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What Kind of Startup Founder Are You?

Executive Summary

When it comes to getting a new venture off the ground, a sense of collective ownership is vital — but it’s not always clear how founders should go about fostering that shared ownership in their teams. In this piece, the authors describe recent research that looked at how different types of leaders attempt to cultivate a sense of ownership in their people, ultimately concluding that a careful balance between delegation and dictation is most likely to be effective. They go on to suggest that the best way founders can keep their teams engaged and their businesses on track is by proactively deciding which elements of their idea are open for discussion, and which are fixed — and then clearly communicating those distinctions to everyone involved.

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Many promising new ventures struggle to get off the ground because their founders fail to cultivate a sense of collective ownership — a feeling that the venture idea is “ours,” and not just the founder’s — in their teams. When teams feel ownership of an idea, they are more collaborative, they take more risks, and they make more personal sacrifices to support the shared goal — and when there’s a lack of ownership, team members quickly become demotivated and unproductive. So what can founders do to foster that all-important sense of collective ownership?

To explore this question, we conducted a series of studies with more than 500 startup founders and team members from both entrepreneurship competitions and university startup launch courses. We collected extensive quantitative data to measure the performance of these companies, including surveys and investor evaluations, and also conducted qualitative interviews with founders and their team members. Based on our research, we discovered that founders tend to adopt one of three styles — and which style they choose can have a major impact on their success:

The Delegator

The first type of founder actively seeks input from their team not just on questions of execution, but on their entire venture idea. For instance, one founder we interviewed, Sam*, was the head of a medical device startup focused on developing a surgical tool for kidney transplants. Rather than just having his teammates implement his idea, he frequently asked them to consider how the tool he had already developed could be redesigned. In response, one person suggested a design change to make the tool adaptable for other surgical procedures, which expanded both the company’s potential market and its social impact. As one member of Sam’s team put it, “Even though he has been working on this for two years, he is not coming in with an attitude of, you know, ‘This is my idea, so you are just going to work on it.’ He still wants all of our input, which is really nice.”

Proactively engaging your team on shaping the core idea is an effective way to build ownership — but only to a point. In our interviews, we found that if a founder encouraged too much feedback, the team was liable to lose focus and motivation. For example, Hallie, the founder of a concert-planning startup, asked her team members to pursue any and all changes to her idea, no matter now far afield of her original plan. Her team suggested a number of useful avenues, such as dynamic ticket pricing and a customer rewards program. But as the team explored all these different directions, Hallie found herself becoming less attached to the venture. As she told us, “The original idea was my baby, and then it really morphed into a new direction. After the change, I became less invested in the idea — and it showed.”

In addition, these founders often fail to set clear boundaries around what is and isn’t up for debate, creating conflict when team members suggest ideas that the founders don’t like. For example, one team member recalled how her founder claimed to be totally open-minded, but in fact struggled to accept certain new ideas: “You could see she had kind of a shock factor and she was trying to defend it. She was holding onto her idea. After that, it just wasn’t worth it to any of us to shake it up any more or put in the effort. There was just an uneasiness that never really went away.” The team ended up disbanding before it had even finished its prototype.

Getting your team involved by delegating important decisions is a great way to cultivate a sense of ownership — but without clear boundaries, you risk losing both your own interest in the venture and the support of your team.

The Dictator

The second type of founder is much more territorial about their ideas. In some cases, this approach can boost collective ownership, as clear direction can reduce ambiguity, minimize potential conflict, and ensure people are focused on the same goals. As one team member reflected when discussing her experience with a dictatorial founder, “She shared with us her personal connection to the idea. After that we knew where she wanted to go with it, so we really didn’t try and change it. It helped us understand the strategy and where the product fit in. Having something tangible helped everyone get excited about it.” A passionate, dictatorial leadership style can in some cases increase collective ownership, because clarity around who is in control can help things run more smoothly.

