How Diversity Powers Team Performance 01-07

The topic of workplace diversity has vexed businesses and employees for decades. Increasing diversity has long been promoted as the right thing to do, but that notion could be viewed as simplistic and ignoring the deep benefits that inclusion can bring to an organization. Scott Page, a professor of complex systems at the University of Michigan, tackles the issue in his new book, The Diversity Bonus: How Great Teams Pay Off In The Knowledge Economy. He discussed why diversity must be more than “feel-good metaphorical statements” on the Knowledge@Wharton show, which airs on SiriusXM channel 111.

Knowledge@Wharton: What drove you to research this topic?

Page: It’s a little bit of a C.P. Snow moment. He was the British academic who said there are two academies: science and arts. Within the University of Michigan or almost any university, you’ve got people in the humanities and in the arts and philosophy departments talking about the need for inclusion on normative grounds, a sort of moral case for a more integrated society. Over in computer science and ecology and business, there are all these people showing in a knowledge economy this incredible value from people who have different perspectives, different ways of looking at problems, different tools.

On one side of campus, there’s a whole bunch of people talking about the pragmatic benefits of diversity. On the other side, people are talking about the normative benefits. They weren’t communicating with one another. I saw this as a real opportunity for a fruitful conversation.

Knowledge@Wharton: Don’t you think this “right thing to do” mindset about diversity feels a little patronizing?

Scott Page: It does in a way. We want our firm to look like America or have people that come from all these different categories, as opposed to asking whether we are bringing in people who can help us fulfill our mission or be better at whatever it is that we do as an organization.

Knowledge@Wharton: Are we seeing a significant shift in companies thinking more deeply about diversity in the workplace?

“The talent of the team depends on having diverse people on that team.”

Page: I think you’re seeing a real shift as the nature of work changes. One of the tropes I use in the book is: Think about a firm that’s hiring people to do physical labor like chopping down trees. In that world, you can figure out someone’s ability, which is how many trees they can chop down. If you’re hiring 10 people, you should hire the 10 best people, and to not hire someone because of their race or religion or gender would be discrimination. Going back to the civil rights movement, that’s how a lot of this was framed. You shouldn’t discriminate. You should hire the person who has the most ability.

Think about Apple: That company generates $2 million in revenue per person. No one in Apple is chopping down any trees; they’re working on really hard problems. As evidence begins to accumulate, it’s becoming clear that you want smart people who think differently, who have been trained differently, went to different schools, have different knowledge bases. The talent of the team depends on having diverse people on that team. This has become something that everyone has started to recognize as more and more data rolls in showing that to be true. You end up with firms recognizing that cognitive diversity is a strategic asset.

Knowledge@Wharton: There are concerns that Silicon Valley is not diverse enough in terms of women working at these companies. Diversity isn’t just people of different backgrounds. There’s also gender diversity as well.

Page: Right. Identity diversity is a difference in who we are. Cognitive diversity is the difference in how we think. If you’re Apple, if you’re Google, if you’re Amazon, the question is, does identity diversity matter? The evidence shows it matters in four ways. The first is syllogism. If you and I come from different identify groups, we have different knowledge bases. You search different things on the web than I search. We read different books. We have different interests.

On some problems, identity diversity correlates with cognitive diversity. It’s also true that if I’m sitting in a room of people who are all trained like me and look like me, I don’t think as hard and don’t feel the need to explain as deeply. Imagine you’re designing a building and put a blind person on your team. You’re going to think about the building entirely differently just because that person is in the room. Or if you put a physically disabled person in the room. Just being around difference, that’s the second thing.

The third one is the things we see as problems vary depending on our identity. Where we want to devote our energies is a function. Having more people from different identity groups in the room just leads to more possibilities, and that is well-documented.

The fourth thing, and I think this is the one that people miss, is that all these women who are not in tech because they just don’t feel comfortable there, or people of color who are not in tech because the culture just doesn’t fit, you’re not only missing out on talent, but you’re also missing out on diversity. Because when you make the pool bigger, you’re just going to get more diversity. Even if women work differently than men, just by having a larger pool, you’d have more diversity.

Knowledge@Wharton: You’re looking at the benefits, but diversity can backfire on companies that don’t commit to a meaningful policy.

“If you don’t bring a lot of diverse lenses to bear, you’re likely to have blind spots and make mistakes.”

Page: Absolutely. If you think of how a consulting company comes in and does an evaluation, they’ll ask, how does this affect people? How does it affect process in terms of the organization? Is there risk? How are competitors responding on a list of dimensions with which you evaluate a business decision? If you don’t bring a lot of diverse lenses to bear, you’re likely to have blind spots and make mistakes.

What I’m trying to do with the book is speak math and logic to metaphor. You know how people say, “Oh, diverse perspectives are useful,” and that sounds like a reasonable thing? You want to ask, what do you mean by diverse perspectives? And what types of perspective are useful? You want this to move in the direction of science and away from feel-good metaphorical statements about different people being in the room.

Knowledge@Wharton: There is a trend of companies wanting to build teams. The days of giving a project to one person and having it done a month later are going away, so the need to have different ideas is more important than ever.

Page: That’s exactly right, and the reason why is because everything is so connected now. When I think about any sort of business policy, there’s an environmental effect, there’s an energy effect, there’s a personnel effect. No one’s going to have the bandwidth to think of all the dimensions to a problem. What you see within universities and within organizations is this rise of team-based work. The effective teams have to be diverse when the problem is hard.

