dining experience with a short wait time, a simple menu with a few items, ample parking and a bill under $12 per meal. Higher quality and an expanded menu did not correlate at all with customer value. Where the company’s CEO went wrong was by relying on salience instead of importance.

Salience refers to factors that are top-of-mind and easy to recall, which become prominent and are then incorrectly prioritized. A classic example is a 1979 study that surveyed people about their perceived risk of dying from causes like drowning, murder or cancer. The study’s authors found that people thought they were more likely to die from causes that were mentioned more often in their local news, such as murder, when in fact they were at much greater risk of dying from common but less prominent causes such as cancer.

The CEO made food quality and expanded offerings salient to himself by talking about them to a small group of customers. It was an easy way for him to feel good about his efforts. But, like many executives, he relied on salience.

Salience is easy and convenient, but it’s also the curse of decision-making. It simply reinforces executives’ prior beliefs rather than diagnosing the true cause-and-effect relationship. Imagine if a doctor saw a patient with stomach pain and recommended an appendectomy because a patient she’d seen the day before needed one. Or if the doctor asked the patient to recommend the treatment himself. Patient outcomes would likely falter and the doctor would go out of business (and perhaps lose her medical license).

Thankfully, doctors don’t operate this way. They rely on the statistically measurable relationship between critical inputs and outputs for decision-making. So should senior executives and CEOs.

Informal customer conversations draw primarily on gut feelings, hunches and top-of-mind ideas, and as such, aren’t reliable indicators of true customer value. Like all of us, customers often tailor their responses to the audience they’re addressing. So a company’s vice president of service might speak with a customer who says they love the service, while the same customer might tell an HR executive they love the employees and then go on to tell the VP of sales that they would like lower prices. These on-the-spot responses typically have no significant impact on or statistical correlation with customer value, which ultimately drives sales and profits.

To craft a successful strategy, executives need to use a systematic, statistical process that starts with choosing a clear outcome or output, such as customer value or employee retention. The next step is to measure inputs that drive that output, and then quantitatively correlate each input to the output. Only those inputs that drive the desired output should be included in the company’s strategy.

Take, for example, a nursing home that attempted to craft a strategy for decreasing employee turnover. Relying on casual conversations with a few dozen employees, executives assumed higher pay would increase retention. They were wrong.

When they statistically correlated multiple inputs — higher pay, health benefits, supervisor respect, promotion opportunities and paid vacation — with retention, they realized their intuitive leaps had been incorrect. Only health insurance and promotions were correlated with increased employee retention. Higher pay had no effect.

Committing to this type of systematic review to drive strategy requires humility on the part of senior executives. The nursing home executives were able to look past their own assumptions and learn from this type of statistical analysis, recognizing the limits of salience-driven thinking and deferring to algorithms that could better predict the inputs of turnover than they could.

Doctors understand this as well. To treat their patients, they rely on data from groups like the Food and Drug Administration or the National Institutes of Health, which run clinical trials and rely on data, statistics and an infrastructure of knowledge.

Unfortunately, many senior executives lack humility when it comes to strategic planning. They equate decades of salience-laden thinking with a deep understanding of correlations between inputs and strategic outputs. They might think, “I’ve been in this industry long enough to know what works,” or “Since this worked then, it will work now as well.” But more often than not, relying on salience-laden intuition alone will not achieve the desired outcome.

“Focus: How to Plan Strategy and Improve Execution to Achieve Growth” lays out specific steps for senior and mid-level executives who want to follow systematic, statistical processes to drive their company’s strategy.

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This article originally ran on Rice Business Wisdom and is based on research from Vikas Mittal, J. Hugh Liedtke Professor of Marketing at the Jones Graduate School of Business and author of “Focus: How to Plan Strategy and Improve Execution to Achieve Growth.”

Most workers surveyed visualize their organization as either a ladder structure or a pyramid, and the quality of relationships in pyramid-structured workplaces is higher than in ladder-structured workplaces. Photo via Pexels

The way a workplace is structured can make or break business, Rice University research finds

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It's a paradox of power: research shows that hierarchies often undermine the very structures they are designed to uphold. Within organizations, conflicts between members can erode entire systems. In a groundbreaking paper, Rice Business Professor Siyu Yu shows that even visual perceptions of the hierarchy can influence its success.

In the first study of its kind, Yu joined a team of colleagues to explore how humans visualize the hierarchies to which they belong – and how that thought process influences group processes and outcomes.

