Marina Gorbis's Blog, page 781

What to Do If Your Career Is Stalled and You Don’t Know Why

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A CEO whom we’ll call Melissa was exasperated. Having delivered seven years of breakthrough performance and nearing retirement, she was eager to select and prepare her successor. Members of her executive team were strong in their current roles but none was quite right for the top job.

As we considered a broader group of potential candidates, the CHRO chimed in with an idea: “What about Tom? He is very strategic and his teams would take the hill for him. He might be worth looking at as an option.” Then the CHRO paused for a moment and added, “Of course there is this issue of his executive presence. Tom often hogs the spotlight in meetings unaware of how that alienates his peers. And…well…I don’t know how to put this, but he has noticeable body odor that’s a real turnoff.” Melissa agreed: “Tom is a brilliant business mind, but I just can’t see him representing our company.” As it turns out, for eighteen years Tom had received stellar performance reviews and top bonuses on the strength of his performance. “Executive presence” was mentioned in several reviews as an improvement area, but without any specifics, Tom had no idea what the real issue was and how damaging it could be to his career.

Having assessed over 2,000 CEOs and over 18,000 C-suite leaders since 1995, we are struck by how often careers of talented executives stall or even derail because of seemingly trivial issues, many of which are utterly fixable. We call these types of issues “pandas.” Pandas look innocent, but their powerful jaws deliver a bite stronger than a jaguars’. Pandas can be painfully costly to individuals whose careers stall for reasons unbeknownst to them and to organizations and managers unable to develop talented leaders to their full potential.

To better understand this phenomenon, we analyzed a sample of 113 strong performers who were finalists for C-suite roles but got turned down in the final decision round. In reviewing detailed assessments of their capabilities, we uncovered that 62% had at least one “panda” issue and 10% had more than one. Furthermore, for 35% of these executives, “pandas” were considered among the top three risks identified with respect to this individual’s fit to a role. Often these pandas live on for years, seemingly innocent, but ultimately gnaw at the career trajectory of otherwise talented leaders.

Our analysis uncovered the most common types of “pandas”:

36% of pandas related to executive presence
28% related to communication style
29% related to peer-level relationships
The remaining 7% included excessive optimism and perfectionism

We’ll now examine each.

Executive presence. This is an ill-defined catchall for a multitude of issues from the seemingly trivial but career damaging body odor, to deeper challenges, such as when someone doesn’t carry herself/himself in a way consistent with company culture. Often executives who fail to appear confident get comments about lackluster executive presence. Dismiss this panda at your peril: Our research shows highly confident executives were 2.5 times more likely to be hired.  This reminds us of Brian, a brilliant investment professional at a top firm who was passed over for promotion to partner due to his poor executive presence. Asked to coach Brian, we gathered extensive feedback from his colleagues and external parties. It turns out that while respected for his intellect, Brian showed up as meek and understated, leaving others with a perception that he was junior and not ready to represent the firm as a partner. We helped Brian identify and address the specific behaviors that created this perception and today he is a highly profitable partner at the firm.

Communication style. Complaints about communication style usually concern how one speaks up (or doesn’t) in various forums. One’s communication style shapes first impressions and can have a significant impact on career trajectory. Lagging on communication effectiveness showed up as a risk area for 28% of executives we analyzed. Take Jim, a front-runner CFO candidate for a leading medical device manufacturer on the verge of an IPO. Jim’s resume checked all of the boxes (and then some), but his Achilles’ heel was a long-winded, almost philosophical communication style — more befitting a cerebral academic than a bottom- line-oriented CFO who can drive performance and credibly represent the company with the investment community.

Our research shows that candidates who used more esoteric, intellectual, or “ivory tower” vocabulary were, eight times less likely to be hired compared to candidates who used more colloquial language. Down-to-earth storytelling, drawing on memorable results, is vastly more powerful than a cerebral, academic style.

Another common communication pitfall has to do with use of “we” and “I.” The weakest candidates for C-suite roles used “I” at twice the rate of the rest of the sample. The most successful candidates are clear about their individual contributions without overusing “I.” Candidates who go on and on with their own accomplishments impress decision makers less than the ones who say, “My proudest achievement was the moment the team began to knock it out of the park” — and then clearly explain their role in the group’s achievement.

About the Research

This article is based on research conducted over 10 years in support of our recently published book, The CEO Next Door (Currency, 2018). ghSMART has assembled a data set of assessments of over 18,000 C-suite executives across all major industry sectors and company sizes. Each executive assessment includes detailed career and educational histories; performance appraisals; and information on patterns of behavior, decisions, and business results. This data was gathered through structured interviews with every executive.

Finally, we were disappointed to uncover that CEO candidates for United States-based companies who had a significant accent were 12 times less likely to be hired. While in-group bias is a deep and persistent issue in hiring, we found that at least for some of these executives their insufficient language fluency lead them to be perceived as less competent than they were and that as this bias was brought to light and they worked to improve fluency and reduce the accent, their career trajectory improved.

Peer relationships. We often see talented executives hitting home runs in their own division and striking out with their peer group. Take Denise, a talented marketing executive who has helped reinvigorate some of the world’s most iconic retail brands. What ultimately cost Denise a coveted CMO job was a pattern of poor peer relationships. Her performance reviews were filled with praise from her bosses and her direct reports for her excellent results and relentless passion, but her peers believed that her own advancement mattered more to her than a team win. Individuals like Denise often do extremely well in the middle management ranks but stall out on the path to the C-suite, because they seem unable or unwilling to think beyond their own division or function. This is easier said than done, especially as powerful corporate incentive systems often reward achievement of individual targets. Furthermore, structural conflicts across functions are common in large complex organizations, leaving peers to fight for finite resources or at odds over projects and issues. Yet, leaders with the highest potential find ways to deliver on their target while also playing for the team.

Our CEO Genome research uncovered that stronger candidates for leadership positions are more effective at persuading others, including their peers. We also found that high-performing CEOs are more likely than lower performers to treat others with respect (73% of the high-performing versus 59% of low-performing). They may break glass when needed to deliver results but over the longer term they build strong followership and the reputation for doing what’s right for the business.

So, why do these dangerous pandas go unaddressed for so long? The problem is both on the giving and receiving side of feedback. For a manager delivering feedback, these issues seem so personal and almost trivial that it’s hard to raise them directly, especially with a strong performer. It is easier to skirt the problem, especially when it doesn’t hinder current performance. And as a receiver of feedback, we often dismiss pandas as unimportant “nice to haves” or at times contradictory to our values. I should be judged on my performance, not on airtime in a meeting! Unfortunately, as we have seen in our research, avoiding these difficult conversations or not acting on the feedback will damage the careers of talented individuals.

