Researchers created a mathematical model that helps transplant centers make decisions about when to move forward with a matching donor and when to wait. This work can potentially help decision making in other industries. Photo via Getty Images

To wait, or not to wait? That is the question — or at least it might be, if you need a kidney transplant.

Nearly 89,000 Americans with chronic kidney disease are on a waitlist for a new organ, and an estimated 13 people die each day while awaiting a transplant. But there are real costs to matching patients with the first donor that becomes available, just as there are equally real costs to having them wait in hopes of finding a better one.

Recently, Rice Business professor Süleyman Kerimov and colleagues at Stanford University and Northwestern University developed a mathematical model that helps clarify when it's best to match patients to donors as quickly as possible and when it's best to wait.

Their findings, which appear in two papers published in Management Science and Operations Research, respectively, could help optimize all manner of matching markets in which participants seek to connect with potential partners based on mutual compatibility — a sprawling category that encompasses everything from e-commerce platforms to labor markets that match employees with employers.

Kerimov and his colleagues focused on programs that match live kidney donors with people who need transplants. Live donors typically volunteer to give one of their kidneys to a loved one. But biological differences between a donor and their intended recipient can render the pair incompatible.

Kidney exchange programs solve this problem by swapping donors amongst different patient-donor pairs, choreographing a kind of kidney-transplant square dance aimed at finding a compatible partner for every willing donor.

In countries such as Canada and the Netherlands, kidney-matching programs perform a batch of matches every few months (called periodic policies). American programs, meanwhile, tend to perform daily matches (called greedy policies). Both models seek to produce the greatest number of high-quality transplants possible, but they each have advantages and disadvantages.

Less frequent matches in a periodic policy allow more patient-donor pairs to accumulate in the kidney exchange network, creating potential for better matches over time. But this approach risks making some patients sicker as they wait for a better match that might never appear.

Arranging feasible matches as soon as they become available in a greedy policy avoids that predicament. But it means passing up the opportunity to make a potentially better match that could represent the possibility of a longer, healthier life.

Balancing these trade-offs is tricky. There is no way of predicting precisely when a patient-donor pair with a particular set of characteristics will show up at the kidney-exchange network. And in the world of organ transplants, there are no do-overs.

Kerimov and his colleagues have constructed a mathematical model that represents a simplified version of a kidney exchange network.

Within the model, the researchers could dictate which patient-donor pairs could be matched with one another. They can also assign different values to individual matches based on the number of life years they provide. And they can establish the probability that various kinds of patient-donor pairs with particular characteristics might arrive at the network and queue up for a transplant at any given time.

Having set those parameters, the researchers applied different matching policies and compared the results. As it turns out, the answer to whether one should wait or not is: It depends.

To determine which policies generated the best outcomes — i.e., performing matches either daily or periodically — the researchers calculated the difference between the total value in life years that could possibly be generated within the network and the amount generated by a specific policy at a particular point in time. The goal was to keep that number, evocatively dubbed "all-time regret," as small as possible over both the short and long term.

In their first paper, Kerimov and his team explored a complex network in which donor kidneys could be swapped amongst three or more patient-donor pairs. When such multiway matches were possible, the cost of applying a daily-match policy turned out to be onerous. Using all available matches as quickly as possible eliminated the chance of later performing potentially higher-value matches.

Instead, the researchers found they could minimize regret by applying a periodic policy that required waiting for a certain number of patient-donor pairs to arrive before attempting to match them. The model even allowed the team to calculate precisely how long to wait between matchmaking sessions to get the best possible results.

In their second paper, however, the team looked at a simpler network in which kidneys could only be swapped between two donor-patient pairs. Here, their findings contradicted the first: Applying a daily-match policy minimized regret; a periodic matching process yielded no benefit whatsoever.