One of the things I play within the book is what I call the opposite proverbs problem. It’s like anything your grandfather said, your grandmother said the opposite. A stitch in time saves nine. He who hesitates is lost. Too many cooks spoil the broth. Two heads are better than one.

It’s not the case that you always want a team. But firms are figuring out that where you need teams are on high-dimensional, complex problems. I’m a professor of complex systems. When I look at complexity, whether I look at ecosystems or engineered systems, I realize the way to cope with complexity is through diversity. The right way to harness that complexity is through diversity. Not all diversity. Don’t turn that dial all the way to 11. There’s an appropriate amount and an appropriate type. I think firms have seized the new challenge: Who should be in the room and how do we get the right people in the room, interacting in the right ways, to lead us to innovative, new ideas and products?

Knowledge@Wharton: You could take this philosophy well beyond the company and put it into society.

Page: Absolutely. The reason the book is called The Diversity Bonus is that it’s not a marketing ploy, it literally is a bonus. One of the most amazing pieces of research that I talk about in the book is a study that looked at 28,000 predictions by economists over a 40-year period. The best economist is 10% better than a random economist. If you average the best economist with the second-best economist, who is 9% better, you get 18% better. Bringing somebody in who is demonstrably worse makes you better because of the fact that they’re different. There literally is a bonus. It’s not marketing. It’s math.

Knowledge@Wharton: That’s why the more perspectives you can bring to a problem, the greater the potential benefit.

Page: With one caveat: They’ve got to be good. This is the challenge, the deep paradox that lies in this sort of logic. If it were possible to create 100 ways of looking at a problem that were all good and diverse, we could nail everything. Therefore, it’s got to be impossible to do because these things are just not predictable. But the point is, typically two is better than one, and three is probably better than two. You may not want to have 15 different ways because you might not be able to provide fuel for 15 reasonable ways of looking at a problem.

“You want diversity to move in the direction of science and away from feel-good metaphorical statements about different people being in the room.”

Knowledge@Wharton: How does all this apply specifically to the knowledge economy?

Page: First, I see increased reliance on teams. I also see firms casting a much wider net in terms of who they hire. A third thing you see when organizations go into a 360 on errors, they’ll ask, “Why did we make this mistake? Is it because we didn’t have someone in the room who would have seen this?”

Sometimes you place your bets, you take your chances, and things are going to work out or not work out. Other times, you just completely forget to look at a particular dimension and realize next time we make this decision, we’re going to have someone from the unions in the room. Or next time we make this decision, we’re going to have someone who knows logistics in the room. You want to make sure that you’ve got the right level of diversity to cover all the bases.

Knowledge@Wharton: Workplace culture is also a factor in the success of diversity, correct?

Page: Ten years ago, I wrote a book called The Difference, which is kind of a mathematical book about the role of diversity in complex systems. Because of that book, I got invited to a lot of high tech firms, including Boeing, Yahoo, Google, Ford and NASA, to talk about the mathematics of diversity and things like random forced algorithms — really geeky stuff.

You go into those places, and you’re like, “Oh my gosh, every one of them is so different.” There’s the famous David Foster Wallace quote where there’s two goldfish swimming in the water and an older goldfish comes up and says, “Morning, boys. How’s the water?” They’re kind of confused. He swims off. Then one says to the other, “What the hell is water?” You go into these firms, and it’s like the water is different in every place. One of the things that’s so important is making sure that you have a culture where people feel comfortable sharing their diverse ways of thinking. If you look back at the O-ring disaster with NASA, that’s a case of a culture where people didn’t share what they know.

Knowledge@Wharton: In the book, you link diversity to the U.S. Supreme Court and some of the decisions by Justice Antonin Scalia.

Page: There was a famous Supreme Court case, Grutter vs. Bollinger, involving the University of Michigan, where Scalia says Michigan has a choice. You can be diverse or you can be excellent. I think “super-duper” is the phrasing that he used. So, it’s a choice between super-duperness or diversity. If we were admitting students and they were going to go chop wood, he’d be exactly right. My point is not that Scalia is wrong. My point is that there are places where Scalia is right, namely chopping wood, but there are other cases where Scalia is not right, and that involves almost anything that’s complex. The fact is, if we really want to be super-duper on complex problems, we have to be diverse. There’s no trade-off.

I think Scalia was kind of pernicious about it. We get back to your earlier comment that it seems patronizing. Well, we’re including some diverse people because we want to do the right thing here. If I really wanted to figure out obesity or the opioid epidemic or inequality, or write a health care plan, the idea that I wouldn’t be bringing people of every race and both genders from different reaches of the country just doesn’t pass the sniff test.

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How a Student Competition Led to a New Cyber Security Approach 11-19

Cybersecurity is a big concern for nearly every industry. But for the banking sector, that concern is paramount and the arms race to stay ahead of digital criminals requires innovative thinking. That’s why the London-based SWIFT Institute, set up by the Society for Worldwide Interbank Financial Telecommunications to enable cross-learning between academics and bankers,  issued a challenge to teams of Canadian university students to come up with new ideas.

The winner, Team Pulse OS, devised a process that allows for reliable early detection by analyzing the unique power-use signatures on mobile devices. Team leader Nataliya Mykhaylova, who is pursuing a doctorate in chemical engineering at the University of Toronto, discussed her project with Knowledge@Wharton following her win at the October 2017 competition. Peter Ware, director of the SWIFT Institute also joined the conversation about cybersecurity.