Of course, this style also limits opportunities for new team members to influence the direction of the company, making it difficult to stay engaged and invested. For example, in one founder’s initial exchanges with his team, he made it clear that his idea was fixed and not open to any design changes. As a result, his team wasn’t able to share their unique perspectives, which they found extremely demotivating. As one team member recounted, “When I joined the team, I was really excited about it. But now it seems like he doesn’t really want me to contribute that much. We’ve been more like advisors than team members, kind of stuck in the backseat.” A dictatorial approach can reduce conflict and ambiguity around direction, but the lack of opportunities for engagement can alienate your team and erode their sense of collective ownership.

The Designator

The final type of founder we observed struck a delicate balance between the two approaches described above. These flexible founders clearly designated which parts of their original idea were “off limits,” and which parts were open for discussion. As one team member described, “He told us there were two core things [about the venture idea] he was not willing to give up, and that those core elements would remain in place. But he also said that [for] other things, like the target market, he wanted input from the team.”

This blended approach captures the benefits of the other two styles while minimizing their downsides. By asking for help in some areas and articulating clear boundaries in others, these founders are able to bolster engagement while keeping their teams from taking the venture in an unwanted direction. For example, Alex worked for a founder who had specified that he wasn’t looking for new feature ideas, but he was very interested in exploring new markets or other business-side changes: “We knew the core technology was ready,” Alex explained, “and that our efforts would be spent on developing the business model for that technology.”

Part of what makes this mixed approach so effective is that it’s not just about designating what’s not up for debate — it’s about explicitly stating where founders would like their team members to contribute. Reflecting on his experience, one founder said, “I think that allowing [my team] to help the company pivot and have their ideas not only heard, but acted on — that’s how they’ve developed a sense of ownership.” It isn’t easy to pull off, but the founders who embraced a combination of these seemingly incompatible leadership styles were the most successful at building collective ownership in their teams.

Takeaways for Founders

So what does this mean for startup founders? Ultimately, there’s a time and a place for both delegation and dictatorship — the important thing is to designate clear boundaries between the two. Based on our research, we suggest a simple three-step plan for founders looking to help their people foster a strong sense of collective ownership:

  1. Start by cataloguing the various elements of your business idea, such as the core technology, target market, product/service design, financial projections, and customer acquisition strategy.
  2. For each of these elements, determine for yourself whether they are fixed or open to change.
  3. Clearly (and consistently) communicate these distinctions to your team.

It’s natural that there will be parts of your idea that feel sacred, and other parts in which you will be happy to welcome feedback. To keep your team engaged and your business on track, what matters most is that you clearly designate which is which.

* Names have been changed to protect privacy.

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Make Tax Planning a Part of Your Company’s Risk Management Strategy

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Companies face a taxpaying dilemma: Paying less means higher earnings and a higher value for shareholders, but overly aggressive tax minimization strategies can lead to fines, public scrutiny, and/or reputational damage. Research finds that companies that incorporate their tax-planning decisions into their overall enterprise risk management are better able to find that balance of risk and reward. To do this, boards should 1) Take responsibility for risk oversight; 2) Engage in risk-monitoring activities on a regular basis; and 3) Foster an appropriate risk mindset.

The five largest U.S. companies (Apple, Microsoft, Alphabet, Amazon, and Facebook) reported an average income tax liability of $7.3 billion in their 2019 annual reports. Yet those same companies have repeatedly faced criticism from politicians and activists for aggressively avoiding paying billions more.

Taxes are one of the largest expenses any company faces; paying less can mean higher earnings and, in turn, higher value for shareholders. So it is no surprise that companies seek to reduce the amount they pay.

Overly aggressive tax minimization, however, can lead to significant adverse outcomes, such as costly and unexpected IRS fines along with public scrutiny and reputational damage. Microsoft and Hewlett Packard have faced criticism from Congress for their tax avoidance policies, and the Senate Permanent Subcommittee on Investigations has labeled Apple a “U.S. tax dodger.” Six of the largest companies in Silicon Valley were recently identified by Fair Tax Mark as having avoided more than $100 billion in taxes over the past decade. Corporate executives are challenged with “threading the needle” between shareholder expectations to not pay more than their “fair share” of taxes and government and the general public’s expectations that they should pay at least their fair share. In sum, companies face a “not too hot, not too cold” Goldilocks problem. What are they to do?

