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“Lean In” Messages and the Illusion of Control

Harvard business - Mon, 07/30/2018 - 09:00

Shana Novak/Getty Images

In a world in which men dominate leadership roles, should we focus on changing the systems and structures that favor men at women’s expense? Or should we emphasize the tactics individual women can use to get ahead?

Our research explored this question. The first message, that it’s processes and organizations that need to change, has been gaining traction in more recent years. But the latter message has been inspiring and motivating to many people; it’s solutions-oriented and individualistic, appealing especially to Americans who tend to appreciate DIY solutions to societal problems. Plus, it has the benefit of seeming to help women now, rather than waiting decades — or even centuries — for societal change.

We suspected that by arguing that women can solve the problem themselves, advocates of the “DIY” approach may imply that women should be the ones to solve it — that it is their responsibility to do so. We also hypothesized that this message could risk leading people to another, potentially dangerous conclusion: that women have caused their own under-representation.

To test these ideas, we designed and ran a series of experiments, the results of which are forthcoming in the Journal of Personality and Social Psychology. Across six studies and approximately 2,000 American participants, we randomly assigned people to different experimental conditions to determine the effects of exposure to these ideas: what we’ll call here the structural approach to confronting sexism, and what we’ll call the DIY approach.

Participants read text taken directly from Facebook COO Sheryl Sandberg’s book Lean In, or listened to audio clips from Sandberg’s TED talks, that described the problem of women’s under-representation in leadership. While there are many books and resources out there that advocate a DIY approach to dealing with sexism, we chose to use Sandberg’s work because it is the most prominent, and the language of “lean in” has come to dominate this debate since her book was published five years ago. It also made good subject matter for our experiment because, while the title emphasizes the DIY approach, the book also extensively cites research on the structural problems women face. This allowed us to test the impact of both messages, while controlling for the messenger.

One group of participants read or listened to the DIY messages, which emphasized that women can act more ambitiously, speak more confidently, demand a seat at the table, and take more risks. The other group read or listened to sections that which emphasized structural and societal factors, such as discrimination. We also employed other control conditions.

People who read or listened to the DIY messages were more likely to believe women have the power to solve the problem. That, on its own, may very well be good news. However, they were also more likely to believe that women are responsible for the problem — both for causing it, and for fixing it.

What’s more, these effects were even associated with people’s policy preferences. For example, in one of our studies, we described a recent problem reported by Facebook, in which managers rejected code written by female engineers more often than they rejected code written by male engineers. This is an ambiguous workplace problem, with possible roots both in women’s own underperformance and in manager bias. After being exposed to the DIY messages, our study participants viewed the female engineers as more responsible for both causing and fixing this problem, and in turn, less likely to think that structural changes at Facebook — such as having managers review code without knowing who wrote it, or training managers on bias — would be worthwhile.

There are important limitations to these findings. First, the findings are new, and thus have not yet been independently replicated by another lab; as such, they must be considered as just initial evidence. Second, Sandberg’s message was primarily oriented at American professional women in majority white companies, and thus, our findings are also limited to that context. We don’t yet know how empowerment messages affect the way people see women of color or women in working class jobs.

Nonetheless, as behavioral scientists who study how people understand and make sense of social inequality, we are troubled by these findings. Humans don’t like injustice, and when they cannot easily fix it, they often engage in mental gymnastics to make the injustice more palatable. Blaming victims for their suffering is a classic example — e.g., that person “must have done something” to deserve what’s happened to them.

We are by no means suggesting Sandberg intended to blame women for inequality. But we do fear that Lean In’s main message — which emphasizes individual action as a way to address gender inequality — may lead people to view women as having played a greater role in sustaining and even causing gender inequality.

These findings should worry anyone who believes we need structural and societal change to achieve gender equality in the workplace, including Sandberg, who has said as much. They suggest that the more we talk about women leaning in, the more likely people are to hold women responsible, both for causing inequality, and for fixing it.

Categories: Blogs

What to Do When Each Department Uses Different Words to Describe the Same Thing

Harvard business - Mon, 07/30/2018 - 08:00

Jorg Greuel/Getty Images

We’ve all experienced some version of this problem: Ask “how many customers do we have?” and the marketing team provides one answer, sales a second, and accounting a third. Each department trusts its own system, but when the task at hand requires that data be shared across silos, the company’s various systems simply do not talk to one and other.

The problem arises because different systems employ different definitions of key terms. Thus, the term “customer” can mean a potential buyer to the marketing department, the person who signed the purchase order to sales, and the legal entity that it bills to accounting. Then people misunderstand the data and make mistakes. These issues grow more important as companies try to pull more and more disparate data together — to develop predictive models using machine learning, for example.

Specialized vocabularies develop in the business world every day to support new or specialized disciplines, departments, problems, and innovative opportunities. The term “customer” means different things to different departments because, at some point, each required the term to mean something specific to them. Language constantly grows and divides, becoming increasingly subtle and nuanced. But over time, systems don’t agree, which can cause tension and conflict in organizations.

To see this, consider two departments of a consumer package goods company. Day-in and day-out, the marketing department is responsible for promotional activities and rates its effectiveness on whether a particular promotion produces the desired results. Similarly, the logistics department is responsible for getting raw materials to factories and delivering finished goods to public warehouses and onto retail outlets. Neither viewed market share as its top priority, but both kept it current in their databases to be ready for the occasional question from senior management.

Which is exactly what happened. An important issue arose and management asked the two departments to determine whether the company had been losing market share. Each arrived at its own answer, and tempers flared as each vigorously defended its system. Eventually a relative newcomer discovered the problem. The respective systems measured market share at different places in the overall supply chain — marketing at the retail outlet and logistics at the public warehouse. Each approach has merits, but the two are fundamentally irresolvable. The two departments finally agreed on an answer for senior management, but the ill will prevented them from working together for months.

In the face of such discrepancies, companies usually seek technological solutions, including data integration, enterprise data architecture, and master data management, since the issue presents itself as a tech problem. But such solutions face long odds, because they do not address the problem at its root.

Instead, companies must thread the needle, following two rules: First, do all you can to encourage innovation and the growth of specialized language that comes with it. Second, provide the skinniest possible common vocabulary (i.e., standards) to facilitate company-wide communication.

Encourage the development of new language. Since developing new language is part and parcel to innovation, you must not interfere with the process. In fact, you should view the development of new language as a sign that people are solving problems in new and creative ways.

Half the battle in encouraging innovation involves removing barriers. Too many people accept the limitations imposed by existing systems and don’t even try. You should advise everyone that computer systems exist to support them and their work, not the other way around.

More proactively, you’ll almost always need new terms when you change the focus of the business. Thus, moving from a sales focus to a customer focus will require you to carefully define and introduce “shopper,” “cook,” “guest,” or some other term that best describes the relationship you hope to create into the lexicon. You should also probe people aggressively on the need for new and more precise words that better capture their work. One good cue to do so is when members of your team include caveats in describing results. For instance, if someone reports that “sales are down 3% this quarter, but the pipeline is full,” ask them to define a new term that succinctly captures the state of the sales pipe. Finally, you should treat the need for new language as you would any other data quality improvement opportunity and address it via the quality improvement cycle or Six Sigma.

Create a common language. You should also follow a structured approach to develop and promulgate the common vocabulary across your company. First, establish the required team. You will need a process owner, often called the Chief Data Architect (CDA), and a network of responsible coordinators (RCs), often called embedded data managers or stewards. It may also be helpful to employ a conceptual data modeler, since they have special skills at capturing common language. Since language is the province of the business, the CDA should not report into IT, but rather to the Chief Data Officer, data quality team lead, or other business-aligned group. Similarly, RCs should report into business units and divisions that create and use data, since the RC’s job is to ensure that his or her unit does its share of the work.

Next, you’ll need to define and manage an end-to-end process. A good way to start is by copying processes followed by national and international standards organizations and adapting them to your specific circumstances. Build the following features into your process.

Allow anyone to request that a standard definition be developed. For each request, form a sub-team to draft the standard. Your process should allow plenty of time to solicit feedback from all interested parties and to revise the standard as often as needed. This is a consensus process, so implement a formal voting procedure and require a large majority to adopt the standard definition. Like most things in the data space, it is best so start with relatively easier terms. An international company, for instance, may start with units of measure: English or metric? Keep in mind, even the most complex company probably needs only 100 or so terms in its common vocabulary. Aera, a California-based energy company, does just fine with 53.

Another important feature of your process involves publishing and promulgating the common vocabulary. Many companies use data dictionaries or business data glossaries, hosted on the company intranet, linked to major systems, and easily accessed by all. It is especially important that CDAs get involved early to include the common vocabulary into the specifications for new systems.

I find that the biggest mistake companies make is being too rigid, or expecting the common vocabulary to apply at all times. But the common vocabulary exists to promote company-wide communication, not dictate how individual departments do their work. Allow individual departments to use terms that best suit their work, reserving the common vocabulary when working with others.

Sound like a lot of work? It is! But unleashing the people’s creativity to invent new language, built on a foundation of a few well-chosen and well-supported data definitions, pays dividends in a myriad of small ways every day. It is much easier for people to find answers to important questions and work across departments.

Categories: Blogs

The Biggest Obstacles to Innovation in Large Companies

Harvard business - Mon, 07/30/2018 - 07:00

jessica solomatenko/Getty Images

It turns out that the word “innovation” is not a Harry Potter-esque magical incantation that, once spoken, renders companies more inventive, creative, and entrepreneurial. The word can be uttered by a CEO speaking to employees or Wall Street analysts. It can be emblazoned on the door to a new innovation center in Silicon Valley. It can be inserted into people’s job titles. (Yes, even Toys R Us had a head of innovation.)

But there are thorny cultural, strategic, political, and budget issues that must be confronted by CEOs and other leaders if they want to ensure that their organizations can be hospitable to — rather than hostile to — new ideas.

