If you've been following the election at all, you've probably noticed that some polls give very different estimates of who's likely to win the presidency in November. For example, at 1:00 PM EDT on Tuesday, September 27th [this will probably change by the time you read this]:

• The New York Times shows Clinton leading 45% to 42%
• The Los Angeles Times reports Trump leading 46.2% to 42.7%
• HuffPost Pollster shows Clinton up 47.6% to 44.1%
• Data analysis site FiveThirtyEight gives three different estimates:
  • Their Polls-only forecast is 55.8% to 44.2% in Clinton's favor
  • Their Polls-plus forecast (which includes such factors as the economy and event-related spikes in either candidate's favor) is 55.2% to 44.7% in Clinton's favor 
  • Their nowcast (what they'd expect if the election were held today) is 52.7% to 47.3% in Clinton's favor

There are a number of reasons for this: they poll different people, using different questions, via different media. For example, polls that use only mobile numbers, and exclude landlines, tend to under-sample older voters. And wording changes as simple as which candidate is mentioned first by the poll can affect responses.

But the biggest differences may be caused by weighting, a method used to make the sample (which may be demographically different from the expected voter turnout) look like the population. Each organization uses its own weighting algorithm, leading to a diversity of predictions. In fact, the New York Times recently shared poll data it had collected with four well-respected analysts.

Even with the exact same data, the different weighting methods led to results varying from a four point lead for Clinton to a one point lead for Trump. That's because each organization has a slightly different idea of what the electorate will look like in terms of gender, ethnicity, education, socio-economic status, etc. These assumptions about who will vote influence what the polls tell us.

One thing is pretty clear: this will be a tight race, and people seem more emotionally invested in it than they have been in many recent elections. And given last night's debate, the numbers will likely fluctuate in the upcoming days.

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Interested in learning more about how to interpret data? Take HBX CORe and discover the basics of Economics for Managers, Financial Accounting, and Business Analytics.

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This article was originally posted to Fortune Insiders and can be found here.

If you, like me, have children, you’ve probably become convinced that the most common word in the English language is “no.” In fact, you may have concluded that “no” is the perfect sentence unto itself — no modifiers, adverbs, or adjectives needed. It’s always on the tip of the tongue with offspring around, no matter the question. “Dad, can I …” “NO!”

The word is also one that children learn to use frequently because of how prolific we parents are in uttering it. It is among the most common first words an infant says. They say it to siblings, to us, and to playmates. It’s just so easy to say — until, that is, we become adults in the working world.

At that point, the word seems to get lost. Why? Warren Buffett famously said, “The difference between successful people and very successful people is that very successful people say ‘no’ to almost everything.” But if that’s true, then why does the word go missing from our vocabulary? Why do we become selectively dumbstruck?

Volumes have been written about this, but the most common explanation is that we are wired to avoid conflict and to seek approval from those around us. So we often say “yes” even when we don’t mean it. In almost all situations, this is bad. A wedding proposal, a request to do something shady, agreeing to pick up somebody at the airport — saying yes when we don’t mean it can be a really miserable experience.

So, how do we say no? If you accept the premise of why it’s hard to say, then you need to find ways to lessen the likelihood of creating a conflict or disappointing someone.

First, remember that saying “no” by itself is almost always provocative. So one key is to provide context when responding to a question or request. People are much more likely to accept a “no” when they understand the train of thought that led to your response. “No” or “I can’t” should always be followed by a “because” clause. For example: “No, I’m not going to be able to get that report done by Tuesday because I’m concerned that rushing it will mean we have inaccurate data.”

I’m not suggesting that such an answer will always be well-received. Interactions between humans are rarely that simple. But by providing a “because,” you have offered information that can be the basis of a discussion if the other side pushes the issue. Without this qualifier, defenses immediately come up and all parties can quickly feel aggrieved.

In addition to explaining your refusal, saying “no” can be more effective if the word “no” is never actually part of the response. In place of it, use information and data to lead the requester to understand they are being turned down.

