Microlearning: 5 Reasons Your Company Should Consider It

Hr Bartender - Thu, 11/08/2018 - 02:57

There are many different types of learning: social learning, mobile learning, and elearning are just a few. A relatively new type of learning that’s attracting attention is microlearning. Think of it as small learning units or bite sized pieces of content.

We use microlearning on a regular basis – we just don’t call it microlearning. Here’s an example. I recently wanted to roast a chicken and, to prepare the chicken, I wanted to truss it. But I didn’t know how. So I went on YouTube, found a two-minute video and viola! I knew how to truss a chicken. People are using short videos to learn all the time.

Which is exactly why organizations might want to consider adding microlearning to their offerings. Here are a few things to consider when discussing microlearning as part of your current learning strategy:

  1. It’s easy to produce. Please notice I didn’t say cheap. Although by definition, microlearning would be shorter than standard training and therefore should be cost effective to produce, it’s possible an organization would have more microlearning options available. That being said, I can see microlearning topics being less complex to design and implement than, let’s say, a traditional elearning project.
  1. It’s flexible. Microlearning can be classified as “on demand” if participants can access it whenever and wherever they wish. It could also be called “just-in-time” if it’s used to refresh/remind/teach someone something immediately before they need it. For example, a manager may want to review the steps of counseling an employee right before meeting with them.
  1. It fits today’s technology. One of my mantras is making stuff “easy to buy and easy to use.” Meaning that people who are trying to engage with the organization shouldn’t get the run-around. Because microlearning is focused on a single concept, it can be created using a simplistic process, it can be easy for the company to share, and easy for employees to view.
  1. It can complement your existing programs. I’ve already mentioned microlearning being able to provide a refresher or reminder. It can do that as a follow-up to a traditional classroom learning experience. Instead of searching for the paper participant guide, an employee can search for the microlearning session. It can provide a solution in a moment of need.
  1. It could be a coaching tool. I think of coaching as being able to help someone reach their goals. Part of helping someone could be sharing with them resources that will improve their skills and knowledge. Managers could use microlearning as part of their employee coaching toolbox. When an employee is stuck and needs some assistance, a manager could recommend microlearning sessions.

There are so many different ways we can learn. That’s a good thing because participants can find a learning method that they connect with. I also understand it’s difficult from a corporate learning perspective because how do you justify the time and resources to create all these different learning methods.

The new learning methods emerging right now – concepts like microlearning – have tremendous flexibility and can bring us a return on investment in more ways than one. Something that traditional classroom training might not be able to do. It doesn’t mean ditch classroom training – it means give microlearning a try.

P.S. I’m very excited to be facilitating a virtual seminar for the Society for Human Resource Management (SHRM) on L&D: Developing Organizational Talent. We’ll be talking about how to design learning initiatives. Details about the learning objectives can be found on the SHRM website. I hope you can join us.

Image captured by Sharlyn Lauby at the 34th Street Graffiti Wall in Gainesville, FL

The post Microlearning: 5 Reasons Your Company Should Consider It appeared first on hr bartender.

Categories: Blogs

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

Harvard business - Wed, 11/07/2018 - 15:12

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.

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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.

Categories: Blogs

Podcast: After Hours

Harvard business - Wed, 11/07/2018 - 12:45

HBR Presents After Hours Harvard professors discuss news at the crossroads of business and culture.
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Latest Episodes Season 2 – Episode 4 Can Netflix Keep Winning? And Why People Are Fleeing Latin America Youngme, Mihir, and Felix 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.Read more Download this podcast

Season 2 – Episode 3 How Bad is Airline Service, Really? And Other Customer Service Complaints Youngme and Mihir welcome their colleague Ryan Buell to discuss whether airlines deserve their reputation for terrible customer service. They also share other customer service pet peeves, as well as their personal “Customer Experience Picks.”Read more Download this podcast

Season 2 – Episode 2 Is Retail Dying? Plus, How Are Companies Spending their Tax Cuts? Youngme, Mihir, and Felix discuss whether the “retailpocalypse” is real, try to figure out how companies are spending their Trump tax cuts, debate whether share buybacks are a good thing or a bad thing, and offer their picks for the week.Read more Download this podcast

Season 2 – Episode 1 Debating Minimum Wage, and Reflections on a Year of #MeToo Youngme, Mihir, and Felix are back with Season 2 of After Hours! In this episode, they debate whether the federal minimum wage should be raised, offer their personal reflections on a year of the #MeToo movement, and share their picks for the week.Read more Download this podcast

Season 1 – Episode 20 New Media and Predictive Policing In this episode, hosts Felix Oberholzer-Gee and Mihir Desai explore the prospects for media outlets like Vice and Buzzfeed, discuss their thoughts on predictive policing, and offer their After Hours picks for the week.Read more Download this podcast

Season 1 – Episode 19 Trade and Soccer In this episode, hosts Mihir Desai and Felix Oberholzer-Gee discuss trade, soccer, offer their After Hours picks.Read more Download this podcast

Season 1 – Episode 18 Food, food, and more food! In this light-hearted episode taped a couple of weeks ago, Youngme, Mihir and Felix discuss the #eatclean movement, their most/least favorite food trends, and offer their After Hours picks for the week.Read more Download this podcast

Season 1 – Episode 17 The #MeToo Movement and Its Impact on Business (Live) In this LIVE! episode taped in front of an audience of Harvard Business School alumni, Mihir and Youngme discuss the #MeToo Movement and its impact on business.Read more Download this podcast

Season 1 – Episode 16 Is the Job of the Presidency Too Big? Plus, Vaping Among Teens In this episode, Youngme, Felix and Mihir debate whether the job of the presidency is too big even for the most competent of executives; discuss whether the vaping trend among teenagers should have us worried; and offer their After Hours picks for the week.Read more Download this podcast

Season 1 – Episode 15 Brainstorming Gun Control Ideas, and the Affordable Housing Dilemma In this episode, Youngme, Mihir and Felix brainstorm out-of-the-box ideas for gun control; discuss whether cities like Boston should be trying to attract companies like Amazon despite the affordable housing crunch created; and offer their After Hours picks for the week.Read more Download this podcast

Season 1 – Episode 14 A Conversation with Teens In this special episode, Youngme asks three teenagers (including her own son) a set of 10 random questions that address everything from how they think about social media, to bullying in high schools, to how optimistic they are about the future.Read more Download this podcast

Season 1 – Episode 13 Antitrust and Big Tech, and Is Corporate Lobbying A Good or Bad Thing? In this episode, Youngme, Mihir and Felix discuss antitrust and whether we should be concerned about the size of the big tech companies; debate the propriety of corporate lobbying; and offer their After Hours Picks for the week.Read more Download this podcast

Season 1 – Episode 12 Why Management Practice Matters In this episode, Mihir sits down with HBS economist Rafaella Sadun, who has dug deep into why and how management practices matter with award-winning large-sample empirical work. Rafaella discusses the problems and promise of family ownership, why Americans do IT better, the secrets of her productive partnership and how she came to economics, and her recommendation for a biography of a pioneering female economist.Read more Download this podcast

Season 1 – Episode 11 The Rise of Voice Assistants like Amazon Echo, and How to Punish Wells Fargo In this episode, Youngme, Felix, and Mihir discuss why voice assistants like Amazon Echo and Google Home are all the rage; debate how to punish Wells Fargo for criminal wrongdoing; and offer their After Hours picks for the week.Read more Download this podcast

Season 1 – Episode 10 The Future of Newspapers, and Debating Big Tech In this episode, Youngme, Felix, and Mihir discuss whether there’s a market for a Netflix for News; debate the future of newspapers like The New York Times; argue about which Big Tech company (Apple, Alphabet, Amazon, Facebook) is most and least vulnerable; and offer their After Hours picks for the week.Read more Download this podcast

Season 1 – Episode 9 Why They Do It: White Collar Criminals Youngme Moon interviews Eugene Soltes, who talks about “Why They Do It: Inside the Mind of the White Collar Criminal.” Among other things, Eugene discusses his unique relationship with Bernie Madoff, the motivations behind white collar crime, how firms can prevent such crimes from occurring, and his most memorable conversations with criminals he has interviewed. Eugene also shares an After Hours recommendation.
Read more Download this podcast

Season 1 – Episode 8 The Gender Wage Gap, and Debating the Benefits of Retail Medicine In this episode, Youngme, Felix, and Mihir debate what it would take to close the gender wage gap; discuss whether retailers like Walmart and CVS entering the medical care space is good or bad for consumers; and share their After Hours picks for the week.
Read more Download this podcast

Season 1 – Episode 7 Zuckerberg Faces Congress, and the Plight of the Post Office In this episode, Youngme, Felix, and Mihir give their quick takes on Mark Zuckerberg’s appearance before Congress; discuss the plight of the U.S. Post Office; and share their picks for the week.Read more Download this podcast

Season 1 – Episode 6 Trump’s Trade War, and the Fate of Tesla In this episode, Youngme, Felix, and Mihir vent about trade deficits and potential tariffs against China; they also debate the future of Tesla. Plus, their After Hours picks for the week.Read more Download this podcast

Season 1 – Episode 5 Fixing the Culture at Uber In this episode, Youngme talks to Professor Frances Frei, who was hired by Uber last year to help rebuild a broken culture. Frances describes how toxic the culture at Uber actually was and how she dealt with difficult work scenarios. She also talks about what should be done about “bad people doing bad things” and the link between strategy and culture. Plus, she gives a behind-the-scenes look at preparing for her TED talk.Read more Download this podcast

Season 1 – Episode 4 How Money Can Buy Happiness In this episode, Youngme talks to her friend and colleague, Professor Mike Norton, about how to spend money to create happiness. Mike’s tips include spending money on experiences rather than on “stuff,” “buying time,” and investing in others. Youngme adds a few tips of her own.Read more Download this podcast

Season 1 – Episode 3 Debating Universal Basic Income, plus Google and the Right to be Forgotten In this episode, Youngme, Mihir, and Felix debate the idea of a Universal Basic Income; discuss Google and the Right to be Forgotten; and offer their After Hours picks for the week.Read more Download this podcast

Season 1 – Episode 2 Making Sense of Online Reviews, Our Best/Worst Service Experiences, plus Debating the Future of Spotify In this episode, Youngme, Mihir, and Felix try to make sense of online reviews, dish about their best/worst service experiences, and offer their thoughts on Spotify. Plus, their After Hours recommendations for the week.Read more Download this podcast

Season 1 – Episode 1 The #NeverAgain movement, Facebook and the Russian Influence Campaign, Should Pornography Be Banned, and Oscar Picks In this pilot episode, Youngme, Mihir, and Felix discuss the NRA and whether the #NeverAgain movement has a chance; disagree about Facebook and the Russian influence campaign; and debate the idea of banning pornography. Plus, they offer their After Hours recommendations for the week and reveal what movies they’re rooting for (and against) at this year’s Oscars.Read more Download this podcast

Season 1 – Trailer Introducing After Hours Listen in as Harvard Business School faculty discuss hot topics at the intersection of business and society.Read more Download this podcast

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.

