Marina Gorbis's Blog, page 794

How Capitec Became South Africa’s Biggest Bank

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The consumer banking industry is notoriously difficult to enter, not least because most customers rarely switch banks. In some countries, people change spouses more often than they change banks.

The banking industry in South Africa was no exception; for decades the industry was dominated by “the Big Four” (Standard, FNB, Nedbank, and Absa). However, in 2000 a new player entered the industry, called Capitec, which started establishing branches rapidly. By 2007 it broke through the barrier of 1 million active customers; 10 years later it had more than 10 million clients and about 800 branches. It has now become the largest bank in the country.

Importantly, profits kept pace. After breaking even in 2002, net profits continued to rise, to 3.8 billion rand in 2017 (about $260 million), while the company’s share price appreciated by a whopping 61,800% (from 117 to 72,500 rand). In 2016 The Lafferty Group ranked Capitec as “The Best Bank in the World,” a feat it repeated in 2017. Its customers seem to agree: Surveys indicate that Capitec has had the most-satisfied customers of all banks in the country — for the past five years running.

Capitec gets many things right in terms of its strategy, including its market positioning, internal operations, and organizational culture. Yet three things stand out that enable it to grow and prosper.

Resisting revenue temptations

Founder and chairman Riaan Stassen said to me: “Our strength has always been our focus.” Indeed, Capitec is more focused, in terms of what it does and does not do, than most companies and certainly most banks. It serves individuals only, not companies or trusts. It offers them a single account: Everybody gets a gold card with exactly the same conditions, prices, and services. A customer can do three things with this account: saving, loans, and transactions — and nothing else. The bank serves these customers through a network of highly efficient physical branches. It has always held on to this model and never wavered.

Companies, and certainly new entrants looking for growth, often find it difficult to resist jumping onto various new sources of revenue. That’s understandable, because if you are looking for growth, any piece of additional revenue seems welcome. Moreover, in advance, you can never be entirely sure that your original market choices will play out and will generate sufficient income by themselves. Hence, when a new potential stream of revenue presents itself, the company’s management feels it cannot afford to just leave it.

The result of this is, however, that a company ends up doing a variety of things that each might make sense on an individual basis but in combination create costly complexity — not adding up to something that is bigger than the sum of the parts. Or, as the late Steve Jobs said, ”Micro-cosmically it might make sense, but macro-cosmically it doesn’t add up.” In order to grow, a company needs a coherent set of choices.

Put differently, a company needs focus. Stanford professor Robert Burgelman called it a “vector strategy”: All the parts of an organization and all the combined efforts of its people need to be working in the same direction. Adding tangentially related sources of revenue gradually wanes strategic focus.

Capitec resisted the temptations of additional sources of revenue that might appear attractive on an individual basis. For many years, it did not offer anything else other than its single account: no insurance, no currency exchange, no small businesses. Recently, however, it has added credit cards to its offering and has begun to offer funeral insurance. This, however, is only after it has become firmly established in the South African market — and that is a point in itself.

Evolving purposefully

Although Capitec has always been remarkably focused, in terms of client segments, its product portfolio, and distribution network, its strategy has changed significantly over the years — as it had planned.

Capitec first entered the industry in rural areas. These areas were underserved by the traditional banks. That is because most people living there are quite poor and the banks figured they could not make much money on them. There were, however, plenty of microlending businesses in those areas, offering unsecured payday loans. Capitec started buying them up and converting them into bank branches. The big banks ignored Capitec: After all, this new entrant focused on the bottom of the market only, something they weren’t interested in anyway.

However, after Capitec had established itself in the rural areas, it started entering the larger cities, such as Cape Town, Durban, and Pretoria. It set up branches near “taxi-ranks”: stations for mini-buses, used by people who generally cannot afford a car. Still, the big banks dismissed Capitec’s travails: These might be customers who already had a bank account, but they still represented the low end of the market, where margins and profits were thin. The big banks happily left them to switch to Capitec.

Yet Capitec’s management was thinking ahead. After it had established itself in the cities, and gained a well-known brand name and reputation, it started setting up branches in high-end shopping malls. The incumbent banks were rattled, but by now it was too late to stop the new kid on the block. Capitec’s foothold was now firm, and it continued growing.

Capitec’s strategy is reminiscent of Harvard Business School professor Clayton Christensen’s model of disruptive innovation: It did not enter the industry taking its competitors head-on, by offering superior products or services. Instead, it focused on the bottom of the market and gradually yet decisively worked itself upward. Now that it is firmly established, it can afford to gradually change its model.

Many entrants into an industry try to offer something new and superior to potential customers, hoping to do even better than the existing players, often targeting the customer segment with the highest margins. But sometimes an entrant’s chances of success are better by focusing its offering on something that is worse than what’s already available in the market, at least on some dimensions.

Yet successful corporate strategists then look ahead and realize that once they have grown, their strategy will likely need to evolve. This does not just mean adding things to their company’s portfolio and value proposition; it also requires ceasing some of the old parts of the original strategy. In Capitec’s case, for example, not a single one of its branches that were converted from microlending shops are still in operation today. Capitec’s management realized the company had moved on and that those branches needed closing. A focused strategy is important, but allowing (or even planning for) that focus to shift in the future is equally relevant.

Breaking outdated habits

Capitec’s founders had learned something, though, from their early forays into the industry, including from the cash loan shops: Companies in the industry seemed to share some puzzling practices. For example, in contrast to the loan shops, all banks in South Africa closed at 3:30 PM. As Michiel le Roux, cofounder and former company chairman, said to me: “I think that is a leftover from the days that money was physical; bank employees needed an hour or two at the end of the day to count the money and balance the books.” Even though most money is electronic, and balancing the books happens in the blink of an eye, banks continue to close at 3:30 PM.

Capitec, by contrast, decided to keep open its branches till 6 PM, or even 8 PM, and on Sundays to accommodate the needs of working customers.