To their surprise, the researchers discovered they could design a foolproof algorithm for making two-way matches in simple networks. The algorithm employed a ranked list of possible match types; and the researchers found that no matter how many patient-donor pairs of various kinds randomly arrived at the network, the best choice was always simply to perform the highest-ranked match on the list.

In future research, Kerimov hopes to refine the model by feeding it data on real patient-donor pairs that have participated in actual kidney exchange programs. This would allow him to create a more realistic network, more accurately calculate the likelihood that particular kinds of patient-donor pairs will show up, and assign values to matches based not only on life years but also on rarity and difficulty. (Certain blood types and antibody profiles, for example, are rarer or more difficult to match than others.)

But Kerimov already suspects that in a real-world situation, the wisest course of action will be to alternate between periodic and greedy policies as circumstances dictate. In a simple region within a kidney exchange network that only allows for two-way matches, pursuing a greedy policy that involves taking the first match that appears on a fixed menu of options would be the best choice. In a more complex region that allows three-way matches, however, pursuing a periodic matching policy that involves waiting to make rarer and more difficult matches would ultimately offer more patients more years of healthy life.

The benefits of choosing flexibly between greedy and periodic policies should hold for any kind of matching market that can be represented by a network with simpler and more complex regions, such as a logistics system that matches online orders to delivery trucks or a carpooling system that matches passengers with drivers across different parts of a city.

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This article originally ran on Rice Business Wisdom and was based on research from Süleyman Kerimov, an assistant professor of management – operations management in the Jones Graduate School of Business at Rice University.

This Halloween, consider your office costume contest or luncheon social a productive part of the day. Socialization in the office has been linked to greater creativity, according to a Rice University researcher. Getty Images

Rice University research finds that office socializing can be a pathway to innovation and creativity

Houston voices

Innovation is a team sport. We know that creative workplaces represent a series of social networks, each brimming with useful ideas and expertise. And there is clearly a link between innovation within a firm and the colleagues and friends with whom employees hobnob off duty.

But how exactly does that alchemy happen? What's the relationship between creativity and the hive of direct and indirect contacts in an employee's cell phone?

A recent study by Jing Zhou of the business school, Giles Hirst of Australian National University, Daan Van Knippenberg of Erasmus University, Eric Quintane of the University of Los Andes and Cherrie Zhu of Monash University sheds new light on this. Mapping the social networks that underlie a creative workplace, the researchers showed that employee creativity rises when social networks are more diverse.

The researchers started with the premise that direct links in a network are offshoots of larger networks. The more diverse these indirect networks are, the researchers found, the more likely that innovative concepts will appear in a company's intellectual landscape.

The most efficient resources for gathering novel perspectives are networks made up of two-step "non-redundant ties"—that is, people you may not interact with directly, but with whom your direct ties do interact. These contacts are effectively the raw material employees use to come up with new ideas and ways of working. But why are these indirect networks so important? They diversify the thinking of the group, Zhou and her colleagues argue. Because these networks include individuals who are not necessarily linked, they lower the chances of groupthink or stale ideas.

To test their hypothesis, the researchers looked at the social networks of a large, state-owned pharmacy corporation in the People's Republic of China. Examining 11 divisions, each with roughly 25 sales representatives, the team studied creativity among the sales representatives. Evenly divided between men and women, the representatives were, on average, 35 years of age with approximately 10 years' of experience. Some had developed networks so large that they reached beyond the corporation's geographic territory.

The representatives' creativity manifested itself in a range of forms: new ways to promote products, strategies to cross-sell products, ideas for connecting with hard-to-access sales targets and plans for boosting client sales. The ideas included making products more visible in retail outlets and personalizing product launches to push customers to specific distributors. Because this kind of inventiveness is critical to gaining an edge, it's one of the most important tools in pharmaceutical marketing.

The researchers devised a matrix that matched sales metrics and managers' creativity rankings to the types of social networks the representatives had. The map showed clearly that a two-step, indirect network with few redundancies correlated to individual creativity. When networks were further removed than this, employee creativity was unchanged.