In a survey fielded earlier this year for Innovation Leader, an online resource for corporate innovation teams of which I am editor, we asked about the most common obstacles to innovation in large companies. (To be constructive, we also asked about the things that foster innovation.) The responses, from 270 corporate leaders in strategy, innovation, and research and development roles, were illuminating.


We invited survey respondents to cite as many factors as they wanted from a list. The top five obstacles were each cited by at least one-third of respondents. They were:

Politics, turf wars, and a lack of alignment (cited by 55% of respondents.)

Some business units or functions believe they’re already doing innovation on their own, and that any sort of new initiative is edging into their terrain — and potentially competing for resources. Some may be hoping that the CEO’s “favorite child” of the moment, a new Chief Innovation Officer or Chief Digital Officer, will go away if ignored.

“Any time you start something new like [an innovation initiative], that cuts across many areas, there’s a potential for people feeling like you’re in their backyard,” says Michael Britt, a senior vice president who heads the Energy Innovation Center at Southern Company, a major utility operator. That’s especially true, he adds, when the core business is successful and doing well.

Senior leaders may not be able to squash every political squabble, but they can be clear about what the innovation or new ventures group is expected to do, and how others are expected to support it.

Cultural issues (45% of respondents.)

The culture at large companies is typically built on a foundation of operational excellence and predictable growth. Change-makers trying to conduct experiments are rarely greeted with open arms — especially when they’re working on an idea that may cannibalize stable businesses or upend today’s distribution model.

And big companies, like elephants, have long memories. Many long-timers can remember — and will happily detail in meetings — all of the “historical attempts [at innovation] that didn’t pan out – and it may just not have been the right time,” says Stacey Butler, director of innovation at NRG Energy.

Influencing the culture at established companies can seem, at times, like trying to walk into an art museum and just make a few small tweaks to the marble statues: no one wants you to do it, and almost anything you do will provoke a strong reaction. But creating new places where people can gather to work on projects — subcultures within the larger culture — can be constructive. So can designing new kinds of incentives, recognizing and rewarding the behaviors you want to encourage, and bringing in new, more diverse viewpoints and types of talent to the company.

Inability to act on signals crucial to the future of the business (42% of respondents.)

We asked about two related barriers in our survey: how well does your company “pick up” on signals of change, and how well does it act on them? Only 18% of respondents said that their companies had trouble with the former — so at most companies, there’s awareness of disruptive startups entering their sector, or changing customer purchase behaviors. The problem is acting on those signals. When your “forward scouts” see something important, what mechanisms exist to set up collaborations with outside vendors or startups, or run a quick pilot test with a function or business unit? Too many companies wait for the annual strategic off-site to roll around before they address the changing dynamics of their market.

Lack of budget (41% of respondents.)

At many of the largest companies, in industries like aerospace and technology, limited budgets are not an obstacle. Over decades, these industries have built up large R&D functions that are expected to crank out new ideas that the company will be able to leverage. But nearly 40% of the respondents to our survey said their innovation efforts had an annual budget of under $5 million, and 23% were below the $1 million mark. (We asked respondents to include both salaries of team members and direct spending.) Many of those lower budgets are in industries that haven’t historically had an R&D department, like retail, hospitality, and financial services.

In most cases, that budget level produces a small innovation team that may be doing some concept development work, trend scouting, or training employees on innovation methodologies — but isn’t having a broad impact on the company.

“With a budget of less than $1 million, it seems like the job is to build a case for innovation investment, versus [doing the work of] innovation itself,” says Rick Waldron, a former Nike executive who ran the apparel company’s innovation accelerator until last year. That level of funding, Waldron suggests, can be used to “bring senior management along on the journey and educate them” with a few concrete project examples that “will be the key to unlocking more resources for an innovation program.”

Lack of the right strategy or vision (36% of respondents.)

This answer includes a multitude of sins. Are employees clear on what kind of innovation they’re supposed to be doing? Are they looking for ideas to streamline operations and serve customers better, or developing new business models around existing products? Without a coherent strategy and clear vision for what the company aims to achieve, innovation efforts wind up feeling scattershot and isolated.

Interestingly, survey respondents said that their least significant was the “lack of CEO support”; just 10% of survey respondents said that it was constraining innovation at their company. The CEO, it turns out, doesn’t wield a sledgehammer that can demolish any obstacle that blocks a team of smart employees with a good idea.

What can help? Clear expectations set about why innovation is necessary. Appropriate recognition and incentives for people who get involved in making positive change happen. Regular communication and bridge-building between innovation teams, and the functions and business units they require as partners. Measures of progress that illuminate not only the performance of the innovation group, but also the functions and business units that they work with to implement their ideas.

One key enabler of innovation, referenced by more than half of our survey respondents, was the “ability to test, learn, and iterate.” How well does your company run quick-and-dirty experiments, gather the results, and then try again?

Finally, long-term commitment is essential. Corporate cultures reject many new initiatives if people believe they are the flavor-of-the-month. (One write-in response to our question about obstacles to innovation was, “Leadership ADHD.”) When CEOs and other leaders talk about innovation, they need to make it clear it will be more like a daily exercise regimen — part of the way things are done here, from now on — than a magical incantation that delivers instant results.

Categories: Blogs

How AI Is Changing Sales

Harvard business - Mon, 07/30/2018 - 06:05

JW LTD/Getty Images

Companies are using AI in all kinds of innovative ways to advance their businesses. If you’ve ever searched Netflix to watch a movie, AI (a recommendation algorithm) was no doubt used in your decision about what to watch.  If you’ve shopped on Amazon, your decision about what to buy was also influenced by AI (via an association algorithm).  If you’ve ever ordered an Uber, AI (a location algorithm) was used to have a car in your vicinity quickly.  If you ever had a thought about a product or a vacation, and it seemed to suddenly pop up on your search page or in your email inbox, I can assure you it was based on AI (a classification algorithm) monitoring your online activity.

These same types of AI algorithms can be used to power any company’s decision-making process, helping you make better business predictions. Based on research for my book Sales Ex Machina: How Artificial Intelligence is Changing the World of Selling, here are five specific areas where AI algorithms can be leveraged to help your business grow by helping your sales team sell more:

Price Optimization: Knowing what discount, if any, to give a client is always a tricky situation. You want to win the deal, but at the same time you don’t want to leave money on the table.  Today, an AI algorithm could tell you what the ideal discount rate should be for a proposal to ensure that you’re most likely to win the deal by looking at specific features of each past deal that was won or lost. Features could include: size of the deal in terms of dollar amount, product specification compliance, number of competitors, company size, territory/region, client’s industry, client’s annual revenues, public or private company, level of decision-makers (influencers) involved, timing (e.g., Q2 vs Q4), new or existing client, etc.

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Forecasting: Sales managers face the daunting challenge of trying to predict where their team’s total sales numbers will fall each quarter. Using an AI algorithm, managers are now able to predict with a high degree of accuracy next quarter’s revenue, which in turn would help a company, from an operations standpoint, to better manage inventory and resources.

Upselling and Cross-Selling:  The fastest and most economical way to grow your top-line revenue is to sell more to your existing client base. But the million dollar question is, who is more likely to buy more?  You can spend a lot of money on marketing to those who won’t buy, or you can use an AI algorithm to help identify which of your existing clients are more likely to buy a better version of what they currently own (up-sell) and/or which are most likely to want a new product offering altogether (cross-sell). The net effect is an increase in revenue and a drop in marketing costs.

Lead Scoring: A salesperson with a rich pipeline of qualified potential clients has to make decisions on a daily, or even hourly, basis as to where to focus their time when it comes to closing deals to hit their monthly or quarterly quota.  Often, this decision-making process is based on gut instinct and incomplete information. With AI, the algorithm can compile historical information about a client, along with social media postings and the salesperson’s customer interaction history (e.g., emails sent, voicemails left, text messages sent, etc.) and rank the opportunities or leads in the pipeline according to their chances of closing successfully.

Managing for Performance: Every month, sales managers have to assess the revenue pipelines of each of their salespeople with an eye towards nurturing deals that might stall, or worse, fall through. Using AI, sales managers can now use dashboards to visually see which salespeople are likely to hit their quotas along with which outstanding deals stand a good chance of being closed. This will allow a manager to focus their attention on key salespeople and associated deals that will help the company hit their quota.

In each of the five examples above, the quantity of gathered data used will increase the algorithm’s ability to give a more accurate prediction, which in turn will drive behavior.  This is key.  The value of any prediction lies in how it can be used to guide a salesperson’s or manager’s behavior to improve the company’s bottom line.

If you choose to harness the power of AI on your own sales team, where do you begin?

First, identify the different types of data sets that exist within a company that can be combined to give a more complete picture of the customer base. For example, the sales department obviously has historical purchase data, and the marketing department has website analytics and data from promotional campaigns (e.g., response rates from clients).  Combining these data sets can allow an AI algorithm to make better predictions about who is more likely to respond to an offer.

These data sets then need to be combined with a Customer Relationship Management (CRM) platform (e.g.,, Microsoft 365, Zoho, and many others) which will serve as a repository for all customer transactions and interactions.  These CRM platforms have tools that will allow you to analyze the data sets for patterns, and generate the types of predictions mentioned in the five examples above. (More and more CRM companies are adding “intelligence” as part of their platform options.  For example, now has an “App Exchange” where you can purchase AI plug-ins like’s Neuralytics to record, store, and analyze phone calls.)

The challenge for any company is always finding new ways to grow their revenue, reduce costs, and expand market share, while at the same time minimizing risks. It’s become apparent to leading edge companies that leveraging their existing internal database, and mining it for new opportunities using AI, will allow them do to so prudently.  If data is indeed the new oil, then companies who can capture the data, analyze it, and generate actionable insights will have salespeople who’ll be able to close more deals, more often.