Our research indicates that strong board of director involvement in a company’s risk oversight as a part of enterprise risk management (ERM) helps companies find that balance of risk and reward in terms of tax-planning decisions. Using the 2014 annual proxy disclosure statements for a sample of companies from the Russell 1,000, we measured companies’ level of board involvement in risk oversight and evaluated their association with previously researched measures of tax planning and avoidance strategies for the years 2014 through 2017. We found that companies where the board is most engaged in important risk-oversight activities pay lower taxes, on average, and face a lower risk of regulatory scrutiny or reputational damage, as evidenced by less-aggressive shifting of income abroad and 31.0% less-volatile income taxes relative to similar companies with lower levels of risk oversight.

ERM helps boards and executives develop holistic approaches to identifying and monitoring all kinds of risks that could potentially affect the achievement of strategic objectives. Its focus is not on indiscriminate risk minimization but on identifying and understanding the company’s portfolio of risks so that management and the board can make sound strategic decisions that balance various risks against the pursuit of growth. Highly engaged boards provide a culture and foundation that can maximize positive outcomes (such as lower tax payments) while minimizing potential negative outcomes (such as higher tax risk).

Our research indicates that boards can do three things to improve their involvement in companies’ ERM systems, resulting in better tax outcomes.

1. Take responsibility for risk oversight.

Boards that engage in and “own” the overall responsibility for monitoring the company’s ERM, rather than delegating that responsibility elsewhere within the organization or to a board subcommittee, establish a mindset that embraces risk oversight as a key aspect of overall board governance. This sends a signal to company leaders that risk management is to be taken seriously.

To start, the board should formally and publicly acknowledge its responsibility for risk oversight in its annual proxy statement. This public disclosure lets management and key stakeholders know that the board will keep a careful eye on the risk oversight process. Moreover, it commits the board to incorporating risk considerations into its decisions and its evaluations of the company’s strategic decisions, including those associated with tax avoidance policies.

2. Engage in risk-monitoring activities on a regular and systematic basis.

Regular engagement in holistic risk-monitoring activities helps the board consider how strategic decisions in one area of the business might trigger risks in other areas. These activities include routine board discussions about the top risks identified by the ERM system and evaluations of emerging risks that are not already on management’s radar. Best practice suggests that boards proactively review the company’s risk-management policies and procedures on at least an annual basis to ensure that processes are in place to identify and tackle key areas of risk exposure, including tax-related risks.

Although it’s important for many financial areas, this process is especially relevant to taxes, owing to the constant evolution and updating of tax laws. Regular monitoring of tax-related risks should help ensure that the board remains comfortable with the outcomes of the company’s ever-evolving tax-planning initiatives.

3. Foster an appropriate risk mindset.

Boards are critical to ensuring that company executives maintain a “tone at the top” that balances the goal of increasing company value against the need to ensure appropriate risk-taking. By fostering an appropriate risk mindset, the board plays a key role in establishing the company’s risk appetite and ensuring that management’s strategic planning decisions are made within the bounds of stakeholders’ appetite and tolerance for risk-taking. Because tax-planning initiatives present the company with both risks and rewards, boards must encourage management to evaluate any potential tax savings against any associated tax-related risks.

Building a strong ERM system is not a costless endeavor. It calls on managers and other leaders to engage in risk identification, assessment, and management efforts, all of which require both time and monetary investment. Although some boards and executive teams may wonder if the investment is worth it, our research provides evidence of a tangible benefit: better tax outcomes.

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Root Out Bias at Every Stage of Your AI-Development Process

Executive Summary

Bias mitigation is a fairly technical process, where certain techniques can be deployed depending on the stage in the machine learning pipeline: pre-processing, in-processing and post-processing. Each offers a unique opportunity to reduce underlying bias and create a technology that is honest and fair to all. Leaders must make it a priority to take a closer look at the models and techniques for addressing bias in each of these stages to identify how best to implement the models across their technology. Ultimately, there is no way to completely eliminate AI bias, but it’s the industry’s responsibility to collaborate and help mitigate its presence in future technology. With AI playing an increasing important role in our lives, and with so much promise for future innovation, it is necessary that we acknowledge and address prejudice in our technology, as well as in our society.