Similarly, across the industry, banks charge a fee on transactions that was a percentage of the sum transferred (which was probably a leftover from the days that money was transferred by check, rather than online, to account for the costs of potential loss or theft). Capitec, instead, charged a fixed fee, regardless of the amount being transferred. Customers loved it, but incumbents found it surprisingly difficult to imitate the practice: Their percentage-based fees were interlinked with various other aspects of their model, such as the budget of their departments, managers’ headcounts, and the bonus system of the executives. It enabled Capitec to remain unique in its offering for an unexpectedly long time.

But it wasn’t only particular practices and systems that Capitec organized differently than traditional banks; it was the whole attitude of the company and its employees, particularly toward customers. In traditional banks, customers had to line up; branches and bank employees could be bureaucratic and intimidating; the inner workings of the banks sometimes were smothering and opaque.

Capitec’s founders had noticed that the cash loan shops often seemed to treat customers much better. Similarly, they decided that Capitec would treat people as what they were: customers. They would be asked to sit down rather than line up if they had to wait; they would look at the computer screen together with the bank employee serving them, rather than face a window or a desk; and they would be made to feel like visiting a retail shop, rather than a banking office. To facilitate this cultural change, Capitec decided to not recruit people from other banks but hire former retailers.

By focusing its new business on removing the industry’s outdated practices, Capitec brought a new model into the industry. Gerrie Fourie, its current CEO, called it “innovating around frustrations.” Companies in well-established industries are often remarkably alike: They do more or less the same thing, and often have all been doing it like that for many years. Sometimes industry insiders just shrug their shoulders when asked why it has to be done that way, proclaiming, “That’s how we’ve always done it.” Sometimes they might even refer the industry’s “best practices.”

But best practices can turn bad, as a result of changing market conditions, customer demands, or progressing technology. Then, innovating by ceasing them can become a source of growth and competitive advantage — just as Capitec has done.

Will Capitec’s success last forever? Probably not: Few things in life do, and business is certainly no exception. The incumbent banks have (finally) started to catch up; moreover, after 18 years Capitec is now an incumbent too, and new, innovative entrants may one day disrupt its model as well. What’s more, the company still relies heavily on unsecured loans, a business that is notoriously risky and hard to value.

But, so far, Capitec’s growth strategy has revealed some lessons for any company that is trying to grow in a crowded, competitive market. It is a story of focused evolution, based on bravely shedding the outdated practices of the industry’s dominant incumbents.

Using Behavioral Nudges to Treat Diabetes

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Health care practitioners and payer organizations increasingly use big data to overcome what might be called a “flaw of averages” in traditional medicine: a treatment that has been tested at a population level might in fact work better for some individuals than others. The goal of precision medicine is therefore to identify treatments appropriate to an individual — rather than a population — based on granular genotype and phenotype data from his or her medical records. The individual data-driven nature of such treatment protocols improves the odds that a specific treatment will work for a specific patient.

But both traditional and precision medicine confront a “last mile problem” involving patient behavior change: even the most appropriate medical treatment will be effective only if the patient follows through on it. The cost of medication non-adherence is conservatively estimated at more than $250 billion a year in the US, and the majority of hospital readmissions after surgery are due to non-adherence to discharge protocols.

Issues of adherence to treatment have been acknowledged and studied for years, but only recently have techniques derived from behavioral science been used to actually improve patient follow-through. Dr. Mitesh Patel, Director of Penn Medicine’s “Nudge Unit” notes, “Human behavior is the final common pathway for the application of nearly every advance in medicine.” Patel and others—including a group at Deloitte—are now exploring whether data-driven precision medicine can also incorporate precision behavioral nudges that improve patient willingness to follow clinicians’ recommendations by offering choices within an incentive scheme designed to address the patient’s specific motivational profile.

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Behavioral scientists are cultivating an ever-expanding repertoire of nudge techniques: subtle design tweaks to environments that prompt individuals to automatically adopt behaviors that are in their best interests. For example, the Wharton behavioral economist Katherine Milkman and her collaborators tested the efficacy of “pre-commitment” strategies” in prompting people to get vaccinated. It turned out that specifying – in writing – the exact time and place when and where they will get vaccinated resulted in measurably better follow-through than making a vague or general commitment. Thus a small, inexpensive bit of choice architecture provides a real shot in the arm for population health. Gamification, “buddy” programs, and text message reminders are other familiar nudge-for-health tactics.

But not everyone will be interested in a game to earn health points, or motivated by a pre-commitment agreement or a buddy keeping tabs on their health behaviors. Just as a particular treatment won’t work equally well for each patient, not every behavioral intervention will nudge everyone equally effectively.

This is where “precision engagement” comes in. Only recently applied to health care, it combines data science and behavioral science to customize the behavioral intervention most likely to motivate a patient to change a behavior and stay engaged in a treatment protocol. In a precision engagement program, instead of only personalizing medicines or treatment protocols, interventions to elicit the desired engagement behaviors are also personalized. Patients are encouraged to adopt recommended health behaviors with interventions that are tailored to their own personalities, motivations, care journeys, and engagement challenges. With the help of artificial intelligence technologies and machine learning algorithms, it is becoming possible to recommend not only medications, but also targeted behavioral interventions. In short, big data can be used to deliver the right nudge to the right patient (or physician), at the right time, and in the right way, to improve adherence to evidence-based therapies.

For precision engagement to work, the provider needs to know a lot about the patient whose behavior is to be influenced. This includes demographic and socioeconomic information, how the patient best receives recommendations in person or through an app, the progress of the care journey, and how he or she responds to social cues and incentives. These all serve as predictive or control variables in analytical models that assess which factors are associated statistically with the desired health behaviors.

To aid in this analysis, the Penn Medicine Nudge Unit is conducting a clinical trial sponsored by Deloitte. The trial, led by Dr. Patel, seeks to understand how different people respond to different types of motivators to influence exercise behaviors among overweight and obese adults. Patients are assessed and placed randomly into one of three different socially driven interventions — competitive, collaborative, and supportive. Typical behavioral interventions like gamification and social incentives are explored with patients.  The trial is collecting the data needed to predict what intervention will work for what patients — to personalize the incentive a patient receives along with their personalized treatments.