Categories: Blogs

Technology and Being Human

QAspire - Sun, 07/29/2018 - 21:34

I created a series of sketch notes for Tiffani Bova’s “What’s Next” podcast where she meets brilliant people to discuss customer experience, growth and innovation. Tiffani Bova is a Global Customer Growth and Innovation Evangelist at Salesforce. I will post sketchnote versions of selected podcast episodes that enlightened me. Tiffani is also the author of a new book “Growth IQ: Get Smarter About the Choices that Will Make or Break Your Business” due for release in August 2018.

Sometimes, when I see a group of people sitting physically with each other yet engrossed in their mobile screens, I feel that technology has turned us into gadgets and made us less human.

Sure, social media has transformed how we connect, collaborate and learn. But it also seems to be taking a huge toll on precisely those things that make us human.

We are not gadgets. We are capable of thinking deep, connecting the dynamic dots, be creative and solve important problems in novel ways. We are capable of dreaming, hoping, perceiving, creating, telling stories, collaborating and connecting. We are capable of deep work and generosity. And these are the things that make us human. This is how we become wise in a world where knowledge is essentially commoditized.

The key then is to leverage the social platforms as much for our learning, connecting meaningfully and collaborating rather than just allow platforms to entice us into mindless consumption.

Austin Kleon, someone whose work and art I admire posted the following:

Do more things that make you forget to check the phone.

Creativity and learning stems from doing meaningful stuff in a way that serves the community and changes others for better. That is at the heart of embracing craftsman spirit.

Do check out the wonderful podcast episode with Arianna Huffington and here is a sketchnote summary of some of the key insights.

Related Reading at QAspire:

Categories: Blogs

Bookmark This! HR Certification Edition

Hr Bartender - Sun, 07/29/2018 - 02:57

Maybe it’s because the Society for Human Resource Management (SHRM) just launched their new Talent Acquisition Specialty Credential, but I’ve been receiving quite a few questions lately about certifications. Over the years, I’ve written quite a bit about the topic, so I thought I would put the articles all in one place for easy reference.

Since I just mentioned it, here’s some information about SHRM’s new Talent Acquisition Specialty Credential. It’s not the same as a certification, but it does demonstrate knowledge and is worthy of your attention.

3 Reasons to Earn the SHRM Talent Acquisition Specialty Credential

SHRM Talent Acquisition Specialty Credential: All the Details

When it comes to certifications, I’ve always said that this is a very personal decision. I can’t tell someone what certification to pursue. I can say this . . . you should definitely want and be proud of any certification you choose to pursue because it will always mean more to you than anyone else. Even when employers encourage and support earning certifications. Even when job openings indicate that a particular credential is preferred. Those letters after your name will always mean more to you than anyone else.

So, take your time and choose the one you want. There are lots of certifications out there too. Here’s a short list below. Oh, and make sure to read the comments because readers added a few I missed.

Choosing the Best HR Certification – Ask #HR Bartender

It’s possible that you’ll put together a short list of certifications to do extensive research on. Here are some thoughts on how to weigh the pros/cons.

How to Decide Which HR Certification Exam to Take – Ask #HR Bartender

One of the certifications I hold is the SHRM-SCP, which is based on the SHRM Competency Model. Here’s some background information about that specific certification.

SHRM Certification: Why Should #HR Pros Pay Attention

Once you’ve decided on the certification to pursue, it’s time to put together an action plan. These articles talk about how to study, including some words of wisdom from individuals who have been there.

The Best Way to Study for an HR Certification Exam – Ask #HR Bartender

Moving Past Exam Failure – Ask #HR Bartender

Finally, no conversation about credentialing would be complete without some information about recertification. I believe this is one of the most important components of the process. Not to take away from all of the hard work that it took to earn the credential, but the on-going commitment to professional development is one thing that sets certification apart from other forms of professional development.

SHRM Certification: You Can Get More Than 60

As human resources professionals, we spend a lot of time advising employees and managers on ways to develop their careers. And credentials and certifications are one of them. Now, it’s time to take our own advice. Do your research and find the right credential or certification that showcases your knowledge and skills.

Oh, and a quick P.S. One of the easiest ways to earn recertification points is by reading. There are several HR and business-related booksthat are eligible for professional development credit (PDC) through SHRM. Including my books “Manager Onboarding” and “The Recruiter’s Handbook”. I hope you’ll check them out.

Image captured by Sharlyn Lauby while doing some training in California

The post Bookmark This! HR Certification Edition appeared first on hr bartender.

Categories: Blogs

Why the U.S. Trade Deficit Can Be a Sign of a Healthy Economy

Harvard business - Fri, 07/27/2018 - 12:20

Yuji Sakai/Getty Images

“We lose $800 billion a year on trade, every year,” President Trump said in March when he announced his new tariff plan, referring to the size of the U.S. trade deficit in goods. Trump has lamented the U.S. trade deficit repeatedly, tweeting that as a result of it, “our jobs and wealth are being given to other countries.”

The trade skirmishes that have broken out as a result have the potential of becoming a full-scale trade war of the sort that the Smoot-Hawley Tariff Act of 1930 started, which is widely credited with either triggering or deepening the Great Depression.

But what is the trade deficit, and what causes it? And is it a bad thing?

For decades, the U.S. has run a deficit in the trade of goods — in other words, importing more goods than it exports. The dominant narrative is that the steadily increasing U.S. “trade deficit” is a function of two things: (1) the availability of cheaper labor overseas and (2) the unbridled consumption habits of Americans. As a consequence, the narrative goes, the U.S. has had to import increasing amounts of capital from investments by foreign governments, businesses, and individuals to “fund the trade deficit,” thus becoming a debtor nation.

Although this is a compelling narrative, there is in fact no evidence to support the conclusion that a deficit in traded goods causes a net import of capital. It is true that there is plenty of evidence that these two things happen together, but that simply confirms macroeconomic measurement convention, according to which three components of a country’s balance of payments must sum to zero: a country’s balance in the trade of goods, its balance in the trade of services, and its balance of capital inflows/outflows. So, if trading in goods and services is collectively in deficit, then capital inflows must be positive by an equal amount. But that statement does not affirm that the trading deficit causes the capital inflow. It could equally be true that the inflow causes the trading deficit.

So which causes which? It is not possible to tell for certain. It is, however, instructive to remember that the last time America ran a persistent and sizable (relative to the economy at the time) goods trade surplus was when it was exporting vast amounts of capital to Europe to fund the Marshall Plan after World World II.

Do a little thought experiment: Imagine that your country is the world’s most attractive country in which to invest capital, because it has the biggest and richest market in the world, and the world’s most used and tradable currency, and it is scrupulous about protecting the rights of investors. Imagine further that its advanced economy is leading the world in the transition to a service-based economy, and as a result, it runs the world’s biggest services trade surplus — by a factor of more than two over the next biggest surplus in the world.

Per standard macroeconomic theory, this imaginary country would run the world’s biggest deficit in traded goods. And it would have absolutely nothing to do with its being uncompetitive or its people profligate. It can’t be the best place to invest and the best service exporter without running a huge goods trade deficit. (Because, remember, all three things have to sum to zero.) Well, the mystery country is, of course, the U.S. — and the U.S. trade deficit, according to this argument, is a logical consequence of America’s success and superior know-how relative to other countries. On this basis, the trade deficit should be something to brag about rather than denounce.

In an inflows-causes-deficits narrative, the trigger for the rise in the U.S. trade deficit is not cheap overseas labor or American profligacy. Rather, it is President Nixon’s 1971 decision to take the U.S. off of the gold standard and end the postwar Bretton Woods period of fixed exchange rates. That decision launched what has turned out to be a nearly half-century period of upward-trending deficits in the trade of goods with other nations. What President Nixon could never have guessed is that when he triggered the end of Bretton Woods, he made it much more important for global investors to choose wisely when deciding where to invest their capital internationally.

Prior to August 15, 1971, it didn’t matter as much because your currency was fixed against the U.S. currency, and the U.S. promised to give you one ounce of gold if you used your currency to buy $35. So, you could invest in France and not have to worry about your francs becoming worth less in U.S. dollars than when you first invested. After 1971 it was really helpful to invest your capital in the most robust and open market in the world, and the world’s investors have increasingly figured that market is the U.S. — not Japan with its shrinking population, or China with its rampant corruption, or Europe with its economic sclerosis.

Since 2000 the U.S. has received, on average, a net capital inflow of over half a trillion — per year! And to put more upward pressure on the goods trade balance, the U.S. services trade balance, which was trivial as late as 1985, is now in the neighborhood of one-quarter of $1 trillion dollars per year.

Don’t get me wrong: I am 100% supportive of going after unfair trade practices. For example, it is truly ridiculous that Japan erects such an incredible array of barriers to U.S. car imports that GM and Ford have all but given up attempting to sell vehicles in Japan, while Toyota, Honda, and Nissan import millions of vehicles a year profitably into the open U.S. market.

However, if the U.S. economy keeps growing at 3%–4% a year with close to zero structural unemployment, nothing that President Trump accomplishes on the front of making trade fairer for U.S. goods exporters will do a thing to reduce the U.S. deficit in traded goods, which is his avowed goal. In 2017 robust U.S. economic growth widened the capital flow surplus — and unsurprisingly, the goods trade deficit widened in step.

If President Trump actually wants to decrease the goods trade deficit, he would need to take a page from the presidencies of Jimmy Carter and George H.W. Bush. In the post-1971 era, they were the presidents who were the most successful in reducing the goods trade deficit. Both accomplished that feat by inheriting a U.S. economy doing reasonably-to-very well and leaving it performing considerably worse, making it considerably less attractive to net foreign capital inflows. I suspect that is the kind of economic sacrifice President Trump would want to assiduously avoid.