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AI has long been enabling innovation, with both big and small impacts. From AI-generated music, to enhancing the remote fan experience at the U.S. Open, to managing coronavirus patients in hospitals, it seems like the future is limitless. But, in the last few months, organizations from all sectors have been met with the realities of both Covid-19 and increasing anxiety over social justice issues, which has led to a reckoning within companies about the areas where more innovation and better processes are required. In the AI industry, specifically, organizations need to embrace their role in ensuring a fairer and less-biased world.

It’s been well-established that machine learning models and AI systems can be inherently biased, some more than others — a result most commonly attributed to the data being used to train and develop them. In fact, researchers have been working on ways to address and mitigate bias for years. And as the industry looks forward, it’s vital to shine a light on the various approaches and techniques that will help create more just and accurate models.

Bias mitigation is a fairly technical process, where certain techniques can be deployed depending on the stage in the machine learning pipeline: pre-processing  (preparing the data before building and training models), in-processing (modifications to algorithms during the training phase), and post-processing (applying techniques after training data has been processed). Each offers a unique opportunity to reduce underlying bias and create a technology that is honest and fair to all. Leaders must make it a priority to take a closer look at the models and techniques for addressing bias in each of these stages to identify how best to implement the models across their technology.


First, we need to address the training data. This data is used to develop machine learning models, and is often where the underlying bias seeps in. Bias can be introduced by the selection or sampling of the training data itself. This may involve unintentionally excluding certain groups, so that when the resulting model gets applied to these groups, the accuracy is inevitably lower than it is for the groups that were included in the training data. Additionally, training data usually requires labels used to “teach” the machine learning model during training. These labels often come from humans, which of course risks the introduction of bias. For label data in particular, it is crucial to ensure that there is a diversity of demographics in the human labelers to ensure that unconscious biases don’t creep in.

Insight Center

Counterfactual fairness is one technique scientists use to ensure that outcomes are the same in both the actual world and in a “counterfactual world,” where individuals belong to a completely different demographic. A great example of where this is of value is in university admissions — let’s say William from Los Angeles, who is white, and Barack from Chicago, who is African American, have similar GPAs and test scores. Does the model process the data the same if demographic information is swapped?

When predicting outcomes or making decisions, such as who gets the final university acceptance letter of the year, the training data and resulting models should be carefully vetted and tested before being fully implemented. It is especially important to assess variance in performance across sensitive factors like race and gender.


When training a machine learning model, in-processing models offer unique opportunities to encourage fairness and use regularization to tackle bias.

Adversarial training techniques can be applied to mitigate bias, where the machine learning model is jointly trained to simultaneously minimize errors in the primary objective (e.g., confirming or rejecting university admissions) while also penalizing the ability of another part of the model to predict some sensitive category (e.g., race).

My company recently conducted research on de-biasing approaches for examining gender bias in speech emotion recognition. Our research found that fairer, more consistent model accuracy can be achieved by applying a simple de-biasing training technique — here we compared a state-of-the-art approach on adversarial training to an approach with no de-biasing. Without any de-biasing, we found that emotional activation model accuracy is consistently lower for females compared to male audio samples. However, by applying a simple modification to the error term during the model training, we were able to effectively mitigate this bias while maintaining good overall model accuracy.


Post-processing is a final safeguard that can be used to protect against bias. One technique, in particular, has gained popularity: Reject Option-Based Classification. This process assumes that discrimination happens when models are least certain of a prediction. The technique exploits the “low confidence region” and rejects those predictions to reduce bias in the end game. This allows you to avoid making potentially problematic predictions. Also, by monitoring the volume of rejected inferences, engineers and scientists can be alerted to changes in the characteristics of the data seen in production and new bias risks.

The Road to Fairer AI

It is imperative that modern machine learning technology is developed in a manner that deliberately mitigates bias. Doing this effectively won’t happen overnight, but raising awareness of the presence of bias, being honest about the issues at hand, and striving for better results will be fundamental to growing the technology. As I wrote a year ago, the causes and solutions of AI bias are not black and white. Even “fairness” itself must be quantified to help mitigate the effects of unwanted bias.