The researchers found that most of the people they studied thought of hierarchies in terms of pyramids or ladders (a tiny minority visualized them as circles or squares). In a ladder hierarchy or stratified structure, each member occupies a particular rung. A pyramid hierarchy is more centralized, with one person at the top and multiple people on the lower levels. Think of corporate giant CISCO, a typical pyramid, versus a mid-size dry cleaning business, with the owner at the top and one person on each rung below, down to the entry-level cashier.

These are far more than fanciful images, the researchers argued. Psychological research has long shown that individuals think, feel and act in response to mental representations of their environment. Intuitively, the link between perception and behavior has been articulated as far back as biblical times: "As a man thinketh, so is he" – or, for that matter, she or they.

To better understand the practical effects of these visualizations, Yu's team conducted five studies with 2,951 people and 221 workplace groups. They chose from nationwide pools monitored by West and East Coast American universities. The studies took place in the United States and the Netherlands and included multiple ethnicities, men and women, and income groups ranging from college students to seasoned professionals earning upwards of $90,000 annually.

In the first study, the team asked participants to indicate the shape that best reflected how they thought about hierarchies: pyramid, ladder, circle or square. In the second study, the researchers measured social relationship quality within different groups: participants were asked to rate their answers to questions such as, "Are your needs met at work? Do you feel socially supported?" In the third study, the researchers focused on professional workgroups, measuring relationship quality, group performance and the likelihood that individuals compare themselves to others in the group.

Subjects who perceived their working group as a ladder, the researchers found, were more likely to compare their rank and station with others. Their relationships were also weaker: when asked whether they trusted their team members, most subjects disagreed or strongly disagreed. When asked whether they thought about if they were better or worse than their colleagues, they agreed and strongly agreed. These comparisons and lack of trust indirectly correlated with lower performance levels, the research showed.

Perceiving one's organization as a ladder structure, Yu's team argued, undermines group members' relationships with each other and hinders collective performance. In contrast, participants who visualized the same company as pyramids rated radically higher on all three quality measures.

Interestingly, the impact of these visualizations is similar, whether the visualizations reflect an actual company structure or simply an individual's perception of that structure. "It can be created by both perception and actual rank, for example, job titles," Yu said in an interview. "So, as a practical implication, companies should think about ways to reduce the ladder system, such as with a promotion system that seems more like a pyramid, or by creating the mutual belief that upward mobility within the company is not a ladder or zero-sum."

Managers, in other words, need to pay close attention to how subordinates see their workplace. Even if your firm is structured as a pyramid, your team members could perceive it to be a ladder – with a cut-throat climb to the top. For the sake of both work performance and quality of life, Yu said, managers, human resources directors and C-suite members should do their best to discern how their workers visualize the company – and, if the paradigm is a ladder, work hard to reduce the workplace vertigo that goes with it.

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This article originally ran on Rice Business Wisdom and is based on research from Siyu Yu, an assistant professor of management and organizational behavior at the Jones Graduate School of Business Rice University.

A Rice Business Professor shows how tailored, personalized health care marketing works better to convince at-risk patients to get screening for liver cancer. Photo via Getty Images

Research: Rice professor reports on the impact of personalized health care marketing

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Amazon is famous for targeted marketing that approaches customers based on their unique needs. Like other successful businesses, such as Netflix, the company taps into machine learning, which uses customer data to understand their behavior.

Hospitals and medical centers rely on marketing too, investing heavily in direct-to-patient outreach to urge at-risk people to get regular screenings. Johns Hopkins Hospital's cancer center, for example, uses emails, letters, seminars and community events to encourage patients to get screened for potential cancer. The high cost of cancer treatment makes this effort worth it: research shows regular screenings help with early detection, leading to more cost-effective treatments and better prognoses.

But hospitals can – and must – improve their outcomes much more, by melding this essential outreach with individually tailored communications based on machine-learning insights.

In an award-winning paper, Rice Business Professor Vikas Mittal and colleagues developed new algorithms indicating that targeted, personalized outreach can increase screenings among at-risk patients. "Outreach marketing" – including sending informational letters and talking to patients about potential barriers to screening – was indeed a powerful motivator for patients to get screened, ultimately lowering health care costs for patient and hospital. But patients with different characteristics, Mittal's team found, responded differently to marketing interventions. When it came to marketing campaigns for cancer screening prevention, one-size-fits-all outreach efforts were neither effective nor economical. Personalized marketing works better for preventing cancer.