Categories: Blogs

How Consultants Project Expertise and Learn at the Same Time

Harvard business - Fri, 07/27/2018 - 09:00

Carlos Osorio/Getty Images

Young management consultants may be novices, but they’re sold as experts. Conversely, even experienced consultants, who legitimately present themselves as experts, still feel like novices when they embark on a new project.

The challenge with effective consulting is that it depends on in-depth situational knowledge that consultants simply can’t have when they start an assignment. What’s more, they may not yet be completely clear on what the client — who’s paying top dollar and expects results immediately — really wants. So consultants must rapidly and discreetly gain knowledge of the client’s business while simultaneously giving an impression of competence and self-confidence. We call this challenge learning-credibility tension.

How do consultants overcome it?

Consultancy Work Is a Performance

For consultants, work is largely a performance. Like skillful actors, they use a combination of “backstage” preparation and “front stage” performance to make the audience (that is, the client) believe the story they want to tell.

Consultants are sometimes accused of trying to hoodwink their clients with smoke and mirrors, using management fashions or buzzwords for their own benefit. But our research suggests that they are far from being arch manipulators who control every interaction. Instead, they are doing everything they can to learn and deliver value at the same time, under the constant risk of failure.

The obvious way to gain knowledge is to ask direct questions. But if consultants try that, they risk looking uninformed or just useless. Clients might reason, “We shouldn’t have to train you!

Experimentation could be another fruitful approach. But when leaders hire an expert to take on a challenging task, they don’t expect the person to try things out. They expect the expert to just know what to do.

Consultants can also attempt to display knowledge right away. But if they make a mistake that reveals their ignorance, they could look incompetent. If things go wrong later, the client might lose faith in the consultant’s expertise, making it even harder for them to deliver.

In other words, consultants really are faking it ’til they make it — or, more precisely, faking it so that they can make it. Their fakery is not cynical, but sincere.

We studied management consulting projects for almost two years and interviewed 79 consultants to understand how learning-credibility tension manifests in practice and how consultants deal with it. What we found is that consultants use a range of verbal and nonverbal tactics that help them manage perceptions and neutralize threats to their professional image.

Consultants deal with three types of threats to their self-image: competence threats, acceptance threats, and productivity threats. To neutralize them, they use three closely related tactics: crafting relevance, crafting resonance, and crafting substance. Let’s look at them in turn.

Crafting Relevance to Seem Competent While Learning

Consultants are usually hired to advise on business transformation, project management, or strategy. However, they must also show that they adequately understand the technical side of their assignments. In other words, they face competence threats, which they deal with by crafting relevance.

Crafting relevance is about having the maximum impact in the minimum time by leveraging all the bits of knowledge that are available. Consultants don’t have to know it all — just enough to be taken seriously and appear competent while they seek more information.

One way to do this is to collect nuggets of information and selectively present them back to clients. The information might come from written material on past consulting assignments, the client’s internal documents, or information in the public domain. By preparing thoroughly and using these nuggets to create a mental map, consultants start to build a high-level view of the client’s situation.

The other way consultants craft relevance is by approximating past experiences — that is, by telling stories from past assignments that have some parallel with the problem at hand. Backstage, they search their track record (or their colleagues’) for experiences that echo the current assignment. Then they bring them up in conversation with the client, perhaps pointing to their own contribution. This preserves face while encouraging the client to share more details.

Of course, clients know very well that their consultant hasn’t really learned an entire technical field in a matter of days. But they still appreciate that they’ve done their homework. For their part, consultants use crafting relevance to develop just enough expertise for them to interact with clients, with or without the ability to execute.

Crafting Resonance by Recycling Insider Knowledge

Clients must accept consultants as fellow professionals before they will follow their advice. But it’s hard for a newcomer to fit in straight away, because it takes time to appreciate “how we do things around here.” This exposes consultants to acceptance threats, which they deal with by crafting resonance: recycling insider knowledge to gain acceptance while acquiring new information.

Clever Hans was a horse who tapped his hoof to signal the answer to arithmetic questions. Of course, Hans couldn’t really do math. He simply watched his trainer for cues that he’d given the right answer.

Similarly, consultants monitor their clients for physical approval cues (such as facial expression or body posture) or the words and phrases they use, which often have special resonance. For instance, lawyers from a top firm responded positively to Latin expressions, as they were part of legal work culture and showed intellectual sophistication. So consultants would rehearse these expressions backstage, and then use them in conversations to show that they knew their Latin too, fostering acceptance. Having picked up these expressions, consultants can say the things that clients want to hear, allowing them to fit in despite being outsiders and triggering more engagement during their exchanges.

Second, consultants borrow internal insights from client staff, and then recycle them by presenting them as their own when they’re with other insiders. Some might say this is the sort of thing that gives consultants a bad name — people who “borrow your watch to tell you the time, then walk off with the watch.” But it’s more than just a confidence trick. By watching how people react to their borrowed judgments, consultants can discover which ideas (and people) have support within the organization and choose to amplify them. This can help them tackle “wicked” problems where there are no simple or clear-cut answers.

Crafting Substance by Creating Knowledge Objects

Consultancy services are usually expensive, so clients are concerned with getting value for money in the short term. But it usually takes consultants a while to get up to speed and deliver their highest-value output. In the meantime, the client may question their value add, exposing them to productivity threats. They deal with this using the third and final tactic: crafting substance. This is about creating knowledge objects to display productivity while seeking information at the same time.

The first way to craft substance is by manufacturing PowerPoint figures. While PowerPoint has a mixed reputation, it’s an indispensable tool for consultants to impress their clients with clear thinking, deep understanding, and task progress. Furthermore, PowerPoint figures also serve as prompts that elicit feedback on technical points — with the added bonus that any criticism is directed toward the figure rather than the consultants themselves.

Consultants often use ideographs, combinations of text and images, to express important ideas, and many consulting firms maintain a library of readymade templates to help consultants create their figures quickly and easily. These provide them with a sort of plug-and-play thinking, allowing them to quickly make sense of a situation, boil it down to its essentials, and communicate it.

Sometimes, client organizations already know the answers to their problems, but still can’t articulate them — which means they can’t act on them. By providing powerful ideographs that clients can’t create for themselves due to lack of time or resources, consultants can make a telling and visible contribution.

The second method of crafting substance is by tendering activity proofs such as timesheets and workload schedules. As well as giving an impression of control and professionalism, they can help draw out what the client expects, which can be a movable feast. They can also function as protective amulets to ward off clients’ anger at a perceived lack of progress.

Putting your ideas out there in a tangible, stable form is a risk. But it’s a risk that consultants must take, however little they know about the business context, because it shows clients that consultants are committed to the project and are providing value for the money. However, it also helps consultants build their understanding of the new setting, and creates a formal space for feedback on the assignment.

Many People Manage Learning-Credibility Tension

We studied how consultants manage learning-credibility tension. But many others must deal with it too, including temporary staff, project team members, analysts, professional advisers, and freelancers. These workers are not just optional extras; they make a crucial contribution to many organizations. No wonder global executives believe they will be in high demand for years to come. Besides, managers in general can also be included in this group — they are sometimes thought to be a kind of “consultant” themselves.

Like consultants, all of these types of workers have to adapt to a different setting with each new client or project and grapple with dynamic, hard-to-grasp problems from day one. They have to prepare carefully, establish their competence, understand the environment, and cultivate acceptance from new colleagues or clients, often by producing deliverables. And they may have to do all this without any backup from a consultancy firm.

Fortunately, anyone can use the tactics we’ve described, not just consultants. Learn to use them successfully, and you can build confidence, feel better about your work, and maintain your face.

However, managing learning-credibility tension is something much deeper than “personal PR” or acting out a role. It will also help you to gain new insights, share information, and work toward longer-term goals. After all, without belief and acceptance from those around you, your important new project will never get off the ground.

Given how chaotic and unpredictable working life can be, it’s not surprising that more and more people are falling prey to impostor syndrome, the fear that you’re not up to the task and will be found out. For most workers today, that feeling is ever-present.

However, when you reframe feeling impostor syndrome as managing learning-credibility tension, you turn it from a psychological flaw into a vital skill. In our research, we found that consultants don’t just have impostor syndrome, they actively embrace it — because it keeps them sharp and on the edge, where they need to be.

Categories: Blogs

4 Ways Women Can Build Relationships When They Feel Excluded at Work

Harvard business - Fri, 07/27/2018 - 08:00

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A male friend of ours recently had a realization. He was walking through the bar at a private golf club, looking for a colleague he was meeting for dinner. The dark-paneled bar was filled with men and they all seemed to know each other. Will wasn’t a member of the club, and he felt a little out of place. When he found his friend and they sat down at a table, he felt more comfortable. Then he looked around and realized that only about five of the 35 people in the large room were women. Even if they were members, these women stood out in this mostly male setting. He could blend in so easily. These women didn’t have that luxury.

Welcome to our world. As female executives, it’s sometimes difficult for us to fit in, but we need to be in that room nonetheless.

There are typically two ways to get things done professionally. One way is explicit, established, and formalized: the job-specific mode we use to get our work accomplished every day. Job descriptions, agenda items, expertise, and hierarchy dictate how this work is done and how formal decisions are made. The other way is informal, highly nuanced, and relationship-based. It involves leveraging human connections, corporate maneuvering, physical proximity to decision makers, and personal and professional influence inside the office and outside at informal gatherings. While both ways are important, we have seen in our work coaching women executives that they overwhelmingly struggle more than men to take advantage of informal networking situations. Part of the problem is systemic: When men go out together after work, women often are not invited. Eighty-one percent of women say they feel this type of social exclusion in work situations. Based on published reports, this problem has further intensified as the #MeToo movement has grown, with men saying that they feel more hesitant to socialize with female colleagues for fear that their motives might be called into question. Many men we know or work with have told us that this is a genuine concern for them today.