About the Hosts Youngme Moon is the Donald K. David Professor of Business Administration at Harvard Business School. She sits on the Board of Directors of Unilever, Rakuten, and Warby Parker. She is the author of the bestseller, Different. Mihir A. Desai is the Mizuho Financial Group Professor of Finance at Harvard Business School and a Professor of Law at Harvard Law School. His research has been cited in The Economist, BusinessWeek, and The New York Times. He is the author of The Wisdom of Finance. Felix Oberholzer-Gee is the Andreas Andresen Professor of Business Administration in the Strategy Unit at Harvard Business School. His work has been profiled by media outlets around the world, including The New York Times, The Financial Times, Le Figaro, Neue Zürcher Zeitung, and The Straits Times. More HBR Podcasts HBR IdeaCast A weekly podcast featuring the leading thinkers in business and management. Dear HBR: The advice show for workplace dilemmas. We take your questions and offer a better way forward. Women at Work Conversations about the workplace, and the women in it.

Categories: Blogs

The Fundamentals of Leadership Still Haven’t Changed

Harvard business - Wed, 11/07/2018 - 10:00
Gary S Chapman/Getty Images

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:

  1. uniting people around an exciting, aspirational vision;
  2. building a strategy for achieving the vision by making choices about what to do and what not to do;
  3. attracting and developing the best possible talent to implement the strategy;
  4. relentlessly focusing on results in the context of the strategy;
  5. creating ongoing innovation that will help reinvent the vision and strategy; and
  6. “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.

Categories: Blogs

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

Harvard business - Wed, 11/07/2018 - 09:00
Hero Images/Getty Images

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

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:

  1. If Children’s Health wanted to improve kids’ health, it needed to focus on families, not just the kids.
  2. 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.
  3. 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.
  4. 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:

  1. 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.
  2. 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.
  3. 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).
  4. 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.

Categories: Blogs

Who Will Lead Us Tomorrow?

Leadershipnow - Wed, 11/07/2018 - 08:54

WE ARE RAISING TODAY, the men and women who will lead us tomorrow. It is a responsibility that should not be taken lightly. It should be done with forethought and with a consideration of the kind of world we hope they and we will live in when it’s their turn to lead.

Developing leaders places a huge responsibility on us today that goes beyond telling those future leaders what we think. To develop leaders, we must not only envision the leaders we want tomorrow, but we must behave in the manner of the leaders we want to see.

We may not like the leadership or lack of it that we see today, but if our reaction to anything we don’t like is anger, outrage, hatred, and vicious rhetoric, we are endorsing those values by way of example. Unwittingly, we perpetuate hatred, outrage, and vulgarity in the leaders of tomorrow. They learn to lead by watching us “lead.”

Martin Luther King succeeded because he calmly but passionately painted a picture of a world that appealed to our morality. He shared a positive idea to replace a negative idea without attacking other people. His example had moral weight. He was silenced by hatred. Hatred and anger is an idea without a reason—it’s unreasonable—a rudderless opinion with no foundation.

We must be the leaders we want to see developed in the generations that follow us. If you want leaders who listen, who are understanding, compassionate, civil, and respectful, then we must display those values in our dealings with what we see happening around us. If not, we are the problem. If we want others to respect us and listen to us, we must respectfully listen to them. We talk when we should be listening.

If we believe people should be respectful of each other, then we must be those people. Returning in kind is tempting and sometimes funny, but it does nothing but add to the discord we see around us. Real leaders resist the temptation and rise above it. Our response should be one that is conscious and empathetic of the other person's frustration and often misplaced angst. To do anything else only adds to the destructive division we see today.

Real leaders connect, they don’t divide. They focus on similarities, not differences. We often think that if I don’t yell, I won’t be heard, but we aren’t heard because we are yelling. The most strident voice is not the leader. Harsh words do not connect with others. “Blood in the streets” is not a mature response to disagreement.

When we become the leaders we should be, those that follow will learn to lead the way they should. As we learn and grow, those around us will learn and grow. We are modeling now the kind of leadership we will have in the future.

American poet Edwin Markham’s poem captures the need for us to grow into the leaders we want others to be:

We are all blind until we see
—That in the human plan
Nothing is worth the making if
—It does not make the man.

Why build these cities glorious
—If man unbuilded goes?
In vain we build the work, unless
—The builder also grows.

If we want our children to be intentional about their lives, we must too be intentional about ours with the end in mind—with the consequences of our personal behavior in mind. Meaningful lives are built; they don’t just happen. If we want them to be adults, we must act like adults. We are shaping the character of future leaders today. We must resolve to be the leaders we wish to see.

What will our future leaders be like? Who will lead us tomorrow? What legacy are we leaving for our children? We only need to look at ourselves.

* * *
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Categories: Blogs

What We Can Learn About the Economics of Discrimination from a Chilling Study of 1930s Germany

Harvard business - Wed, 11/07/2018 - 08:49
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Large-scale, government-directed discrimination against a group of people is extremely damaging to those being targeted. It also permeates every aspect of society, including business. For example, talented people are often excluded from leadership positions if they belong to the group that faces discrimination. What are the costs of this, beyond stifling or ending the careers of thousands of people? Do corporations become less profitable when they adopt discriminatory attitudes and exclude highly qualified individuals from leadership roles? And how much do entire economies suffer when governments enact discriminatory policies against certain groups?

Answering these questions is crucial if we want to better understand two types of government policies: those that encourage members of discriminated-against groups to rise to leadership positions, and those that actively prevent them from doing so. The latter type of government policy in particular is reflected in current events and global history. Here are just a few examples: The travel ban on citizens of seven Muslim-majority countries, which has raised fears among U.S. corporations (including Amazon, Nike, and MasterCard) that increasing discrimination will leave them unable to recruit, retain, and develop talent. In Turkey, several thousand executives who follow the cleric Fethullah Gulen have been arrested or have fled overseas since 2016, fueling concerns of an economic collapse. The U.S. government gave in to “race prejudice” and forcibly interred Japanese-Americans during World War II. And in 17 th century France, the entrepreneurial Huguenots had to flee due to religious persecution.

Despite the importance of the issue, we currently have little evidence on how costly discrimination against highly qualified individuals in leading positions can be. Our recent study breaks new ground by measuring the economic losses caused by discrimination. Specifically, we analyze discrimination against senior managers with Jewish origins in Nazi Germany. Using data on individual managers and corporations, we learned more about how the stock prices and the profitability of firms evolved when Jewish managers were removed from the German economy due to rising antisemitism.

First, we needed to understand how the makeup of managers in Germany changed over the 1920s and ‘30s. We collected new data on almost 30,000 manager positions in German firms listed on the Berlin Stock Exchange. The data include managers with no Jewish ancestry, managers who worked at companies commonly perceived as Jewish, and managers at companies that weren’t perceived as Jewish, but happened to employ managers of Jewish origin (examples include Allianz, BMW, Daimler-Benz, and I.G. Farben).

We found that managers of Jewish origin (either practicing Jews or Christians with a Jewish ancestor) held around 15% of senior management positions in 1928 and 1932. When the Nazis came to power and Adolf Hitler became chancellor on January 30, 1933, however, discrimination against Jews became commonplace in Germany. Many firms voluntarily dismissed managers of Jewish origin or were coerced into removing them by Nazi officials. Deutsche Bank, for example, forced CEO Oscar Wassermann and executive board member Theodor Frank to resign their positions by June 1, 1933. By 1938, virtually no Jewish managers remained in firms listed in Berlin.


We then compared firms with Jewish managers to other firms that had not employed any managers of Jewish origin and, therefore, remained unscathed by the removal of these managers due to the Nazi ideology. We controlled for a number of factors that may have affected firm stock prices, including connections to the Nazi party; the financial reporting period; and the firm size, age, and industry.

We found that losing the Jewish managers changed the observable characteristics of senior managers at firms that had employed Jewish managers in 1932. Specifically, the number of managers with managerial experience, university degrees, and the total number of connections to other firms (measured by seats on other supervisory boards) fell significantly. These effects persisted at least until the end of our sample period on manager characteristics in 1938. These results show that the firms that had lost Jewish managers did not replace them with managers of similar characteristics. A likely explanation is that there were very few such highly qualified managers, so the firms were unable to find adequate replacements.