An edited version of the transcript follows.

Knowledge@Wharton: What prompted the SWIFT Institute to devise this competition?

Peter Ware: We launched the SWIFT Institute Student Challenge last year primarily to engage with students. Part of what the institute does is give research grants to academics. We’ve been dealing with academics for about five years now, so we wanted to go beyond that and try and tap into some young, upcoming, engaging minds.

We linked this specific challenge to a conference that we held in Toronto called Sibos. We thought that we would focus primarily on students at Canadian universities. Before the challenge started, we went to the Canadian banking community and asked, “what is at the forefront of your minds? What is keeping you awake at night that we can try and help you solve?” Unsurprisingly, it was cyber. They helped to find the idea of trying to protect a bank’s channels to its customers from cyber attacks. That’s the challenge that we put to students.

Knowledge@Wharton: Nataliya, why did you want to be a part of this competition?

Nataliya Mykhaylova: I was excited to hear about this competition because cybersecurity was something that is really big on everybody’s mind. A lot of the attacks right now are undetected. I have been kind of researching this field from the hardware side. Doing my Ph.D. at the University of Toronto, I was testing different devices and got lots of ideas about how this could be prevented on a hardware level. I was really excited by this competition and thought I would submit my ideas.

Knowledge@Wharton: Tell us more about your winning idea.

Mykhaylova: You hear on the news all of these companies that have an issue with cybersecurity. What I noticed when looking through those cases is that there is a lot of effort being put into preventing the attacks, which is understandable. But I noticed there is not quite as much attention being spent on detecting those things early. In fact, only 30% of the cyber security attacks are detected in-house. This is a huge problem. There are lots of creative ways in which those attacks happen, and we need better systems to detect them at the edge or before they have a chance to spread.

“There are lots of creative ways in which cyber attacks happen, and we need better systems to detect them at the edge or before they have a chance to spread” –Nataliya Mykhaylova

When I was doing my Ph.D., I was assembling and testing different devices, different sensors. I discovered there is this pattern that you can detect and correct through artificial intelligence models. And you can actually detect the changes in those patterns very early. For example, if the system is compromised even in the early stages, those performance signatures — like heat, CPU, other patterns — change very quickly. You are able to differentiate them from the normal operations of the system. Basically, an attack would leave a series of breadcrumbs as they are compromising the system, so you can detect them before it has really a chance to spread. This was an interesting discovery. This is something that inspired this idea going forward.

Knowledge@Wharton: Do you give consideration to the fact that so much banking is done on mobile devices?

Mykhaylova: Yes. The interesting aspect of the system is that it can work across different types of devices. We are checking up on our accounts on our mobile devices all the time — our  laptops, our desktops. You have to have a system that works effectively throughout interfaces so we can detect things before they have a chance to spread through the banking channels. Part of this system is going down to the very low level, to the hardware level.

With each new version of these devices, they have better and better ICs, the integrated circuits that go into those devices. A lot of them are now able to use features that allow us to run machine-learning models in real time to be able to detect changes in the operation of the systems.

This is a very interesting area, and I feel that it’s been unexplored. This is something that we have been doing, and realizing that there is a lot of opportunity to explore those parts of the system. Because this is something that is much harder for the cyber attackers to fake, they cannot really change the hardware patterns as easily as they would be able to change the software that is running on the system and to hide their traces.

Again, this is something that can be deployed running across the devices, so this makes it very powerful to be able to run the script on your cellphone, on your tablet, on your laptops.

Knowledge@Wharton: Peter, what is the significance of what she is describing?

Ware: It’s something that is very useful, and quite advanced and different from what I think a lot of banks have been looking at. A lot of the ideas that came from other teams in the challenge were all very good ideas. They were dealing with things such as four-factor authentication, voice and facial recognition. But this was a very unique approach from Nataliya, the idea of looking at pattern or usage recognition on our devices. It’s a novel approach. It’s something that, hopefully, banks can take forward and try to implement.

Knowledge@Wharton: Has there already been a reaction from banking institutions to the ideas generated by this contest?

Ware: It was actually the banks that voted on Nataliya to be the winner. We had a panel of four judges, which included some bankers from within Canada and some fintech experts, and we did audience voting online as well. It was the banking community itself that voted on the winner. There was also a lot of engagement among the banks and Nataliya and the other team members. A lot of these ideas are going to be taken forward, I am sure.

Knowledge@Wharton: Is there any possibility that some of those institutions will get involved in developing this idea?

Ware: That is something that would happen directly between the banks and Nataliya, so it is something that we are trying to foster. We are trying to foster that engagement and contact between the banks and the students. What happens next is something that is on a direct relationship between the two of them.

Knowledge@Wharton: Nataliya, can your idea be adapted and applied to sectors beyond banking?

Mykhaylova: I am really interested in potentially scaling this solution. I am passionate about cybersecurity, and I think banking is a great place to start. But I feel like every day we have new channels through which we interact with the world, and we have new devices in our homes through which we interact. We have IoT devices [internet of things], we talk to Alexa and so on. They are really easy channels for attackers to get into our system. I think we can make pretty much any channel more secure.

We have already started conversations with some banks in Canada as well as internationally, so I am very fortunate to have been part of the Sibos competition. But there is a lot of interest I received from the IoT technology sector, which is developing these devices that we all have in our homes now. I am quite excited about the interest and potential scalability of this.