Another attempt at precision engagement is being put into action in a clinical setting in Mexico. The clinics, called Clinicas de Azucar (“Sugar Clinics”) — or CdA — the largest private network of diabetes and hypertension clinics in the country, are focused on diabetes treatment for middle and low-income populations. When patients first arrive at the clinic, their HbA1c (blood glucose) levels are usually around 11% (a “crisis” level), but within a couple of visits focusing on treatment and behavior change, their levels stabilize at approximately 7%. This drop results in a 200% to 400% reduction in negative outcomes. This short-term success is worth celebrating. But the fear is that unless patients come back year after year, they may revert to old behaviors and gains will be lost.

Miguel Garza, COO of CdA, says that data can be part of the answer. He notes, “We have been providing diabetes care for more than seven years and we have seen more than 30,000 patients in a one-stop-shop model. So we have a lot of data. We need to find the nudges that eliminate barriers and motivate our patients to exercise more, to eat better, and to take the drugs that are prescribed. And we need to leverage the data to find out which nudges work for which patients.”

CdA and Deloitte are now establishing a Behavior Change Learning Lab to gather and analyze precision engagement data and build predictive algorithms applicable to the larger population. Javier Lozano, the Founder and CEO of CdA, says that the goal is to make sure that precision engagement insights learned from the current clinics can be scaled to support millions of people with diabetes in Mexico and beyond. The typical changes that patients with diabetes have to make in their lifestyle are usually difficult. If we can use precision-engagement data to recommend only the interventions that are most likely influence each patient, we’ll lower patients’ costs and see better outcomes.

At the CdA Learning Lab, the impacts of various types of precision engagement on different care goals will be measured. Goals include clinic membership renewal attendance at 3-month appointments, use of healthy behaviors and habits, and clinic visits for things like nutrition and psychological counseling. Behavioral interventions of various types—targeted on the basis of a patient’s responsiveness to social collaboration and reinforcement—will be tested along with a growing content (message) library to determine what types of messages improves which type of patients’ engagement.

The early success in engagement CdA clinics are seeing with diabetic patients are encouraging, but should become even more impressive as precision engagement plans are rolled out. If these go as planned, the goal then will be to test and scale what we learn for a variety of diseases that can be managed with behavior change, including other aspects of metabolic syndrome (such as hypertension and obesity) and substance use disorder.

The field of disease management has had a somewhat troubled history. We believe this is because effective behavioral nudges have not been widely used. Just as individuals respond differently to drugs, it seems increasingly clear that they will respond differently to well-designed, personalized engagement interventions.

The Problem of Visibility for Women in Engineering, and How They Manage It

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Women engineers have a visibility problem. Like women in other ultra-masculine sectors, they are often excessively visible as women, but overlooked when it comes to their technical expertise. This paradox gets in the way of forming relationships at work and hurts their advancement.

We wanted to know how women deal with this. In 2014 we interviewed 50 women engineers in three leading FTSE 100 organizations in the UK. All three organizations said they were committed to diversity and were attempting to hire, retain, and promote more women engineers. However, numbers remained persistently low, and in all three organizations attrition was high, especially among junior women. But the women we spoke to had remained in their companies, and several had advanced to senior positions. We asked them about their day-to-day experiences of work, opportunities for career progress, and how they overcame the challenges they faced.

More on our sample

We interviewed female engineers from three companies. The first supplies fuel, energy, and petrochemicals to customers around the world (and women comprise 12% of its engineering workforce); the second is one of the world’s leading suppliers of gas and diesel engines (and women comprise 9% of its engineering workforce); and the third is a luxury motor manufacturer owned by a multinational automotive company (and women comprise 8% of its engineering workforce). Our respondents ranged in age from mid-20s to mid-50s, and were evenly divided between early, middle, and later career. Within their engineering sectors, they worked in a range of specialties.

Our respondents talked at length about how their competence was obscured by their gender. They felt sexually objectified, and they had to work harder than men to prove their technical competence. They said colleagues often focused on their looks as opposed to their work.

From our interviews, we recognized four strategies that women reported using to deal with this situation.

They conformed to “unchallenging” gender stereotypes.

One common strategy involved positioning oneself as a daughter or sister when interacting with men. This was used by early-career women to generate support from colleagues. In Rosy’s* words:

I’ve got blond hair and I make blond jokes and I’ll say, “Yeah, I know I’m asking a stupid question. Tell me what you’re doing. Tell it to me like I’m a five-year-old.” They’re like a bunch of my big brothers or my dad, and playing the girlie card a little bit sometimes can help diffuse some of those situations.

This strategy tended to be employed by the youngest and most junior respondents. Drawing on daughter/sister stereotypes reduced the focus on their sexuality and allowed them to concentrate on the job at hand. However, it was infantilizing, and women could not carry on with this strategy if they wanted to advance. Several respondents complained about being patronized by “fatherly” male colleagues. And many believed they missed out on important assignments because they were viewed as needing frequent assistance, guidance, and care, and not as the most-promising candidates.

They embraced feminine stereotypes.

Some women embraced feminine gender stereotypes in their appearance (dress, hair, makeup, and nails) while demonstrating high levels of engineering competence at the same time. They made themselves visible in both spheres. Becky described her approach:

It’s kind of a running joke now with my nails because I change my nail color pretty much every couple of weeks. I’m on the shop floor and I’m helping with tooling…. I mean, I get all sorts of excited looks and questions like, “How can you function with those nails?” And I tell them to move over and I get some gloves on and do it.

Only a small minority of women used this strategy — all of them in mid-career. Although celebrating what might be seen as a proscribed identity might seem risky, for these highly skilled engineers, it worked. They were recognized for their engineering expertise and, on the basis of this, saw opportunities for advancement. However, they were aware that this strategy worked only because they were highly competent and that any technical error could result in it backfiring.

They downplayed their gender.

The most popular strategy we heard about was women presenting themselves conservatively to downplay their gender and avoid being sexualized. Women who used this approach carefully managed their appearance and interactions: choosing unremarkable corporate dress, moderating their behavior to avoid any possibility of gossip, and being mindful of others’ scrutiny. Clara explained, “I’ll be friendly but not too friendly…. I don’t want to be misinterpreted. I want to be respected.”