The implication: Firms should attend closely to the kind of social networks their workers cultivate. Not only that, it's possible to teach employees how to design networks for maximum efficiency. Persuading employees to make that effort might be another matter. Luckily, possible incentives abound, from bonuses to the satisfactions of a varied network to the simple pleasure of a more ample expense account. Executives just need to get creative in making their case.

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This story originally ran on Rice Business Wisdom.

Jing Zhou is the Mary Gibbs Jones Professor of Management and Psychology in Organizational Behavior at the Jones Graduate School of Business of Rice University.

In a recent study, a Rice Business professor found that board members actually need incentives — both short- and long-term — to act in stakeholders' best interests. Getty Images

Rice University research finds executive board members are driven by incentives

Houston voices

If you're a stockholder, you may envision your investment helmed by a benevolent, all-knowing board of directors, sitting around a long finely-grained wooden table, drinking coffee, their heads buried in PowerPoint charts as they labor to plot the best course for the company. Too often, however, you can't take for granted that a company's board will steer it wisely.

Companies choose directors because they offer rich and varied experience in the business world. Many who serve on boards, moreover, are CEOs of other corporations, or have headed big companies in the past. As of October 2018, for example, six of the 11 directors on Walmart's board and eight of 13 on AT&T's board hold CEO or CFO positions in other firms. So it's easy to assume that board members will act in the best interests of stockholders.

But in a recent study, Rice Business professor Shiva Sivaramakrishnan found that board members actually need incentives — both short- and long-term — to act in stakeholders' best interests.

Corporations usually compensate board members with stock options, grants, equity stakes, meeting fees, and cash retainers. How important is such compensation, and what sort of incentives do board members need to perform in the very best interests of a company? Sivaramakrishnan joined co-author George Drymiotes to trace how compensation impacts various aspects of board performance.

Recent literature in corporate governance has already stressed the need to give boards of directors explicit incentives in order to safeguard shareholder welfare. Some observers have even proposed requiring outside board members to hold substantial equity interests. The National Association of Corporate Directors, for example, recommended that boards pay their directors solely with cash or stock, with equity representing a substantial portion of the total, up to 100 percent.

To the extent that directors hold stock in a company, their actions are likely influenced by a variety of long-and short-term incentives. And while the literature has focused mainly on the useful long-term impact of equity awards, the consequences of short-term incentives haven't been as clear. Moreover, according to surveys, most directors view advising as their primary role. But this role also has received little attention.

To scrutinize these issues, the scholars used a simple model, which assumes the board of directors perform three roles: contracting, monitoring and consulting. The board contracts with management to provide productive input that improves a firm's performance. By monitoring management, the board improves the quality of the information conveyed to managers. By serving in a consulting role, the board makes managers more productive, which, in turn, means higher expected firm output.

This model allowed the scholars to better understand the relationship between the board of directors and the company's managers, as well as with shareholders. The former was particularly important to take into account, because conflict between a board and managers is typically unobservable and can be costly.

The results were surprising. Without short-term incentives, the researchers found, boards did not effectively fulfill their multiple roles. Long-term inducements could make a difference, they found, but only in some aspects of board performance.

While board members were better advisors when given long-term motivations, short-term incentives were better motivators for performing well in their other corporate governance roles, according to the research, which tied specific aspects of board compensation to particular board functions.

Restricted equity awards provided the necessary long-term incentives to improve the efficacy of the board's advisory role, the scholars found, but only the short-term incentives, awarding an unrestricted share or a bonus based on short-term performance, motivated conscientious monitoring.

The scholars also examined managerial misconduct. Board monitoring, they concluded, lowered the cost of preventing such wrongdoing — but only if the board had strong short-term incentives in place.