Using the example from above, let’s suppose my boss asks me if I can get the monthly production report done by Tuesday. The response I suggested above still has a bite to it because it begins with “no.” What if, instead, you responded, “I’m not sure if you know, but I need to gather information from our global sites and I’m concerned that if we don’t give them time to respond, the report will be less useful.” As long as the information presented is legitimate, this can be an effective way to respond without ever having to say the dreaded “no.”

Take it from Mahatma Gandhi: “A ‘no’ uttered from the deepest conviction is better than a ‘yes’ merely uttered to please, or worse, to avoid trouble.”

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The U.S. Competitiveness Project is a Harvard Business School initiative led by Professors Michael Porter and Jan Rivkin. This year's report was released today and included research from HBX Professor Mihir Desai on U.S. tax reform. Professor Desai teaches the new HBX certificate program Leading with Finance.

Harvard Business School (HBS) launched the U.S. Competitiveness Project in 2011 as a multi-year, fact-based effort to understand the disappointing performance of the American economy, its causes, and the steps needed by business leaders and policymakers to restore economic growth and prosperity shared across all Americans. Read the full report here.

This year's report outlines an eight-point plan for restoring U.S. competitiveness. Professor Desai's research focuses on tax reform, an area where much attention is given. According to Professor Desai's research, "tax reform is the single area with the greatest potential for immediate impact on the economy and is long overdue given changes in the global economy. Corporate tax policy has become a key obstacle to U.S. competitiveness and economic growth, and reforming both corporate and personal taxation is essential to achieving a sustainable federal budget."

The report goes on to say, "the top corporate tax problems, according to the surveyed business leaders, are the high corporate tax rate and the taxation of international income. Business leaders reported overwhelming and bipartisan support (over 95%) for corporate tax reform...The feasibility of corporate tax reform is promising given the broad consensus on the nature of the problem and the required direction for reform."

The report calls on leaders to be frank about the challenges the U.S. faces and to work harder to move the U.S. economy in the right direction. "To achieve the right kinds of tax reform, leaders must begin to speak more realistically about the fiscal realities America faces. In addition, simplistic polarizing and protectionist rhetoric must be avoided. The time for tax reform is long overdue."

Read the full press release on the U.S. Competitiveness Project here.

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Professor Desai teaches Leading with Finance, an online program designed to provide business leaders with a thorough understanding of the principles of finance and a toolkit for making smart financial decisions. 

 

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Graphs can be an effective way of communicating information about data. However, when poorly used they can be confusing, inaccurate, or misleading. Thanks to the internet, many of the worst displays of data remain long after their creators have identified the problems and corrected or removed them. Here are five of the more egregious instances that have shown up over the past few years.

1. The pieces of a pie should add up to 100%.

There's a couple of things wrong with this graph. First, any chart (such as a pie chart) that divides a single image into subsection should sum to 100%. This chart shows distinct stripes, but clearly if 88% of organizations raise funds via one-on-one solicitations and 87% use direct mail, there must be some overlap. Secondly, the four categories are virtually the same size, but there's about six times as much ink for Direct Mail (which 87% of organizations use) as for Special Events (which 88% use).

2. Shapes have meaning.

This chart does show about 100% in each column of figures, but the choice of shape makes it confusing. The different parts of the map have distinct meaning, beyond the demographics listed. Given this, it looks like Asians only live in Maine and Washington and that Texas existed only in 2010.

3. Start numbering at zero.

One common problem in graphs is misuse of the y-axis (the vertical axis at the left of the graph, which often indicates frequency). The y-axis isn't labelled here, but it looks like it probably ranges from about 73 to 78, which makes the drop from 77.3 to 75.3 seem precipitous. But if the graph covered a more reasonable range of knuckleball speeds (say 40-100 mph), the decrease would seem much smaller.

4. Numbers should read up from zero.

In this case, the y-axis has actually been inverted, so that the highest numbers are on the bottom. Logically, there's no reason you couldn't make a graph like this, and the graph does include the scale of the y-axis. However, we're so used to seeing graphs with the high numbers on the top, that we automatically assume that the change after 2005 is a decrease, when it's actually an increase.