As we navigate the lasting effects of the pandemic and social unrest, mitigating AI bias will continue to become more important. Here are several ways to get your own organization to focus on creating fairer AI:

  • Ensure that training samples include diversity to avoid racial, gender, ethnic, and age discrimination.
  • Whether labeling audio samples or generic data, it is critical to ensure that there are multiple and different human annotations per sample and that those annotators come from diverse backgrounds.
  • Measure accuracy levels separately for different demographic categories to see whether any group is being treated unfairly.
  • Consider collecting more training data from sensitive groups that you are concerned may be at risk of bias — such as different gender variants, racial or ethnic groups, age categories, etc. — and apply de-biasing techniques to penalize errors.
  • Regularly audit (using both automatic and manual techniques) production models for accuracy and fairness, and regularly retrain/refresh those models using newly available data.

Ultimately, there is no way to completely eliminate AI bias, but it’s the industry’s responsibility to collaborate and help mitigate its presence in future technology. With AI playing an increasing important role in our lives, and with so much promise for future innovation, it is necessary that we acknowledge and address prejudice in our technology, as well as in our society.

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Are You Ready to Be Coached?

Executive Summary

Before you decide to work with an executive coach, assess your readiness to ensure you’ll actually benefit and grow from the experience. Take a look at yourself in the context of seven characteristics of successful coachees. Are you willing to hold yourself accountable for making progress? Are you open to new behaviors and ways of thinking? Are you ready to exercise the discipline necessary to stick to your coaching goals? Expect that the experience will cause you both excitement and some anxiety, and be ready to have an honest conversation with your coach about which characteristics are challenging for you. You may find that you’re not yet ready to get the most out of executive coaching, or you may gain insight into what it will take for you to meaningfully develop as a leader.

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Executive coaching can help you achieve higher performance and greater personal satisfaction at work. While you may be aware that you need to make changes — in behavior, mindset, or both — to advance your career, you won’t reap the benefits of coaching unless you’re prepared to fully engage in the process. This requires a substantial investment of time and effort, so before you move forward, the most important question you should ask yourself is, “Am I ready to be coached?”

Having discussed challenging client experiences with many accomplished executive coaches, it’s clear that the corresponding question — “Is this leader coachable?” — figures prominently in their evaluation of whether and how to proceed. Drawing on these conversations, I identified seven core characteristics that differentiate leaders who evolve through coaching from those who don’t.

Tolerance for discomfort. Successful coaching requires you to be proactive in embracing new ways of perceiving and acting. In doing so, you will likely experience fear or emotional blocks about new realizations and realities. You must be able to endure these periods of discomfort to realize the rewards of taking new and different approaches.

Openness to experimentation. Trying something new means taking risks, and experiments with new behaviors may not work the first time. Waiting for the perfect timing or perfect performance will stand in the way of progress. If you think you already have the answers and are unwilling to explore new options, you are unlikely to be open or do the necessary reflection to change. You have to try out new ideas and actions, fail, learn, and try again.

Ability to look beyond the rational. Behavior is not rational — it’s driven by emotions like fear, anger, and pride. Just because you “know” what to do doesn’t mean that you’ll act accordingly. You’ll gain a deeper understanding of your own behaviors and relationships if you explore their emotional dimensions.

Willingness to take responsibility. It’s hard to change if you don’t believe you have the power to shape your future. Blaming the organization, the boss, too many responsibilities, and so on will block you from growth. Even if there is some truth in your reasoning, it’s impossible to move forward if you see yourself as a victim. You have to hold yourself accountable for making progress.

Capacity for forgiveness. Even if you feel you’ve been mistreated, it’s essential to make peace with the past and channel your energy into progress. The need to “be right” or “show them” is rarely helpful for you or the people you work with. You must be willing to forgive and move on.

Self-discipline. Somewhat counterintuitively, your development as a leader will likely require you to let go of ways of thinking and behaving that helped make you successful in the past and be prepared to live with the consequences. It may be hard for others to accept changes in your personal or work relationships. For example, you may have succeeded up to this point by saying yes to helping out colleagues and making yourself available. But disciplining yourself to say no and learning to focus on what’s important are essential parts of becoming a more effective leader. Even if those around you bristle at you no longer being available 24/7, you have to stay focused on your coaching goals.