Even at the highest rungs of the corporate ladder, in other words, short-term self-interest is the greatest motivator. Maybe it's not surprising. In the corporate world, acting for one's own benefit is a given — so stockholders need to look more closely at those at the very top. Like everyone else, board directors need occasional brass rings within easy reach to do their best.

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This story originally ran on Rice Business Wisdom.

Shiva Sivaramakrishnan is the Henry Gardiner Symonds Professor in Accounting at the Jesse H. 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.

As more and more offices have remote workers, managers need to know how to measure virtual employee success. Getty Images

Rice University research calls for more ways to measure virtual employee success

Houston Voices

Managers are always hunting for ways to measure performance. They need to know what's succeeding and what's not so they can make adjustments and improve a work team's output. This has led to countless research that looks at ways to measure and boost employee performance. Indeed, one recent study showed there were more than 130 models and frameworks for measuring team performance in the workplace.

But how we do business has been changing in the last two decades. Communication technology and information sharing increasingly has decentralized the workforce. More and more people are working remotely. Consider telecommuters, online messenger services such as Slack and customer service call centers routing their calls across the world. What forces determine how these virtual teams function?

In a recent study, Rice Business professor Utpal Dholakia and colleagues René Algesheimer of the University of Zurich and Călin Gurău of GSCM-Montpellier Business School looked closely at what motivates remote teams and how to measure what they do. They began with a standard input-mediator-output-input model (IMOI) to measure team characteristics such as size, tenure, communication, strategic consensus and intentions. Then they dove further, including expected team performance, actual team performance and past team performance into the equations. Finally, they analyzed the influence of motivational (desire to perform) and rational (shared goals) dimensions.

To conduct the research, Dholakia, Algesheimer and Gurău analyzed professional computer gaming teams, reasoning that such teams work together in highly competitive environments. The gamers' lack of organizational context, meanwhile, eliminated any bias that could be linked to traditional institutional structures such as culture and goals. There was a downside, however: the gaming teams didn't fully replicate the situation of virtual teams in business organizations.

Still, by choosing the European Electronic Sports League (ESL) the researchers were able to pick from more than half a million teams that play in excess of 4 million matches a year. In the end, 606 teams participated in the study by answering a questionnaire in the course of a year. The teams all had stable structures and specific objectives, strategies and training, just like virtual work teams. Data was also collected from the ESL database and included in the model.

The findings: most studies do not consider expected and actual team performance in their calculations. This is important because research shows a strong link between expectation and performance. Including both sets of results can help managers choose the right steps to enhance team strategy and effectiveness. (The study did not analyze issues such as trust, training, conflict resolution or leadership, areas Dholakia recommends for further research).

The framework devised by Dholakia and his colleagues gives researchers a more precise way to analyze remote or international teamwork. It also could help guide managers in examining a team's cultural diversity, and how that might affect output. In a time when the workplace is growing ever less tangible, Dholakia's model is a sturdy tool to measure what's happening out there.

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This article originally appeared on Rice Business Wisdom.

Utpal Dholakia is the George R. Brown Professor of Marketing at Jones Graduate School of Business at Rice University.

According to research done by a Rice University professor, businessmen and women are more likely to help out colleagues who attended the same university. Pexels

Rice University research finds that investors and executives are more likely to help out those from their alma mater

Houston Voices

Friends help each other out, right? Imagine young men or women racing down a New England playing field, effortlessly passing a lacrosse ball on their way to the goal. Now imagine some of those old friends as CEOs of large firms, and others as managers of mutual funds. Do they still have each other's backs?

That was the question Rice Business Professor Alexander W. Butler explored in a recent paper. What he found makes perfect sense given human nature, and raises serious questions about the dynamics of the financial market.

Yes, Butler and his coauthor, Umit G. Gurun of the University of Texas at Dallas, found, CEOs of publicly traded corporations and mutual fund managers from the same schools do appear to help each other out. It may be conscious or unconscious: they do what friends do the world over. But the effect on the market can be profound.