Knowledge@Wharton: The SWIFT Institute will have its 2018 conference in Sydney, Australia. Do you plan to stick with cybersecurity as the theme?

“I am passionate about cybersecurity, and I think banking is a great place to start.” –Nataliya Mykhaylova

Ware: We are going to run the Student Challenge again, but we will come up with a different idea. We’ve gone to the Australian banking community and explained the concept of the challenge to them. There is a great deal of excitement there. They are in the midst of coming up with the idea that is relevant to their community. At this point, we don’t know what the idea is. We have already contacted 43 universities across Australia to explain what Sibos is, what the SWIFT Institute is and the idea behind the challenge. There is a great deal of interest from universities.

Knowledge@Wharton: What are the next steps for you, Nataliya?

Mykhaylova: Our goal right now is to test this system on all of the possible use cases, finalize the models and launch it through a few partner banking institutions to really showcase the benefits that it could provide.

As I mentioned, it can be run on any system, it’s fairly low cost and fast to set up, it’s an easy solution to implement, and it could have a higher return on investments for banks. We are looking to finalize the model and launch it by next year.

Knowledge@Wharton: Banks operate on different systems. Was that a challenge for you in the process of developing this concept?

Mykhaylova: Yes. Banks have all of the infrastructure right now for various types of divisions and for most internal interactions between the employees as well as with the customers. That was one of the biggest aspects that we wanted to incorporate into this solution so that we could deploy a system at scale to detect issues before they have a chance to spread through the network, which I think is one of the biggest concerns with the recent cases of companies being compromised.

Ware: Even within a single bank, they have multiple systems. There are so many different mergers and takeovers that have happened over the decades, and they all have these legacy systems that they try and put together. The idea of Nataliya having something that could be relatively easy to implement is going to be music to the banks’ ears. It’s a great initiative.

Knowledge@Wharton: Do you have to consult with, in this case, the Canadian government for implementation?

Mykhaylova: To some extent. Currently, this system can be operated across a number of different devices and trained on a number of different systems. Right now we are starting kind of small, really validating on very focused case scenarios. But later as it expands, I do feel that it would be important to involve the government because cybersecurity is going to be key for all of our operations. It would be important to think about it on a larger scale.

Knowledge@Wharton: As banks have retreated from some places, a vast number of areas are becoming unbanked, and there is a tremendous increase in financial inclusion with some of the fintechs entering the spaces. Is the cybersecurity solution that Nataliya has proposed relevant to those kinds of entities as well?

Ware: I think it is. You’re absolutely right that the more fintechs open up their systems and create new systems to provide banking services to anyone and everyone around the world, it’s creating more opportunities for cyber attacks. A lot of those smaller fintech companies are not as well regulated, if they’re regulated at all, compared to the banks.

The security they put in place might not be as good as what the banks have in place. Nataliya’s idea could be very relevant to them, and I think it’s absolutely necessary that a lot of those fintech companies try to adopt as stringent security measures as possible.

“The people perpetuating cyberattacks actually operate as a business. They buy and sell information from and to each other.” –Peter Ware

Knowledge@Wharton: Financial institutions may be hesitant to partner with each other, but sharing information would help ensure everyone has a high level of cybersecurity. Do you agree?
Ware: Absolutely. Looking at how banks can share information is something that we have explored from a research perspective. Banks do share cyber-threat information with each other anyway, but we’re always looking for ways on how that can be improved.

The people perpetuating cyber attacks actually operate as a business. They buy and sell information from and to each other. From a protection point of view, the banks are increasingly starting to think along those lines as well. The same would be true for any other industry.

Knowledge@Wharton: Another concern for consumers is the speed in which the information from a breach is relayed to the public. Many within the IT community say time is needed to understand what happened. From that perspective, maybe Nataliya’s solution would speed up this process.

Ware: Exactly. The earlier that those threats can be detected, the more time that banks and anyone else would have to be able to react to it.

Mykhaylova: It takes an average of 98 days to detect an attack, sometimes after years. This is very crazy that we still have to spend so much time detecting those things. Part of the reason is that it is also becoming harder and harder to detect. There are new types of malware, new types of zero-day attacks and other threats that are becoming more and more common. So, it’s important to have systems that don’t need to be signature-based, that can detect those kinds of attacks without any prior knowledge of the threat. This is where our system excels, and it can detect patterns in an unsupervised manner. You don’t need to build up those signature libraries ahead of time.

Knowledge@Wharton: Do you think we will get to a point where potential break-ins are done and figured out in real time?

Mykhaylova: Yes, so that is the goal. Our system runs in real time, continuously tracking things, categorizing them and evaluating how risky they are. I think that is key to be able to do that in real time.

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The User Experience: Why Data – Not Just Design – Hits the Sweet Spot 08-03

The successful user experience is about meeting a consumer’s needs on an individual level – a “segment of one” not “one-size-fits” all, many experts say. But what does that look like in practice? “What really differentiates companies is their personalization through data — which allows them to build unique experiences that lead to increased engagement and better outcomes, …” write Scott A. Snyder, president and CSO of Mobiquity and a senior fellow at Wharton, and Jason Hreha, founder of Dopamine, a behavior design firm, in this opinion piece.

Today, design has a seat at the table. With the success of products like the iPod and the iPhone, businesses have realized that a good user experience is key for the bottom line.

Yet even with this determined focus on design, most digital experiences fall short of user expectations. Of the 700 million websites that exist, 72% fail to consistently engage users or drive conversions. Of the 1.6 million apps available, just 200 account for 70% of all usage, and three out of four apps aren’t even used beyond the initial download.