As a manager, your responsibility is to develop your team by delivering candid feedback with caring courage. By dodging it, you are actually doing a disservice to your direct report and to your team as a whole. No matter how uncomfortable, you need to be clear about the feedback. Offer specific examples and describe the impact one’s actions — or inactions — have on the individual’s ability to reach their goals in the current role as well as on his or her upside potential.

As a feedback recipient, don’t be misled by the innocent appearance of a panda. If one appears in your review, ask clarifying questions to get to the root and specifics of what you are doing, as well as how it is impacting your performance and other’s perceptions of your performance and potential. If you are still not getting a straight answer from your manager, engage a third party to provide candid expert feedback. Don’t let the dangerously innocuous pandas maul your career.

Is Your Company Ready to Protect Its Reputation from Deep Fakes?

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After a public outcry over privacy and their inability — or unwillingness — to address misleading content, Facebook, Twitter, and other social media platforms finally appear to be making a real effort to take on fake news. But manipulative posts from perpetrators in Russia or elsewhere may soon be the least of our problems. What looms ahead won’t just impact our elections. It will impact our ability to trust just about anything we see and hear.

The misinformation that people are worried about today, such as made-up news stories or conspiracy theories, is only the first symptoms of what could become a full-blown epidemic. What’s coming are “deep fakes” — realistic forgeries of people appearing to say or do things that never actually happened. This frightening future is a side effect of advances in artificial intelligence that have enabled researchers to manipulate audio and video — even live video.

The end result of this manipulated reality may be that people no longer believe what they hear from a world leader, a celebrity, or a CEO. It could lead to “reality apathy,” when it is so hard to distinguish truth from lies that we stop trying altogether. This means a future in which people believe only what they hear from a small circle of trusted friends or family — more similar to a conflict region than to a modern economy. Try factoring that into your quarterly earnings call or televised speech.

An obvious scenario, one that some companies might find themselves dealing with in the not-too-distant future, is a faked video of their CEO making racist or sexist comments, or bribing a politician. But equally damaging could be a video about, for example, corporate spending.

Imagine an authentic-seeming video of a CEO saying their company will donate $100 million to feed starving children. This surprise announcement — which never actually happened — leaves the company with a stark choice: go ahead with the donation or publicly state that you don’t care that much about starving children after all.

As corporate leaders grapple with the question of how to prove something is (or isn’t) real, they will need to invest in new technology that helps them keep one step ahead of bad actors. And they will have to do it quickly. A company won’t be able to stay ahead of determined, tech-savvy manipulators if it has a yearlong procurement cycle.

One crucial step is for the social media platforms to incorporate real-time forgery detection into all of their products, building out systems that can adapt with improvements in the technology. But that technology is still in its early stages, and as it develops you can be sure that bad actors will be working on ways to defeat it.

It may also be possible to create software that can timestamp video and audio, showing when they were created and how they have been manipulated. But relying on the tech sector to quickly address societal challenges like this without accountability from regulators and users hasn’t worked all that well in the past.

Corporate marketers and communicators, as the people who supply platforms with the money that is their lifeblood, are in a strong position to push for faster action. Last year P&G pulled $140 million in digital ad spend, in part because of brand safety concerns that arose when its ads were placed next to questionable content.

You can bet this got the attention of social media companies. But it worked only because P&G was willing to back up its words with action. Platforms are more likely to take proactive measures if they know that inaction will hurt their profitability. Industry pressure helped push YouTube, for example, to reevaluate its content policies and dramatically increase its investment in human moderation.

Industries often form coalitions to influence the government on regulations affecting their business interests. With some of the biggest tech companies starting to rival governments in their reach and power, the same model could be employed here, using the threat of lost ad revenue. These coalitions may find it helpful to partner with consumer groups and NGOs to amplify their message. Pushing these platforms to take the future of misinformation seriously would be good not only for corporations but also for society at large.

In addition, companies must begin to factor deep fakes and other reality-distortion techniques into their crisis-scenario planning. Reputation protection in this new world will require adding a new layer to a company’s rapid response and communications strategies. Executives must be prepared to communicate the facts quickly and to correct the fictions before they spread too far.

Communicators should make sure they have the right tools in place to deal with a fast-moving manipulated-reality crisis. New companies are forming that use technology, open-source intelligence techniques, and crowdsourcing to quickly discern what’s real and what’s not. The key to uncovering a falsehood may lie in someone using geolocation, or simply their own knowledge, to recognize that a street sign in a faked video isn’t really at that location. As with any crisis, social-media analytics tools are critical when it comes to tracking the spread of misinformation. These tools can help executives see whether a story is gaining traction and identify the most-influential people spreading the misinformation, whether wittingly or unwittingly.

It is crucial that individual companies learn to understand and mitigate their particular risks — but that alone will not protect them. Our information ecosystem is like a game where deceivers have a massive edge; a company may lose even if it “plays” perfectly. That’s why we need to fix the rules. We all must pitch in to support cross-company, cross-industry, and even cross-sector efforts to turn the tide. It will be incumbent on everyone with a stake in a reality-based society to work together to ensure that we can continue to discern fact from fiction.

Under-Management Is the Flip Side of Micromanagement — and It’s a Problem Too

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Micromanagement gets most of the attention, but under-management may be just as big a problem.

This is the term I’ve given to a constellation of behaviors that I’ve seen occurring together often during my 24 years in management: weak performance management, a tendency to avoid conflicts with employees, and generally lackluster accountability. As the name suggests, there’s just not quite enough management being done—and results often suffer as a result. But under-management can often fly under the radar because the managers who have these tendencies aren’t necessarily incompetent; on the contrary, they often know their business well, are good collaborators, and are well-liked.

One HR executive I spoke with about the problem estimated that some 10% to 25% of her company’s managers were under-managing. And I well remember one of my own company’s Human Resource VP’s exclaiming in frustration, “The trouble with our managers is that too often they just don’t manage!”

Take Jamie, a product development manager (he’s not a real person, but a composite of numerous people I’ve known). He knew the technical details of his team’s products well and got along well with other department heads in his division. He was a good communicator—unlike several other product development managers in the division, who were stronger on the technical side than in dealing with human beings—and his team liked working for him. They reported above-average morale, unlike many teams in the company.

But his team struggled to deliver results. For example, on large projects they had persistent trouble meeting deadlines. When this came up with Jamie’s boss and peers during management team meetings, he maintained his team couldn’t be working any harder—though other managers didn’t always agree. When Jamie’s boss or other members of the management team pressed Jamie about members of his team who might possibly be weaker links, Jamie strongly defended them. There are no weak links on my team. In baseball parlance, Jamie was “a player’s manager.”