Next, we show that the stock prices of firms with Jewish managers fell sharply after the Nazis grabbed power in 1933, as the Jewish managers started to leave their firms. These losses persisted until the end of our stock price sample period in 1943, a full 10 years later. The stock price of the average firm that had employed Jewish managers in 1932 declined by about 12% after 1933, relative to a firm without Jewish managers in 1932.


Stock prices declined only for firms where the removal of the Jewish managers led to large losses in the number of university-educated managers and managerial connections, however. Stock prices did not significantly fall when the removal of the Jewish managers hardly affected these two measures. These results suggest that losing highly qualified managers, i.e. managers with a university education or with many connections, is responsible for the lower stock market performance of firms that lost Jewish managers. There is no evidence that these firms were hit by other shocks after 1933.

Interestingly, our estimated short-run effect of losing Jewish managers on stock prices is close to the initial stock price responses to prominent manager exits in recent times. For example, after Apple CEO Steve Jobs took permanent medical leave in 2011, Apple stock fell by 6%. When Fiat Chrysler CEO Sergio Marchionne stepped down due to surgery in 2018, the Fiat Chrysler stock lost 5%. This implies that the stock price response to losing highly qualified managers can still be as large today as it was in the 1930s.

In our third set of results, we analyzed the effects of losing Jewish managers on two additional measures of firm performance: dividend payments and returns on assets. We found that after 1933, dividend payments fell by approximately 7.5% for the average firm that lost Jewish managers, compared to a firm that did not lose any Jewish managers. We also found that after 1933, the average firm that had employed Jewish managers in 1932 experienced a decline in its return on assets by 4.1 percentage points. These results indicate that the loss of Jewish managers also led to real losses in firm efficiency and profitability.

This research helps inform our understanding of how the rise of a discriminatory ideology can cause real economic harm. A back-of-the-envelope calculation suggests that excluding the Jewish managers reduced the aggregate market valuation of firms listed in Berlin by 1.8% of German gross national product, a first-order economic loss.

While our study covers what’s arguably the most severe form of discrimination against a particular group of individuals, even less severe forms of discrimination can lead to a loss of talent. Even the perception of not being welcome in a country may lead to outflow of high-skilled individuals. A recent survey in the wake of the Brexit referendum suggests, for example, that 12% of Europeans who make between £100,001 ($130,000) and £200,000 a year were planning to leave the United Kingdom in the coming years. The results in our paper indicate that such an exodus could significantly hurt people, firms, and the economy.

Categories: Blogs

The Kinds of Data Scientist

Harvard business - Wed, 11/07/2018 - 08:30
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In 2012, HBR dubbed data scientist “the sexiest job of the 21st century”. It is also, arguably, the vaguest. To hire the right people for the right roles, it’s important to distinguish between different types of data scientist. There are plenty of different distinctions that one can draw, of course, and any attempt to group data scientists into different buckets is by necessity an oversimplification. Nonetheless, I find it helpful to distinguish between the deliverables they create. One type of data scientist creates output for humans to consume, in the form of product and strategy recommendations. They are decision scientists. The other creates output for machines to consume like models, training data, and algorithms. They are modeling scientists.

  1. Data science for humans: the consumers of the output are decision makers like executives, product managers, designers, or clinicians. They want to draw conclusions from data in order to make decisions such as which content to license, which sales lead to follow, which medicine is less likely to cause an allergic reaction, which webpage design will lead to more engagement or more purchases, which marketing email will yield higher revenue, or which specific part of a product user experience is suboptimal and needs attention. These data scientists design, define, and implement metrics, run and interpret experiments, create dashboards, draw causal inferences, and generate recommendations from modeling and measurement.
  2. Data science for machines: here the consumers of the output are computers which consume data in the form of training data, models, and algorithms. Examples of the work products of these data scientists are: recommendation systems which recommend what shirt a customer might like or what medicine a physician should consider prescribing based on a designed optimization function, such as optimizing for customer clicks or for minimizing readmission rates to the hospital. Depending on the engineering background of these data scientists, these work products are either deployed directly to the production system, or if they are prototypes they are handed off to software engineers to help implement, optimize and scale them.

The elusive full stack data scientists do exist, though they are hard to find. In most organizations, it makes sense for data scientists to specialize into one type or another. But data scientist are curious creatures who thrive from being able to creatively dabble; there are benefits to giving them flexibility to work on projects that touch both “types” – both for them and for the organization.   (The sidebar offers more detail on how the two types of data scientists differ not only in their skills and the work they do, but in whom they partner with and their measures of success.)

Decision Scientist vs. Modeling Scientist

Who consumes the output?

Decision scientist: Humans.

Modeling scientist: Machines.

What is the output?

Decision scientist: Dashboards, presentations, memos, new metrics, predictive models to inform decision-making, opportunity analysis to determine what to invest in or prioritize, reports on the results of experiments including recommendations.

Modeling scientist: Models, training data, algorithms.

What are the measures of success?

Decision scientist: Improved decision-making in the organization.

Modeling scientist: Direct improvements in the product or business from the code developed and shipped.

What are some examples?

Decision scientist: Which content to license, which sales lead to follow, which medicine is less likely to cause an allergic reaction, which webpage design will lead to more engagement or more purchases, which marketing email will yield higher revenue, which specific part of a product user experience is suboptimal and needs attention.

Modeling scientist: recommendation systems that recommend what shirt a customer might like or what medicine should be prescribed based on a designed optimization function such as optimizing for customer clicks, or for minimizing return rates to the clinic.

What skills are required?

Decision scientist: Statistics, experimentation, analytical thinking, communication and collaborations skills to work with both technical and non-technical partners, knowledge of both scripting and query languages (e.g. Python, R, SQL), and ideally also formal computer science background.

Modeling scientist: Computer science, machine learning, production-grade coding skills, strong communication to work with both technical and non-technical partners

Who are their main partners on the job?

Decision scientist: Decision makers (executives, business leaders, product managers), data engineers, software engineers responsible for the applications generating data.

Modeling scientist: backend engineers, product managers (to determine what to optimize for), other modeling-scientist colleagues who share techniques, decision scientists on what features to consider and datasets to use.

A more detailed look at data roles

In larger and more sophisticated data operations, more fine-grained roles are necessary. Here are five key areas that contribute to data science operations. In small organizations, one person will do several of these things. In slightly bigger teams, each of these may be a role staffed by one or more individuals. In larger operations, each may be a team unto itself. These roles cover the creation, maintenance, and use of data, and are in addition to the data scientists described above (decision scientists and modeling scientists).

  • Data infrastructure: data ingestion, availability, operations, access, and running environments to support workflows of data scientists. e.g. running Kafka and a Hadoop cluster
  • Data engineering: determination of data schemas needed to support measurement and modeling needs, and data cleansing, aggregation, ETL, dataset management
  • Data quality and data governance: tools, processes, guidelines to ensure data is correct, gated and monitored, documented, standardized. This includes tools for data lineage and data security.
  • Data analytics engineering: enabling data scientists focused on analytics to scale via analytics applications for internal use, e.g. analytics software libraries, productizing workflows, and analytic microservices.
  • Data product manager: creating products for internal customers to use within their workflow, to enable incorporation of measurement created by data scientists. Examples include: a portal to read out results of A/B tests, a failure analysis tool, or a dashboard that enables self serve data and root cause diagnosing of changes to metrics or model performance.

Who to hire

So which kind of data scientist should you be recruiting? To answer that question, first decide what stage you are in with your data operation, and second ask how vital data is to your product. If you’re a small organization just starting off and hiring your first data scientist, try to hire someone who can span as many of these roles as possible — the elusive full stack data scientist. If you’re larger or farther along in your data operation, the answer will depend more on how essential data is to your product. If your product is going to depend on machine learning from inception, you’ll need machine learning expertise in your first hire, or your first leader. If, by contrast, you’re looking to identify product opportunities or to improve general decision-making throughout the organization, you’ll need someone more trained in decision science, descriptive and predictive analytics, and statistics, and someone who can translate how to use data across the leadership team and to non-technical partners.

Finally, if you don’t have internal data in a format that is consumable or reasonable, you will need a data scientist with a strong enough engineering or computer science background that they can work with engineers to guide what data must be captured and how, before they can start their work.

How to organize

Much has already been written about how data science functions should be organized. Perhaps the most important point is that if data science is a strategic differentiator for the organization, the head of the data science unit should ideally report into the CEO. If this is not possible, they should at least report into someone who understands data strategy and is willing to invest to give it what it needs. Data science has its own skillset, workflow, tooling, integration processes, culture; if it is critical to the organization it is best to not bury it under a part of the organization with a different culture.

The other big question is whether and how to embed data science into the different business lines. There are three basic models: centralized in one data science team, distributed throughout the business lines, or a hybrid between the two where you have a centralized team reporting into one head, but physically co-locate and embed teams of data scientists into business units long term. Unless your data operation includes several hundreds of employees, it’s pretty clear at this point that the hybrid model is most effective. (If you reach this scale, a fully distributed model can make sense, but very few companies work this way.)

In the hybrid model, the centralization in reporting structure enables data scientists to have career progression and growth in a ladder specialized for data scientists, to grow with and be assessed against their peers, and to facilitate and ensure that best practices will be shared across them since they are not each in their own silos. (Establishing this peer group is key; data scientists are curious creatures that want to grow and learn from each other.) Due to the reporting structure, it also enables the leader to more easily promote internal mobility across business groups; this cross-pollination across the company is usually a large benefit.

At the same time, embedding within business groups enables data scientists to establish themselves as domain experts in their business group, and develop a rapport with business partners as an essential long-term part of the team. This partnership will provide the data scientists with rich business context, enabling them to have maximal impact by truly understanding and guiding what business priorities should be addressed using data, and how.