So where did things go wrong? Or more importantly, how can we get them right? Surprisingly, the answer does not lie with design. It lies with data.

Netflix is an example of a company that pays attention to user experience. Early on Netflix chose not to charge late fees, like Blockbuster did, in order to help build its subscription DVD business. Netflix soon put Blockbuster out of business, but also came under threat from other online video streaming businesses like Sling and Roku. Fortunately, Netflix was able to use its viewing analytics to create personalized content recommendations, and even create its own shows geared toward viewer interests, such as House of Cards and Orange is the New Black.

For Netflix, the user experience was the price of entry, and the viewing data they gathered and analyzed became the strategic advantage of the business. Because of their approach, we don’t order special TV/Movie packages anymore. Instead, thanks to Netflix analytics, we have our viewing experience tailored to who we are. This is one example of a new breed of data-driven user experiences created by companies like Amazon, Pandora, Sephora, Nike, Progressive and Disney.

Good user experience design has become table stakes. If you don’t do it well, you can’t even get out of the gate in this hyper-competitive digital world. What really differentiates companies is their personalization through data — which allows them to build unique experiences that lead to increased engagement and better outcomes for the user and company. However, there is a fine line between “helpful” and “annoying” in the digital world, and the price of getting your data-driven personalization right or wrong may be the difference between a delighted customer and one who will never come back to your brand.

Good user experience design has become table stakes. If you don’t do it well, you can’t even get out of the gate in this hyper-competitive digital world.

How Can We Achieve Truly Personalized Experiences?

There are three reasons why digital solutions fail to engage users long term and drive positive outcomes: segmentation, relevance and rewards.

1. Segmentation: Behavioral

Are you someone who likes competition and rewards? Or are you someone motivated by helpful nudges from friends and family? Do you respond to text messages during work, or do you catch up on your personal messages at night? Do you travel a lot? Do you have a “wearable” (or are willing to use one)?

These are the types of questions we should be asking our users. We can either ask them directly, or infer answers from user interactions and behaviors. People are all different — but you wouldn’t know it by looking at most digital products. The majority of applications create a one-size-fits-all experience that fails to engage even a fifth of those who sign up. The good news is that we have the ability to collect individual behavioral data from users so that we can segment them more accurately, and present them with experiences that speak to their unique experiences and preferences.

2. Relevance: Getting Context Right

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In order to deliver relevant, impactful interactions at the right moment, we need to understand each user’s context. But context is much more than just time (when?) and location (where?). With richer data being collected from both users and third-party sources, context is now evolving to include situation (what am I doing?) and emotion (how am I feeling?). An expanded definition of context is shown in the figure above.

(Reference: Mobiquity and Wireless Innovation Council Research, 2014)

With this multifaceted model of context, we move closer to the ideal “segment of one” (a unique profile for each user at a given point in time). You would not want to send weight loss content to a customer who is maintaining a healthy weight, or give a shopping coupon to a stressed out traveler in an airport security line. Context-aware applications like Google Now and Tempo AI (acquired by Salesforce) leverage a user’s calendar as a source of context, so that they know when a user may be busy, in a meeting or enjoying downtime. This information is used by these applications to adjust their content and experience to fit the context-determined mindset of each individual user.

Context-aware applications like Google Now and Tempo AI (acquired by Salesforce) leverage a user’s calendar as a source of context, so that they know when a user may be busy, in a meeting or enjoying downtime.

Most users are only willing to share their data if they perceive that they will get real benefits in return. More than 60% of consumers want real-time promotions, yet 67% don’t trust retailers with their data (Opinion Lab Survey, 2015). We have the opportunity to do better.

3. Reward: Overcoming the Effort versus Benefit Challenge

In order to get, you have to give. Unfortunately, most applications ask for too much and offer too little. Twitter It’s common for apps to have a long-winded sign-up process that asks you every question under the sun. This is not a recipe for success.

Popular applications like Waze and Pandora are case studies in proper information gathering. They provide us with immediate benefits right after we download their apps. Waze improves our driving route in exchange for our location. Pandora gives us a personal DJ, tailored to our tastes, in exchange for rating the songs we’re listening to. In both these cases, our effort seems minimal in comparison to the benefits we get back. Contrast this with the majority of digital solutions that ask for a lot of data (like registration, profile, location, etc.) before delivering one ounce of benefit. We have to “earn the right” to collect the type of data we need to appropriately segment users. We have to win the “benefit versus effort” trade-off with our users by providing them with immediate, tangible benefits and using the data being collected to further personalize their experiences.

Evolving to a Data-driven UX Approach

Eighty-six percent of mobile marketers have reported success from personalization — including increased engagement, higher revenue, improved conversions, better user insights, and higher retention. However, only 1.5% of apps personalize their experiences (Mobile Marketing Automation Report, VB Insight, July 2015). In order to get to true personalization, and deliver greater effort than benefit, we need to make our user-experience (UX) design data-driven.

A traditional UX design process starts with user research followed by user flow creation, persona creation, storyboards/wireframes creation, and (finally) a graphical mock-up or prototype of the design. The desired result of this process is a single beautiful design that attempts to deliver the best possible experience to meet the needs of all the different user types.

By knowing something about each user’s behaviors, motivations and contexts, we have the opportunity to deliver a variation of the core experience that is best suited to each individual user by using robust analytics and an adaptive user interface.