5. Use the same scale for both axes.

The lack of labeling on the y-axis is particularly confusing, because it appears that the two lines on the graph are using entirely different axe. The change in both lines appears to be about the same, even though one change is almost 30 times as great as the other (the red line goes up 37,250 and the pink line goes down 1,071,987). Furthermore, on the left side of the graph, the smaller number is on the bottom, while on the right side, the smaller number is at the top.

Graphs can be a great tool to tell stories about data. However, just like language, images can confuse or deceive. So it's worthwhile to be a conscientious consumer of data and make sure that the pictures you see accurately reflect the numbers.

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Interested in learning more about how to interpret data? Take HBX CORe and discover the basics of Economics for Managers, Financial Accounting, and Business Analytics.

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This post was originally published on Fortune.com.

By soliciting ideas from large groups, the U.S. can come up with the right policies to reform the nation’s tax code — similar to the way complex computer systems are managed around the world.

Complaining about the complexity of the tax code has become a treasured ritual during spring tax season. The code has grown ever more complex and this complexity has considerable costs. As one example, the incredible complexity of tax incentives for education limits uptake and redistributes wealth away from those targeted and toward sophisticated taxpayers. How could we transform this ritual of complaining into spring cleaning?

Addressing complexity in the tax code requires analogizing to other complex systems and drawing on the research that demonstrates how to manage that complexity. Indeed, there is a well-developed literature on how to manage complex systems that can provide the foundation for simplifying the tax code. In particular, we know a lot about how to manage the evolution of software codes. This analogy yields two primary lessons.

First, “over the wall” engineering is highly problematic and “concurrent” engineering is preferred. Throwing completed ideas “over the wall” to the next part of the production process limits learning and engenders complexity relative to a concurrent and iterative production process. Currently, policy ideas are often developed without a clear vision of the associated language and with even less attention to the perspective of administrators. As with software, this yields bulky and contradictory language that could be avoided if the practice of policy formulation and drafting were a collaborative activity with the administrative agency in charge of enforcement. While the 1998 IRS Reform Act calls for such an approach, the reality does not live up to the law’s aspiration.

Second, and more radically, we should embark on an effort to crowd source the code. Much as the development of software capitalizes on a distributed talent pool, our legislative and regulatory processes on taxes could be opened up radically during comment and drafting.

Currently, the code is managed much as it was 50 years ago – in a fundamentally closed manner. Laws and regulations are drafted by small groups in a non-transparent way that pays little attention to the overall architecture of the tax system. As a consequence, vested interests can influence the management of complexity toward their advantage and complexity grows by ignoring interrelationships.

Research shows that effective management of complex codes – be it Linux or the tax code – requires three things. First, the code must be mapped so that the interrelationships, technically and conceptually, of different parts of the code and associated regulations and rulings become manifest. Second, this mapping enables modularization whereby the code is reorganized into pieces that reflect these relationships. Finally, this modularization provides the foundation for opening up the code to experts throughout society – so-called crowdsourcing – who contribute suggestions for rationalization and simplification.

By mapping, modularizing and opening the code and associated regulations, we could draw upon widespread expertise, provide transparency on a critical process, address the imbalance in resources between the taxing authority and sophisticated taxpayers and begin the process of simplifying the code and its administrative guidance. In the limit, one could imagine a detailed mapping of the tax code and associated regulations hosted by the IRS much as software code is mapped. This mapping would then serve as a guide to reorganizing laws and regulations over time. While decision making rights would remain with Congress and the IRS, opinions on policies would then be solicited widely and the drafting of laws and regulations could be aided by experts around the country through an open platform.

The commentary and drafting process that is so critical to policy formulation and administration would be completely open in real time. Such transparency is the only guard against capture of the process by vested interests and will allow for broad expertise to inform the highly complex matters that the code addresses. Even more than with software, there is deep expertise distributed broadly and government staff and the IRS could benefit immeasurably from this assistance. It is possible that more sophisticated groups with more resources will govern the process even with this open architecture. Hopefully, their efforts will be countered by other citizen groups and transparency will yield benefits relative to current processes.