To conduct their research, the researchers randomly divided 1,800 patients at UT Southwestern Medical System at risk for hepatocellular carcinoma – the most common type of primary liver cancer – into three groups – usual care, outreach alone, and patient navigation, which includes help such as follow-up calls, motivational messages and assistance spotting specific barriers. They followed each group to see if patients scheduled an MRI or CT scan within six months, from 6-12 months and from 12-18 months.

The first group was asked to receive a screening during their doctors' visits and wasn't contacted after that. The second group received a one-page letter in the mail, then staff called patients who didn't schedule a screening. The third group receiving patient navigation got the same treatment as the second group supplemented with phone calls designed to identify potential barriers, which they used to give customized motivational messages encourage coming in for a screening.

The researchers used patient data from medical records, including patients' age, gender, ethnicity, income, commute time, health status, how often they received healthcare services, whether or not they had insurance and how populated their neighborhoods were.

Following traditional methods, Mittal's team found that the patients who got a letter and call were 10-20% more likely to complete a screening, while those who got the customized motivational messages were 13-24% more likely to schedule their screening. But this is where traditional medical research stops, without asking a crucial question: Within each group, such as those of the 600 patients receiving patient navigation, could screening rates differ based on patients' individual characteristics?

In past research, everyone receiving the same stimulus is presumed to respond the same way. There was no statistical technique to separately estimate the responsiveness of patients with different characteristics. Mittal's team solved this problem by using a machine learning technique called causal forests.

By using "causal forests" to quantify how each of the three marketing approaches could be applied to different patients, Mittal's team found, improved returns on the traditional approach by a remarkable 74-96% – or by $1.6 million to $2 million.

Using traditional methods, physicians would have concluded that every patient should get patient navigation because it was a more intensive marketing approach. The causal forest method showed otherwise: there are small groups of patients with unique characteristics who respond best to specific types of overtures. Minority women in good health who had insurance, visited the doctor often and lived close to clinics in more populated neighborhoods responded especially well to all three types of outreach interventions. Younger patients with long commutes who live in neighborhoods with more public insurance coverage embraced the second type of intervention, outreach alone. And older patients in higher-income neighborhoods favored the patient-navigation approach.

The stakes for common marketing practices like "AB testing" could not be higher. In AB testing, marketers run randomized experiments such as showing ads to some people and not to others. If those seeing an ad, on average, buy more, the conclusion is to blanket the market with ads. But AB testing ignores the fundamental idea that customers exposed to an ad might buy differently in response to an ad based on their individual characteristics. In fact, research shows, many customers seeing a non-tailored ad will buy less than those not seeing an ad.

Personalized marketing can uncover these differences and substantially increase the return on marketing investments in many settings such as retail and ecommerce, services marketing, business-to-business marketing and brand management. Healthcare companies should consider dedicating more resources to machine learning, which can power data-driven patient-centric outreach programs. Because individual health is a civic good, policy makers and organizations need to support these personalized outreach programs.

As for patients themselves, giving detailed personal data to a doctor or receiving highly personalized, unsolicited phone calls legitimately can seem like an invasion of privacy. But Mittal's research shows, it measurably has the potential to save your life.

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This article originally ran on Rice Business Wisdom and is based on research from Vikas Mittal, the J. Hugh Liedtke Professor of Marketing at the Jones Graduate School of Business.

When access to a location is the difference between financial success and failure, cooperation from the community might be the right move to prevent costly conflicts. Pexels

Rice University research: Collaboration with the community can be key to success

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In Pittsburgh, a coalition of 100 community groups brokered a deal with developers of the Pittsburgh Penguins ice hockey team for $8.3 million in neighborhood improvements. In Oakland, California, developers of an $800 million high-tech complex promised local residents 50 percent of its construction jobs. And in Chicago, the Obama Presidential Center is working with residents to shield them from skyrocketing rents.

Community Benefits Agreements, or CBAS, as these agreements are called, are increasingly common between businesses and the places where they want to set up shop. But are they worth the money? To find out, Rice Business professor Kate Odziemkowska joined Sinziana Dorobantu of New York University to analyze market reactions to 148 CBA announcements between indigenous communities and mining firms in Canada. The financial value of these agreements, the researchers found, was real.