But the reality is that all users are not the same — and they don’t all want to interact with your app in the same way. By knowing something about each user’s behaviors, motivations and contexts, we have the opportunity to deliver a variation of the core experience that is best suited to each individual user by using robust analytics and an adaptive user interface. In a data-driven UX approach like this, we start with the desired outcomes and behaviors we are trying to achieve with the target user base.

We then develop an initial behavioral segmentation model, and identify the optimal interaction strategies and user experience for each segment. And finally, we use analytics and machine learning to have our system adapt over time, so we can further optimize the design and underlying interaction models.

The figure below depicts the difference between a traditional and data-driven UX approach.

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Make it Real

Data-driven UX design is a fundamental shift in how companies approach product design and development. While the journey is not easy, the potential payoff is huge in terms of long-term engagement and positive outcomes for your customers. If you want to move to this new model, you need to consider the following:

1. Expand your definition of context beyond location and time. Situation and Emotion matter.

2. Deliver immediate benefits to users before asking for more of their data. There is a fine line between useful and creepy.

3. Segment your users based on digital behaviors, preferences, motivations and context to drive the most relevant interactions.

4. Set up a big data and analytics environment capable of capturing and acting on behavioral analytics data in real time.

5. Use analytics and machine learning to adapt the target interactions for each user-segment over time, based on user responses.

6. Recruit a new breed of user experience designers—those with analytics skills to support the design of adaptive user experiences.

7. Start with desired outcomes, then pilot and adjust quickly.

It’s no longer good enough to know your customers. It’s what you do with that knowledge that really matters. Your customers are willing to engage and share their data if they perceive a real benefit for them.

Are you ready to live up to your end of the bargain?

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The Downside of Making a Backup Plan – and What to Do About It 07-13

Always take backup.

We hear it all the time on cop shows; in everyday life, it translates to something like, “It pays to have a Plan B” or allusions to the Robert Burns poem about “the best laid plans” often going awry.
But new Wharton research shows that there is an important downside to making a backup plan – merely thinking through a backup plan may actually cause people to exert less effort toward their primary goal, and consequently be less likely to achieve that goal they were striving for. Jihae Shin, a former Wharton Ph.D. student who is now a professor at the University of Wisconsin, and Katherine Milkman, a Wharton professor of operations, information and decisions, detail their findings in the paper,

“How Backup Plans Can Harm Goal Pursuit: The Unexpected Downside of Being Prepared for Failure,” which was published in the journal, Organizational Behavior and Human Decision Processes.

The paper was inspired by a conversation that Shin and Milkman had when Shin was working to get an academic faculty job while completing the Ph.D. program at Wharton. While some of her peers were thinking about backup options in case they didn’t find a job in academia, Shin found herself not wanting to because she worried that, “if I make a backup plan, it could make me work less hard to achieve my goal, and ultimately lower my chances of success.”

“When people thought about another way to achieve the same high-level outcome, they worked less hard and did less well.”–Katherine Milkman

Shin and Milkman agreed that they should test Shin’s idea. In a series of experiments, they found that thinking through backup plans did quash people’s motivation to achieve their primary goal. For example, after all participants in one experiment were told that performing well on a task would earn them a free snack, or the privilege of leaving the study early, some were prompted to think about “another way they could have an extra 10 minutes or another way they could get a free snack,” Milkman notes.

“When people were prompted to think about another way to achieve the same high-level outcome in case they failed in their primary goal, they worked less hard and did less well.”

The researchers add that the effect wasn’t about putting a concrete backup plan in place. “Just thinking about it — you haven’t invented a backup plan, you haven’t created a safety net, you’ve just contemplated the existence of one” — causes people to lose focus on their goal, Milkman says.

Outsourcing Plan B

But can you really get through life without contemplating backup plans? Milkman says no – and nor should you. “There are huge benefits to making a backup plan,” Milkman points out. “If you don’t have one in life, sometimes it can be really disastrous.”

What you can do, the researchers say, is to become more strategic about when and how to make a backup plan. “You might want to delay making a backup plan until after you have done everything you can to achieve your primary goal,” Shin says.

Or you can outsource it. Milkman notes that while Shin was focusing on her goal of landing a faculty job in academia, Milkman and Shin’s other mentors were thinking about what she could do if it didn’t work out. “In a work environment, if an employee is given a task, you can tell him or her not to think about failure; just put all your eggs in one basket and know that it’s not your job to think about a backup plan,” Milkman says. “That’s the boss’s job, and the boss doesn’t have to tell the employee that he or she is worrying about it.” Alternately, Shin adds, companies can give one group of employees the job of pursuing a goal, and another group the responsibility of coming up with backup plans.

“You might want to delay making a backup plan until after you have done everything you can to achieve your primary goal.”–Jihae Shin

The researchers note that the effect is only relevant to goals that are dependent on effort, rather than luck. In addition, while it’s often impossible for the most cautious among us not to think about what happens if our goals don’t fall into place, Shin says people can avoid making specific, detailed backup plans. “The more specific and detailed your backup plans, the more potent their negative effects will likely be,” Shin notes.

“My dad told me when I was coming to the U.S. to do a Ph.D. that, ‘Nothing valuable in life is achieved easily,’” adds Shin, “I believe that persistence and grit toward a goal, which can be affected by making a backup plan, could make a difference in deciding who succeeds and who doesn’t in that goal.” Shin says one next direction for the research would be to examine whether the attractiveness of the backup plan impacts people’s level of motivation to achieve their primary goal — whether making an unattractive backup plan would hurt motivation less than making an attractive backup plan.