Embarking on this process of crowdsourcing the code would bring our tax system in line with the way in which complex systems are managed around the world. Let’s all stop complaining about the complexity of the tax system and start contributing to its simplification.

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Interested in gaining a toolkit for making smart financial decisions and the confidence to clearly communicate those decisions to key internal and external stakeholders?

This post was originally published on Linkedin Pulse.

If you want to be a great negotiator, you have to be a great improviser. There’s no choice in the matter. You can’t script the process. It’s too unpredictable. The people you deal with will have their own ideas about how things should go.

That’s why we all can learn from master improvisers in other fields, especially jazz. I described a business application of this principle in one of my early posts. In another—on the importance of paying heed—I quoted pianist Herbie Hancock of sometimes being so focused that “I’m listening with my toes.”

Today’s negotiation lesson comes from trumpeter Miles Davis who said, “It’s the notes that you don’t play that matter.” 

I found another great example of how this maxim applies powerfully to negotiation in my colleague Deepak Malhotra’s new book Negotiating the Impossible. Right there on page 145 in bold type he channels Miles by saying: “Ignore ultimatums. The more attention you give to them, the harder it will be for the other side to back down if the situation changes.” 

He’s absolutely right. (I only wish the book was available back in January when I wrote a post on dealing with take-it-or-leave it job offers, as his advice applies there, as well.) 

When someone says, “absolutely not” or “it’s against company policy,” the natural impulse is to ask why or ask for an exception--or to challenge the assertion itself. But often it’s smarter to let the remark pass without comment. Your counterpart may have spoken in haste. Given time, he or she may soften their position—provided you haven’t reinforced it. 

The worst thing to do is to rise to the bait. Don’t ask if they really mean what they just said. If someone paints themself into a corner, why hand them another bucket? Instead, let the moment pass, as Miles said. It’s in the same spirit of the feisty credo of the actress Ruth Gordon (the star of the cult classic, Harold and Maude.) “I never face facts,” she said. “I never listen to good advice. I’m a slow starter but I always get there.” 

But what if your counterpart persists? Deepak recommends re-framing the ultimatum using less rigid language so it’s easier for them to back down. If not now, then maybe later. For example, say something like, “I can understand how, given where things stand today, this would be difficult for you to do . . .” 

Note how much those three italicized words pack so much meaning into that short phrase: 

• Understand is an acknowledgment that you have heard their problem, so they don’t have to state again;
• Today reminds them that things may change, especially if you can jointly tackle their underlying constraints; and
• Difficult sounds more pliable than impossible. It implies that somewhere within a tangled problem, there’s a solution struggling to find its way out. 

This style of response is what another colleague of ours, Deborah Kolb, calls a “turn.” It’s a deft rephrasing that keeps the door open for further discussion. Done well the transformation might take hold without even being noticed. 

Deepak realizes, of course, that some ultimatums are truly non-negotiable, but thinks there’s little harm in ignoring one when you first hear it. If it is real, he says, “they will repeat it over and over again, in all kinds of contexts and in all kinds of ways.” 

That advice reflects Deepak’s refreshing perspective on the overall negotiation process. He is skeptical about street wisdom such as never make the first offer, or always negotiate on your own turf. Depending on the circumstances, what would be right in one situation might be disastrous in another. 

It comes down to making judgment calls, he says, case by case. And that requires operating from more general principles such as controlling the frame, being mindful of optics, and helping others save face (all of which are factors in deciding how to respond to ultimatums). 

Thinking about the wisdom of (sometimes) not facing facts and ignoring ultimatums (at least the first time you hear them) reminded me of a case I was involved in years ago. I was a member of the local land use planning board. Seldom did all five of us agree on the applications that came before us. But in one instance, we turned down a developer’s proposal with an unequivocal five to zero negative vote.

When we announced our decision, the guy cheerfully said, “Okay. What’s the next step?” 