While it's easy to imagine that CBAs are just costly giveaways, they're more than goodwill gestures. Instead, they are legally enforceable contracts to distribute benefits from a new project and to govern the response to any potential social and environmental disruptions. For businesses, the researchers found, they are also good strategy, because they prevent costly, drawn-out conflict.

To conduct their research, Odziemkowska and Dorobantu analyzed a sample of 148 legally binding CBAs signed in Canada between mining firms and indigenous communities between 1999 and 2013. In Canada, mining companies and indigenous communities often hammer out agreements about extraction and use of local resources. Studying only the mining sector let the researches control for the economic variations that characterize different industries.

Since CBA negotiations cannot be disclosed, the announcement of such agreements represents new market information. To conduct their study, the researchers tracked the market reaction to these announcements, using a technique that measured short-term returns.

Creating CBAs from the start, they found, can head off catastrophic costs later. That's because even when a company has disproportionate economic strength, the public relations, legal and economic costs of community conflict can be draining. Consider the 1,900-kilometer Dakota Access oil pipeline, whose developers faced six months of round-the-clock protests that included nearly 15,000 volunteers from around the world. The drumbeat of litigation and negative news coverage still continues today.

In general, the researchers found, the more experience a community has with protests or blockades, the more firms gained from signing a CBA. Property rights protections also provide strong incentive for making a deal. Mining companies, for example, need access to land to do business. Communities with robust property rights to the resource or location sought by the firm have strong standing to stop that firm if they don't make a deal.

Because access to valuable resources like land or intellectual property can mean the difference between financial success or failure, Odziemkowska and Dorobantu said, the lesson from their findings extends far beyond Canadian mines. It's a lesson Disney learned the hard way when it failed to acknowledge the culture of Norway's Sami people in "Frozen." Assailed for cultural appropriation by using, but not crediting, traditional Sami music, Disney quickly made amends. After negotiating with the Sami people, Disney pledged to consult with them and portray them thoughtfully in the film's sequel.

The deal may have cost Disney on the front end, but it was nothing compared to the advantage of freezing out years of bad press.

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This story originally ran on Rice Business Wisdom. It's based on research by Kate Odziemkowska, an assistant professor of Strategic Management at Rice University's Jones Graduate School of Business.

By accounting for both known and unknowable factors, managers can identify salespeople with traits that work best in different types of sales. Getty Images

Rice University research uses data to spot your best sales team members

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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.

Rice University will launch online classes next week for small business leaders planning their recovery. Courtesy of Rice University

Rice University launches online programming for entrepreneurs dealing with COVID-19 closures

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Houston small businesses and startups have a long road of recovery ahead of them, and Rice University and some of its partners want to help local entrepreneurs prepare for it.

Rice University's Susanne M. Glasscock School of Continuing Studies has partnered with the Ion — along with the Center for Houston's Future and Rice Alliance for Technology and Entrepreneurship — to launch the Back In Business Initiative. The program will begin with three courses in the week of April 20 to 24. The three courses are:

"Glasscock's mission has always been to provide education to the residents of Houston," says Robert Bruce, dean of the Glasscock School, in a news release. "We specialize in providing responsive, practical information that will help our constituents when and how they need it most. To assist our struggling Houston small business community during this crisis, we created this trilogy of courses to help analyze their current situation, use creative problem-solving and provide meaningful communications to help them weather this situation."

More classes will be added as needed. The classes have a $25 registration fee, and anyone can enroll online.

"Today's health crisis may have changed many aspects of our daily lives, but it has not affected our commitment to providing the right tools and education to help our community succeed," says Jan Odegard, senior director of academic and industry partnerships at the Ion, in the release. "We all have a role to play in meeting the challenge of COVID-19 and we are excited to be partnering with the Glasscock School of Continuing Studies to support Houston small businesses in this time of uncertainty."

The university also touts OpenRICE as a resource for businesses. The online education platform is available to the Houston community for free. Rice also has a 20 percent discount for all professional studies courses and programs enrollment — with the ability to postpone for up to a year without a fee. This deal runs through April 30.

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Houston-based health tech startup is revolutionizing patient selection for clinical trials

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On many occasions in her early career, Dr. Arti Bhosale, co-founder and CEO of Sieve Health, found herself frustrated with having to manually sift through thousands of digital files.

The documents, each containing the medical records of a patient seeking advanced treatment through a clinical trial, were always there to review — and there were always more to read.