You and Your Team Series Networking

The other issue is that women themselves often can’t or don’t want to socialize after work or during work hours. They keep their heads down at the office to maximize their efforts, and then they feel the pressure to head home to spend time with their families (and often to start their “night shift” of cooking, laundry, homework help, and bedtime routines). Many of our women coaching clients have told us things like: I don’t have time to go out with the group. Nothing gets done at these things anyway. It’s all politics.

Regardless of the rationale, the effect is the same: Doing less relationship building limits women’s access to sponsorship and diminishes their chances for career advancement. Developing informal relationships is one of the most important things women can do to advance their careers. With our livelihoods on the line, we need to turn this dynamic around.

By committing to a manageable combination of informal relationship building inside and outside the office, we can amplify our efforts and develop genuine influence with senior colleagues and decision makers. Here’s how:

Leverage informal norms. Is your workplace a coffee culture? Do people play cards or grab a drink together after hours? Knowing what social rituals define your organization makes relationships easier to maneuver. There’s no need to get a lunch on the calendar, for instance, if you know the executive vice president is in line at Starbucks every morning at 7 AM. Regardless of the specifics, seize easy opportunities to connect.

Similarly, examine the cross-silo social networks that underlie your organization. Perhaps the tech-savvy crowd all sit together at staff meetings, or the young moms meet at the park on Sundays. Even if you don’t fit within any of the social networks yourself, just knowing who does can tell you who’s closely connected to whom. This also applies to the social networking tools that people use. Knowing how people connect allows you to reach out to them more easily.

Make meaningless time more meaningful. Legitimate time constraints are the most common reason women cite for ditching dinner with colleagues or skipping “optional” work events. Because of that, it’s crucial to maximize the time we do have. For instance, arrive five minutes early to meetings and start a conversation. Walk to the train with someone you know is going your way. An accomplished publishing executive we coach arrives to the office 10 minutes early every morning and walks around the building. Sometimes she has an agenda; other times she simply stops to chat with whoever’s milling around. She always catches somebody and finds out what’s going on. If she’s proposing a new project at the following week’s meeting, she gets early feedback and she’s more prepared for her presentation. The point is to make your extraneous time more meaningful by using it to form connections. The informal information flow is powerful.

Suit yourself. Relationship building is never a one-size-fits-all proposition. Don’t bother learning to play tennis if that’s not your thing. Decide what you like — opera, ball games, wine tasting, trendy eateries — and invite a few colleagues along for fun. If you are an introvert, don’t go it alone. Meet a few work friends and head to the company party with them. It’s fine to work the room in pairs. The same goes for informal socializing. It doesn’t need to be a one-on-one event. Getting a group together to have drinks or dinner makes it easier to talk to someone you don’t know. Many women prefer to invite colleagues and their spouses or partners into their home, instead of meeting solo or going out to dinner together. Most of us are more comfortable on our own turf.

Doing it the way you want to makes you more comfortable and lets people get to know you in a way that can change how they perceive you.

Face forward. It’s not only teenagers who can’t tear their eyes away from their smartphones; screens rob all of us of precious face-to-face interactions. This is an easy one: Stop hiding behind your phone. Look people in the eye and talk to them, whether it’s before the meeting starts, on your way to lunch, on the stairs, and in the elevator. Simply being fully present will help you make many more crucial connections.

As women, we need to continue to work together to think of new solutions to this old problem. The higher we rise in organizations, the more important informal interactions become. Regardless of the venue or activity, relationship building is just another part of the job.

Categories: Blogs

The Democratization of Data Science

Harvard business - Fri, 07/27/2018 - 07:00

Patricia Toth McCormick/Getty Images

Want to catch tax cheats? The government of Rwanda does — and it’s finding them by studying anomalies in revenue-collection data.

Want to understand how American culture is changing? So does a budding sociologist in Indiana. He’s using data science to find patterns in the massive amounts of text people use each day to express their worldviews — patterns that no individual reader would be able to recognize.

Intelligent people find new uses for data science every day. Still, despite the explosion of interest in the data collected by just about every sector of American business — from financial companies and health care firms to management consultancies and the government — many organizations continue to relegate data-science knowledge to a small number of employees.

That’s a mistake — and in the long run, it’s unsustainable. Think of it this way: Very few companies expect only professional writers to know how to write. So why ask only professional data scientists to understand and analyze data, at least at a basic level?

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Relegating all data knowledge to a handful of people within a company is problematic on many levels. Data scientists find it frustrating because it’s hard for them to communicate their findings to colleagues who lack basic data literacy. Business stakeholders are unhappy because data requests take too long to fulfill and often fail to answer the original questions. In some cases, that’s because the questioner failed to explain the question properly to the data scientist.

Why would non–data scientists need to learn data science? That’s like asking why non-accountants should be expected to stay within budget.

These days every industry is drenched in data, and the organizations that succeed are those that most quickly make sense of their data in order to adapt to what’s coming. The best way to enable fast discovery and deeper insights is to disperse data science expertise across an organization.

Companies that want to compete in the age of data need to do three things: share data tools, spread data skills, and spread data responsibility.

Sharing Tools

Most data tools sit with the data science team. While this may seem logical, creating a silo of data tools and restricting access to a narrow group of employees places too heavy a burden on those employees. Most inquiries from other departments — engineering, finance, product, marketing — are relatively simple requests that anyone with basic training could fulfill. By saddling data scientists with basic gatekeeping tasks, organizations divert their attention from the larger projects that require their deep expertise.

Airbnb, a huge believer in the democratization of data science, strives to empower every team member to make data-driven decisions. To ensure that, the company created its own Data University.

Collaborative tools help too. At Airbnb, anyone can post an article to a Knowledge Repository. The rest of the company sees new analyses in a news feed, letting them know (1) which new problem has just been solved and (2) who solved it, so anyone with further questions can know whom to call. In addition to helping the whole company become more effective, such articles give recognition to the people who post them — which incentivizes others to do the same.

Sharing Skills

Of course, when you share data tools, you also need to enable people to use those tools. Not every company can create its own Data University. Depending on the data tools your organization uses, though, a variety of educational programs, both online and in person, can get your team up to speed. (Of course, I’m biased: I cofounded one of them.)

As your team gains the opportunity to learn those skills, they’ll feel more comfortable bringing data to bear on every important decision. It will become clear that some team members are more comfortable using data skills than others are. Encourage the proficient ones to mentor the others. Even at our company, where data science is our business, some people don’t work with data all the time. When they need help on a knotty problem, they pair up with those who do.

A data-literate team makes better requests. Even a basic understanding of tools and resources greatly improves the quality of interaction among colleagues. When the “effort level” — the amount of back-and-forth needed to clarify what is wanted — of each request goes down, speed and quality go up.

Shared skills improve workplace culture and results in another way, too: They improve mutual understanding. If you know how hard it will be to get a particular data output, you’ll adjust the way you interact with the people in charge of giving you that output. Such adjustments improve the workplace for everyone.

Sharing Responsibility

Once an organization is delivering the access and education needed to democratize data among its employees, it may be time to adjust roles and responsibilities. At a minimum, teams should be able to access and understand the data sets most relevant to their own functions. But by equipping more team members with basic coding skills, organizations can also expect non–data science teams to apply this knowledge to departmental problem solving — leading to greatly improved outcomes.

If your workforce is data-literate, for example, your centralized data team can shift its focus from “doing everyone else’s data work” to “building the tools that enable everyone to do their data work faster.” Our own data team doesn’t run analyses every day. Instead, it builds new tools that everyone can use so that 50 projects can move forward as quickly as one project moved before.

Data science isn’t just for data scientists anymore, if it ever was. Smart companies today ensure that many of their employees can speak the language of data and use it to improve work outcomes. By empowering employees with these fundamental skills, companies are realizing tremendous levels of innovation and efficiency.

Categories: Blogs

How to Be a Smart Consumer of Social Science Research

Harvard business - Fri, 07/27/2018 - 06:05

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Academic studies in the social sciences often find very different results. Even in disciplines like medicine, where one might imagine there to be a direct, physical relationship between the intervention being tested and its consequences, results can vary — but many think the situation is worse in the social sciences. This is because the relationship between an intervention and its effects may depend on multiple factors, and differences in context or implementation can have a large impact on the studies’ results.

There are other reasons that studies might report different effects. For one, chance errors could affect a study’s results. Researchers may also consciously or subconsciously bias their results. All these sources of variability have led to fears of a “replication crisis” in psychology and other social sciences relevant to business. Given this variability, how should we consume evidence?

The immediate answer is to not rely too much on any one study. Whenever possible, look for meta-analyses or systematic reviews that synthesize results from many studies, as they can provide more-credible evidence and sometimes suggest reasons why results differ.

When considering how much weight to give a study and its results, pay attention to its sample size. Studies are particularly likely to fail to replicate if they were based on a small sample. The most positive and negative results are often those with the smallest samples or widest confidence intervals. Smaller studies are more likely to fail to replicate in part due to chance, but effects may also be smaller as sample size increases, for several reasons. If the study was testing an intervention, there may be capacity constraints that prevent high-quality implementation at scale. For example, if you were testing out a training program, you might not need to hire any full-time personnel to run it — but if you were to expand the program, you would need to hire new staff, and they may not run it quite as well.

Smaller studies also often target the exact sample that would yield the biggest effects. There’s a logic to this: If you have a costly intervention that you can allocate to only a few people, you might perform triage and allocate it to those who could benefit from it the most. But that means the effect would likely be smaller if you implemented the intervention in a larger group. More generally, it can be helpful to think about what things might be different if the intervention were scaled up. For example, small interventions are unlikely to affect the broader market, but if scaled up, competitors or regulators might change their behavior in response.