He acted as if he had just won the first round—which was nuts under the circumstances. Anyone with sense would have given up. But this fellow came back again and at least two more times after that. He revised his plans and we tweaked our policy. Ultimately his project got built. 

Hats off to him! And my guess is that Miles and Deepak would give him two thumbs up for ignoring our initial veto. 

PS: If you’re interested in learning more about Deepak’s work, here's a recent interview with him.

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There’s been a lot written about cognitive biases in the last decade. If you walk into the Psychology section of Barnes of Noble today or browse Amazon for “decision-making,” you’re sure to see a library of books on how irrational humans can be.

These human flaws, or biases, are fun to learn about—it can be amusing and informative for us to discover things about the way we may operate. In my opinion, most cognitive biases really stem from three core human distortions—a trio of errors that can befall even the smartest of fellows. This trio extends to all reaches of the globe and can afflict all individuals and businesses alike. In this series of posts, I’ll address this trio and what managers and employees can do about them.

So—what is the first of these three major biases?

Confirmation Bias

Anyone who has ever been in a decision-making meeting knows this bias well. Confirmation bias is the human tendency to search for, favor, and use information that confirms one’s pre-existing views on a certain topic. It goes by other names as well: cherry-picking, my-side bias, or just insisting on doing whatever it takes to win an argument. We all know someone like this. 

Confirmation bias is dangerous for many reasons, but most notably because it leads to flawed decision-making. Imagine a business considering launching a new product. The head of the company has the best idea for the “next big thing” so he directs his team to conduct market research to explore its feasibility. The team then conducts surveys, focus groups, and competitive analyses with this in mind.

I hope you see how there is confirmation bias all over this scenario. First, the company head is using market research as a sham to confirm his preconceived beliefs about a product idea. He’s not letting data do the talking at all. Next, the team is launching into the product development process knowing what their boss wants. As a result, the questions they craft for their research will likely be biased to give him the answers that he wants. While this is a hypothetical scenario, it’s all too common for companies to do this today.

How can you, as a business leader, combat confirmation bias? Taking a page out of a statistics textbook may actually be helpful. When gathering data, it’s always important to remember that the question you ask and your method of measurement will have a big impact on your results. When conducting a survey, for example, what you get depends upon what questions you ask. And what questions you ask depends upon what answer you want to get. Make sure to try to craft unbiased survey questions and have an objective third party vet your survey before releasing it. For example, instead of asking, “Do you think x is a good idea for a product? Would you be interested?” you might ask consumers to rank features of products in the form of a conjoint analysis to discover their preferences.

Another option would be to appoint someone on your team to play the role of a “devil’s advocate” when a big decision needs to be made. A devil’s advocate is someone who takes a position they don’t necessarily agree with for the sake of debate. Does your company create dissent in its decision-making process?

Confirmation bias is also the culprit behind many regrettable hiring decisions. Think about a traditional hiring process. HR or a hiring manager typically sits down with a candidate and asks them to sell themselves to the company. If they like the candidate, they might even give them a softball question about weaknesses for them to knock out of the park, just to assure themselves they are going with the right person. If all goes well, they then proceed to ask the person trying to get the job to provide their own references. How much negative or even neutral information do you think is revealed about the candidate in this process? Probably little to none. For many companies, the whole process is nothing more than a series of confirmatory checkboxes on the way to hiring the wrong person. And the result? Employee turnover and big headaches.

A better way would be to structure the interview process completely around disconfirming evidence. “Why aren’t you the person for this job?” “What did you hate about your last job?” Ask references for contact information of other employees that the individual worked with. They are much more likely to provide an objective perspective on their work.

Confirmation bias is extremely difficult to overcome, in both our personal and professional lives. Humans don’t like to be wrong and we will search for any evidence to prove the path we are pursuing is right. But, through some of the strategies above, you as a manager can stir up debate and ask some of the tough questions necessary to become a more rational, and successful, organization.

To learn more about confirmation bias, check out THIS article from Scientific American.

Check out the second bias that befalls many organizations here.