This strategy effectively shifted the spotlight from women’s physical presence to their engineering know-how. Interestingly, many women who used it were keen for others to behave likewise. Their view was that “toning it down” — in appearance and behavior — made life easier for everybody.

But not everyone wanted to suppress their femininity in this way, and not everyone could. For example, Yolanda explained that as a “tiny black woman” (in a largely white male space), she just didn’t blend, which meant that she did not fit into conventional images of success or what “promising” candidates looked like. As she saw it, her only option was to celebrate her difference — which she did through flamboyant clothes and by talking openly about her African heritage in such contexts as formal presentations. This worked for her because she knew that her technical knowledge and skills were beyond reproach.

They tried to be “one of the boys.”

Some women went further, attempting to camouflage their femininity by looking and talking like men. As Katya told us:

It’s nice to fit in, right? I’ve worn a button-up shirt and they’re all wearing their blue button-up dress shirt, and then we’re talking about fishing and I’m just like, this makes it a lot easier.

As one of the only senior women in her department, Katya was used to being excessively visible. So it was a relief to occasionally feel like “one of the guys.” This strategy was mostly adopted by women in late career, maybe because during their early years there were fewer role models and thus fewer ways of being female in their organizations.

Some senior women also adopted what they saw described as stereotypically male behaviors: authoritative, individualistic, combative. Although they saw this as necessary to earn their colleagues’ respect, it was a double-edged sword. Women who act this way at work often face backlash, and those we talked to who did were harshly judged and even subjected to name calling (“ice queen,” “Cruella”). Women who used this approach drew attention away from their sexuality and toward their engineering competence, and they advanced career-wise, but they said they often paid a price.

Can organizations step in?

The women we spoke to recognized the need to manage this paradox of gender visibility and professional invisibility, using one of these strategies (or in some cases a combination) to shift the focus. The majority adopted the more conservative approach of downplaying their gender. While this approach helps some women in their individual careers, it also reproduces existing gender stereotypes, and can sustain men’s dominance in the field overall.

What can managers do to change this dynamic? A starting point is to acknowledge and challenge stereotypes. Implicit bias training has a role to play — not as a one-off quick fix, but through regular interventions specifically focused on how to remove stereotypical assumptions from recruitment, training and development, and promotion. Take promotions, for example. Well-worn criteria about who is ready to advance cannot be taken for granted — they should to be reviewed each time to ensure that they are applied in a systematic and transparent way to all candidates.

Everyone should be made aware of what constitutes unacceptable behavior, from excessive and unwelcome comments on a person’s appearance to more-overt sexual harassment — with sanctions applied to those who transgress. Women should know that they have the right to report behaviors that make them feel sexualized, understand how to go about this, and expect to be listened to. Organizations can also try to highlight different modes of success, to show that women do not have to look and act like men or moderate their femininity in order to progress.

*We used pseudonyms to protect respondents’ identities.

3 Ways to Build a Data-Driven Team

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It is no doubt a sign of progress that a significant proportion of organizations and managers today appear to feel guilty when they admit that they are making big management decisions in an intuitive rather than evidence-based way. Indeed, being data-driven has joined the ranks of “innovative”, “diverse”, and “socially responsible” as the one of most laudable features of organizational culture, at least if we go by company websites.

Although feeling the pressure to demonstrate that objective facts — instead of subjective preferences — underlie managers’ key choices is no doubt a major step towards actually becoming a data-driven organization, it’s an ambitious goal for any company, requiring a big cultural transformation, which will need to transcend the wishes of senior leaders to create real changes in how people think, feel, and act at all levels of the organization. And, as with any cultural transformation, managers are a critical agent of change. Here are three key talent management recommendations that should help your team to become more data-driven:

1. Foster critical thinking: While much of the current discussions around data focus on the role of technology and AI, it is really the human side of the equation that will remain the biggest differentiator for teams and organizations. As organization turbocharge their ability to gather more and more data — and it’s not so much about size, but rather about quality — what matters most is having people who can ask the right questions to the data. In fact, as Ajay Agrawal and colleagues argue in their recent book, artificial intelligence (AI) will allow for cheaper prediction, which explains why there’s so much demand for it. But human curiosity and critical thinking are needed to identify the main problems that AI and data can help to solve, and this process starts with you.

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This means questioning your own biases, distrusting your intuition, and displaying a healthy degree of skepticism when presented with ideas and suggestions from others, in particular your team. Equally important, don’t reward others for coming up with intuitive ideas or ideas that feel intuitively right. Instead, celebrate critical thinking, curiosity, and the deeper desire to question things. For example, Amazon encourages disagreements to avoid groupthink and leverage the benefits of cognitive diversity.

Although people will differ in their general predisposition towards critical thinking, you can help them develop whatever potential they have if you put in place the right incentives, give people accurate feedback, and establish an informal and non-hierarchical learning culture where people can share views and ideas. For instance, at AirBnB, employees post problems into an internal knowledge repository that allows other people to provide answers or solutions. This simple attempt to crowdsource knowledge will elevate the problem-solving capabilities of your team by leveraging its collective intelligence.

2. Invest in training: Too often, there is a mismatch between the things managers and organizations say they value — e.g., innovation, soft skills, leadership talent, and data-driven decision making — and the resources they devote to enabling those things. The implications are obvious: if you want your team to embrace, or at least keep up with, the current data revolution, and approach work in a more evidence-based way, you will need to train them. This does not mean turning everyone into a data scientist, but leveraging the vast universe of virtual resources that exist within and outside of organizations. For example, many top universities — including the Ivy Leagues — offer free online courses on AI, data visualization, and data science, and leading corporations in this space, such as Google, offer a wide range of free resources and online courses on AI, analytics, and big data. So, the primary investment is not money, but time. And, of course, you need to incentivize people to make use of this time.