Ability to ask for support. Finally, you must be engaged with other potential supporters, not just your coach, throughout the coaching process. You are accountable for change, but you will develop faster if you make yourself vulnerable to others (judiciously), including your boss, peers, and even direct reports. Share goals, ask for advice, listen with curiosity, and most critically, accept and act on the constructive feedback you receive.

It’s normal to feel both excitement and trepidation when deciding to work with an executive coach. Start by assessing the degree to which you have these seven characteristics, then discuss which are the most challenging for you. You may mutually decide that it’s not the right time to proceed. More likely, it will help you develop a stronger relationship and a deeper awareness of how to meaningfully develop as a leader through coaching.

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How to Solve Your Most Difficult Leadership and Talent Challenges

Guest post from Stephen Shapiro:

To find better solutions to your most difficult business problems, paradoxically, you don’t want o focus on solutions.

Instead you want to make sure you are asking the right questions. Changing the question changes the range of possible solutions.

Changing Just One Word Can Change Your Solutions

If your challenge is, “How can we hire the right talent?”, you might put your energies into time-consuming campus outreach programs, complicated recruitment campaigns, or expensive technology.

But changing the question to, “How can we retain the right talent?” may shift your focus to internal motivation and performance management strategies.

Simply changing one word yields a completely different set of answers.

You could change it again to, “How can we develop the right talent?” Now we are looking at leadership opportunities that might not have been previously considered.

Before investing in developing solutions and strategies to your problems, first make sure you are moving in the right direction.

Be More Specific to Reduce Waste

When problem-solving, it is common to start off with an opportunity that is too broad. When we ask broad questions, we invite a lot of wasted energy. When asking the question, “How can I improve the business?”, (the default question associated with most suggestion boxes), you could get literally hundreds or thousands of possible answers.

In fact, over 99% of the ideas submitted to most suggestion boxes are low value and are not implemented. This wastes the time of those who submit the ideas and those who have to evaluate the duds.

But if you make the problem statement more specific, you focus people on what matters most. 

Going back to the original statement: “How can we hire the right talent?” What does “right” mean? Maybe the question could be, “How can we hire for unique skills that make our products differentiating?”

This now focuses your efforts on a specific skillset. Of course, it might lead you to ask the question, “What differentiates our products from the competition?” Answering this gives you deeper insights into your business and the people that are required to support it.

Sometimes Being More Abstract Can Increase Creativity

Although we often start with broad problem statements, there are times when we are too specific. Either our focus is so specific that it limits our ability to find solutions. Or in some cases our questions are really just solutions masquerading as questions.

I remember a client who was focused on, “How can we use 360-degree feedback to improve performance?”

Their myopic focus on this one tool limited their ability to “see” other leadership development solutions.

The broader question might be, “How can we improve performance?” 360-degree feedback was too specific.

This then forced them to ask, “What is the performance issue we need to solve?” After some analysis, they determined that the issue was a silo mentality within the company. When they shifted the question to, “How can we break down silos in our organization?”, they found a wider range of solutions. As it turns out, 360-degree feedback was not part of the approach.

Our Best Solutions are Often Invisible

The questions we ask impact the solutions that are visible. Subtle changes to the problem statement can reveal solutions that were previously hidden.

Or to paraphrase a quote that is attributed to Albert Einstein, “If I had an hour to save the world, I would spend 59 minutes defining the problem and one minute finding solutions.” From my experience, most organizations are spending 60 minutes solving problems that are unimportant or irrelevant.

When everyone in your organization learns how to powerfully reframe business problems, you will get better results, faster, with lower risk. It’s the simplest tool you have to find the best solutions that will grow your business.

For over 20 years, Stephen Shapiro has presented his provocative strategies on innovation to audiences in 50 countries. During his 15-year tenure with the consulting firm Accenture, he led a 20,000-person innovation practice. He is the author of six books, including his latest: Invisible Solutions: 25 Lenses that Reframe and Help Solve Difficult Business Problems. His Personality Poker® system has been used around the world to create high-performing innovation teams. In 2015 he was inducted into the Speaker Hall of Fame.