What data scientists need to succeed

Although different kinds of data scientists may have different specialties or duties, there are a few things they all need to succeed. They need business partners who can help them integrate into the core business line and product line. They need data partners — such as software application engineers and data infrastructure engineers — who help ensure the necessary foundational data instrumentation and data feeds are correct, complete, and accessible. And they need leaders willing to invest in the foundations necessary for their work, including data quality, data management, data visualization and access platforms, and a culture of expecting data to be part of the process of business and product development. Key to this is allotting appropriate (and often underestimated) time within the development process for data and measurement. Far too often, product and software teams think of data and measurement as something they can quickly “add on” at the end.

A final piece of advice for those hiring data scientists: Look for people who are in love with solving problems, not with specific solutions or methods, and for people who are incredibly collaborative. No matter what kind of data scientist you are hiring, to be successful they need to be able to work alongside a vast variety of other job functions — from engineers to product managers to marketers to executive teams. Finally, look for people who have high integrity. As a society, we have a social responsibility to use data for good, and with respect. Data scientists hold the responsibility for data stewardship inside and outside the organization in which they work.

Categories: Blogs

The Hidden Costs of Initial Coin Offerings

Harvard business - Wed, 11/07/2018 - 08:00
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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:


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.


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.


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.

Categories: Blogs

To Give a Great Presentation, Distill Your Message to Just 15 Words

Harvard business - Wed, 11/07/2018 - 06:05
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Fearless public speaking is about more than combating nerves. It’s about knowing the technique, the art, and the business of public speaking.

In my two years working as a TedX producer, and my 27 years working in film, television, theater, and events production, I have worked with hundreds of speakers, and with actors including Kate Winslet, Christopher Walken, Susan Sarandon, and the late James Gandolfini. All of the speakers and actors I’ve worked with rely on technique when they walk on to a stage or a set. They don’t simply hope they will connect with the scene or with their scene partner. The same applies to anyone who’s public speaking. While you may not deliver a captivating talk every time, you can learn to apply technique, and in turn, become a fearless speaker every time. But your nerves are not the only thing you have to master. You must also:

Know how to pitch. When you understand and master the pitch, you’ll get onto more stages, which in turn will give you the confidence to become fearless each time you pitch. Start with the idea and why you are the right person to take the stage and deliver this big idea. While it must be a big idea, you need to be able to communicate it in fifteen words or less. Organizers are busy, and they don’t have time to read through lengthy pitches. Share what the audience will take away, as well as the global impact of the talk. Don’t save the most important part of your pitch for the end; people may stop reading before they ever get to it, landing you in the “no” pile. And don’t try to sell your book or business in a pitch for a speaking gig. If you want to sell from the stage, that conversation happens after you book the gig. 75% of the potential speakers who apply to my events, including TEDxLincolnSquare, The Speaker Salon, and currently Speakers Who Dare, end up pitching their business. That’s a lot of people who do not understand the art of a pitch, and who subsequently end up in the no pile.

You and Your Team Series Public Speaking

Know your audience. When you do research on your audience ahead of time, it gives you the opportunity to craft your talk with the language that your audience speaks. For example, if you’re speaking on a panel, you can speak more intimately to the audience. If you’re at an event that’s more high energy, your language can reflect that — you can entertain the audience a bit more. If you’re at a conference that’s for professionals, you can speak in more technical terms. Speaking the same language as the audience increases the odds that they will hear you, understand you, and be inspired by you. You’re more likely to connect with them emotionally. If you’re walking into a speaking gig without knowing your audience, you’re bound to fall flat and end up looking at the tops of their heads as they check their cell phones. You have to know who you’re talking to.

Know your objective. In order to have an authentic scene, actors have to know what they want from their scene partner, and want to be believable when they are going about getting it. It’s the same for public speaking. It’s about being authentic. Even though the audience is probably not going to audibly respond to you when you’re speaking on a stage, you are in a scene with them, and when you have a clear objective in terms of what you want, and how to get it, you will be more believable and captivating from the stage, therefore building your confidence as a speaker. Think about the objective you have going into your speech. Maybe your goal is to get the audience to donate to a worthy cause, or spread the word about your ideas. If you want your audience to accept your ideas, or change their opinion about something, how are you going to get them to do it? You can inspire, motivate, or even scare them into changing their minds. But you can’t do any of those things until you know what you want the ultimate outcome to be.

Know the difference between a good talk and a bad talk. A good talk has content that is fresh and well-edited, with a clear arc that takes us on a journey. A good talk is one that is so well rehearsed that you are able to let go of the script and freely share the content in the moment. A good talk is one where your audience wants to adopt your idea at the end of the talk. A bad talk, on the other hand, is one that meanders, does not have a clear through-line, ends more than once, and is apologetic. A bad talk is so well rehearsed that you sound robotic and scripted, or so unrehearsed that you stumble too often and lose your audience’s attention.

Know yourself. Public speaking is hard work. It’s time-consuming, and it’s emotionally and physically draining — especially if you are an introvert. But introverts can become engaging public speakers by flexing the muscle of being in public. Practice by going to events and coming out of the corner. If you have a speaking engagement, take extra time that day to sit quietly, meditate, and refuel. If you are an extrovert, be sure to save your voice before you take the stage — you can always socialize after your talk.

Fearless speaking is the sum of many parts; it’s not just about wrangling the butterflies in your stomach. When you approach public speaking as the sharing of ideas as well as a business, understanding what makes this a successful exchange, your confidence will improve in direct proportion to the number of times you nail it, on and off the stage.

Categories: Blogs

Avoiding Miscommunication in a Digital World

Harvard business - Tue, 11/06/2018 - 11:02

Nick Morgan, a communications expert and speaking coach, says that while email, texting, and Slack might seem like they make communication easier, they actually make things less efficient. When we are bombarded with too many messages a day, he argues, humans are likely to fill in the gaps with negative information or assume the worst about the intent of a coworker’s email. He offers up a few tips and tricks for how we can bring the benefits of face-to-face communication back into the digital workplace. Morgan is the author of the book, Can You Hear Me?: How to Connect with People in a Virtual World.

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Categories: Blogs

Ego Is the Enemy of Good Leadership

Harvard business - Tue, 11/06/2018 - 10:00
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On his first day as CEO of the Carlsberg Group, a global brewery and beverage company, Cees ‘t Hart was given a key card by his assistant. The card locked out all the other floors for the elevator so that he could go directly to his corner office on the 20th floor. And with its picture windows, his office offered a stunning view of Copenhagen. These were the perks of his new position, ones that spoke to his power and importance within the company.

Cees spent the next two months acclimating to his new responsibilities. But during those two months, he noticed that he saw very few people throughout the day. Since the elevator didn’t stop at other floors and only a select group of executives worked on the 20th floor, he rarely interacted with other Carlsberg employees. Cees decided to switch from his corner office on the 20th floor to an empty desk in an open-floor plan on a lower floor.

When asked about the changes, Cees explained, “If I don’t meet people, I won’t get to know what they think. And if I don’t have a finger on the pulse of the organization, I can’t lead effectively.”

Further Reading

This story is a good example of how one leader actively worked to avoid the risk of insularity that comes with holding senior positions. And this risk is a real problem for senior leaders. In short, the higher leaders rise in the ranks, the more they are at risk of getting an inflated ego. And the bigger their ego grows, the more they are at risk of ending up in an insulated bubble, losing touch with their colleagues, the culture, and ultimately their clients. Let’s analyze this dynamic step by step.

As we rise in the ranks, we acquire more power. And with that, people are more likely to want to please us by listening more attentively, agreeing more, and laughing at our jokes. All of these tickle the ego. And when the ego is tickled, it grows. David Owen, the former British Foreign Secretary and a neurologist, and Jonathan Davidson, a professor of psychiatry and behavioral sciences at Duke University, call this the “hubris syndrome,” which they define as a “disorder of the possession of power, particularly power which has been associated with overwhelming success, held for a period of years.”

An unchecked ego can warp our perspective or twist our values. In the words of Jennifer Woo, CEO and chair of The Lane Crawford Joyce Group, Asia’s largest luxury retailer, “Managing our ego’s craving for fortune, fame, and influence is the prime responsibility of any leader.” When we’re caught in the grip of the ego’s craving for more power, we lose control. Ego makes us susceptible to manipulation; it narrows our field of vision; and it corrupts our behavior, often causing us to act against our values.

Our ego is like a target we carry with us. And like any target, the bigger it is, the more vulnerable it is to being hit. In this way, an inflated ego makes it easier for others to take advantage of us. Because our ego craves positive attention, it can make us susceptible to manipulation. It makes us predictable. When people know this, they can play to our ego. When we’re a victim of our own need to be seen as great, we end up being led into making decisions that may be detrimental to ourselves, our people, and our organization.

An inflated ego also corrupts our behavior. When we believe we’re the sole architects of our success, we tend to be ruder, more selfish, and more likely to interrupt others. This is especially true in the face of setbacks and criticism. In this way, an inflated ego prevents us from learning from our mistakes and creates a defensive wall that makes it difficult to appreciate the rich lessons we glean from failure.

Finally, an inflated ego narrows our vision. The ego always looks for information that confirms what it wants to believe. Basically, a big ego makes us have a strong confirmation bias. Because of this, we lose perspective and end up in a leadership bubble where we only see and hear what we want to. As a result, we lose touch with the people we lead, the culture we are a part of, and ultimately our clients and stakeholders.

Breaking free of an overly protective or inflated ego and avoiding the leadership bubble is an important and challenging job. It requires selflessness, reflection, and courage. Here are a few tips that will help you:

  • Consider the perks and privileges you are being offered in your role. Some of them enable you to do your job effectively. That’s great. But some of them are simply perks to promote your status and power and ultimately ego. Consider which of your privileges you can let go of. It could be the reserved parking spot or, like in Cees ‘t Hart’s case, a special pass for the elevator.
  • Support, develop, and work with people who won’t feed your ego. Hire smart people with the confidence to speak up.
  • Humility and gratitude are cornerstones of selflessness. Make a habit of taking a moment at the end of each day to reflect on all the people that were part of making you successful on that day. This helps you develop a natural sense of humility, by seeing how you are not the only cause of your success. And end the reflection by actively sending a message of gratitude to those people.