Meta-analytic studies suggest that well-designed training interventions can be expected to boost formal learning outcomes by .60 of a standard deviation — implying that the average individual in the training group will end up outperforming 73% of individuals in a no-training group. That said, individuals’ potential constrains how much they will benefit from a training intervention. Indeed, a comprehensive meta-analysis shows that for most jobs and work-related tasks, deliberate practice accounts for just 1% of the variability in performance, with the remaining 99% depending on individual qualities that were present (and measurable) before the training took place. In other words, most of the training-related gains in expertise or knowledge can be predicted by people’s initial potential, which makes good hiring more consequential than great training (see next point).

3. Hire the right people: When it comes to the training of quantitative, data-driven, or fact-based reasoning skills, there is well-established evidence for the competencies that predict individuals’ likelihood to learn and display these skills. First, this depends on their level of general intelligence or cognitive ability, which is the single best predictor of a person’s ability to solve well-defined reasoning problems and acquire formal knowledge in any area of competence. Think of it as a general measure of mental horsepower or cognitive processing speed. More specifically, individuals with higher quantitative or numerical ability levels (a subset of general intelligence) will find it much easier to pick up any training related to data analytics. Regardless of the expertise or knowledge base they already have, they will learn faster and better.

This may sound obvious, but the practical implication is that if you want your team to be quantitatively skilled, your best bet is to avoid hiring people with lower levels of numerical reasoning ability. And yet, there are also other psychological qualities determining whether individuals will learn to think more empirically and quantitatively: being high on Openness to Experience, curiosity and learnability will enhance people’s willingness to learn and think more rationally, as will their general level of motivation and conscientiousness. Thus, no matter how smart your learning intervention might be, and how well-designed and executed your program is, it will be more effective if the recipients are generally bright, curious, and hard-working — in fact, the profile of your team will be the biggest determinant of the success of your intervention.

The Problem with Using “I Statements” at Work

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It has become common advice for businesspeople to use “I statements” — such as, “I feel frustrated that you missed the budget deadline twice” — as a way to raise challenging conversations without causing colleagues to feel blamed or under attack. Indeed, I statements may be helpful during situations in which you have a close personal relationship to a colleague who cares about your well-being, or when you want to show that a particular issue has moral implications for you.

But in most cases, I statements are more likely to undercut your argument than to strengthen it. Here are three reasons why I statements backfire, and what you can do instead.

They can be seen as expressions of emotionalism, particularly when they’re used by women. One vice president I coached was frustrated by a decision her executive team was planning to make. She sought advice from HR about how to convince two crucial members of the disadvantages of one course of action and the benefits of another. Her HR business partner advised her that framing her argument in I statements, to show how much she cared and how strongly she felt, would help her sound less negative and be more persuasive. But when the vice president met with the two executives, they were clearly unmoved, and they began to discount her perspective publicly in subsequent group meetings.

When she told me about the conversation, I noted how personal her comments sounded, and how she might have damaged her credibility if the execs believed her feelings were hurt because her advice hadn’t been taken, rather than recognizing that she was concerned about potential harm to the business. We brainstormed a solid case complete with specific examples, trends, and likely outcomes. She went to the next meeting armed with data from past similar situations and projections for future results, and was significantly more effective when she let the numbers do the talking for her, rather than appearing to have taken things personally.

They can appear to be about what’s best for you personally. Here’s another example from one of my clients. A sales rep had a special accommodation to use a private office several times a day to tend to a health condition. His sales manager approached him and explained that the room would not be available for a few days because of construction, but that the rep could use a conference room or another manager’s office, or could work from home until the construction was completed. The rep reacted negatively to all three options and made a number of both formal and informal complaints about being displaced.

When I debriefed with the sales manager about the situation, he reported that he had used language like “I really need you to give up the private room for a few days” and “I’m really trying to make this work for you” as a way to create a sense of mutual interest and concern. But the appeal didn’t work: The rep felt that the manager was doing what was easy for him, and that if he was really trying to help, he would have changed the construction schedule. The manager and I discussed how the language could have been more neutral, impersonal, and inevitable to prepare for future, similar circumstances: “Unfortunately, there’s going to be construction in this room for a few days. We have three different possible accommodations available for you during that time. Please let me know which will be best for you.”

They can put you at risk of appearing weak. This is particularly a concern because leaders tend to be less empathetic the higher in the organization they go, and are more likely to be interested in what you can accomplish than sympathetic about the challenges you’re facing. A director I coach described his plan to confront his boss about an interdepartmental problem. His intention was to use an I-statement structure to elicit his boss’s concern and convey how strong a stand he was taking: “I feel I cannot deal with the way things are going with department X anymore.” I suggested that he start the conversation by asking his boss what outcomes she wanted; say something more authoritative, like, “Our current approach with the other department is ineffective”; and then describe the steps he was taking to work with the difficult department. Otherwise, he was likely to come across as if the issue was his inability to handle the problem or his refusal to see the situation from the other department’s point of view. He agreed that his boss would be irritated if she thought he was demonizing the other department and emphasizing his personal frustration as if he needed to be spared the responsibility of finding a solution.

Many decision makers are uncomfortable with emotional content, and can react badly if they feel they’re being embroiled in drama or are being emotionally blackmailed. It’s typically more convincing to use analytical or evidence-based appeals than descriptions of personal impact. After many years of workplace consulting, I’ve found that it’s often more persuasive to leave oneself out of the equation, and to highlight instead what’s beneficial to the work team or the business itself.

The Power of Curiosity

Francesca Gino, a professor at Harvard Business School, shares a compelling business case for curiosity. Her research shows allowing employees to exercise their curiosity can lead to fewer conflicts and better outcomes. However, even managers who value inquisitive thinking often discourage curiosity in the workplace because they fear it’s inefficient and unproductive. Gino offers several ways that leaders can instead model, cultivate, and even recruit for curiosity. Gino is the author of the HBR article “The Business Case for Curiosity.”

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The Scale of the Climate Catastrophe Will Depend on What Businesses Do Over the Next Decade

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This week brought some sobering news on the near future of our planet and species. The Intergovernmental Panel on Climate Change (IPCC) issued an important new report about how dire the consequences of climate change are becoming, and how fast we need to move to avoid the worst.