Similarly, consider peculiarities of the sample, context, and implementation. How did the researchers come to study the people, firms, or products they did? Would you expect this sample to have performed better or worse than the sample you are interested in? The setting could have affected the results too. Was there anything special about the setting that could have made the results larger?

If the study was evaluating an intervention, how that intervention was implemented is very important. For example, suppose you hear that reminder messages can improve attendance at appointments. If you were considering implementing a reminder system, you would probably want to know the frequency of the messages the researchers sent and their content in order to gauge whether you might have different results.

You may also have more confidence in the results of a study if there is some clear, causal mechanism that explains the findings and is constant across settings. Some results in behavioral economics, for instance, suggest that certain rules of human behavior are hardwired. Unfortunately, these mechanisms can be very hard to uncover, and many experiments in behavioral economics that initially seemed to reflect a hardwired rule have failed to replicate, such as a finding that happiness increases patience. Nonetheless, if there is a convincing reason that we might expect to see the results that a study has found, or if there is a strong theoretical reason that we might expect a particular result to generalize, that should lead us to trust the results more.

Finally, if it sounds too good to be true, it probably is. This might sound like a cliché, but it’s based on a principle from Bayesian statistics: Stranger claims should require stronger evidence in order to change one’s beliefs, or “priors.” If we take our priors seriously — and there is reason to believe that, on average, humans are pretty good at making many kinds of predictions — then results that seem improbable actually are less likely to be true. In other words, holding constant the significance of a result or the power of a study, the probability of a “false positive” or “false negative” report varies with how likely we thought it to be true before hearing the new evidence.

This article emphasizes the importance of drawing on many studies, rather than relying too much on any one study. What if there haven’t been many studies? If that’s the case, you may wish to consider other sources of evidence, such as advice or predictions from others. Just as with social science research, you may get conflicting advice, but aggregated forecasts can be quite accurate. However, make sure your sources are not relying on the same information; research has found that people are subject to “correlation neglect,” so that when multiple experts or news outlets base their reports on the same study, people incorrectly treat those sources as independent and end up over-weighting that study’s results.

Overall, trust a mix of your experience and the evidence, but be careful not to be overconfident in your assessments. Most people could benefit by weighing the evidence more, even when results vary.

Categories: Blogs

Find Time to Focus on Accuracy – Friday Distraction

Hr Bartender - Fri, 07/27/2018 - 02:57

(Editor’s Note: Today’s post is brought to you by our friends at Kronos, a leading provider of workforce management and human capital management cloud solutions. Have you checked out the Kronos blogging community? Lots of great resources focused on being a department of one, workforce management, and competitive differentiation. Enjoy today’s article!) 

Years ago, I worked for a company that did everything at the last minute. Even if they didn’t need to. They loved working under the pressure of pulling a project together under a time crunch. It drove me crazy! They could have easily planned the project out, worked on a little bit each day, and completed the project early … without stressing everyone out.

I also wondered if the quality and accuracy of the project suffered as a result. It’s not always the case, but let’s face it, sometimes in an effort to meet a tight deadline we have to cut corners. Obviously, we don’t want to do that. Depending on the project, rushing our work could have an impact on safety and security. As today’s Time Well Spentfrom our friends at Kronospoints out, we need to find ways to focus on the accuracy of our work.

Recognize that all work isn’t eligible for multi-tasking. I realize that we often have to multi-task. That being said, not all work should bemulti-tasked. There are some activities that should be completed on their own. Sometimes that’s because the task is complex. In other cases, it’s because we’re new at the task and need to concentrate. Regardless, we shouldn’t multi-task all day, every day.

Identify tasks that need greater focus and attention. Speaking of multi-tasking, try to think about the tasks you’re responsible for and the best way to complete them. Would it make sense to do them at the beginning or end of the day, when it’s less noisy around the office? Is it possible to do two things at the same time? For example, I do a lot of reading and listening to webinars while walking on my treadmill desk.

Set aside uninterrupted time to complete complex work. If you need to get something done, don’t hesitate to block off an hour on your calendar, close the door, and get it done. It’s better to complete a task in an hour uninterrupted versus two hours with interruptions. Now, I will admit that everything can’t be an uninterrupted task. We do need to be approachable. But when we’re faced with a deadline, sometimes it’s necessary.

I totally get it. Our professional lives are busy and full. On some levels, I wouldn’t have it any other way. But there’s a fine line between busy and overwhelmed. We need to be able to focus and have the time to do our best work. That means knowing when to multi-task and understanding the best ways to disconnect and focus on our work accuracy.

The post Find Time to Focus on Accuracy – Friday Distraction appeared first on hr bartender.

Categories: Blogs


Harvard business - Thu, 07/26/2018 - 11:33

Is a recent firing weighing on you? In this episode of HBR’s advice podcast, Dear HBR:, cohosts Alison Beard and Dan McGinn answer your questions with the help of Susan David, a psychologist, lecturer at Harvard Medical School, and the author of Emotional Agility. They talk through what to do when your coworker has been wrongfully fired, your company has massive layoffs, or you’ve been fired.

Download this podcast

Listen to more episodes and find out how to subscribe on the Dear HBR: page. Send in your questions about workplace dilemmas by emailing Dan and Alison at

From Alison and Dan’s reading list for this episode:

HBR: The Right Way to Be Fired by Maryanne Peabody and Larry Stybel — “It’s natural to want to believe that the company for which you work so hard cares about you. But allowing yourself to be lulled into a false sense of security sets you up for shock and disappointment when you are fired or laid off.”

First Round Review: How to Lead and Rally a Company Through a Layoff — “A layoff shouldn’t be a surprise to leaders, nor to its people. It’s not something that happens to a company. It’s an act by its leadership when no other routes can be pursued. In other words, when a layoff is your way forward, you should implicitly be telling people that you’ve exhausted every other route.”

HBR: Firing Back: How Great Leaders Rebound After Career Disasters by Jeffrey A. Sonnenfeld and Andrew J. Ward — “No one can truly define success and failure for us—only we can define that for ourselves. No one can take away our dignity unless we surrender it. No one can take away our hope and pride unless we relinquish them. No one can steal our creativity, imagination, and skills unless we stop thinking. No one can stop us from rebounding unless we give up.”

HBR: After Layoffs, Help Survivors Be More Effective by Anthony J. Nyberg and  Charlie O. Trevor — “If your firm has downsized recently, you’re now managing a bunch of survivors—the lucky ones who didn’t get laid off. But good fortune doesn’t make for good performance—at least not in this situation. Chances are, you’re presiding over a heightened level of employee dysfunction, even if you don’t see it yet.”

Categories: Blogs

A Quick Review of 250 Years of Economic Theory About Tariffs

Harvard business - Thu, 07/26/2018 - 10:48

Lya_Cattel/Getty Images

As the saying goes, “History does not repeat itself, but it rhymes.”

After a long exile, tariffs are back, and they’re being levied on billions of dollars of traded goods, ranging from steel and aluminum to Harley-Davidson motorcycles. They’re part of a trade war between the U.S. and China, and between the U.S. and the EU (although a conversation this week between President Donald Trump and Jean-Claude Juncker, president of the European Commission, may ease some of those tensions — we will see).

Tariffs are taxes imposed by a country that make imports more expensive. The U.S. enacted this recent round of tariffs as a response to its trade deficit (when a country buys more from abroad than it sells). The idea is to make foreign products less desirable and thus protect domestic industry.

But the greatest economists in history would be wary of imposing taxes to address a trade imbalance. The better way to reduce a trade deficit is to export more, not to reduce imports by making them more expensive.

Using tariffs to improve a country’s trade position was essentially what Britain rejected over a century ago. The argument was won due to the work of two great economists, Adam Smith, the father of economics, and David Ricardo, the father of international trade. When the UK repealed the Corn Laws, a piece of protectionist legislation, in 1846, it marked an era of greater opening for Britain, then the dominant trader in the world.

What the Great Economists Thought About Tariffs

Unlike many economists, Smith had the chance to put his theories into action. As the commissioner of customs for Scotland, he advocated removing all trade barriers, which was qualified only by the need to raise revenue for what he considered to be the proper purposes of governing a country, such as providing roads. He supported levying duties on imports and exports at a moderate level, but not so high that smuggling would be profitable.

True to Smith’s beliefs about government policies not distorting the market, he would set duties to be equal for different producers and importers, so that one group or one country would not have an advantage over another. For instance, he saw the inequity of exempting the product of private brewing and distilling (which was imbibed by the rich) from excise duty while taxing the preferred tipples of the poor.

So, if tariffs were necessary, they should treat all traders and trading nations the same, so as to not distort the “invisible hand” (his most notable contribution in The Wealth of Nations) of the market allocating what producers should make.

Later economists deviated from Adam Smith in developing new lines of inquiry, but retained his insights. Inspired by The Wealth of Nations, David Ricardo developed the theory of comparative advantage, which shows that nations should specialize and then trade, which led to greater prosperity.

In the 20th century, great economists such as Paul Samuelson further enhanced our understanding of international trade by pointing out that there are those who benefit more, and others who benefit less, when a nation specializes, even if the economy gains overall. Thus, his work highlights the distributional impact of trade and points to ways of helping the losers of globalization.

Even as our understanding of the issues around trade has evolved, the central tenets laid out by the great economists from two centuries ago remain. Tariffs are a protectionist measure that is inefficient and also distortionary if higher taxes on some imports mean they become less competitive relative to others.

Looking Ahead

Countries have often used protectionism to foster home industries until they are able to compete with established firms. This was the case for the United States in the 19th century when competing against Britain, and is still the case for China in a number of sectors.