There are several intertwined causes behind this phenomenon. Too strong a desire to be liked can get in the way of fully productive management because it can make you reluctant to do the things you need to do. Conflict avoidance is a related element of the equation; conflict is inherently stressful and unpleasant, and it’s easy to think that if one can get by with less of it, so much the better!

True, pushing your people and holding them accountable for strong performance won’t win you any popularity contests, and it requires some level of comfort with conflict. But while maintaining positive relationships with your own employees is a good thing, over the long run your priority is to deliver results.

If you think you might be under-managing, here are three tangible steps to take. The good news is that it’s possible to improve one’s performance in these areas; though it takes practice these are primarily issues of will, rather than ability: you need to commit to them first.

Don’t be a conflict-avoider. Let’s start with the handling of conflict. Early in my management career I was fortunate to have a mentor who took me aside and told me straight-out that if I was going to succeed in management, I needed to become more effective in my handling of conflict. I still remember his exact words. He praised my abilities (my knowledge of our business and my work ethic), but added, “Frankly, I don’t know if you want to handle conflict. I don’t know if you have the stomach for it.” I realized that if I was going to be successful in management, this was a problem area and I was going to have to work on it. So I did — diligently. I became highly conscious of conflict and not ducking it. Truth be told I still don’t like dealing with conflict (most people don’t), but I recognized it was a vital part of the management role and over time I became more comfortable with it and competent at it.

View goal-setting as mission-critical. If you’re not delivering the results you need to, which is the risk at the heart of under-management, first make sure the goals your employees need to achieve are well-conceived and clear. Most managers don’t spend nearly enough time on goal setting; too often we approach it as a nettlesome bureaucratic exercise (why is Human Resources torturing me this way, making me fill out these endless forms?). But thoughtful goals that are agreed to by employees can be a manager’s best friend because you can manage to them: they become a roadmap to guide your work with your team all year.

“Is this work the absolute best you can do?” This is a simple but powerful question I learned from a longtime colleague and friend who was a retired U.S. Army colonel, who had picked it up from one of his officers. Asking it when someone hands in an assignment will make them aware that they’re being held accountable. (It’s also a good question to ask yourself if you suspect you are under-managing as an exercise in self-accountability. Is this work the absolute best you can do? Are you doing all you can to set appropriate goals, hold people accountable to them, and deliver the results you need to?)

Ultimately, rising above under-management is the proverbial win-win situation: better for your organization—and for your career.

Using Analytics to Align Sales and Marketing Teams

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Many companies struggle to deliver a consistent and easy buying experience for their customers.

Consider the following scenario: A manager wants to purchase some computer software for her business. She asks an analyst on her team to do an online search for information. The analyst recommends a particular software company’s solution. The manager peruses that company’s website and requests more information by entering data about her needs through a webform. The software company emails relevant materials which the manager reviews before reaching out to an inside salesperson with questions.

But then things begin to break down. The inside salesperson hasn’t seen the webform data, so the manager must repeat much of the information she had already entered. Furthermore, some of the advice the inside salesperson shares contradicts what the manager recalls reading on the website. The manager decides to meet with a field salesperson to get clarity and to work out some details for a quote. Then, just days after receiving the quote, the manager gets an unsolicited email from the software company’s marketing team offering a better deal. The mounting number of inconsistencies and redundancies confuse and frustrate the manager. At the same time, the software company has wasted time and resources on duplicate, uncoordinated, and ineffective marketing and sales outreach.

As customers have begun interacting with sellers through websites, emails, texts, social media posts, print and TV ads, and salespeople, it’s become difficult for companies to synchronize these communications. (The profusion of independent information sources, such as customer reviews and price comparison sites, adds to the confusion.) When it’s time to actually buy, customers may do so via purchasing portals, internet chat reps, call centers, field salespeople, or other sources.

Customers move frequently and unpredictably between these various channels when buying. For simple purchases, they might buy online exclusively. For complex purchases, they might start with online information, then talk with salespeople, and then return to online sources to validate what the salespeople said. The buying process is no longer linear or consistent.

For companies that sell to businesses, meeting the buying needs of today’s customers requires a mindset shift.  Companies need an orchestrator to ensure marketing and sales outreach is well-coordinated and aligned with customer buying needs. In some cases, the orchestrator is a computer system. In other cases, the orchestrator is a person enabled by data and analytics.

Amazon is a prime example of a company using a computer system to effectively orchestrate customer buying. Amazon’s analytics use data to make inferences about what products each customer might buy. The analytics also suggest an automated–yet coordinate–way to reach each customer with the right offer at the right time. For example, Amazon makes customized purchase suggestions on its website. If a customer clicks on a suggestion but doesn’t purchase, Amazon can follow up with a reinforcing email or post on the social media platform the customer uses. Companies are using computer-based orchestration frequently with business customers, especially for smaller accounts and simpler purchases.

For larger accounts and more complex purchases, companies are giving account managers responsibility for orchestrating marketing and sales outreach to customers. In their expanded role, account managers decide what the company should offer each customer, along with the best message timing and delivery channel (e.g. digital message, phone call, personal visit). Account managers are more effective when they are armed with insights from data and analytics.

For example, a telecom company used predictive analytics to help account managers orchestrate outreach to under-performing, high-potential customers. The analytics found “data doubles” for these customers – i.e. similar customers who were buying much more. The company shared insights with account managers about which customers had significant unrealized opportunity and what sales strategies had worked previously for their data doubles. The insights helped account managers offer the right products with the right sales messages, thus increasing sales at under-performing accounts.

In another example, a pharmaceutical company used a computerized suggestion engine to help account managers orchestrate the sharing of prescription drug information with physicians. The company provided physicians with information through various sales team members (e.g. account manager, reimbursement specialist, medical science liaison) and marketing channels (e.g. emails, podcasts, mobile apps, invites to conferences, company website). By examining data about each physician’s situation and preferences, the suggestion engine told account managers which actions, and the timing of those actions, were likely to produce the best results. This allowed account managers to tailor communication to each physician’s needs. For example, an account manager might get a message on his tablet: “Dr. Jones just logged on to the company’s website to investigate drug side effects. Suggest visiting Dr. Jones to discuss her concerns.” During the visit, Dr. Jones asks about drug effectiveness and mentions she hates receiving unsolicited email. The account manager updates Dr. Jones’ profile to stop marketing emails and asks a company medical science liaison to call Dr. Jones to answer her questions. By tracking physician preferences, behaviors and results, and sharing insights with account managers, the company continually improved its relationships with physicians.