The report’s beginnings trace back to 2009, when the annual UN global climate conference resulted in an agreement that the world should hold warming to 2.0°C (3.8°F) — a level that seemed politically feasible, but still leads to vast damage, including the death of all coral; even more deadly storms and heat; and rising oceans covering low-lying island nations and major coastal areas. By the time of the Paris climate meeting in 2015, which resulted in the more robust global agreement now supported by every country in the world except the United States, it was clear that we needed to consider a more ambitious target, 1.5°C (2.7°F). The UN then asked the IPCC to study what it would take to achieve that goal.

This week, the report came back, and it’s not pretty. The scientists put out a helpful document with FAQs, but in short, the primary takeaways are these:

While the world has already warmed 1.0°C (1.8°F) since pre-industrial times, holding the world to 1.5°C (2.7°F) is still technically possible.
Keeping the world at 1.5 degrees will still result in devastation (e.g., 70-90% of coral dying), but is far better for us than 2 degrees (both in terms of overall well-being and economic impacts).
Getting to 1.5 degrees will require “rapid and far-reaching transitions in energy, land, urban and infrastructure (including transport and buildings), and industrial systems” and this transition will need to be “unprecedented in terms of scale…and imply deep emissions reductions in all sectors.”

We will need to cut CO2 emissions by 45% from 2010 levels by 2030, the report says, and get to no emissions by 2050.

Keep in mind that this would need to happen as the world most likely adds a couple billion people, with a billion or more entering the middle class. We will need to produce a lot more stuff to feed, house, clothe, and entertain everyone, but with drastically lower emissions.

So, what should companies take away from this latest warning? What should they do?

First, companies must accelerate ongoing efforts to decarbonize their businesses. The list of actions companies take is well-developed and documented, and most large companies do the following:

Slash energy use and emissions in operations. This includes investing in more efficient lighting and HVAC systems; using new software and AI to make buildings and operations more efficient; improving fleet logistics and introducing greener vehicles; and reducing packaging and product weight.
Engage employees, through awards and incentives, to innovate, find operational savings, and develop products that cut customers’ emissions as well.
Embrace renewable energy. More than 150 big brands that have already committed to use 100% renewable energy in their electricity.
Set science-based carbon reduction targets for operations. Nearly 500 companies have signed on to set emission reductions in line with science.
Work with suppliers on systemic reductions across the value chain and set big goals for them as well.
Set internal prices on carbon to incentivize reductions, preferably imposing an internal tax that collects funds or using “shadow” prices to influence investment decision making.

These actions are becoming the norm because they’re just good business. But what this new report is saying, loud and clear, is that it’s not enough. With a few exceptions, most companies are only doing the things that pay off in traditional return-on-investment terms — for example, when solar and wind get cheap enough, they buy it. Really sticking to the latest science, however, requires an accelerating pace of carbon reduction.

So, let me suggest four somewhat uncomfortable actions that companies must take to truly shake things up and accelerate climate action.

Lobby for aggressive pro-climate policies at all levels of government. Today, most companies use their significant lobbying influence (on their own and through trade groups) to fight regulations and defang government. But that has to change in the face of this crisis. The first priority — which the IPCC makes clear — is to put a price on carbon. Companies must lobby for escalating prices on carbon everywhere.

In parallel, the way companies approach all regulation should shift. Consider the example of the U.S. auto industry. As soon as the 2016 election was over, an auto industry group asked the new administration to give them some more wiggle room on aggressive fuel efficiency standards established by the Obama administration. The current administration gave the auto companies way more than they wanted and froze the fuel efficiency levels. It puts companies in a weird position where they want to make improvements, but have no regulatory pressure that moves the whole sector upward.

But imagine if auto companies approached the issue not through a lens of “how do we structure regulations to help us?” but through a lens that recognizes an urgent global climate crisis. They could say to government, “We need much higher fleet efficiency to help the world hold warming to 1.5 degrees. But we’re having some trouble selling the mix of cars that would get us there (people are buying too many big vehicles). What policies can we put in place to make it much more attractive for buyers to get the EVs and smaller cars? Can the government help build the charging infrastructure? Provide aggressive tax breaks for EVs and good incentives for trading in older cars? Can we invest in public-private R&D to bring the cost of batteries down even faster? Could the government commit to buying EVs in all of its fleet? Or, even more radical, how can we work together to greatly increase the availability of all public mobility and transport?”

But even if companies come to the table with an outside-in, climate-change-first approach to their policy goals, a conversation requires two sides. So, to go even further, companies need to also consider who they support for political office. Candidates that don’t advocate for action on climate are not allies, no matter what other issues they support.

Publicly and loudly support truth, science, and scientists. In the era of claims of “fake news,” and attacks on science, companies must help support a key pillar of a working democracy and economy. Most companies let it be known clearly that racism or sexism is unacceptable — why not send a similar message to employees and suppliers about anti-science behavior? They could also support efforts like Let Science Speak and call out government or any institutions that reduce the role of science in policy and decision-making.

Use all available platforms to engage consumers. Within companies, the level of internal conversation about sustainability and climate change is rising. But how many big brands use their advertising, social media, or their packaging to talk directly to consumers about climate change? Besides a few messages around Earth Day, not many. It’s time to break some taboos on what mainstream companies can talk about; they can and should encourage consumers to make better day-to-day choices that reduce their footprint.

Rethink investment decisions and heavily bias them toward carbon reduction. This could mean different things depending on the business, but we have to release ourselves from the arbitrary two-year hurdle rates and capital return ratios that hamstring more aggressive action. Solar and wind power are becoming easy investments, but there are always new efficiency techs that may not be “in the money” yet, like on-site power storage. And what if companies and governments retired some energy-hogging assets before their asset life was up?

In the end, governments and companies have a basic choice: One, move very quickly with large-scale investment in deep transitions across all sectors of the economy, investing trillions to reduce energy costs, improve health, and avoid many other risks. Or two, ignore these warnings and decarbonize the economy at the pace of change that simple-ROI economics allow, not retiring any existing assets early, and transitioning technologies at the pace they would naturally shift under normal market conditions.