China in particular is not as open to trade as the U.S. and EU, which has been a perennial complaint of Western businesses, and so far China has been measured in its tit-for-tat responses to each round of American tariffs. The U.S. is threatening to levy tariffs on nearly all Chinese exports, some $500 billion, unless the U.S.-China trade position improves. China won’t easily be able to retaliate in a like fashion since it doesn’t import half a trillion dollars of goods from the U.S. But China could choose to mirror the U.S. in imposing investment restrictions, which would be very damaging as they would distort the supply chains and the operational decisions of multinational companies. This would not be easily reversed, unlike tariffs, which can be levied one day and removed the next. There are some signs that investment has been affected by trade tensions. China scuppered U.S. tech company Qualcomm’s bid for Dutch chipmaker NXP even though the global deal had been approved by U.S. and EU regulators.

Further distorting trade, which partly comes about through companies investing in supply/distribution chains and conducting M&A across national borders, would be something that the great economists would oppose. After all, there is consensus among them that international trade benefits an economy.

The great economists would likely say that there are better ways to improve a country’s trade position, such as opening up the global market for services trade. This would disproportionately benefit the U.S. as the biggest exporter of services worldwide, competing well even with trade barriers in place. If China opened up more of its services sector, as it is already warily looking to do, then that could increase U.S. exports to China and reduce the trade deficit, for one. The UK, the second biggest exporter, and other advanced economies such as the EU and Japan would also see an improvement in their trade position, as the bulk of these advanced economies comprises services. Even accounting for the fact that services are not always traded (for example, restaurants), the EU has pointed to the potential to sell more services that would better reflect what it produces. For example, the economy of the EU is 70% services, while services make up just a quarter of exports.

In sum, selling more, rather than importing less (and thus consuming less or producing with more-expensive components), is one of the lessons to draw from history’s greatest economists.

They argued for the opening up of markets around the world so that countries could sell more of what they produce — which would bring about greater prosperity. Their insights continue to underpin economics today. Politics, however, are another matter.

Categories: Blogs

Check Out My Interview on Jennifer McClure's Impact Maker's Podcast...

Hr Capitalis - Thu, 07/26/2018 - 10:16
Recently I had to the opportunity to appear on Jennifer McClure's Impact Makers Podcast. Jennifer's doing a great job with this podcast - very high end, go subscribe here - and of course, take a listen to my interview by... Kris Dunn
Categories: Blogs

How to Advance in Your Career When Your Boss Won’t Help

Harvard business - Thu, 07/26/2018 - 09:00

Andrew Lichtenstein/Getty Images

I recently moderated a panel at a conference and asked the group of successful executives to describe someone who has been instrumental in their careers. Two panelists eagerly jumped in with stories of bosses who had mentored, encouraged, and opened doors for them. Then, hesitantly at first, the last person shared a far different experience.

She lamented that she’d never been lucky enough to work for someone like that, and at times felt that the lack of an effective boss was career-derailing — even a personal failure. At one point she had worked for a leader who had started to coach her but was then replaced by someone with such a lack of political savvy that she learned to do exactly the opposite of whatever he advised. Eventually she figured out that instead of waiting for a boss who could advocate for her, she had to create a work-around.

As she spoke I noticed how many people in the audience were nodding their heads, and afterward she was flooded with questions.

A sponsor can be invaluable to helping you achieve your career goals and getting ahead in an organization. The first place we all look for an advocate is our immediate boss, the person who is closest to our work. A good advocate offers advice and mentorship while also shining a light on our potential — revealing capabilities that we may not know we have. We borrow an advocate’s confidence in us until we adopt it fully ourselves. One of the panelists recounted a story of how his boss had shocked him by suggesting him for a job before he was ready. He took it, and with his boss’s close guidance, learned as he went.

They also serve as role models, allowing us to see how we can accomplish what they’ve done. (This is one reason why representation is so critical to changing gender and racial imbalances in companies.)

But in my experience, having a career-supporting advocate is an uncommon find in our direct managers. Supervisors too often lack people development skills or organizational influence. Or they are too protective of their own status to risk elevating someone else.

So what should you do if you’re not one of the lucky ones with a powerful boss who supports you? First, know you’re in good company: The playing field isn’t as uneven as you may think. Second, use the following advice to find what you don’t have in your boss.

Create an advocacy team. Instead of having one person in your corner, consider putting together a team of people who can help you advance your career. Think broadly across levels and functions, both inside and outside your organization. Look for people whose careers are further along than yours and whose style or achievements you admire. It can help to write the qualities you want to develop and match them with a list of people who exhibit them.

You and Your Team Series Office Politics

A graceful way to approach a potential advocate is to ask for advice. Rather than showing inadequacy, asking for advice makes people seem more credible, according to research from Harvard Business School and the Wharton School. Further, when people provide advice they become invested in it, and therefore in you. This doesn’t have to be formal, and in fact your advocates may not ever know that’s how you view them.

Being forced to assemble a group of advisers rather than having one great boss can be an advantage. If you’re too dependent on one person, you might fail to establish a resilient network and end up in the corporate abyss if your boss leaves the company. Further, while having your brand tied to one leader is an asset when that leader’s stock is rising, if the leader falls out of favor, that closeness can create a reputational hit.

Prioritize visibility. Without your boss putting you in front of stakeholders, you need to find your own platform. Look for cross-functional or internal projects that will involve or be debriefed to stakeholders. If one doesn’t exist, propose a project that aligns with the corporate values or vision or that solves a stated need.

For example, a client of mine volunteered to start a diversity and inclusion working group to determine why the company wasn’t attracting diverse talent above the manager level, despite its a stated corporate priority. She used her leadership and strategic skills to drive the process and presented the team’s findings to the executive team. The CEO created a VP of diversity role and promoted her into it.

Find the influencers and offer to help. In every organization there are centers of influence, some of which may not map to positional power. Think, for example, of the influence of a strategic adviser who retires from the executive team, or the CEO’s long-standing assistant.

Babson College professor Rob Cross advises drawing maps of how people are connected to show spheres of influence in the organization, paying special attention to those with large numbers of connections. His research shows how new employees can succeed without a formal mentor by developing productive relationships with key opinion leaders.

When you determine who the influencers are in your work, make yourself helpful to them. Look at what you can offer them rather than just what they can give you. Contribute to their efforts without expecting a short-term return. Trust in the long-term benefit of the relationship. Being a giver, as Wharton professor Adam Grant calls it, is often far more beneficial and effective than being just a taker.

Use positive outside pressure. Building your status outside the organization can often gain you visibility inside it. Corporate leaders notice who is visible to customers, stakeholders, and the broader industry. Professionals at any level can build a solid platform that has a greater reach than their position might indicate.

Choose a way to do this that is genuinely interesting to you. You might decide to join an industry association and work toward holding a leadership position there. You can build a following on social media by demonstrating expertise and engaging with known thinkers in your field. Corporate public relations departments are typically eager for employees to provide ideas and to be available for media interviews or article submissions. Ask the PR team how you can best assist them in their goals, and follow up on what they suggest. Bringing ideas around your interests and expertise — and continually feeding the PR team interesting topics — can make you a go-to resource.

Imagine a customer telling your leadership that one of the reasons they selected your company was because of an article you wrote about industry trends. This is not a farfetched concept: I have heard clients include industry recognition as an important factor when evaluating team members. It’s hard for even the best internal recognition to match external validation.

If you have the option, there’s no question that finding a supportive boss with influence is a direct benefit to your career. But even that may not be enough. Companies are dynamic, and having other ways to advocate for yourself — or having others do it — is a more sustainable approach. Building a range of supporters who can help you grow in diverse ways may be the best advantage you can have.

Categories: Blogs

For Some Platforms, Network Effects Are No Match for Local Know-How

Harvard business - Thu, 07/26/2018 - 08:46

SinghaphanAllB/Getty Images

When is it possible for David to beat Goliath in the platform economy? On March 25 mighty Uber bowed out of Southeast Asia by selling its operation in several countries to local rival Grab. The news came as a surprise to many observers. Grab, which launched its service in 2012 with 40 drivers in Malaysia, came late to the ride-hailing game, only after Uber had established a formidable position in the United States. Three months after the sale, in June 2018, Toyota decided to pour $1 billion into Grab, in a bid to expand other offerings in the region including food delivery and electronic payments.

Uber’s setback in the international market, however, wasn’t its first. In 2016 the company sold its China operation to Didi Chuxing because of the fierce competitiveness of the local player. Uber had reportedly spent $2 billion over a two-year period trying to battle Didi. A year later, Uber admitted defeat in another region, selling its operation in Russia to Yandex.

This seems to be a strange situation. In the internet economy we often see winner-take-all dynamics playing out, meaning one company, or platform, rules a certain sector: Google dominates online searches, Facebook dominates social networks, Twitter has microblogging, Netflix has entertainment streaming, YouTube has video sharing, and Spotify has music streaming. But Grab versus Uber seems to defy this winner-take-all narrative. When and how can a smaller local player fend off a global giant? And what can Grab teach us about the future of platform businesses?

To venture capitalists and the financial market, no business model is more attractive than a platform. A platform is essentially a marketplace that connects the supply side (goods and services) and the demand side (people who want to buy them). For example, Uber and Grab link riders and drivers, Airbnb links hosts and travelers, and Amazon links shoppers and sellers. The spectacular growth of these businesses has been commonly explained by “network effects,” a common refrain among economists and academics. They argue that the value of a platform depends in large part on the number of users on either side of the exchange. The more users a platform has, the more attractive it becomes, leading even more people to use it. And once a platform reaches a certain size, the thinking goes, it becomes too dominant to unseat.

But Grab’s triumph over Uber illustrates that size is more a consequence of success than the direct source of it. Any platform still needs to achieve a product-market fit to succeed in the long run. What works well in one country may fare badly in another, especially when the product being sold is a physical rather than a digital one. Uber, like all transportation services, has never and will never offer a product that’s composed purely of digital “bits,” as companies do in media (Netflix and YouTube), music (Spotify), or advertisements (Facebook and Google). When a platform strategy requires mixing the digital and the physical, the area of differentiation lies in service delivery in the physical world. And in the physical world, products can’t exist as an app, like Uber’s, that has only one version and is uniformly rolled out across the world.