To trace the role of social connections in the world of corporate and finance, Butler and Gurun studied how mutual fund managers vote when shareholders proposed limiting executive pay. They cross-referenced these data with information about the educational background of the firms' executives and of the mutual fund managers who took part in the votes.

When voting fund managers and an executive went to the same schools, Butler found, those halcyon days at A&M or Wharton clearly corresponded to fewer votes to limit executive pay.

Now, this may reflect all kinds of things. Shared school ties could mean fund managers have more relevant information about a firm's CEO and his or her value. The shared culture and vocabulary of a school environment might ease information flow between a CEO and managers. But there is also another possibility: Perhaps the value a mutual fund manager places on a CEO's firm has nothing to do with the company's actual value. The manager may simply support him because he's a school friend.

CEOs weren't the only ones to benefit from old-school ties. Well-connected investors prospered too. When a fund manager shared a school background with a given CEO, Butler found, the fund outperformed funds whose managers weren't part of the network. For investors as well as CEOs, in other words, school ties with decision makers at mutual funds raised the chances of a winning outcome.

So a shared school or social background leads to well-paid CEOs, successful fund managers and happy investors. What's not to celebrate?

Plenty, it turns out.

The better trading outcomes of well-connected mutual fund managers have implications far beyond one happy set of shareholders. The Securities and Exchange Commission protects a level playing field because it's in the public interest for the U.S. financial markets to be liquid.

Consumers buy and sell stocks more easily when they are confident that a product's price is reasonably close to its actual value. When one party seems to know more about a stock – perhaps through friendship with the CEO – other investors may lose confidence that they can assess the value of stocks as accurately. When too many consumers distrust the market, liquidity drops. Fewer people buy and sell.

Think how much it easier it is to buy a used car with public resources such as Carfax, or pre-owned car certifications. In the past, a buyer had to wonder what a car seller knew but wasn't saying – or else try to buy a car from someone she already knew and trusted.

Almost everyone has a friend. Almost everyone has experienced the memories, common lingo, and wordless sense of goodwill that come from sharing a common history. Butler and Gurun's study of corporate and financial markets, however, shows how these natural instincts can disadvantage players outside the alumni circle. Shareholders may have less power to limit CEO pay. And consumers may end up less confident about the value of stocks, shaking trust in the financial markets overall. Surely, that's not what friends are for.

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This article originally appeared on Rice Business Wisdom.

Alexander W. Butler is a professor of finance at Jones Graduate School of Business at Rice University.

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$100M Houston VC fund launches to back technical founders

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A new venture capital fund has launched with an initial $100 million mission of supporting founders with innovative critical infrastructure solutions.

Fathom Fund, which is looking to build out a portfolio of advanced computing, material science, climate resilience, and aerospace startups, announced they've launched with an initial close of over $100 million. The fund is founded by longtime investors Managing Partners Paul Sheng and Eric Bielke.

"We believe recent technological advances have accelerated the pace of scientific discovery, increasing the pool of technology companies that can produce venture-scale returns," Sheng says in a news release.

According to the fund, it hopes to bridge the gap for early stage capital for physical innovations and "moonshot" projects.

“What’s lacking in venture is rigorous technical diligence at the early stages and a playbook to scale these innovations at the pace necessary to lead industries," Bielke adds. "With this launch, we are looking forward to supporting founders with some of the most disruptive and novel ideas.”

The founder duo will bring each of the career expertise to their future portfolio companies. Sheng spent decades at McKinsey & Co and was the firm's head of the Global Energy & Materials practice. Bielke is a former director at Temasek’s Emerging Technologies Fund.

Houston is the 4th best U.S. city for Black professionals, report finds

Black History Month

In acknowledgement of Black History Month 2024, a new report compiled by Black employees at online rental marketplace Apartment List has ranked Houston the No. 4 best U.S. city for Black professionals.