More companies and industries are taking on the challenge of orchestrating marketing and sales outreach to align with modern customer buying needs. As the volume, variety, and velocity of business data escalate, analytics (including artificial intelligence) will play an even bigger role in the effort to improve the customer buying experience.

How European Health Care Providers Are Engaging Doctors with New Technologies

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Physician discontent over deteriorating working conditions and growing risks to patient care has risen to alarming levels in European hospitals. To understand physicians’ evolving reality, Bain’s biennial Europe Front Line of Health Care Survey tracks European practitioners’ attitudes, priorities and decision-making power. The findings are based on input from 1,156 physicians across nine specialties and 154 hospital procurement administrators in Germany, France, the UK, and Italy.  Our research shows that a majority of doctors wouldn’t recommend their hospital to family or friends as a place to work or receive care. Citing staffing shortages, budget cuts, aging equipment and inadequate facilities, physicians warn they are unprepared to cope with looming healthcare challenges. Provider organizations have attempted structural changes over the past few years to fix specific problems, but, on the whole, their efforts have fallen short.

When an entire system needs renewal, it’s hard to know where to start. In our experience, providers can create powerful momentum for change and reengage doctors by focusing specifically on technologies that doctors feel improves their ability to deliver care. However, technology alone is insufficient. Getting physician buy-in by assuring that they experience the technology’s benefits is essential.

We see a few leading provider networks in Europe that are starting down this path. They are reengaging physicians by setting out a clear vision to provide exceptional care, innovating at scale in a few core areas and making technology investments that will help them deliver substantial improvements in care delivery. These organizations are targeting technologies that have a proven impact on patient outcomes, efficiency of care delivery, workforce engagement, or population demand management.

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The UK Salford Royal NHS foundation trust is one provider network leading in both frontline engagement and technology deployment. With a reputation as one of the best performing hospital trusts in the UK, it is one of 16 hospitals the NHS has cited as a “global digital exemplar”, a provider delivering superior care efficiently through the use of world-class digital technology.

The management team at the UK’s Salford Royal NHS foundation trust has launched 50 digital projects aimed at improving patient experience and safety, increasing operational efficiency and improving reliability. Many of those investments already have produced positive outcomes for patients, including an electronic assessment tool for detecting delirium which has reduced the average length of a hospital stay for patients by half, IT infrastructure that enables patients to send their wearable data directly to clinicians for real-time monitoring, and an electronic assessment tool that has reduced patients’ venous thromboembolism rate by 20%. Salford’s strategy also has significantly reduced documentation time for staff. Ninety-three percent of clinicians said they were satisfied with the hospital’s electronic patient record services according to a recent survey by KLAS research, compared with an average of 60% among clinicians generally.

Many provider organizations are still at the beginning of the journey. In Spain, Badalona Serveis Assistencials, a local provider outside Barcelona is deploying various technologies to develop a more integrated and effective care model for patients with complex chronic conditions. It has used advanced analytics to build a predictive model of patient populations by risk so that doctors can intervene proactively; it uses fully integrated electronic healthcare records to coordinate care across different care sites, including home, social care and health services; and it uses telemonitoring to keep a close watch on patients’ status at home. To date, the effort has reduced the average length of stay in hospitals, average bed days and emergency visits. Overall, it has improved patient outcomes and reduced the operating costs of clinical services.

In France, four Paris hospitals are part of a trial using machine learning and Big Data to tackle the problem of staffing shortages by forecasting patient visits and admission rates. The project, run by Assistance Publique-Hôpitaux de Paris, the largest hospital system in Europe, combines historical (anonymized) data with external datasets including weather, public holidays and flu patterns, to forecast visits and admission rates for the coming 15 days. The hospital group plans to use the data to ensure adequate staffing levels during peak periods, reduce waiting times and improve quality of care. Although still in development, the forecasting model has proven accurate within a 5% variance for the actual admission rate and management hopes to roll it out eventually across all 44 hospitals.

Europe’s healthcare providers face broad systemic challenges, including rethinking care delivery for a rapidly aging population. Targeted investments in technology that improve patient care and provider efficiency can help enable that shift. The efforts by Salford, Badalona Serveis Assistencials and Assistance Publique-Hôpitaux de Paris highlight the way forward. Setting ambitious goals for improving care and using smart investments in technology can play a vital role in galvanizing broader change — and help address the discontent that so many doctors in Europe face.

How to Help Your Employees Learn from Each Other

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When your team wants to learn a new skill, where do they turn first? Google? YouTube? Their corporate training programs? No. According to a study conducted by our company, Degreed, more workers first turn to their peers (55%)—second only to asking their bosses. Peer-to-peer learning can be a powerful development tool that breaks through some common barriers to skill-building — and it has other benefits as well.

Yet many organizations have yet to create a formal structure for peer-to-peer learning. In a McKinsey survey, Learning & Development officers report that while classroom training, experiential learning, and on-the-job application of skills are now in regular use as learning mechanisms, less than half of organizations have instituted any kind of formal peer-to-peer learning. One in three respondents said their organizations don’t even have any systems in place to share learning among employees.

In the research for our book The Expertise Economy, we found that managers are often reluctant to establish formal peer-to-peer learning primarily because of a perception that experts outside the company are more valuable as teachers than those inside it, and because peer-to-peer programs are spaced out over numerous sessions. In this context, sending employees to a single day of intense training from an outside expert is assumed to be more fruitful.

It isn’t. First, peer-to-peer learning taps into the expertise that already exists in your organization. Think of all the smart people that you hire and surround yourself with every day, and how much could be gained if peers shared their expertise with each other to learn and build new skills.

Peer-to-peer learning is also uniquely well suited to the way we learn. People gain new skills best in any situation that includes all four stages of what we call the “Learning Loop”: gain knowledge; practice by applying that knowledge; get feedback; and reflect on what has been learned. Peer-to-peer learning encompasses all of these.

For example, when Kelly was in charge of learning at LinkedIn, her team created a peer-to-peer learning program designed around the company’s key corporate values. One section of the program focused on difficult conversations; each participant was asked to identify a real-life difficult conversation they needed to have at work (especially one they might be avoiding). They were first taught about difficult conversations (stage 1); next they practiced with each other before holding the conversations in real life (stage 2). One of the participants, John, confronted his employee Mark about his missed deadlines, a pattern which had been negatively affecting the team. The conversation did not go well — John felt awkward, and Mark got defensive. When John shared this experience with his peers in the learning group, they openly shared their views and ideas, and their own experiences of similar situations (stage 3). As everyone in the group — not just John — reflected on what they had learned, they concluded that they had all become more confident and armed with ideas about how to better handle a similar situation in the future (stage 4). Later group members indicated that their real-world difficult conversations indeed had become more productive.