The inflated ego that comes with success — the bigger salary, the nicer office, the easy laughs — often makes us feel as if we’ve found the eternal answer to being a leader. But the reality is, we haven’t. Leadership is about people, and people change every day. If we believe we’ve found the universal key to leading people, we’ve just lost it. If we let our ego determine what we see, what we hear, and what we believe, we’ve let our past success damage our future success.

Categories: Blogs

U.S. Health Plans Can Save Billions by Helping Patients Navigate the System

Harvard business - Tue, 11/06/2018 - 09:00
Shana Novak/Getty Images

Most people at one time or another have struggled to navigate the complexities of the U.S. health care system. Many have received unpleasant surprises, such as a medical bill they expected to be covered by their health insurance or an unexpectedly expensive bill for a simple service. This type of confusion results in a lot of administrative work, including avoidable calls to customer service centers or time spent helping people find lower-cost options for services. It is costing employers and health plans billions of dollars each year.

Recognizing this exorbitant cost, Accenture developed a literacy index to evaluate how well consumers can obtain, understand, and navigate information and services. We used this index to assess how health care literacy affected the performance of nine consumer experience touchpoints. We then calculated the correlating impact to administrative costs. From this, we identified strategies in which health plans could save themselves billions of dollars — by simplifying the “user experience” of a system that was not designed with the preferences of the consumer in mind.

Our analysis found the health care system is so complex that more than half (52%) of consumers are unable to navigate it on their own, triggering avoidable customer service calls and more costly care. Consumers with low health system literacy are three times more likely to contact customer service. Our estimates found health insurers and employers spend $26 more on administration fees for every consumer with low health system literacy. This translates into a total cost of $4.82 billion, which would be even higher if accounting for medical cost.

Insight Center

We found that consumers with low literacy struggle to make informed decisions about everything from the health plan types they choose and the premiums they pay to the doctors they see and the procedures they have done. It is worth noting this issue has nothing to do with education level: Roughly half (48%) of low-literacy consumers are college educated and nearly all (97%) have at least a high school diploma.

Difficulty in making informed decisions impacts consumers’ ability to get the medical care they need. This is especially detrimental for the one in four (26%) consumers who have both low understanding and the highest need for health care interventions, such as individuals who are facing chronic or serious conditions. While our study assessed the impact of low literacy on administrative expenses, two decades of research has documented the impact of literacy on the overall health economy — some estimate the cost to add up to as much as $238 billion, or 17%, of all U.S. health expenditures.

Education has a role to play in reducing costs for health insurers, but it alone will not eliminate the problem. To ease their cost burden, health plans should instead aim to simplify the user experience. Our research points to a few strategies that health plans can implement a new model of consumer service and engagement. This can be achieved by harnessing digital channels to make the user experience easier, incentivizing progress driven by other stakeholders in the system, and shifting the complexity burden off consumers.

Harness digital channels to improve user experience. While systemic complexity won’t be eliminated in the short term, health plans can approach service differently to make navigating the health care system feel simpler and easier. Amazon and other digital retailers have done just that. Consumers can select one-click options to get their delivery within a specific timeframe, but are oblivious to the operational complexity that goes on behind the scenes to make it happen. In today’s increasingly technological world, consumers expect this type of simplicity and digital access across all industries that they interact with.

One example of a company in the health industry that is seeking to simplify the process is Oscar Health, a New York City-based insurance company serving eight states and 250,000 members. While widely known for using digital, telemedicine, and concierge service to augment care, Oscar Health has also tackled operational complexity across core insurance functions, like claims processing, providing its 240,000 members with cost estimates for select medical services.

Incorporating intelligent technologies such as artificial intelligence to customer service initiatives can also help with delivering easy-to-follow programs and relevant products.

Incentivize progress. Another solution to cut through complexity is incentivizing health providers and consumers to work together in navigating health insurance options.

We know that providers influence where consumers go for health services. A recent NBER study found that, when choosing between low- and high-cost care settings, referring physicians had far more influence over where consumers sought care than cost did. Employer plans — such as those offered by startup Centivo — are bucking this trend by incentivizing physicians and patients to work together to lower the cost of care.

Other programs focus on educating consumers on how to choose affordable care settings on their own. Programs provided by Vitals, for example, offer consumers cash-back rewards when they select a lower-cost service or procedure such as an MRI or mammogram. Incentives such as these are more likely to drive consumers to change their behaviors, and in the process will educate them about how to make better and cost-efficient care choices.

Shift the complexity burden off consumers. Health plans also need to deploy new product concepts that take us closer to the goal of simplification and orchestrate service options to reach low literacy consumers on their terms.

For example, organizations can offer simple, per-visit copayments instead of complex deductible and coinsurance plans. That is what Minneapolis-based startup Bind Benefits is doing by offering employers on-demand plan options with no deductibles. The idea is to offer simple, straightforward pricing rather than complex plan structures so consumers can easily engage and know the price of their services at the time of consumption.

Ultimately, the only way to eliminate systemic complexity in health care is by actually making health care simpler. Rather than forcing consumers to battle the complexities, the health care system must design user experiences to align seamlessly with the needs, behaviors, and preferences of the people it serves.

Categories: Blogs

Transforming Customer Experiences: Driving Performance and Profitability in the Service Sector - SPONSOR CONTENT FROM HBS EXECUTIVE EDUCATION

Harvard business - Tue, 11/06/2018 - 08:30

The service sector is a large and growing part of our economy. But a lot of service businesses are managed according to old ideas imported from more traditional industries, says Ryan Buell, UPS Foundation Associate Professor of Service Management at Harvard Business School (HBS).

In today’s rapidly changing service sector, a new set of frameworks is required to build a robust and competitive service business, says Buell.

“Service jobs have a reputation for not being great jobs—and in many cases, I think it’s a well-earned reputation. But it shouldn’t be that way,” says Buell. “Service is the business of people helping people, and when employees lack the capability, motivation, and license to perform, there’s no hope they’ll deliver excellent service to customers.”

Transforming Customer Experiences

Transforming Customer Experiences draws upon the latest research and insights to equip senior managers with a new toolkit for leading and managing a professional services firm or a customer service or sales team. As a participant in this program, you will work alongside some of HBS’s most renowned service management thought leaders. You will learn innovative methods for designing exceptional service offerings, creating a distinct and sustainable service model, and effectively managing employees and customers.

Learn more.

Buell is faculty chair of the HBS Executive Education course Transforming Customer Experiences, which explores how service leaders can create distinctive and sustainable service organizations that “turn customers into raving fans and employees into dedicated stewards of the mission.”

The program is distinctive in developing a holistic curriculum that speaks to the challenges faced by modern service organizations, Buell says. Participants in the program learn the fundamentals of transforming customer experiences through cases from and interactive lectures by HBS faculty members.

For instance, one case, developed by Buell, focuses on the way IDEO uses human-centered design thinking as a systematic methodology to help create new products and services. The case explores this process through the example of Cineplanet, a leading movie cinema chain in Peru. The company hired IDEO to help them determine how to better align their operating model with the needs of their customers. “This case study may change the way you think about thinking,” says Buell.

The HBS program also includes workshops and one-on-one coaching sessions with faculty who are experts in their fields to help participants discover gaps in the design and execution of the service businesses they lead so they leave with road maps for how to transform and revitalize those businesses.

“Our goal each day is for participants to walk away with practical ideas that can be put to work in their own organizations to make an immediate impact on performance—for employees, customers, and owners alike,” says Buell.

Peer-to-peer learning is also a key part of the program, which assembles a learning community of exceptional service leaders from all around the world.

“My colleagues and I will certainly bring ideas to the table, but just as importantly, we’ll work to set the conditions for participants to leverage and benefit from each other’s experiences,” says Buell.

“At any given point, there will be someone in the room who has faced a challenge similar to another person’s. Getting those people to have a conversation about how they solved the challenge is incredibly valuable, and it doesn’t necessarily happen by itself. We’re very intentional about fostering those interactions.”

The program features workshops on service design and service execution, and those workshops are particularly valuable for companies that send cross-functional teams to the program—that is, when they send multiple people who understand the organization from different angles, says Buell. In this context and setting, teams have an opportunity to deeply understand and diagnose challenges that their organization faces, but they also leverage their cross-functional expertise to identify opportunities to improve their business. Also, having a shared experience allows teams to go back to their organization with a common language and a common set of tools and frameworks for addressing business challenges.

To learn more about Transforming Customer Experiences at Harvard Business School Executive Education, taught by Ryan Buell and other renowned faculty, visit the program website.

Categories: Blogs

If Your Employees Aren’t Speaking Up, Blame Company Culture

Harvard business - Tue, 11/06/2018 - 08:17
PM Images/Getty Images

Companies benefit when employees speak up. When employees feel comfortable candidly voicing their opinions, suggestions, or concerns, organizations become better at handling threats as well as opportunities.

But employees often remain silent with their opinions, concerns or ideas. There are generally two viewpoints on why: One is the personality perspective, which suggests that these employees inherently lack the disposition to stand up and speak out about critical issues, that they might be too introverted or shy to effectively articulate their views to the team. This perspective gives rise to solutions such as hiring employees who have proactive dispositions and are more inclined to speak truth to power.

By contrast, the situational perspective argues that employees fail to speak up because they feel their work environment is not conducive for it. They might fear suffering significant social costs by challenging their bosses. This perspective leads to solutions focused on how managers can create the right social norms that encourage employees to voice concerns without fear of sanctions.