Apartment List reviewed 76 cities across four major categories to determine the rankings: community and representation; economic opportunity; housing opportunity; and business environment.

Houston earned a score of 63.01 out of a total 100 points, making it the second-highest-ranked city in Texas for Black professionals, behind San Antonio (No. 3).

The city earned top-10 rankings in three out of the four main categories:

  • No. 3 – Business environment
  • No. 4 – Community and representation
  • No. 10 – Economic opportunity
  • No. 21 – Housing opportunity

Houston is commended for its strong Black business environment and economy, but there is some room for improvement when it comes to housing. Similarly to Apartment List's 2022 report – which also placed Houston at No. 4 – a little less than half (44 percent) of all Black Houston households are spending over 30 percent of their income on housing, which has increased two percent since 2019.

Houston has a larger Black population than San Antonio, at 19 percent, but its Black population share is overall lower than other cities in the top 10.

"Furthermore, the community is well-represented in some critical occupations: 20 percent of teachers are Black, as are 21 percent of doctors," the report said. "Houston is also home to the HBCU Texas Southern University, helping a job market when the median Black income is several thousand dollars above average."

Houston also has the highest rate of Black-owned businesses in the entire state, at 18 percent.

"From the Mitochondria Gallery to Ten Skyncare and Wisdom’s Vegan Bakery, Houston has it all!" the report said.

Here's how Houston stacked up in other metrics:

  • Black homeownership: 42 percent
  • Black lawyers: 14 percent
  • Black managers: 14 percent

Elsewhere in Texas
Texas cities dominated the overall top 10. San Antonio ranked just above Houston, with Dallas (No. 6) and Austin (No. 7) not too far behind.

San Antonio came in less than 2.5 points ahead of Houston with a total score of 65.44 points. The report praised San Antonio's scores across its economic opportunity (No. 2), housing opportunity (No. 7), and community and representation (No. 10). The city ranked No. 20 for its Black business environment.

But like Houston, San Antonio also fell behind in its Black homeownership rates, according to the study.

"While the Black homeownership rate is higher than average at 44 percent, the homeownership gap (Black homeownership rate - non-Black homeownership rate) quite low at -19 percent," the report's author wrote. "Perhaps this could be explained by San Antonio’s overall homeownership rate, which is also lower than the state’s average. Additionally, the lower homeownership gap could explain the cost burden rate also being lower than average at 41 percent."

The top 10 cities for Black professionals are:

  • No. 1 – Washington, D.C.
  • No. 2 – Atlanta, Georgia
  • No. 3 – San Antonio, Texas
  • No. 4 – Houston, Texas
  • No. 5 – Palm Bay, Florida
  • No. 6 – Dallas, Texas
  • No. 7 – Austin, Texas
  • No. 8 – Colorado Springs, Colorado
  • No. 9 – Lakeland, Florida
  • No. 10 – Charlotte, North Carolina
The full report and its methodology can be found on apartmentlist.com.

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This article originally ran on CultureMap.

Houston expert: Can Houston replicate and surpass the success of Silicon Valley?

guest column

Anyone who knows me knows, as a Houston Startup Founder, I often muse about the still developing potential for startups in Houston, especially considering the amount of industry here, subject matter expertise, capital, and size.

For example, Houston is No. 2 in the country for Fortune 500 Companies — with 26 Bayou City companies on the list — behind only NYC, which has 47 ranked corporations, according to Fortune.

Considering layoffs, fund closings, and down rounds, things aren’t all that peachy in San Francisco for the first time in a long time, and despite being a Berkeley native, I’m rooting for Houston now that I’m a transplant.

Let’s start by looking at some stats.

While we’re not No. 1 in all areas, I believe we have the building blocks to be a major player in startups, and in tech (and not just energy and space tech). How? If the best predictor of future success is history, why not use the template of the GOAT of all startup cities: San Francisco and YCombinator. Sorry fellow founders – you’ve heard me talk about this repeatedly.