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Taking the Disruptive Strategy with Clayton Christensen course was the first introduction I had to the idea of “jobs to be done.” Professor Christensen's theory essentially explains that people “hire” different products to do “jobs” that they need done. Sounds easy enough, right?

That’s what I thought, too. But, the more I thought about it, the more I realized that I didn’t really understand it. Certainly, things in the course helped me better grasp the concept. I could explain the theory to you, give you examples, but I was still missing the deeper understanding of where I could apply it to my everyday life.

I finally had my “ah-ha” moment when I was riding with my mother in the car and watching her simultaneously put on makeup, drive, and talk on the phone. Here is what I learned from this terrifying experience.

1. Observe

You can’t find jobs to be done without observing people. This was my first lesson. Maybe it was the fact that I was scared for my life. Maybe it was because I have seen many women struggle to drive and put on makeup. Whatever the reason, it was in that moment with my mom where my time spent thinking about jobs to be done clicked.

The thought popped into my head, “how could I make this easier and safer?” Then I made the important connection, what was the job to be done here? Help me put on makeup and drive safely? It was the mindset of not taking an idea and then defining a job to be done, but rather observing people and asking the important question, “how could I make this easier/cheaper/better” that led to me seeing a job to be done that my mom could hire a product for.

2. Focus on the Job, Not the Product

Upon further reflection I realized that in that moment of terror and enlightenment, I wasn’t at all worried about the product. Jobs to be done isn’t about the product; that comes later down the line. I had been so focused on the development of the end product that I missed the bigger picture. Finding the product is the end goal in most brainstorming sessions and I think, because of that, we tend to miss the bigger picture: What job are we hiring for? The product will come once the right job is found. That is the truly difficult part.

3. It is a Process

This is a process, a way of thinking. First, I had to understand the theory. I spent time with it and the cases; I thought about it while I was walking around, trying to apply what I'd learned. But, it wasn’t until my understanding of – and mindset towards – the concept had changed that I finally witnessed it firsthand with my mom. I wasn’t contemplating the theory when I was watching her, I was just sitting there with my life flashing before my eyes. But the theory had become a part of my outlook on the world, part of me, and because of that I was able to make the connection.

Maybe jobs to be done is easier than I made it out to be, but for me there was a difference between being able to explain it and find a "job to be done" for already existing products, and identifying a job to be done in real life, from which a product could be developed.

Learn more about Professor Christensen's "jobs to be done" theory HERE.

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Want to learn more about "jobs to be done" and other theories from Professor Christensen? Disruptive Strategy will equip you with the tools, frameworks, and intuition to make a difference.

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For many people in the workplace, finance is a department shrouded in mystery. But finance affects each and every person in a company – it explains how their actions impact the company’s success, creates guidelines for the future, and sets meaningful metrics to determine performance. But what if you could see inside the mysteries of finance? How can understanding finance benefit you?

1. Learn how to analyze performance for your department

Finance gives you the tools you need to determine how well your department is performing, both by itself and as part of the greater company. Are you doing well? Who should you be compared to? What measures should you use for performance? Many companies choose the wrong metric for performance, or use the same metric for every department, and miss the unique ways in which each department contributes to corporate profits. A company that measures performance strictly in increased revenue targets, for example, may entirely miss the costs of increasing those targets (even as they may grow higher than the increased revenue!).

2. Interact better with your company's finance department

Many people think of their company's finance department as gatekeepers – a group primarily designed to say “no” to promising ideas. With the language of finance and an understanding of the factors they are considering, your finance department can become your partners, improving ideas and generating value-creating opportunities.

3. Unlock the true sources of value creation

Where does value come from? How do you improve your company’s worth to investors and the public? Is the project you’re working on actually making the company better off than if it were not done at all? Finance gives you the knowledge and the skills to answer these questions and to ensure that every project you take on will directly and meaningfully impact your company’s success.

4. Understand that actions tell stories

Everything that you or your company does tells a story that will be interpreted by someone else. What story are you telling? Are you accidentally sending a signal to your investors that hard times are coming? Or are you intentionally ensuring that your actions line up with your words and paint an accurate picture of the future of your company? In a world where investors must make guesses about what goes on inside a company, everything is analyzed – are you sending the right messages?