These two perspectives aren’t mutually exclusive, but we wanted to test which one matters more: If personality is the primary predictor of speaking up, situational factors shouldn’t matter as much. This means that employees who are inherently disposed to speak up will be the ones who more frequently do so. By contrast, if the situation or environment is the primary driver of speaking up, then employee personality should be less important – employees would speak up, irrespective of their underlying dispositions, when the work environment encourages speaking up, and they would stay silent when the environment doesn’t.

In our research we collected survey data from a manufacturing plant in Malaysia in 2014. We surveyed 291 employees and their supervisors (from 35 teams overall). We asked employees how likely they were inherently disposed to seeking out opportunities in their environment (also known in psychology as their approach orientation); this was how we assessed whether employees had a personality inclined toward speaking up. We also asked them whether speaking up is expected as part of their everyday work, and whether it is encouraged and rewarded or punished; this was how we assessed the situational norms associated with their work environment. Each employee rated their approach orientation, as well as the expectations in their job, using validated measures. For each employee in the team, we asked their supervisor to rate the frequency of speaking up.

The firm was responsible for manufacturing and sales of soaps, detergents, and other home cleaning products, and employees often encountered situations where there was compelling need to speak up about issues around current work operations. For instance, employees could suggest novel approaches to stacking raw materials, improving equipment layouts, or enhancing coordination during shift changes. They could also call out problems such as faulty safety gear or violations of standard operating procedures on the shop floor.

When we analyzed the data, we found that both personality and environment had a significant effect on employee’s tendency to speak up with ideas or concerns. Employees with a high approach orientation, who tend to seek opportunities and take more risks, spoke up more often with ideas than those with a lower approach orientation. And employees who believed they were expected to suggest ideas spoke up more than those who didn’t feel it was part of their job.

But we found that strong environmental norms could override the influence of personality on employees’ willingness to speak up at work. Even if someone had a low approach orientation, they spoke up when they thought it was strongly expected of them at work. And if someone had a high approach orientation, they’d be less likely to speak up with concerns when they thought it was discouraged or punished. Our data supported the situational perspective better than the personality perspective.

This finding suggests that if you want employees to speak up, the work environment and the team’s social norms matter. Even people who are most inclined to raise ideas and suggestions may not do so if they fear being put down or penalized. On the flip side, encouraging and rewarding speaking up can help more people do so, even if their personality makes them more risk-averse.

We also found that the environment could influence how employees spoke up. Employees voiced their opinions in two different ways—by identifying areas for improvement at work, and by diagnosing potential threats to the organization and calling out undesirable behaviors that might compromise safety or operations. We found that when norms at work encouraged detection of potential threats or problems, employees spoke out more on issues such as safety violations or breaches of established work practices. But when such norms encouraged improvements and innovation, employees more often spoke up with novel ideas for redesigning work processes that promoted innovation on the shop floor.

This suggests that work norms can not only encourage all employees to speak up but also focus their voice on specific issues confronting the organization. Managers working in contexts where innovation is important would do well to create an environment that specifically encourages employees to come up with ideas that can offer new opportunities for success. On the other hand, managers working in contexts where reliability is critical would do well to specifically create an environment where employees are focused on forecasting and speaking up about potential threats that can hinder or disrupt work operations.

Though we find convincing evidence in favor of the situational perspective for why employees do or don’t speak up, our study has its limitations. For instance, it was conducted in East Asia, where people ascribe to cultural value of collectivism and social norms might play a stronger role than in the more individualist West. Despite this caveat, our research suggests that if you want your employees to be more vocal and contribute ideas and opinions, you should actively encourage this behavior and reward those who do it.

Categories: Blogs

Competing in the Huge Digital Economies of China and India

Harvard business - Tue, 11/06/2018 - 08:00
Jeff Greenberg/Getty Images

The global digital economy crossed an important milestone recently: the number of internet users in two countries — China, with just over 800 million users, and India, with 500 million users  – surpassed the aggregate number of internet users across 37 OECD countries combined. In both countries, users spend more time on the internet than the worldwide average of 5.9 hours per day. They also have room to grow; China has just under 60% of its population online, while India, with one of the lowest rates of internet penetration in the world, has under 25% of its population online.

While it’s tempting to group China and India together as a block of emerging digital markets, they offer several important distinctions, especially for international entities and countries looking to invest. In our Digital Evolution Index (DEI), we place them in the “digital south” which means the full deployment and adoption of online systems is still in development. Our DEI research classifies both China and India as “Break Out” countries, which means they are experiencing strong digital growth. China has 783 million smartphone users and, as reported by the Cyberspace Administration of China, had 469 million registered on a mobile payment platform in January 2017. It is also the world’s largest market for e-commerce. And India is on track to become the youngest country in the world by 2020 and its digital economy is expected to balloon from $413 billion today to $1 trillion dollars by 2025.

Both China and India present barriers to entry for foreign players. The most obvious distinction between the two markets is that China is mostly closed to international players because of state restrictions, while India is, technically, open for business. Top U.S. companies are investing heavily in India —  as are Chinese companies, such as Alibaba and Tencent.  However, India presents barriers that are less visible. Consider two examples:

  • Languages: Language poses a high barrier to entry or growth for any company. Less than 100 million out of India’s 700 million literate population can read or write English. There are 32 different languages with a million-plus speakers each across India, whereas in China, Mandarin is understood by the majority. In India, 90% of the country’s registered publications do not have a website because of language barriers and 95% of video consumption is in local languages. It is essential to crack at least five Indian languages to truly break into this market.
  • Protectionist policies: While China’s protectionist policies are transparent, India’s protectionist agenda is in the form of regulations and red tape. For example, a recently proposed Indian government policy on e-commerce and a similar order from the country’s central bank seeks to prohibit data on Indian e-commerce consumers from being stored outside India. Many international players view this as favoring homegrown digital companies and a case of India borrowing from China’s playbook, that mandates local storage of Chinese user data considered “sensitive”.

The few international players active in China have scaled the entry barriers through adaptive (and sometimes risky, complex, or controversial) strategies, while others that have been blocked – e.g. Google and Facebook – keep experimenting with ways to comply with the state restrictions and invite fresh controversies. In parallel, companies will need to tailor their approaches to fully crack India, but in different ways. Building on our example above, in response to the language barrier, Google has invested in its Translate app and in its AI-enabled multi-local language publishing platform while Amazon plans to launch in multiple local languages in India. Even for these giants, there is a long way to go.

Both China and India have governments deeply engaged in orchestrating the digital economy and in citizens’ data. It is well-known that China’s government has ambitious objectives for the country’s digital future. According to China scholar Adam Segal’s analysis, the Chinese President Xi Jinping “aims to build an ‘impregnable’ cyber-defense system, give itself a greater voice in Internet governance, foster more world-class companies, and lead the globe in advanced technologies.” Among its other ambitions, a July 2017 State Council document aims to position China as the world’s AI leader by 2025.

In the context of this agenda, the Chinese government is assembling a comprehensive database on its own citizens with help from Chinese technology companies that routinely synchronize with the government.  The data will establish a social credit system  expected to be both mandatory by 2020. Every Chinese citizen’s “social credit score”, drawing upon public and private data sources can determine what services – from no-deposit apartment rentals to booking airline tickets to dating to government services — are accessible to the citizen. The private sector, companies such as Alibaba – e.g. Sesame Credit, run by the Ant Financial, an Alibaba affiliate. — and Tencent, through its popular messaging platform, WeChat, have become enormous repositories of user data, with which they can better design and target new services, discern key user attributes, such as credit-worthiness, and train algorithms. They also help the government with necessary data and algorithms. This public-private collaboration not only helps serve the state objectives of citizen surveillance and preserve social order, but also produces user data that improves China’s AI capabilities.

Meanwhile, India’s government also has ambitious objectives for the country’s digital economy. Relative to its Chinese counterparts, India’s authorities have been focused on the fundamentals — on low-cost access to digital tools and on creating an open and inter-operable infrastructure.  The country has embarked on a broad Digital India initiative that encompasses everything from broadband “highways” to e-governance to digital literacy. There are also plans to establish 100 “smart cities” across India in collaboration with public agencies and private companies.

Like China, India, too, has a citizens’ database.  The aspirations for such a database were to establish a universally accepted form of identification to promote inclusive access to a variety of services in a country where many are excluded because of a lack of key documentation. As the core visionary behind this initiative, technology pioneer and Infosys co-founder, Nandan Nilekani, writes, the essential idea was to “empower users with the technical and legal tools required to take back control of their data.”

Nilekani led the initiative that produced such a system, Aadhaar, which has enrolled 1.2 billion citizens. Aadhaar has become the foundation for an “India stack”, the world’s largest API that allows any enterprise, private or public, to build services and linking them to each individual’s unique identity.

While each country has chosen a different path, both markets are being shaped by governments defining a framework and working with the private sector to populate it. Of course, state-organized citizen databases raise plenty of concerns.  China’s social credit system raises worries about “Orwellian” mass surveillance. In addition, the growing use of facial recognition technologies across China adds to worries about privacy and government over-reach.

In India, Aadhaar had increasingly become mandatory for privately offered services, such as mobile communications, banking and airline bookings as well as government programs, triggering concerns from consumer privacy and advocacy groups. The Aadhaar database itself has not proven to be secure and there were worries about both commercial abuse of data and government surveillance of citizens. As in China, India has also entertained proposals to add facial recognition to the database. The mandatory aspect of Aadhaar was re-visited after being legally challenged and the country’s Supreme Court has ruled that while the ID system is constitutionally valid and is required as proof-of-identity for government programs, it cannot be mandated for private services, making it harder for companies to authenticate their customers.