YCombinator is considered the GOAT of Startup Accelerators/Incubators based on:

  1. The Startup success rate: I’ve heard it’s as high as 75 percent (vs. the national average of 5 to 10 percent) Arc Search says 50 percent of YC Co’s fail within 12 years – not shabby.
  2. Their startup-to-unicorn ratio: 5 to 7 percent of YC startups become unicorns depending on the source — according to an Arc Search search (if you haven’t tried Arc Search do – super cool).
  3. Their network.

YC also parlayed that success into a "YC Startup School" offering:

  1. Free weekly lessons by YC partners — sometimes featuring unicorn alumni
  2. A document and video Library (YC SAFE, etc)
  3. Startup perks for students (AWS cloud credits, etc.)
  4. YC co-founder matching to help founders meet co-founders

Finally, there’s the over $80 billion in returns, according to Arc search, they’ve generated since their 2005 inception with a total of 4,000 companies in their portfolio at over $600 billion in value. So GOAT? Well just for perspective there were a jaw-dropping 18,000 startups in startup school the year I participated – so GOAT indeed.

So how do they do it? Based on anecdotal evidence, their winning formula is said to be the following well-oiled process:

  1. Bring over 282 startups (the number in last cohort) to San Francisco for 90 days to prototype, refine the product, and land on the go-to-market strategy. This includes a pre-seed YC SAFE investment of a phased $500,000 commitment for a fixed min 7 percent of equity, plus more equity at the next round’s valuation, according to YC.
  2. Over 50 percent of the latest cohort were idea stage and heavily AI focused.
  3. Traction day: inter-portfolio traction the company. YC has over 4,000 portfolio companies who can and do sign up for each other’s companies products because “they’re told to."
  4. Get beta testers and test from YC portfolio companies and YC network.
  5. If they see the traction scales to a massively scalable business, they lead the seed round and get this: schedule and attend the VC meetings with the founders.
  6. They create a "fear of missing out" mentality on Sand Hill Road as they casually mention who they’re meeting with next.
  7. They block competitors in the sector by getting the top VC’s to co-invest with then in the seed so competitors are locked out of the A list VC funding market, who then are up against the most well-funded and buzzed about players in the space.

If what I've seen is true, within a six-month period a startup idea is prototyped, tested, pivoted, launched, tractioned, seeded, and juiced for scale with people who can ‘make’ the company all in their corner, if not already on their board.

So how on earth can Houston best this?

  1. We have a massive amount of businesses — around 200,000 — and people — an estimated 7.3 million and growing.
  2. We have capital in search of an identity beyond oil.
  3. Our Fortune 500 companies that are hiring consultants for things that startups here that can do for free, quicker, and for a fraction of the extended cost.
  4. We have a growing base of tech talent for potential machine learning and artificial intelligence talent
  5. A sudden shot at the increasingly laid off big tech engineers.
  6. We have more accelerators and incubators.

What do we need to pull it off?

  1. An organized well-oiled YC-like process
  2. An inter-Houston traction process
  3. An "Adopt a Startup" program where local companies are willing to beta test and iterate with emerging startup products
  4. We have more accelerators but the cohorts are small — average five to 10 per cohort.
  5. Strategic pre-seed funding, possibly with corporate partners (who can make the company by being a client) and who de-risk the investment.
  6. Companies here to use Houston startup’s products first when they’re launched.
  7. A forum to match companies’ projects or labs groups etc., to startups who can solve them.
  8. A process in place to pull all these pieces together in an organized, structured sequence.

There is one thing missing in the list: there has to be an entity or a person who wants to make this happen. Someone who sees all the pieces, and has the desire, energy and clout to make it happen; and we all know this is the hardest part. And so for now, our hopes of besting YC may be up in the air as well.

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Jo Clark is the founder of Circle.ooo, a Houston-based tech startup that's streamlining events management.