5. Appreciate the impact of your job

Ultimately, every position impacts the bottom line of a company. But how? It’s easy to see the impact that the Sales department may have on increasing revenues, but what about the IT department? Or accounting? Every department makes a measureable impact to the success of the company, and understanding the impact of your own job, using the tools of finance, can be the best first step to reaching a higher level of performance.

6. Understand investing and capital markets

Everyone interacts with capital markets, whether they know it or not. Your retirement fund is likely invested in a pension plan. Your personal investment portfolio is managed through a broker or packaged in a mutual fund. Finance can help you understand what makes a good investment – the places that can give your savings a secure and prosperous place to grow and multiply. Equally as important, it can show you what people are looking for in terms of investments and how your actions at your company can help to give it to them.

Finance doesn’t have to be a mystery. It can instead be the secret to your – and your company’s – success.

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Interested in gaining a toolkit for making smart financial decisions and the confidence to clearly communicate those decisions to key internal and external stakeholders?

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This is an excerpt of a post that originally appeared on Flarrio.

In my last post, I looked back some of the key lessons that have guided the development of HBX, the online learning platform of Harvard Business School, to date. So, what does the future hold?

Given how fast technologies change, are adopted, and abandoned, that’s difficult to say. That said, at HBX, we are actively trying to address several questions:

How Does Mobile Factor in to Our Strategy?

For example, how does online learning translate to a mobile device? Given the ubiquity of mobile phones and tablets, this is an area where the borrow/release principle will play in a big way. Trying to adapt the desktop platform completely to a mobile one may not be the best path forward for us.

However, there is much to borrow not only from our own platform and other mobile ones but from some of the technologies mobile devices offer. Geo-location is a wonderful example. How might this capability allow online learners to connect in person to form study groups or work on a project? The cameras on mobile equipment also suggest an opportunity. For example, could student-supplied videos and pictures augment a case discussion?

How Can New Technology Enhance Peer-to-Peer Interaction?

In addition to this work, we also are considering how peer-to-peer interaction in the context of a case activity might be facilitated through new technologies or adaptations of current ones. In the Harvard Business School’s negotiations course (offered in the on-campus MBA), students are asked to pair up and negotiate with each other after each is given information that allows them to take on the role of a principle in the negotiation. In the physical classroom this is easy. And certainly technologies exist online that would facilitate such a scenario in the virtual world (e.g. Skype).

But if we are to create a seamless experience for our learners conducting a negotiation exercise on our platform then it should be as easy as turning to the person next to you in a physical classroom. This is where the principle of student first comes in. What role could virtual reality (VR) play in this case? As more smart phones ship with VR goggles and full-featured goggles come to market, could students feel as if they were in a boardroom in New York City sitting across from a counterpart, negotiating a major merger? And even if they could, would this have value?

What Value Do These Technologies Add?

It is that question – would this have value? – that we must not lose sight of. Technology for technology’s sake is the express lane to irrelevance, poor learning outcomes, and user frustration. We must push boundaries, but not at the expense of students actually learning. This is our EdTech Hippocratic oath.

Immediately after graduating from college, I served four years in the US Air Force operating intelligence satellites. Inevitably, when I told people this is what I did, they asked, “Can you really read a license plate from orbit?” I was not allowed to answer, but I always turned the question around: “Why would you want to?” There are easier ways to track somebody and, in any case, the laws of physics don’t allow a satellite in low earth orbit to “hover” over a location despite what the movies show you (although this is something drones can now do). The message was this: just because technology can do something doesn’t mean there is efficacy in doing it. And this couldn’t be truer than in the digital education space.

I am confident that we will be surprised and amazed by how technology will revolutionize education in the years to come. I am also confident that some will use innovations even when they do little to further learning. But by focusing on student first, reinforcing community, and borrowing what works and releasing what doesn’t, we believe it’s possible to create a rich, immersive educational experience that stands the test of time … at least until somebody invents a Holodeck.   

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