Pathway two is what we’re doing now, and it sounds so tranquil and market-based. But it has one heck of kicker: that path will require spending some indeterminate future amount, and soon, on greater levels of adaptation, on resettling people away from coasts, on reduced health, and on managing extreme weather impacts on our communities and supply chains. Pathway two also likely takes us beyond the 2.0°C mark, leading to the non-trivial chance that the world will become uninhabitable by humans.

None of this is easy, but the IPCC report shows we’re truly out of time now. We’re not talking about theoretical models on a computer, but larger versions of the weather horrors we’re already seeing around the world. Business can take the lead here. It has the tools, resources, and the responsibility to help make this rapid transition happen. The improvement in long-run economics and human well-being is more than worth the effort.

What to Do When You’re Covering for Colleagues — and Can’t Keep Up

The summer vacation season may be behind us, but the holidays are right around the corner. And soon enough your colleagues may be asking you to cover for them while they’re away. All of a sudden, you’re juggling not only your normal work but also someone else’s. That’s potentially more email, more tasks, more meetings, and more searching for answers to questions about items outside of your normal day-to-day.

You want to help where you can and act like a team player. But sometimes it feels overwhelming. You can’t keep up on everything the way that you usually do. You don’t want to let your colleague down, and you don’t want to fall behind on your own work.

This sense of overload can compound when you have multiple individuals out of the office or longer absences such as sick leave, sabbaticals, or maternity leave. What do you do when you have to carry the load of two or more people? Do you work crazy hours trying to do everything for everyone? Do you just give up and hope the fallout isn’t too bad when everyone gets back? Or is there an answer in between?

As a time management coach, I believe the best option is the final one — finding an in-between solution where you keep up on the essentials but avoid putting the full weight of multiple jobs on your shoulders. These six strategies can help you strike that delicate balance.

Accept reality. When someone asks you to cover their projects while they’re out, be aware of what you can reasonably do. You can’t do everything — and that’s OK. If you also have some time out of the office at the same time (for example, a business trip), you may not have the capacity to take on extra tasks. The same holds true if you have large important deadlines that correspond with the request to cover for a coworker. In cases like these, you may need to encourage them to find someone else. But if you do take on the extra workload, starting from the place of acceptance puts you in a position to not freak out when your responsibilities rise while colleagues are out. Your coworkers’ work will not get done to the same level as if they were in the office, and some of your work may also need to happen at a slower pace. Again, that’s OK. This natural and normal consequence of vacation time needs acknowledgment. And if your office tends to have consistently heavy vacation times during certain times of the year, factor that variance into planning milestones, before someone asks for your help.

Ask for a plan. Your colleagues need to take the onus to do a clear handoff to you of responsibilities while they’re away. That may mean an email where they detail the status of projects, next steps, deadlines, and any key contacts, or you may have a meeting to communicate this information. Either way, it’s essential that you have clarity on what needs to be done, so you don’t have to figure out what to do while you’re handling the extra work. If appropriate, have them put your email on their out-of-office message so that others will proactively contact you about items you need to accomplish for others.

Focus on deadlines. When you need to do multiple jobs at once, revert to survival mode. That means a radical focus on deadlines and what’s critical to accomplish that day or that week. If possible, have one consolidated list of your deadlines and those you need to meet for others. When you look over the week, think through how you will meet them. Because you have to juggle multiple people’s tasks, that may mean working further ahead than usual because there’s more of a chance of the unexpected happening or having multiple deadlines clustered together. On a daily basis, focus on the deadline items first. Other, less-urgent items likely will need to wait.

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Pause the nonurgent. If you have a massive increase in urgent work, you may need to suspend nonurgent work entirely, such as a project with no deadline, process improvement items, or networking meetings. You can focus on these items when your colleagues return to the office. But in the interim, it’s likely a good idea to delegate them, shelve them, or even suspend any meetings about them until more time opens up in your calendar.

Limit extra work time. You may be tempted to spend some extra time in the office while your coworkers are out, but try not to overdo it. If you must work additional hours, pick a few times when you’ll come in early, stay late, or complete some work on the weekends. But don’t turn this time into working late every night and working all weekend long. Not only will you feel burned out and resentful but you will also lessen your productivity. Working too much and never taking a break decreases motivation and focus.

Ask for help. Sometimes when you’re giving help, you also need to ask for it. See if a boss can cover a few responsibilities, if a coworker can take notes for you at meetings so that you don’t need to attend, if direct reports can take on more of the day-to-day tasks, or if you can get some contract or temp help. The temporary help can be of particular value for long absences, such as a medical leave. When you have colleagues out of the office for a month or more, it’s better to be up front with your boss about what you can or can’t do than to allow your or another’s work to significantly suffer.

Helping colleagues while they’re out of the office will increase the workload. But with the right strategies, you can keep up on the basics of your work while also making sure their most critical tasks get done.

We Deserve Better Than “Attagirl”

From the Women at Work podcast:

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Hearing your manager say you’re doing a great job is, of course, lovely. But without examples of your greatness in action, or suggestions for how to be even better, you don’t have the information you need to keep improving. Studies have found that women tend to get feedback that’s vague or tied to their personalities, which doesn’t boost our performance ratings. Meanwhile, men get feedback that’s specific and tied to business outcomes, which sets them up to develop and be promoted.

First, we talk with Harvard Business School professor Robin Ely about the research on women and feedback. Next, we talk with Tuck School of Business professor Ella Bell Smith about how to draw out actionable, useful feedback from our managers, and how to respond when we’re not getting what we need to succeed.

Guests:

Robin J. Ely is a professor at Harvard Business School and the faculty chair of the HBS Gender Initiative.

Ella L.J. Bell Smith is a professor at the Tuck School of Business at Dartmouth.