This is a subtle but important distinction. As more sectors embrace a digital strategy — transportation, aviation, health care, energy, and so on — managers will find that a deep understanding of their market is still the most potent defense against competition. These sectors have never been, and never will be, composed purely of digital bits. Transportation, aviation, health care, and energy all require physical delivery, whereas media, music, and advertisement do not. What Grab has shown us is that there are sectors where digitalization favors the local players, or players who possess deep know-how about the specifics of their industries. Such knowledge is in fact the prerequisite to innovation.

Anthony Tan, cofounder and chief executive of Grab, saw that it was imperative to understand, appreciate, and build regional distinctions into a product. In the Philippines, where eight major dialects are spoken, Grab’s customer representatives speak the local dialects when someone calls them. Passengers can also text drivers through a chat feature with automated translation. These features are design elements that Uber never showed interest in seriously pursuing. And unlike Uber, which forces drivers to accept credit card payments in the name of “frictionless” transactions, Grab embraces cash. “We understood the taxi drivers’ need for daily income. We understood that a lot of people really use cash. We respect the hyper-local culture in places we operate,” Tan said. Credit card transactions may be frictionless in California; they are impractical for many drivers in the Philippines.

Grab’s success has come from other features, too: In Singapore, it lets users input numeric codes for nearby taxi stands in lieu of addresses. In other parts of Asia, where lack of trust and scanty safety records plague the taxi industry, Grab lets riders retrieve drivers’ police records through the app and share routes and license plate numbers with friends and family. The app also masks passengers’ phone numbers on the driver’s end as an additional safety precaution. Again, Uber never took the lead to pioneer such features.

In Indonesia, road congestion is endemic. Grab decided to offer rides on motorcycles, a service it called GrabBike. Thanks to this service, the company has surpassed Google in the efficacy of its route-planning suggestions in and around Jakarta: Tens of thousands of motorcyclists navigate back roads and side streets to avoid traffic, all the while sweeping up copious amounts of GPS data. Though none of these tweaks can be claimed to be a technological breakthrough, they have collectively helped Grab win over local consumers.

From this perspective, Uber’s ultimate mistake was letting its app stay largely unchanged. In other words, the initial innovations that made Uber dominant also left it vulnerable. What Grab has vividly illustrated is that local adaptation — the timeless advantage of traditional companies — is essential for platform businesses. Historically, some platforms haven’t embraced localization because the allure of quick scaling was too much to resist. But network effects don’t negate the importance of customization.

So if an indiscriminate rollout across geographic regions is becoming less viable, how can companies accelerate growth for the platform?

As improbable as it might seem, a role model for platform growth and customization can be found in a Japanese publisher. Recruit Holdings started out in the 1960s as an advertising company that published magazines for job seekers. (Today the company specializes in HR and recruitment services; among its acquisitions have been the U.S. job websites Indeed and Glassdoor.) Spurred on by the internet revolution in the early 2000s, the company added verticals such as real estate, the bridal industry, travel, beauty salons, and restaurants. But moving to digital publishing and simply being online had very little growth potential.

During this time, management noticed that proprietors who placed ads with Recruit often represented small businesses. Although fiercely independent, these entrepreneurs struggled with back-end administrative tasks. A beauty salon, for example, might get more reservations with Recruit’s online ad service, but most likely it would still rely on paper scheduling, done by hand, to avoid double-booking phone-in customers.

Over the next few years Recruit introduced several innovations to keep businesses using its platform. In 2012 it launched the Salon Board, a cloud-based platform for reservations and customer management. The platform was an instant hit among beauty salons, with the killer feature being an automated reply function that eased administrative burdens. A year later it announced AirREGI, a point-of-sale cash register that worked with smartphones and tables and was integrated with a cloud-based data management system. In 2014 the company unveiled AirWAIT, an app that streamlined the waiting process by allowing customers to queue virtually. In 2015 AirPAYMENT went live, eliminating the small-business headache of processing payments and managing cash.

“‘Why us?’ is always the main question. Is there any quality that will give us the upper hand?” Yoshihiro Kitamura, the president of Recruit, said to me. “If it doesn’t give us an upper hand, a Google app or Facebook plugin is enough to kill us. So, when evaluating business opportunities, we must ask, ‘Can we really do it better than everyone else?’”

Recruit Holdings thus offers an alternative strategy for platform growth, one where it’s less about geographic spread than about the depth of a chosen market. China’s WeChat has most evidently pursued this strategy. What was once a stand-alone messaging app is now seen as an indispensable mobile platform for making payments, booking doctor appointments, filing police reports, hailing taxis, accessing banking services, conferencing over video, playing games, and much more. WeChat is Facebook, Twitter, WhatsApp, Apple Pay, and Electronic Arts all wrapped up into one.

Amazon has similarly perfected this pursuit in the United States. It started off by selling books, CDs, and DVDs. Next came many more products, the Kindle, video streaming, and its audiobook company, Audible. When Amazon was building Alexa, its digital assistant, the company positioned it as a portal for consumers to access all of Amazon’s other services.

Both WeChat and Amazon began with basic offerings but gradually branched out to new areas that built on their initial relationships with customers in their largest home markets. There are early signs that Uber is also pivoting toward this strategy, include its increasing emphasis on Uber Eats, a food delivery service, in the remaining international markets where it operates.

As the world embraces digitalization in transportation, aviation, health care, and energy, it is increasingly unattainable to conquer international markets with the simple switch of an algorithm. It was possible for Facebook, Google, YouTube, and Twitter only because of the nature of their businesses, where digital bits are all they deliver. But for platforms that involve any physical offerings, the future is looking more traditional than the past.

Categories: Blogs

How Behavioral Economics Could Help Reduce Credit Card Delinquency

Harvard business - Thu, 07/26/2018 - 08:42

Ryan McVay/Getty Images

With U.S. household credit card debt at an all-time high of more than $1 trillion, delinquent payments can be more costly than ever. For companies, delinquencies can mean massive collection costs and write-offs of entire accounts. For consumers, delinquency can mean late fees, increased interest rates, downgraded credit scores, the loss of vehicles or homes, or even bankruptcy, despite their intentions to bring their accounts current by making a payment large enough to satisfy their credit card balance. Recent research indicates that simple modifications of automated phone prompts provide an inexpensive way for companies to help consumers make good on their intentions, benefiting both parties.

My colleagues Daniel Mochon and Dan Ariely and I collaborated with a large North American store that offers credit cards, aiming to study how to get recently delinquent customers to pay at least a portion of their balance. These are customers who have just missed paying at least their minimum payment and are therefore considered one month delinquent. Most credit card companies, including our collaborating card company, use interactive voice recordings (IVRs) — large-volume automated phone calls — to remind early-stage delinquent customers to pay. This assumes that there are only two groups of delinquent customers: those who are unable to pay and those who simply forgot. To take care of those who forgot, a short automated reminder is thought to suffice: “[Customer name], you have a past due amount. If you have already paid, press 1. If you are going to pay within the next three days, press 2. If you want to speak to an agent, press 3.”

However, we know from many other domains of life that people can have the best of intentions but fail to follow through on them. For example, many of us intend to save more money, live a healthier lifestyle, or start working on our taxes early instead of at the last minute. But life gets in the way; we procrastinate and end up not doing what we intended to do. My colleagues and I thought that this might also be true for some of the delinquent credit card customers. So we tested two separate modifications to the baseline IVR to see if they would help overcome this type of inaction in the case of recipients who indicated they would pay within the next three days.

Our first modified version added an interactive menu level that asked call recipients to select a concrete timeframe within which they would make their payment during the ensuing three days: “If you are going to pay within the next 24 hours, press 1” and so on, continuing through 36, 48, and 72 hours. We expected this intervention to prompt deeper mental engagement that would help them remember their intention.

Our second modified version added yet another interactive menu level right after this new one. Call recipients were asked to take a personalized pledge: “[Customer name], you have committed to pay [total amount due] within the next 24 hours. Press 1 to confirm your commitment to this pledge.” The idea was to strengthen call recipients’ sense of commitment to their expressed intention.

Over nine months we randomly assigned a small subgroup of the company’s early-stage delinquent customers, around 50,000 people, to one of the three IVRs. We found that compared with the baseline IVR, the prompt with the concrete timeframe increased customers’ likelihood to pay by 2.26 percentage points and led them to pay 0.23 days faster. Adding both the concrete timeframe prompt and the pledge increased the likelihood by 2.54 percentage points and the speed by 0.51 days.

What does this mean in dollars? The people in our small subgroup had a mean total amount due of $142. Some 15,000 indicated they would pay within the next three days. If all 15,000 had received the IVR with the timeframe prompt and pledge, instead of the baseline IVR, the improvement in response would have translated into an increase in immediate revenue of more than $56,000.

When scaled to a credit card company’s entire customer population, these interventions could result in significant revenue increases. Moreover, additional customers become delinquent every day, increasing the long-term revenue benefits of such interventions. In addition, they cost little, they scale easily, and they reduce more-costly later-stage collection efforts, which can include letters, live agent calls, and collection agency fees. Meanwhile, consumers benefit from avoiding the costs associated with debt delinquency.

These results demonstrate that even simple, minimal prompts delivered through automated, high-volume IVR calls can bridge the intention-action gap that so often prevents people from completing beneficial behaviors. Asking people to express their intentions more precisely about when they will act and to take a pledge could work in areas ranging from tax compliance to medication adherence to students’ procrastination on assignments. More generally, the results affirm that applying behavioral insights has great potential for increasing economic and individual well-being at low cost, as the recent work of Daniel Kahneman, Steven Levitt, Cass Sunstein, Richard Thaler, and others has shown.

Categories: Blogs


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