Despite the tediousness of prescreening, which could take years, the idea of missing a patient and not giving them the opportunity to go through a potentially life-altering trial is what kept her going. The one she didn’t read could have slipped through the cracks and potentially not given someone care they needed.

“Those stories have stayed with me,” she says. “That’s why we developed Sieve.”

When standard health care is not an option, advances in medical treatment could be offered through clinical trials. But matching patients to those trials is one of the longest standing problems in the health care industry. Now with the use of new technology as of 2018, the solution to the bottleneck may be a new automated approach.

“Across the globe, more than 30 percent of clinical trials shut down as a result of not enrolling enough patients,” says Bhosale. “The remaining 80 percent never end up reaching their target enrollment and are shut down by the FDA.”

In 2020, Bhosale and her team developed Sieve Health, an AI cloud-based SaaS platform designed to automate and accelerate matching patients with clinical trials and increase access to clinical trials.

Sieve’s main goal is to reduce the administrative burden involved in matching enrollments, which in turn will accelerate the trial execution. They provide the matching for physicians, study sponsors and research sites to enhance operations for faster enrollment of the trials.

The technology mimics but automates the traditional enrollment process — reading medical notes and reviewing in the same way a human would.

“I would have loved to use something like this when I was on the front lines,” Bhosale says, who worked in clinical research for over 12 years. “Can you imagine going through 10,000 records manually? Some of the bigger hospitals have upwards of 100,000 records and you still have to manually review those charts to make sure that the patient is eligible for the trial. That process is called prescreening. It is painful.”

Because physicians wear many hats and have many clinical efforts on their plates, research tends to fall to the bottom of the to-do list. Finding 10-20 patients can take the research team on average 15-20 months to find those people — five of which end up unenrolling, she says.

“We have designed the platform so that the magic can happen in the background, and it allows the physician and research team to get a jumpstart,” she says.” They don’t have to worry about reviewing 10,000 records — they know what their efforts are going to be and will ensure that the entire database has been scanned.”

With Sieve, the team was able to help some commercial pilot programs have a curated data pool for their trials – cutting the administrative burden and time spent searching to less than a week.

Sieve is in early-stage start up mode and the commercial platform has been rolled out. Currently, the team is conducting commercial projects with different research sites and hospitals.

“Our focus now is seeing how many providers we can connect into this,” she says. “There’s a bigger pool out there who want to participate in research but don’t know where to start. That’s where Sieve is stepping in and enabling them to do this — partnering with those and other groups in the ecosystem to bring trials to wherever the physicians and the patients are.”

Arti Bhosale is the co-founder and CEO of Sieve Health. Photo courtesy of Sieve

Houston nonprofit unveils new and improved bayou cleaning vessel

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For over 20 years, a nonprofit organization has hired people to clean 14 miles of bayou in Houston. And with a newly updated innovative boat, keeping Buffalo Bayou clean just got a lot more efficient.

Buffalo Bayou Partnership unveils its newest version of the Bayou-Vac this week, and it's expected to be fully operational this month. BBP Board Member Mike Garver designed both the initial model of the custom-designed and fabricated boat as well as the 2022 version. BBP's Clean & Green team — using Garver's boat — has removed around 2,000 cubic yards of trash annually, which is the equivalent of about 167 commercial dump trucks. The new and improved version is expected to make an even bigger impact.

“The Bayou-Vac is a game changer for our program,” says BBP field operations manager, Robby Robinson, in a news release. “Once up and running, we foresee being able to gain an entire workday worth of time for every offload, making us twice as efficient at clearing trash from the bayou.”

Keeping the bayou clean is important, since the water — and whatever trash its carrying — runs off into Galveston Bay, and ultimately, the Gulf of Mexico. The improvements made to the Bayou-Vac include removable dumpsters that can be easily swapped out, slid off, and attached to a dump truck. The older model included workers having to manually handle trash and debris and a secondary, land-based vacuum used to suck out the trash from onboard.

Additionally, the Bayou-Vac now has a moveable, hydraulic arm attached to the bow of the vessel that can support the weight of the 16-foot vacuum hose. Again, this task was something done manually on the previous model of the Bayou-Vac.

“BBP deeply appreciates the ingenuity of our board member Mike Garver and the generosity of Sis and Hasty Johnson and the Kinder Foundation, the funders of the new Bayou-Vac,” BBP President Anne Olson says in the release. “We also thank the Harris County Flood Control District and Port Houston for their longtime support of BBP’s Clean & Green Program.”