Companies looking to enter either of these markets will need to be prepared to navigate a digital landscape being actively shaped by the government. They will also have to contend with some difficult privacy issues; in China the rules of play on these issues are clearer, while in India the rules can change with political turnover, as well as the outcomes of legal challenges and citizen advocacy.

Both China and India are key contributors to the world’s growing middle class. Currently, China is ahead on the major economic metrics: to add as much to its GDP as China will in 2018, India would need to grow by  40%.  But there are other measures that suggest that India might have a chance to narrow the gap. India’s middle class (defined as $11 – $110 a day in 2011 purchasing power parity terms) is expected to exceed that of China’s by 2030, according to the OECD and Brookings.  Simultaneously, India’s high growth rate of 7.7% in the first quarter of 2018, continues to maintain its position as the world’s fastest-growing large economy.  Some India-enthusiasts argue that its demographic advantage and democratic political system will prove beneficial over the long-term in catching-up with state-controlled China.

China is ranked 36th and India 53rd out of the 60 countries ranked by our DEI. In light of the potential narrowing of the broader economic gaps, it makes sense to ask if the gap between the digital economies of the two countries might narrow. How long will it take for India to get to China’s current level of digital evolution?  What key drivers might help accelerate the journey? Could India plausibly narrow the gap? These questions are important for companies that would rather pursue opportunities in India, rather than contend with the high barriers in China, but are concerned about how far behind India is relative to China.

Using our DEI model, there are three possible catch-up scenarios:

First, if India were to pick up China’s momentum, it would reach China’s current level of digital evolution by 2029.

Second, if India could achieve 3% growth annually across several drivers, it could achieve China’s current level of digital momentum by 2022; these drivers are: physical infrastructure, government facilitation of the ICT sector, digital access, use of digital money and payments, national investment in R&D, gender digital inclusion, digital footprint of business, mobile internet gap.

Third, if India could accomplish the following combination of growth rates, it could reach China’s current state of digital evolution by 2024.

  • 18% annual growth in Gender Digital Inclusion
  • 3% annual growth in Physical Infrastructure
  • 3% annual growth in national investment in R&D
  • 1% growth in Digital Access Availability

This analysis suggests that narrowing the digital gap is within India’s reach. If international technology players and investors were to consider where they might intervene in India’s digital economy and provide leverage to the country’s policy objectives, they can participate in India’s digital economy while helping it accelerate and narrow the gap with China, a perennial economic rival. If this happens, India’s economy could even catch up to China’s. It is important for businesses, innovators, and policymakers to be aware of this potential for convergence between the two great powers of the digital south just as much as they see the differences in order to make wise strategic choices for approaching the two most essential digital markets in the world.

Categories: Blogs

9 Out of 10 People Are Willing to Earn Less Money to Do More-Meaningful Work

Harvard business - Tue, 11/06/2018 - 06:05
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In his introduction to Working, the landmark 1974 oral history of work, Studs Terkel positioned meaning as an equal counterpart to financial compensation in motivating the American worker. “[Work] is about a search…for daily meaning as well as daily bread, for recognition as well as cash, for astonishment rather than torpor,” he wrote. Among those “happy few” he met who truly enjoyed their labors, Terkel noted a common attribute: They had “a meaning to their work over and beyond the reward of the paycheck.”

More than forty years later, myriad studies have substantiated the claim that American workers expect something deeper than a paycheck in return for their labors. Current compensation levels show only a marginal relationship with job satisfaction. By contrast, since 2005, the importance of meaningfulness in driving job selection has grown steadily. “Meaning is the new money, an HBR article argued in 2011. Why, then, haven’t more organizations taken concrete actions to focus their cultures on the creation of meaning?

To date, business leaders have lacked two key pieces of information they need in order to act on the finding that meaning drives productivity. First, any business case hinges on the ability to translate meaning, as an abstraction, into dollars. Just how much is meaningful work actually worth? How much of an investment in this area is justified by the promised returns? And second: How can organizations actually go about fostering meaning?

You and Your Team Series Making Work More Meaningful

We set out to answer these questions at BetterUp this past year, as a follow-up to our study on loneliness at work. Our Meaning and Purpose at Work report, released today, surveyed the experience of workplace meaning among 2,285 American professionals, across 26 industries and a range of pay levels, company sizes, and demographics. The height of the price tag that workers place on meaning surprised us all.

The Dollars (and Sense) of Meaningful Work

Our first goal was to understand how widely held the belief is that meaningful work is of monetary value. More than 9 out of 10 employees, we found, are willing to trade a percentage of their lifetime earnings for greater meaning at work. Across age and salary groups, workers want meaningful work badly enough that they’re willing to pay for it.

The trillion dollar question, then, was just how much is meaning worth to the individual employee? If you could find a job that offered you consistent meaning, how much of your current salary would you be willing to forego to do it? We asked this of our 2,000+ respondents. On average, our pool of American workers said they’d be willing to forego 23% of their entire future lifetime earnings in order to have a job that was always meaningful. The magnitude of this number supports one of the findings from Shawn’s recent study on the Conference for Women. In a survey of attendees, he found that nearly 80% of the respondents would rather have a boss who cared about them finding meaning and success in work than receive a 20% pay increase. To put this figure in perspective, consider that Americans spend about 21% of their incomes on housing. Given that people are willing to spend more on meaningful work than on putting a roof over their heads, the 21st century list of essentials might be due for an update: “food, clothing, shelter — and meaningful work.”

A second related question is: How much is meaning worth to the organization? Employees with very meaningful work, we found, spend one additional hour per week working, and take two fewer days of paid leave per year. In terms of sheer quantity of work hours, organizations will see more work time put in by employees who find greater meaning in that work. More importantly, though, employees who find work meaningful experience significantly greater job satisfaction, which is known to correlate with increased productivity. Based on established job satisfaction-to-productivity ratios, we estimate that highly meaningful work will generate an additional $9,078 per worker, per year.

Additional organizational value comes in the form of retained talent. We learned that employees who find work highly meaningful are 69% less likely to plan on quitting their jobs within the next 6 months, and have job tenures that are 7.4 months longer on average than employees who find work lacking in meaning. Translating that into bottom line results, we estimate that enterprise companies save an average of $6.43 million in annual turnover-related costs for every 10,000 workers, when all employees feel their work is highly meaningful.

A Challenge and an Opportunity

Despite the bidirectional benefits of meaningful work, companies are falling short in providing it. Our study found that people today find their work only about half as meaningful as it could be. We also found that only 1 in 20 respondents rated their current jobs as providing the most meaningful work they could imagine having.

This gap presents both a challenge and an opportunity for employers. Top talent can demand what they want, including meaning, and will jump ship if they don’t get it. Employers must respond or lose talent and productivity. Building greater meaning in the workplace is no longer a nice-to-have, it’s an imperative.

Among the recommendations we offer in our report are these critical three:

Bolster Social Support Networks that Create Shared Meaning.

Employees who experience strong workplace social support find greater meaning at work. Employees who reported the highest levels of workplace social support also scored 47% higher on measures of workplace meaning than did employees who ranked their workplaces as having a culture of poor social support. The sense of collective, shared purpose that emerges in the strongest company cultures adds an even greater boost to workplace meaning. For employees who experience both social support and a sense of shared purpose, average turnover risk reduces by 24%, and the likelihood of getting a raise jumps by 30%, compared to employees who experience social support, but without an accompanying sense of shared purpose.

Simple tactics can amplify social connection and shared purpose. Explicitly sharing experiences of meaningful work is an important form of social support. Organizations can encourage managers to talk with their direct reports about what aspects of work they find meaningful, and get managers to share their perspectives with employees, too. Managers can also build in time during team meetings to clearly articulate the connection between current projects and the company’s overall purpose. Employees can more easily see how their work is meaningful when team project goals tie into a company’s larger vision.

Adopting these habits may require some coaching of managers, as well as incentivizing these activities, but they can go a long way toward building collective purpose in and across teams.

As Shawn’s book Big Potential demonstrates, social support is also a key predictor of overall happiness and success at work. His recent study of a women’s networking conference demonstrated that such support outside the workplace drives key professional outcomes, such as promotions.

Make Every Worker a Knowledge Worker.

Our study found that knowledge workers experience greater meaning at work than others, and that such workers derive an especially strong sense of meaning from a feeling of active professional growth. Knowledge workers are also more likely to feel inspired by the vision their organizations are striving to achieve, and humbled by the opportunity to work in service to others.

Research shows that all work becomes knowledge work, when workers are given the chance to make it so. That’s good news for companies and employees. Because when workers experience work as knowledge work, work feels more meaningful.

As such, all workers can benefit from a greater emphasis on creativity in their roles. Offer employees opportunities to creatively engage in their work, share knowledge, and feel like they’re co-creating the process of how work gets done.

Often, the people “in the trenches” (retail floor clerks, assembly line workers) have valuable insights into how operations can be improved. Engaging employees by soliciting their feedback can have a huge impact on employees’ experience of meaning, and helps improve company processes. A case study of entry-level steel mill workers found that when management instituted policies to take advantage of workers’ specialized knowledge and creative operational solutions, production uptime increased by 3.5%, resulting in a $1.2M increase in annual operating profits.

Coaching and mentoring are valuable tools to help workers across all roles and levels find deeper inspiration in their work. Managers trained in coaching techniques that focus on fostering creativity and engagement can serve this role as well.

A broader principle worth highlighting here is that personal growth — the opportunity to reach for new creative heights, in this case above and beyond professional growth — fuels one’s sense of meaning at work. Work dominates our time and our mindshare, and in return we expect to find personal value from those efforts. Managers and organizations seeking to bolster meaning will need to proactively support their employees’ pursuit of personal growth and development alongside the more traditional professional development opportunities.