That said, after their conversation about her job prospects, Shin suspected that Milkman might have been thinking about a backup plan for her. “For this I am thoroughly grateful,” Shin says.

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What Insights lie at the intersection of Neuroscience and Marketing 07-02

Research into the interplay between the discipline of neuroscience — which studies the brain and the nervous system — and marketing could help to explain how people make decisions, how they react to stimuli and what triggers might amplify or diminish the impulses that drive social interactions or even innovation in a business setting. Such research also raises ethical questions on how those insights might be used, and how to prevent them from getting into the wrong hands.

Those are the opportunities and challenges for the Wharton Neuroscience Initiative, which was launched in September 2016, according to Michael Platt, its director. Platt, a neuroscientist, is also a Penn Integrates Knowledge professor with appointments at the University of Pennsylvania’s Perelman School of Medicine, the department of psychology in the School of Arts and Sciences, and the marketing department at Wharton. Creating the neuroscience initiative “at the intersection of medicine and business … is a provocative idea,” said Platt. But he is convinced that “it sends a clear signal to business schools, universities and people in industry that neuroscience is here, and the future of business is in neuroscience.”

Technological developments in the space also make it an opportune time for such an initiative, according to Elizabeth (Zab) Johnson, who is managing director and senior fellow of the Wharton Neuroscience Initiative. She pointed to the “huge boom” in wearable neurotech, and the proliferation of devices such as heartbeat monitoring watches, sleep monitoring gadgets and brainwave headbands. “[Students] need to know how to tell hype from what’s practical,” she said. “We need them to be savvy about that.” Platt and Johnson were previously colleagues at Duke University’s Institute for Brain Sciences.

Platt and Johnson discussed the intersection of neuroscience and business on the Marketing Matters show on Wharton Business Radio on SiriusXM channel 111. (Listen to the podcast at the top of this page.)


How We Tick, Why We Tick

Businesses and marketers need to get up to speed on the use of neuroscience in advertising and marketing, according to Catharine Hays, executive director of the Wharton Future of Advertising program, who co-hosts the Marketing Matters show. “The essence of the initiative is grounded in helping people, understanding how we tick, why we tick, and then using that information to make sure that we tick well,” she said. It helps that Penn has a large neuroscience community, she noted.
Platt expanded on Hays’s comments and said, “Knowing something more about how we tick as individuals and how we tick together sometimes and sometimes we don’t could impact the way we do business and educate the next generation of students….”

According to Platt, the “tremendous strides” in neuroscience over the last couple of decades will help people with brain disorders like Alzheimer’s disease. Those same advances in neuroscience will also help businesses and individuals “reach their maximum potential to create value for society,” he added.

The Wharton Neuroscience Initiative this year started an Introduction to Brain Science for Business course. It essentially uses business as a vehicle to teach students neuroscience, and also a means to convey some of the emerging areas for applications, said Platt. Some of those are in the area of marketing, to test the effectiveness of advertising such as engaging people and predicting sales, he explained. The idea is to broaden the domain of neuroscience beyond attention or decision-making to social neuroscience or studies of creativity, he added.

“The brain is trying to figure out ambiguity, and is trying to find solutions for what we see and what we perceive.” –Elizabeth (Zab) Johnson

Takeaways for Businesses

Research being conducted by Platt and Johnson could find numerous applications in the world of business. Johnson’s research includes studies in vision and color vision. For example, she would examine why different people identify the same color differently, such as some seeing blue as black or white as gold. She pointed to applications, for example, in the cosmetics industry. “We spend a lot of time looking at whether or not we can make ourselves more attractive” by adding different colors, she said.

Johnson saw big opportunities for research into those varying perceptions of color. “People had very emotional responses when they realized that what their friends saw was different from what they saw, even though it is same [color],” she said. The neuro-scientific explanation for people seeing colors differently is still being probed, she added.

“Inherently … what you perceive is all in your head, which as neuroscientists we always knew,” Johnson said. “We also know that the brain is trying to figure out ambiguity, and is trying to find solutions for what we see and what we perceive.” She has also begun to research how colors on people’s faces change depending on their emotional state “and the signals that we might be getting but we don’t think about,” such as when people blush.

Hays noted that 80% of the decisions or choices people make are based in their subconscious. “[In] bringing them to the fore and making them explicit, the business applications are mind boggling,” she said.

Platt said his research includes trying to understand at “a very deep level” aspects of interpersonal interactions. That begins with how people perceive each other to “higher-order processes” such as how that might prompt people to be kind or deceptive, he explained.

“We are working out the circuitry [and] trying to understand how we might turn up the volume on some of those signals and turn down the volume on some others,” Platt said. “So, could you do various kinds of nudges to promote more social behavior, to make us more attentive to each other, or [to become] better able to read social cues and be better listeners?”

“Could you do various kinds of nudges to promote more social behavior, to make us more attentive to each other, or [to become] better able to read social cues and be better listeners?” –Michael Platt

A Measured, Cautious Approach

Penn research is focused on using those insights to test new therapies to treat people with disorders, including both medicines and non-invasive brain stimulation, Platt explained. “We need to do research to figure out how to do it right, and how to do it safely.” Some of those therapies are being put into practice at the Children’s Hospital of Philadelphia, he added.