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A learner’s development is dependent on a willingness to make mistakes, challenge ideas, and speak up about concerns — as John and his colleagues did in their group. Unlike some learning methods — like tests or exams, or high-pressure demonstrations of skills — peer-to-peer learning creates a space where the learner can feel safe taking these risks without a sense that their boss is evaluating their performance while they are learning. You’re more likely to have candid conversations about areas you need to develop with a peer than with someone who has power over your career and income. In peer-to-peer learning, the dynamics of hierarchy disappear. And unlike other methods — like classroom lectures or online compliance training — peer-to-peer learning provides a structured opportunity to have these discussions to begin with.

A secondary benefit of peer-to-peer learning is that the format itself helps employees develop management and leadership skills. Group reflection conversations help employees master the difficult skills of giving and accepting honest, constructive feedback. Because feedback flows in both directions, participants in peer-to-peer learning tend to put more time and energy into making sure the feedback they provide is meaningful. They think from the perspective of their peer, consider where each is coming from, and try to get specific about what will be most helpful and constructive. This doesn’t happen as often when a boss delivers one-way feedback to employees. Similarly, peer learning gives employees experience in leadership, handling different points of view, and developing skills such as empathy.

Setting Up a Peer Learning Program

Formal peer-to-peer learning programs can take many forms. As a manager, you can hold your program online or in person. Your program could pair participants in one-to-one sessions, create cohorts working together on real work problems over a few months, or involve weekly sessions in which individuals share the latest knowledge they’ve gained with their peers with plenty of time for discussion and reflection.

To make any peer-to-peer learning program successful for your team, we recommend a few best practices:

Appoint a facilitator. Although the structure of peer learning is horizontal rather than hierarchical, it’s important to have a neutral party who is not the team’s manager facilitate the program to keep in on track. This person — ideally a skilled facilitator — should organize sessions, keep everyone on topic, keep conversations moving forward, and maintain a positive atmosphere for participants to learn, experiment, and ask questions.

Build a safe environment. Peer learning only works when participants feel safe enough to share their thoughts, experiences, and questions. They need to be open and vulnerable enough to accept constructive input, and also have the courage to give honest feedback rather than telling people what they want to hear.

To build a safe environment, set ground rules. Some suggestions: confidentiality must be honored; feedback should be perceived as a generous gesture that should always be met with gratitude; participants should practice empathy, putting themselves in others’ shoes; and participants should never be mocked or embarrassed for expressing themselves in front of their peers.

Focus on real-world situations. Whenever possible, these sessions should focus on genuine problems to solve. People are more likely to participate, learn, and remember new skills if they are learned in the course of addressing a real-life challenge.

Encourage networking. It helps to set up online social networks around learning, organize networking events for people to discuss their area of expertise, and establish learning groups that meet regularly to discuss ideas. Some organizations build company-wide campaigns in an effort to get everyone involved.

With a well-built peer-to-peer learning program in place as a complement to more traditional learning programs, your team will build lasting skills and relationships that will allow them to bring the skills they learn in those programs into their daily work.

Can Netflix Keep Winning? And Why People Are Fleeing Latin America

Youngme Moon, Mihir Desai, and Felix Oberholzer-Gee debate whether Netflix’s success is sustainable, before trying to wrap their heads around the unthinkably high murder rate in Latin America. They also share their After Hours picks for the week.

For interested listeners:

Latin America is the Murder Capital of the World (Wall Street Journal)

You can email Youngme, Mihir, and Felix with your comments and ideas for future episodes at: harvardafterhours@gmail.com .

HBR Presents is a network of podcasts curated by HBR editors, bringing you the best business ideas from the leading minds in management. The views and opinions expressed are solely those of the authors and do not necessarily reflect the official policy or position of Harvard Business Review or its affiliates.

The Fundamentals of Leadership Still Haven’t Changed

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Recently the Chief HR Officer for a healthcare firm asked us to identify the best new framework for leadership that she could use to train and develop a cadre of high potentials. The challenge, she said, was that these managers were highly proficient in their own disciplines such as finance, marketing, research, clinical care, and insurance reimbursement — and had demonstrated that they could manage people in these areas — but she needed them to be “bigger” leaders. What, she asked us, did the newest thinking about leadership development say they needed to learn to lead multiple functions, or influence whole segments of the organization, particularly in the rapidly changing world of healthcare?

Explicit in our HR officer’s question was her assumption that the newest thinking on leadership development must contain something essential. After all, there are hundreds of books written about leadership every year, adding to the thousands of titles already available on Amazon.  There also are new assessment tools based on advancements in brain science, emotional intelligence, and relational modeling; new computer aided algorithms for decision-making; virtual reality simulations; and a host of new experiential programs, online courses, and university certifications. With such a flurry of developments, there must be some useful new ways to think about leadership.

The reality, however, is somewhat different. Yes, the leadership development industry is thriving, and yes there are a lot of new and interesting ideas, some of which may prove to be helpful. But despite many changes in our context — as organizations have become more democratic and networked, for example — in its fundamentals leadership has not changed over the years. It is still about mobilizing people in an organization around common goals to achieve impact, at scale.

This tried and true perspective on leadership was reinforced for us during the past year as we researched and wrote the HBR Leader’s Handbook. We interviewed over forty successful leaders from a variety of organizations (corporate, non-profit, startup), across different industries. We then reviewed several decades worth of articles from the Harvard Business Review to understand the recurring messages from academics and practitioners about what leaders should do. Our conclusion from this research, and from our own years of experience as leadership and organizational advisors, was that the best leaders with the most outsize impact almost always deploy these six classic, fundamental practices:

uniting people around an exciting, aspirational vision;
building a strategy for achieving the vision by making choices about what to do and what not to do;
attracting and developing the best possible talent to implement the strategy;
relentlessly focusing on results in the context of the strategy;
creating ongoing innovation that will help reinvent the vision and strategy; and
“leading yourself”: knowing and growing yourself so that you can most effectively lead others and carry out these practices.

Sure, sometimes the starting point is different, or one of the six areas requires more heavy lifting than another, or the sequence of activities varies. And yes, leaders go about these practices in different ways depending on their personalities and their situations. But the same handful of practices are always present.