Support Meaning Multipliers at All Levels.

Not all people and professions find work equally meaningful. Older employees in our study, for instance, found more meaning at work than do younger workers. And parents raising children found work 12% more meaningful that those without children. People in our study in service-oriented professions, such as medicine, education and social work, experienced higher levels of workplace meaning than did administrative support and transportation workers.

Leverage employees who find higher levels of meaning to act as multipliers of meaning throughout an organization. Connect mentors in high meaning occupations, for instance, to others to share perspectives on what makes work meaningful for them. Provide more mentorship for younger workers. Less educated workers — who are more likely to work in the trenches — have valuable insights on how to improve processes. They’d be prime candidates for coaching to help them find ways to see themselves as knowledge workers contributing to company success.

Putting Meaning to Work

The old labor contract between employer and employee — the simple exchange of money for labor — has expired; perhaps it was already expired in Terkel’s day. Taking its place is a new order in which people demand meaning from work, and in return give more deeply and freely to those organizations that provide it. They don’t merely hope for work to be meaningful, they expect it — and they’re willing to pay dearly to have it.

Meaningful work only has upsides. Employees work harder and quit less, and they gravitate to supportive work cultures that help them grow. The value of meaning to both individual employees, and to organizations, stands waiting, ready to be captured by organizations prepared to act.

Categories: Blogs

Employee Check-Ins: 6 Essential Components for Success

Hr Bartender - Tue, 11/06/2018 - 02:57

(Editor’s Note: Today’s post is brought to you by our friends at Readex Research, which provides expert online and mail survey services to help businesses understand their internal and external customers. Their services include employee experience surveys. Enjoy the post!)

Over the past few months, we’ve talked about the importance of “checking in” with new hires to make sure their employee experience is going well. This activity can take place in-person or online. The goal with a new hire check-in is to make sure that employees are in a position to focus on their work, which ultimately fosters employee engagement and retention. Here are a couple of resources you might want to check out:

New Hire Onboarding: Take a Pulse to Increase Employee Retention

New Hires Not Engaged? How to Design an Onboarding Intervention

But I’ve spoken with many people who tell me that the challenge isn’t about convincing anyone that check-ins are valuable. Organizations know that. The challenge is in designing a check-in process that the organization will embrace.

6 Essential Elements for Successful New Hire Check-Ins

Check-ins should meet the needs of the company as well as the employee. I know it might seem like a check-in is all about the employee…and it is. But if the process is cumbersome or expensive, then organizations run the risk of having no one do it. And that defeats the purpose of getting employee feedback. So here are six things to consider:

Check-ins must meet the needs of the company and the employee. Let’s start with how a new hire check-in should meet the company’s needs:

1.  Low on administration. But high on value. This is the beauty of today’s technology. Organizations can have activities, like a new hire check-in, that are scheduled to distribute automatically. This doesn’t mean the organization doesn’t care just because someone in HR wasn’t sitting at their desk hitting the ‘send’ button. Rather, automating a regularly occurring process allows the company to focus on the piece that cannot be automated…dealing with employee responses.

2.  Clear goals. Speaking of results, the only way that a check-in program brings value is when the organization is positioned to react to the new hire’s responses. That involves establishing clear program goals and designing questions that will provide the company with relevant feedback. The questions shouldn’t be leading the new hire to respond a certain way and they should be designed to give the new hire the feeling that their comments are welcome.

3.  Timely. The whole reason that the organization is doing new hire check-ins is to encourage employee engagement and prevent unnecessary turnover. Asking a new hire after six months on the job what they thought about their first day doesn’t send the message that the company cares. Check-ins allow organizations to send brief surveys to new hires on regular intervals, so the feedback can be heard and responded to in a timely fashion.

New hire employee needs are somewhat similar. Here are a few things to consider:

4.  Convenient. If organizations want employees to respond, then they need to create activities that are easy to use so it encourages participation. Personally, I know my response rate when someone asks me to respond to a five-question survey versus the one that will take 20-minutes. Employees need to also feel that they can keep their comments confidential and, if they wish, they can leave their contact information for follow-up. Let new hires drive their own feedback.

5.  Intuitive. Whatever method is used to deliver the check-in, it needs to be user friendly. There’s nothing worse than offering to give feedback and then having to jump through a bunch of hoops to finish the process. It might be tempting to add other goals to the check-in process because you have the employee’s attention. Resist that urge. Also, if the feedback will be given over a technology platform, make sure it’s mobile responsive and secure.

6.     Timely. Like the organization, new hires don’t want to waste time. But for new hires, the focus is a bit different. They want to deliver their feedback quickly and efficiently, so they can get on with their work. They also want the organization to respond in a timely fashion. Doing so, will encourage employees to keep on providing even morefeedback. I’ve said it before, but I’ll say it again, the worst thing organizations can do is ask for an employee’s feedback and then do nothing with it.

I asked Readex CEO Jack Semler if there was one aspect of check-ins that might be more important than the others. While I knew he would tell me they’re all important, he did share that the key comes down to connection.

“Thinking from my own experience as a manager, I feel what is ‘most important’ is a two-fold:  First, is the new employee connecting with what the job really is and what the employee’s personal vision of the job is?  If reality isn’t in line with their vision, then danger exists, and has to be corrected immediately.  Second, is the new employee connecting with peers and management in a positive, good way?  There are so many other factors that need to be checked out, but in the end, if what the job entails is not in line with the employee expectations, and good relationships aren’t forming, the employee may be a flight risk.”

New Hire Check-ins Help Retain Employees

Employee check-ins are a valuable way to easily and quickly take a pulse on the new hire experience. For example, surveys are only as good as they are structured. In this case, structure means making it easy to take the survey and easy to interpret the results – for the employee and the organization.

If you want to learn more about how to implement an employee check-in program, visit the Readex website. You can see first-hand how technology can help your organization retain employees and maintain engagement and productivity.

The post Employee Check-Ins: 6 Essential Components for Success appeared first on hr bartender.

Categories: Blogs

Sisterhood Is Scarce

Harvard business - Mon, 11/05/2018 - 14:54

From the Women at Work podcast:
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The glass ceiling is the classic symbol of the barrier women bump into as we go through our careers. But for women of color, that barrier is more like a concrete wall. If we’re going to reduce workplace sexism and racism, women of all ethnicities need to work together. And it will be tough to do that unless we feel more connected to each other.

We talk with professors Ella Bell Smith and Stella Nkomo about how race, gender, and class play into the different experiences and relationships white women and women of color have at work. They explain how those differences can drive women apart, drawing from stories and research insights in their book, Our Separate Ways.


Ella L.J. Bell Smith is a professor at the Tuck School of Business at Dartmouth.
Stella M. Nkomo is a professor at the University of Pretoria, in South Africa.


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Our theme music is Matt Hill’s “City In Motion,” provided by Audio Network.

Categories: Blogs

Turning Observation into Innovation

Leadershipnow - Mon, 11/05/2018 - 08:19

EVERYONE WANTS to be an innovator. Every organization wants to be innovative; it doesn’t matter if it’s a church, a for-profit or non-profit business, or a government agency. To not be innovative is to risk being left behind. But how many of us are truly innovative? What have we done that could be called really innovative in the last year?

To be innovative requires a risk tolerance that most people just don’t have. It requires skills that too few have developed. We make incremental changes to be sure, but innovation necessitates something more. Often we just are too close to the situation to see the opportunities. It’s why companies like Google and Intel have called upon corporate anthropologists to bring give them fresh perspectives on their own businesses.

Corporate anthropologists, like traditional anthropologists, explains Andi Simon in On the Brink, look “at a company as a new and unfamiliar culture” to arrive at fresh insights.

Corporate anthropologists “see things that are really happening out there in the field, not what business leaders think is going on. They look for the deeper meaning in the interactions that make up people’s lives and the objects they surround themselves with. They search for those cultural symbols that people live by but have a hard time telling you about. And then they use their findings to help companies rethink how, and why, they’re doing things.”

Andi Simon is a corporate anthropologist that wants to help you do just that—act like an anthropologist for your own organization (or life). Often on the brink of new heights, the challenge is to react appropriately to changing circumstances— “a challenge that requires seeing, feeling, and thinking in new ways.”

Simon says she is amazed at how often we miss what is right in front of us. As expressed in Russell Conwell’s 1890 classic, Acres of Diamonds, “many business leaders fail to recognize that they’re sitting on acres of diamonds of unmet needs or obvious future opportunities.” There are ways to figure out our customer’s pain points and gain insights from observing both the customer and the processes of a business that lead to meaningful innovation and growth.

The anthropologist’s toolkit consists of these four steps to help you change the way you see things; to find meaning in what people do or don’t do:

1. Conduct observational research. You need to go out and watch not only your customers but also your employees. Watch and record how they think and interact with your product or service. Find their pain points. “When companies cannot seem to figure out why they have stalled, customers’ pain points and headaches are often great places to start.” This is true for churches too. What questions are people asking that you aren’t answering?

2. Find out what’s coming in to you already. Users connect with you through call centers, emails, searches, your website, and networking events. What are they happy with, upset about or frustrated by? You’re looking for gaps. In the case of Centenary College, “we needed to experience the college as if we were students, to understand it as if we were their families, and to visualize it through the eyes of high school guidance counselors or a business’s human resource staff.”

3. Capture the stories. Listen. Hold listening and storytelling sessions. Records your observation with photos and videos.

4. Evaluate your culture and perhaps even change it. How does work get done in your organization? Does it fit with your strategy and goals? “As important as branding is, it is equally important that the culture is in sync with that message.”

These steps are pretty straightforward and perhaps obvious, but they require some skill to implement. Simon applies these steps to seven case studies to help you see how they work in practice. The case studies will help you to look at your organization differently.

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Categories: Blogs


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