Resources:

● “What Most People Get Wrong About Men and Women,” by Catherine H. Tinsley and Robin J. Ely

● “The Gender Gap in Feedback and Self-Perception,” by Margarita Mayo

● “How Gender Bias Corrupts Performance Reviews, and What to Do About It,” by Paola Cecchi-Dimeglio

● “Research: Vague Feedback Is Holding Women Back,” by Shelley Correll and Caroline Simard

Email us here: womenatwork@hbr.org

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

A New Hospitalist Model for Managing High-Cost, High-Need Patients

A partnership between the Boston Medical Center and Commonwealth Care Alliance, a community-based health care organization, provides a promising new hospitalist model for inpatient treatment of complex care patients — patients with extensive, persistently expensive medical needs.

Complex care patients typically have complicated medical histories, functional limitations or disabilities, numerous medications prescribed by multiple outpatient providers, and social drivers of illness. Providing hospital inpatient treatment for them is challenging.

For example, the increasingly prominent hospitalist model depends on hospital-based physicians with expertise in hospital care for admitted patients. But these physicians have little to no prior experience with the patients they treat. Some data has shown that this model can lead to lower average length of stay without increasing costs, though the impact on patient-centered outcomes and total medical costs is unclear. Particularly for more complex, chronically ill patients, it is not known whether a hospital physician with expertise in complex care and understanding of an individual patient’s history could achieve better patient-centered outcomes than a traditional hospitalist.

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Creating better outcomes at reduced cost.

Care delivery organizations that assume financial risk have also invested in models that improve transitions between inpatient and outpatient settings, with the goal of decreasing readmissions and other complications that come with disconnected care. For example, organizations such as CareMore have invested in “extensivists,” primary care physicians who travel to hospitals where CareMore patients are admitted and link the hospital stay with primary care. Extensivists (also known as “comprehensivists”) aim to influence the hospital course of treatment and, following discharge, the transition to outpatient care. CareMore credits this model with a 30-day hospital readmissions rate for Medicare patients that is 40% less than the national average.

Extensivists do not, however, manage the patient in the hospital and thus cede ultimate control of decision making and clinical care to their patients’ hospitalists. Most of these hospitalists do not specialize in the care of patients with complex medical and social needs and disabilities. Nevertheless, as the CareMore results indicate, extensivists do improve patient outcomes through a degree of influence over the hospital setting. Could a hospitalist service dedicated to the care of complex patients have even greater impact?

To find out, Commonwealth Care Alliance and Boston Medical Center created a hospitalist service staffed with physicians and mid-level providers who specialize in complex care. (Commonwealth Care Alliance offers health plans to individuals who are dually eligible for Medicare and Medicaid and serves patients who are significantly more medically and socially complex than the average population.) This complex care hospitalist model — which launched in July 2016 —has four fundamental, replicable components.

Communication. The complex care hospitalist team communicates frequently with patients’ primary care teams, something that conventional hospitalists do not often do. Primary care providers are contacted on admission, are given updates throughout the hospitalization, and are consulted when discharge planning begins. Communication occurs via e-mail, phone, and text and is used to verify medications, history and context of illness, and social factors that may be relevant to an admission. For example, if a new diagnosis is made during the hospitalization, the primary care team is notified and asked to help deliver the news to the patient and the family, improving both patients’ experiences and the transition out of the hospital.

Continuity of care. Patients admitted to the complex care service are co-located on the same hospital unit, with consistent nursing staff and a core rotating group of hospitalists. Since many of the patients are admitted at least annually, the inpatient nurses and providers often have familiarity with the patients, providing continuity of treatment over time. To ensure a safe discharge, a nurse-led, in-person, transitions-of-care team coordinates the discharge plan with the hospital staff, hospitalists, and primary care teams, in addition to the patients and their families or home health providers.

Social determinants of health. For complex patients, expenditures on social needs such as food and housing can have a greater impact on health outcomes and well-being than medical care. The Complex Care service trains physicians, nurses, and care transitions teams in social determinants of health and how to identify patients’ social needs. For example, a patient with diabetes may also have food insecurity, leading to difficulty accessing food that will help his medical condition and resulting in more hospitalizations for diabetes. Providers on the Complex Care service would search for underlying drivers of the patient’s diabetes hospitalizations, then coordinate with a food bank or Meals on Wheels to provide a diabetic diet when the patient returns home.

Specialists in complex care. The Complex Care hospitalist team employs physicians and mid-level providers with expertise in caring for patients with complex medical conditions and disabilities. Whether with formal training through a complex care clinical fellowship or experience working in a specialized primary care practice, the complex care hospitalists are trained in both acute care medicine and caring for the needs of this population. The nurses on the unit received training in nursing care for complex patients — for example, how to care for patients with disabilities and functional limitations.

We’ve only began to assess the effectiveness of the effort, but initial results are promising. We conducted a preliminary chart review and examined the differences in 30-day readmission rates between all of the patients from Commonwealth Care Alliance’s primary care practice, Commonwealth Community Care, admitted to BMC in one month. Ten patients were admitted to the complex care service; five were admitted to hospitalist/general medicine services. Patients discharged from the complex care service had a 20% 30-day readmission rate and 20% went to the emergency department (ED) within 30 days after discharge; those discharged from hospitalist and general medicine services had an 80% 30-day admission rate, and the remaining 20% of those patients returned to the ED within 30 days. While the population of this exploratory evaluation is small, the data support the anecdotal, qualitative experiences of patients and providers on the complex care service. We are now conducting an evaluation of more than 1,000 admissions.

These initial results also suggest that some complex patients may be better served by providers more intimately connected to the outpatient setting who specialize in caring for patients with complex medical and social needs and disabilities. Other patients may be appropriately served through an adjunct consultant, or extensivist, model. Still others, who may not need the level of expertise or intensity of either a complex care hospitalist or an extensivist can be adequately served by the traditional hospitalist model.

The challenges for value-based organizations will be how much control to exert over the inpatient hospital setting and how to triage patients to the model of inpatient care best suited to their particular needs. But in an era where hospital costs and outcomes, particularly for high-cost, high-need patients, are more relevant than ever, the complex care hospitalist model offers an achievable and replicable option for value-based hospital medicine.

The author would like to thank Sagar Raju for his research assistance.