For example, when Seraina Macia (one of the leaders we interviewed) joined XL Insurance in 2010 to head their North American Property and Casualty unit, it was a stable, but slow-growth business.  As she learned about the numbers, the organization, and the markets, Macia envisioned that the unit could be transformed into a much faster-growing and more profitable company with a wider range of product offerings. Bringing her team together around this vision, and sharpening it with their help, which is the first fundamental practice, became the focus of her early days with XL.

To translate that vision into action, Macia then challenged her team to triple the level of premiums, without sacrificing underwriting quality, in three years — and asked each of them to quickly develop a strategy for how to make that happen in their product areas, and how to best use underwriting and the other support functions to do it. She then worked with each manager to help them craft these strategies, making choices about how to deploy resources, where to focus, and how fast to proceed.  This is the essence of the second core practice that we heard about in our research.

When some of Macia’s team members struggled to come up with thoughtful strategies, or couldn’t move quickly into action, she gave them tough feedback, pushed them beyond their comfort zones, gave them developmental help as needed, and in some cases replaced them or moved them to other positions. These actions were all in the service of building the best team to implement the strategy, which is practice number three.

This stronger team was then able to respond to Macia’s unrelenting drive for results by quickly testing new ideas, engaging local brokers, expanding target markets, and a host of other specific action-steps, all of which were aimed at focusing on results, which is the fourth practice. As results came in, Macia encouraged the team, to reassess their plans, learn from their experiences, innovate, and continually improve, which exemplifies the fifth practice, innovation. For instance, some of the teams experimented with sending underwriters out to the field to work with brokers so that they would send them business that was more likely to be underwritten by XL, a complete departure from past practices, and one that turned out to be key to the unit’s success.

While taking these actions, Macia also was learning about her own leadership, what worked and what she needed to do differently. Gradually she learned how best to allocate her time, how to build support from other parts of the company, what metrics were most useful, and how to make faster decisions about people, all of which is part of the leading yourself practice.

Most importantly, by putting all six of these practices together, Macia succeeded in doubling the level of profitable premiums in two years and (after she left for another job) seeing her successor reach the original goal of tripling the business the year after.

To move their organizations to the next level, all of the leaders we talked with deployed these practices — practices that are supported by numerous studies and articles, many of them far from new. And even though these leaders were operating in different industries, geographies, and with new technologies and structures, they were still dealing with people who needed to work together to achieve a common goal, which is what leadership has always been about. So when it’s time to think about developing bigger leaders—as our HR executive wanted to do—we believe the secret is not to look for a new framework, but rather to help leaders master the tried and true practices that already exist.

How Children’s Health System of Texas Is Improving Care with Design Thinking

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The potential for improving the quality of healthcare has never been greater. Advances in data analytics give us the ability to look at large populations and precisely segment their needs and new technologies such as tele-medicine give us the capabilities to deliver customized experiences at scale.

But the most powerful drivers of change are not necessarily technological; radical improvements increasingly also come from applying new innovation methodologies like design thinking that focus on developing a deep understanding of patient experiences and invite patients and partners into co-creation processes.

Insight Center



The Future of Health Care
Sponsored by Medtronic

Creating better outcomes at reduced cost.

These methodologies free us from cognitive blinders.  Healthcare professionals often see the patient experience through the lens of their own expertise. They come with a theory about what needs changing, which they assume will improve the system.  That can be helpful, but by not looking at the experience from the patient’s own perspective, they may well not recognize where the system has lost its relevance to patients’ needs.

In order to bridge the gap between what patients need and what the system offers, healthcare professionals must begin by setting their expertise aside. This creates the conditions in which key stakeholders can explore new strategies together.   The co-creation journey involves seven steps:

Step 1: Find the future in the present.

We begin by developing insights into today’s experiences.  Exploratory research using design thinking’s ethnographic tool kit helps define the jobs that key stakeholders, patients, caregivers and partners, want or need done.

A partnership between the Business Innovation Factory and the Children’s Health System of Texas provides a good example. As its first step in addressing a decline in children’s health in North Texas, Children’s identified a number of families to study, working through what BIF called “trusted agents” such as pastors and neighbors.

The agents interviewed the patients and their families to gain a deeper understanding of patients’ lives and to gauge their “say-do” divide (the difference between what people say they will do and what they actually do). The team used journaling, journey mapping, shadowing and collage making to increase patients’ ability to reflect on their own perceptions and experiences. The following conclusions emerged:

If Children’s Health wanted to improve kids’ health, it needed to focus on families, not just the kids.
What families wanted was a better life, not better health. If parents needed to feed their kids fast food to get to work on time, they would do so.
Families also wanted to feel in control of their health journey. This was difficult in a system where things were done to and for people, not with them.
Families listened to those they knew and trusted: teachers, pastors, YMCA staff, and other families who had been through similar experiences. 

Step 2: Identify opportunity spaces

The findings emerging from step 1 translate into a set of opportunity spaces, promising areas in which to look for new solutions.  At Children’s, each such space posed a different question:

How might Children’s create more convenient sources of care? Because the emergency department was often seen as a family’s most convenient source of care, making alternatives more convenient was another opportunity space, involving solutions built on leveraging trusted information sources within the community and on improvements in the attractiveness of nonemergency care.
How might Children’s make children more responsible?  Because it is difficult for kids to see the link between their health and the choices they make, nudging them towards awareness and accountability was critical, suggesting solutions that made healthy goals more meaningful to children and provide frequent real-time feedback.
How might Children’s deliver care beyond the child? Because families can play such a critical role in children’s health, moving from a place that ignored the whole context of a child’s environment to one of acknowledging and treating root causes and built a family network that was a positive influence was key (suggesting solutions that equipped children with life skills to make healthier choices as they grow).
How might Children’s inspire, guide, and support other change agents? Because families cannot always be relied on to make and encourage good choices, reaching beyond them offered a third opportunity space, suggesting solutions that provide mentors and offer children opportunities to share their stories and get positive reinforcement.

Helping the staff at Children’s Health understand and own these opportunity spaces was critical. By listening to the children and their families telling the story of their experiences, staff could move from judging these families to co-imagining possibilities.

Step 3: Identify organizational capability gaps

Once they understood the main features of the future they wanted to create, the Children’s team began identifying, unbundling, and realigning their capabilities in order to get there. Capabilities are made up of people, processes, and technologies.

Once a key capability was identified, staff could engage in conversation about how to use that capability differently, which allowed the owners of that capability an opportunity to identify with the new future. For example, Children’s has a strong care management capability, which is largely comprised of a team of people who help patients manage their medical care, medications, etc. As Children’s began to imagine a well-being model that emphasized patient agency, it began to imagine how might it repurpose that team to focus less on managing care and more on activating agency.