Platt’s research extends to studying decision-making and how people weigh trade-offs between continuing to exploit something they know well versus taking risks to explore new ways of doing things. “That is where the spark of innovation comes from,” he added. As that research advances, it will also try to uncover the mechanisms of that process, measure it on individuals unobtrusively through a wearable device or “stimulate that circuitry on people whose job it is to be innovative.” The research work will also extend to innovating on devices at an ideas lab to improve quality and make them cheaper so they can be used more in everyday lives.

Platt acknowledged that such research raises “important ethical questions,” but clarified that they are not specific to neuroscience in a business context. He said that among other resources to grapple with those issues, he wants to tap into the deep expertise in bioethics at Penn. Johnson called for continuing debate on these issues to come up with the right applications.

Reproduced from Knowledge@Wharton

How Anticipating Future Variety Curbs Consumer Boredom 06-29

Image credit Shyam's Imagination Library

If your favorite chocolate brownie ice cream were on sale, then surely buying a few containers to stock in your freezer would makes sense, right? Surprisingly, the answer may be no, according to recent research from Wharton marketing professor Barbara Kahn, who also serves as director of the school’s Jay H. Baker Retailing Center. In a paper titled “Anticipation of Future Variety Reduces Satiation from Current Experiences,” Kahn and her co-authors — Julio Sevilla from the University of Georgia and Jiao Zhang from the University of Oregon — debunk the notion that consumers respond positively to an endless supply of the exact same product.

Through controlled lab experiments, Kahn and her team found that when consumers are offered more variety for future consumption, their perception of present satisfaction changes. The paper was published in the Journal of Marketing Research. Kahn spoke with Knowledge@Wharton about what the research means for marketers. 

An edited transcript of the conversation follows.

Knowledge@Wharton:  Could you give us a summary of your research?

Barbara Kahn: What the research shows is that if you anticipate consuming a variety of things in the future, you will satiate slowly on what you’re consuming now.

Knowledge@Wharton: This sort of sounds like the reason why we all overeat at the buffet.

Kahn: Except overeating is consumption, and this is about eating the same thing over time, how fast you get bored with it or how fast you satiate with it. The reason it’s interesting to marketers is, of course, that marketers want you to consume as much as possible of their product. But the problem is when you consume a lot over time, you get bored, or satiate. This is not just for food; it could be for music or for anything else that you consume over time. Is there a way to reduce the boredom so that you’ll enjoy what you’re consuming for a longer period of time?

What we found was that some of that boredom and satiation is cognitive. It’s not all physical. If we can encourage you to think about something in the future that’s related to what you’re consuming now, and that will offer more variety, then you’ll satiate more slowly.

In an article you wrote for the American Marketing Association on this research, you introduced the example of yogurt, which I think helps to clarify this. Could you explain that example?

Kahn: Say you’re eating vanilla yogurt every single day for lunch for a week, two weeks, three weeks. You could imagine over time that you’d get bored with vanilla yogurt. What can we do to make you less bored?

Knowledge@Wharton: If you went to Costco or BJs or some warehouse and bought a whole pallet of yogurt, and it was all different flavors or some flavor different from vanilla, and you knew in the future you would consume that, it would make you satiate more slowly with the vanilla yogurt you’re eating over time today. That’s the idea.

Knowledge@Wharton: What are the implications for retailers like Costco, for example?
Kahn: It’s that selling a variety of things has a benefit over and above what you might think. Just having the variety in the refrigerator will make the enjoyment of a single flavor more pleasurable.
Knowledge@Wharton: What is the biggest surprise that came out of this research?

Kahn: We’ve always known a lot about anticipation; a lot of past research has shown that you should savor the anticipation of something good. There’s an advantage in planning for a vacation or a wedding or something that’s really fun. You might actually enjoy the anticipation of the event more than the event itself. That’s something that’s been shown before.

But what’s different about this research is that we show that anticipating variety in the future affects your current consumption. That’s somewhat surprising because you wouldn’t think that just thinking about something in the future could affect how you’re enjoying something today.

Knowledge@Wharton: One of the other interesting examples you brought up in your AMA article was the idea that maybe it’s not always best to keep a surprise gift a secret from a significant other. Could you explain that?

“You wouldn’t think that just thinking about something in the future could affect how you’re enjoying something today.”

Kahn: The point is that if people can anticipate something that’s going to happen in the future, not only do you savor the excitement of the future, but it also can affect your current consumption, so that’s a little counter-intuitive.

Knowledge@Wharton: If someone’s going to give you a surprise vacation, for example, knowing about it earlier helps you to anticipate and actually enjoy something else in the present, correct?

Kahn: Right. You know you’re going to have a lot of varied activities — you’re going to go skiing and mountain climbing or whatever you’re going to do in the future — so maybe you won’t be as bored with what you’re doing right now.

Knowledge@Wharton: There are all sorts of implications for this. What are you going to look at next?

Kahn: It’s interesting to think about how consuming variety can affect things besides the actual utility you have for the variety. One of the projects I’m working on with a doctoral student at Drexel University is how consuming variety can make you feel less guilty or more fulfilled when you’re in a self-regulatory mode — like when you’re trying to like control your weight or eat more healthily. Sometimes, using variety as a cue for doing more of a good thing or less of a bad thing can alleviate guilt. That’s kind of an interesting thing — that variety in and of itself can affect these other kinds of feelings or emotions.

Reproduced from  KNOWLEDGE@WHARTON