It allocated a portion of the team’s time to serving as “coaches” and a new protocol was developed to help the team understand the differences in the role that they would be playing. In an agile and experimental process, the team participated in reimagining this new role, critiqued it and iterated on it, helping them feel that they were leading change rather than being subject to it.

Step 4: Test critical assumptions

Before an organization actually applies a new strategy, it must test the critical assumptions underlying it. To do this, the Children’s Health team designed, with patients, two programs.

The first was called “Your Best You” and involved self-discovery and education for self-knowledge through a six-week summer camp that aimed to activate kids’ sense of self by marrying hip hop education and Design Thinking.  This helped the kids to figure out who they were, what they wanted to do in this world, and who could help them achieve their goals.

The second program (“What’s Cookin’, Dallas?”) engaged family members in curating a food and nutritional experience for other families in their communities. This measured people’s sense of connection and belonging, as well as their sense of agency and control.

Step 5: Co-create the new model with key partners

The opportunity spaces Children’s identified pointed toward a transformational business model that was wellbeing (versus sickness) centered, citizen (versus physician) driven, prevention (versus intervention) focused, partnership based, and community supported.

In four opening sessions, the team identified the key institutions, resources, and people who might offer valuable local knowledge for designing the new business model.  They then invited these partners to a participatory design studio focused on a single question: How might we design a new system that connects convenient clinical care with self-managed well-being?

The new healthcare delivery model that Children’s came up with from these processes consists of a series of twelve activities, from generating family awareness of the child’s needs and the available resources, through to the creation of a wellbeing plan, and culminating in sharing and comparing treatment experiences.  For each stage they identified the people who needed to be involved, the medium of the meeting (face-to-face/phone/e-mail/online), and the goals of the interaction, both functional and emotional.  For instance, in assessing the barriers getting in the way of health needs the professionals interacting with the children and families would have a functional goal of raising the children’s and families’ understanding of those issues and an emotional goal of making sure that the children and family felt heard.

Step 6: Find sustainable funding for continued experimentation

In a world still dominated by fee for service, it is often a challenge to sustainably fund new business models.  Children’s identified a way to combine private and public sources of funding.   It could use resources from its licensed insurance company (funded by the savings from enrollees’ utilizing less expensive medical care) coupled with funding from the Texas Medicaid Section 1115 Waiver program, plus philanthropy and grants. This package would give them five years to pilot the new approach.

Children’s recruited 15 families for 16 weeks to engage in a change process centered on family meals where families met the supportive coaches who would act as their “navigators” to access the wide range of community services that could improve children’s wellbeing. Families did an exercise where they were asked what the one thing was that they wanted to address. Navigators contracted with relevant agencies to deliver this service (for example, providing a gym) and checked in frequently to assess and guide progress.

  Step 7: Measure progress

Children’s developed a metric of family wellbeing, based on five key dimensions: family members’ sense of control over their healthcare, their understanding of their wellness goals, their sense of self, the quality of their access to information and knowledge, and the quality of the community support system. The test was administered both before and after the pilot, as was the family’s adherence to the model. At the end of the program these metrics were then correlated to observed changes in health management behavior (for example, compliance with prescriptions).

Children’s observed that the pilot engaged people in their wellbeing. With a greater sense of control in their lives, people also started taking greater control in their health management by, for example, regulating their blood pressure and following through on smoking cessation programs.  Following the pilot, the program was rolled out as a core health offering through its HMO.  The program is currently being rolled out with other populations.

New strategies that offer dramatic increases in value creation for stakeholders, and are executable within the constraints of today’s reality, emerge most readily from the kind of bottom-up, patient-centered approach that the Children’s story illustrates. This approach involves combining a deep understanding of the realities of patients’ lives with a critical assessment of organizational delivery capabilities to create a real conversation about marrying the two.

The Hidden Costs of Initial Coin Offerings

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In recent years, much has been written about how the Blockchain is poised to transform traditional industries such as banking, real estate, and healthcare. More recently, it has gained attention as a way to finance new ventures, through what is known as an Initial Coin Offering (ICO). Less noticed, though, is ICOs appear almost antithetical to the standard approach to financing a risky venture.

In fact, ICOs have upended the conventional pattern of staged experimentation and fundraising. Blockchain startups raised over $5 billion in 2017 through ICOs and over $12 billion through the first three quarters of 2018. The average amount of capital raised by a Blockchain project through an ICO in 2017 was $13 million; through the third quarter of 2018 it was $25 million. These ICOs are nearly always held when a project is at an immature stage of development akin to a seed stage startup — when it is testing hypotheses around its consumer value proposition and forming a founding team.

Blockbuster capital raises will always occur in unusual situations (e.g., EOS raising over $4 billion in their ICO and Telegram raising nearly $2 billion in a private financing), but if the average amount of capital raised by a Blockchain project is 10-20x that of a normal startup at an equivalent stage of development, while the failure rate remains roughly similar to staged financing startups, then either investors are foolishly leaping into a dangerous bubble or there are more profound differences in early stage financing at play.

3 Defenses of Large ICOs

Some observers have pointed out that blockchain projects may have an inherent incentive and strategic reason to be more aggressive in raising capital earlier in the experimentation process. Those benefits fall into three categories:

To jumpstart network effects that provide a first-mover advantage:

Many of the projects being built using blockchain technology are “protocols” that govern the interactions between users in a decentralized autonomous network. In this framing, the native tokens issued through the ICO are the means through which users transact between a decentralized network of participants without the need for any central organization or platform.

Just as with other such platforms or marketplaces that connect users, the value of the decentralized network is a function of the users who choose to transact using the given protocol.  By making the tokens issued through the ICO widely available and liquid (and by using the cash raised to finance further development of activity on the network), projects can rapidly channel developer attention towards their protocols. For example, Sia is a decentralized storage platform on the blockchain, leveraging underutilized hard drive capacity around the world. The more hosts offer up their storage capacity, the more users will be attracted. The more users that come online to store files, the more hosts will be attracted. If the users and the hosts are both owners of the Sia tokens, which appreciate with greater usage of the network, they have an even greater incentive to see the network grow. This so-called “token network effect” creates a positive feedback loop, making it more valuable to be transacting using a given protocol when many others are also transacting through it.

To generate publicity that allows them to solicit broad feedback on their beta product

The publicity around the upcoming launch of an ICO that plans to raise several tens or even hundreds of million dollars is a related way to drive developer interest and engagement. This focused attention from developers has the added benefit of crowdsourcing feedback on the beta version of the project. When the decentralized exchange protocol 0x raised $24 million in their ICO in the middle of 2017, a few months after releasing an early-stage version of the software, it created an enormous amount of developer attention. By completing its ICO shortly after going live with its over-the-counter (OTC) platform for exchange tokens, developers and investors were attracted to testing out the protocol. Today, 0x is widely considered one of the leading decentralized exchange protocols with numerous other applications built on top of its platform. 

To create a decentralized governance structure that is inherently beneficial to the nature of the project

Blockchain projects that can achieve a fully decentralized architecture and governance are inherently more valuable because they are more resistant to attacks and collusion. As Ethereum founder Vitalik Buterin notes, “Once you adopt a richer economic model…decentralization becomes more important.” But achieving decentralization requires a meaningful investment in capital in order to attract a distributed network of users and network managers that maintain the decentralized ledgers (or nodes). A larger injection of upfront capital is more likely to create the incentives for autonomous agents to participate in the creation of the blockchain network, thereby making the network that much more valuable.

The Downside to Large ICOs

In some cases, these benefits are real. However, there are very real potential downsides to a large, public fundraising through an ICO. To understand the downsides and why they’re important, though, it helps to understand why staged venture-capital financing has been so successful in the first place.

One of the fundamental elements of commercializing new ventures is the high failure rate they face. Failures are not necessarily due to bad execution; it is just that most new ideas fail, a few become incredibly successful and it is virtually impossible to know which outcome it will be without undertaking the hard work to develop and commercialize an idea. Indeed, over 60% of startups backed by venture capitalists fail and evidence points to the most successful VCs having bigger “hits” as opposed to fewer failures.

A solution to this challenge is multi-stage financing, which allows entrepreneurs and investors to learn about the ultimate viability of an idea through a sequence of investments over time. Multi-stage financing is usually seen as benefiting the investors: It allows them to commit only a fraction of the money upfront, preserving the option to abandon the investment if the idea does not pan out, but allowing them to reinvest if things continue to go well.

What is often less appreciated is that this methodology is equally valuable for entrepreneurs. For the entrepreneur, the earliest money invested into a venture, which is raised when uncertainty is highest, is the most expensive. By raising only a small amount of money initially and de-risking the venture through a series of structured experiments, entrepreneurs who succeed raise subsequent capital at higher prices and are able to retain a higher share of the venture they have built — never mind avoid wasting years of their lives fruitlessly pursuing bad ideas.

This approach to structured experimentation from the entrepreneur’s perspective, popularized by Eric Ries’ The Lean Startup with concrete steps for how to de-risk the venture in the most capital efficient way, has been widely embraced as the gold standard for how to approach the commercialization of radical new ideas. From Boston to Beijing to Bangalore, entrepreneurs and investors rattle off the importance of designing focused experiments to test hypotheses in a capital-efficient fashion in order to achieve product-market fit.  Moreover, as the cost of experimentation has fallen in software (due to the cloud, open source tools, reusable code components and global distribution platforms), hardware (due to rapid prototyping, 3D printing, improved design and modeling software) and biotech (due to technological advances in gene sequencing and editing) and across-the board increases in computational power, modeling tools and big data techniques, so has there been a massive explosion of experimentation in a broad range of industries.

How ICOs Constrain

ICOs substantially limit the benefits associated with such staged experimentation, for three reasons:

Architecture

One of the benefits of blockchain technology is that it is immune to centralized parties making changes of their own accord.  But this also implies that the software protocol at the time of the ICO needs to embed — as much as the project’s creators can — the set of rules that will govern the protocol forever.

It is hard for the project’s creators to fully anticipate the technological and incentive issues that will arise from a given protocol, and being able to learn from the way in which users engage can have a consequential effect on the ultimate usability and quality of the platform.  An ICO “bakes in” the protocol early in the life of the project and makes it hard to adjust architecture to enhance performance and capabilities.

Governance

ICOs cede control of decision making to the community. In the early stages of a venture, centralization can be very powerful as it allows for speed, focus and collaborative effort towards one direction.  Centralized decisions can be valuable when testing a particular idea and deciding when to abandon, pivot or double down on the effort.  Once the project has an ICO, governance becomes decentralized, slowing down decision-making and reducing flexibility.

Value

While some entrepreneurs believe that selling tokens is different from selling equity in that it is “non-dilutive” — they don’t give up stock in the company — there remains substantial risk that the protocol will not succeed. When you’re raising money, there is no free lunch. As the markets become more sophisticated, the price at which the ICO happens will reflect this risk and the price of the token will appreciate as the risk is mitigated over time.  Selling tokens early therefore has implications for the amount of value that is captured by the entrepreneur who creates the protocol — potentially leaving substantial “value on the table” for raising capital when the risk is so high.  This dynamic is no different from the dilution cost faced by an entrepreneur raising a substantial money at the earliest stages as opposed to raising a small amount of this expensive capita, de-risking, and raising further funding once the odds of success have improved.  For example, Ethereum’s original crowdsale in the summer of 2014 raised $18 million. Today, Ethereum’s market capitalization is $24 billion.

In addition to these constraints on experimentation, there is a another cost to ICOs:

Exposing Strategic Roadmap to Competition

Many early stage ventures start off in “stealth mode” to prevent their idea from being widely accessible and among the reasons firms have taken advantage of the abundance of growth capital to remain private much longer (e.g., Uber, Airbnb, WeWork) is that it allows them to only selectively disclose confidential information that can be important for strategic reasons to not be available to competitors. An ICO exposes a startups strategic roadmap and, in many cases, actual software code to the public, allowing competitors to learn and adopt elements of it into their own protocols.

In summary, while there are particular benefits of ‘going public’ early through an ICO, there are also a number of potential costs.  Entrepreneurs, investors, and managers need to understand the full implications and risks of having a large ICO early and seek ways to mitigate unintended consequences while taking advantage of the inherent benefits. For example:

Complete a few rounds of more traditional staged equity financings in advance of an ICO.
Wait to expose the actual software code and detailed design as long as possible.
Use a subset of your community to enhance feedback and speed up experimental cycle time (e.g., private briefings of product road maps).
Begin with a more centralized governance structure (e.g., NEO choosing to launch with seven consensus nodes, growing to over 1000 over time) and then migrate the governance structure to a more decentralized one over time.
Consider the ICO more conceptually equivalent to the firm’s “IPO” — executed at the moment in time when the idea has become mature and is ready to be widely held and governed in a more decentralized manner.

Disclosure: One of the authors, Ramana Nanda, is a board director at Dunya Labs, a blockchain startup. The other, Jeffrey Bussgang, is an investor in and board member of numerous blockchain startups as part of his role as a general partner at Flybridge Capital Partners.