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Harvard Business Review
More than half of Americans feel “overworked or overwhelmed at least some of the time” and 70% say “they often dream of having a different job,” according to a recent study by the Families and Work Institute. That’s a lot of unhappy people at work, and many of them may choose to resign. But my research shows that quitting can be premature; what you might need to do instead is pause and recalibrate.
Chances are that if you were to jump into a new role or organization, whatever is causing you to leave may follow you. Taking a pause — which I define as any intentional shift in behavior — allows you to lift your head up, assess your situation objectively, and change your attitude, thoughts, or emotions. It doesn’t have to be a major break in your routine; it might be that after you get home from for work, you intend to spend 20 minutes of quality time with a partner or loved one. Or you intend to show up fully present every morning at the office by taking six deep breaths before you walk in. Even small pauses can help.
Here are some signs that you may need to work more pauses into your life:
- You used to love your job and now you loathe it. Perhaps you used to thrive on the pressure of your role but it no longer seems worth it. Or maybe you’re in a slump. Burnout is a signal to take note of what isn’t working and make a change.
- Someone informs you things aren’t working out. It may be a hint in the hallway or a direct hit — you missed your quota or the new strategy you developed backfired.
- A concerned family member or colleague intervenes to separate you from work or technology. It’s easy to get hooked on what you do, but when it starts to affect your well-being and relationships, those who care about you notice.
- A major life event or challenge occurs. Change is inevitable, and can be a natural inflection point to assess your options and align with what matters to you.
- A new opportunity arises. An irresistible job offer or an invite for a passion project or trip comes along. You may need to take a pause to find out how serious you are about setting course on a new path, especially if it is high risk.
Once you’ve determined that you need to pause, the next question is how to do it. A common misconception is that you take a break so that you can think something through.In some cases it is helpful to reflect while pausing and ask yourself questions you haven’t had time to ask yourself in your busy life. What could you do differently? How can you shift or plan to make your existing role more aligned with how you want to work and live? Are there new boundaries to create, or responsibilities to own or shift? But the purpose is actually to step away from your everyday activities and not focus on what’s dominating your thoughts. Instead, it can be best to just relish the present moment, not reflect on any specific issues, and let answers emerge.
There are three steps for planning a pause. First, write down some quick thoughts on your situation – what’s happening, what isn’t working, what the challenges are, and any actions you want to take.
Next, set an intention. What do you want to get out of this pause and how do you want to feel at the end of it? One study published in Psychological Science showed that by distancing yourself from a challenge and taking the perspective of an observer, you can enhance your reasoning, leading to insights and new solutions that hadn’t occurred to you before.
The third step is to plan how much time you’ll pause for and what you’ll do. You may not know how you want to spend your time so it’s also OK to let your pause to unfold more organically. Daily “mini” pauses, sometimes done several times throughout the day, are a great way to start if things aren’t dire at work. You can also pause by getting up from your desk every 90 minutes, heading outside at lunch, taking a walk, or setting a period of time when you don’t check your digital devices. If you are really short on time, you might spend five minutes at your desk doing a simple breathing exercise: follow your breath, counting each slow inhale and exhale until you get to ten breaths.You and Your Team Series Stress
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A pause can also be a day-long activity. Visit a place that brings peace of mind and joy to your day. Wherever you go, notice colors, textures, and take in your surroundings. You might consider starting a “pausebook” or journal to document what you experience.
Other pauses might include doing something outside of your comfort zone like taking a class, coaching your child’s sports team, or going a surprise weekend getaway or day trip with a loved one.
If you have more time, consider taking a week-long pause. Most of us understand the benefits of taking a vacation and yet many of us don’t use the time, afraid of work piling up while we’re gone. According to a 2015 survey by the Creative Staffing Group, 72% of executives wouldn’t take additional vacation days even if they were unlimited, however about four in 10 (39%) think output would actually increase if employees took more time off. The benefits of returning refreshed after pausing are worth the time away and often lead to greater creativity and less stress. Increased distraction and dopamine levels can actually help lead to new insights, according to neuroscience research.
If you’re considering leaving your job, I invite you to pause first and explore how things could be different without moving on. If you are feeling burned out or overwhelmed, taking an extended pause over a few weeks is another option that might help you gain perspective outside your day-to-day routine. You may be pleasantly surprised and realize all you needed was an intentional shift to realign and experience things differently.
No parents should have to watch their child die, yet my former colleague “Will” and his wife “Mary” watched powerless as two of their children succumbed to spinal muscular atrophy (SMA). “Isaac” and “Lizzy” were never able to sit, talk, or eat on their own, and each passed away as toddlers.
SMA is the most common genetic cause of infant mortality, affecting 1 in 11,000 newborns yearly. Infants with SMA1, the most common and severe form, develop progressive paralysis before six months. Most die before their second birthday. The genetic cause of SMA, a mutation in the spinal motor neuron 1 gene (SMN1) was discovered 20 years ago, but despite intensive research, no effective therapy was found — until now. In December, the U.S. Food and Drug Administration (FDA) announced its approval of nusinersen (sold as “Spinraza”), an effective SMA treatment licensed to Biogen by Ionis Pharmaceuticals.
Nusinersen is an antisense oligonucleotide, a brief DNA sequence that increases SMN protein production. In a landmark trial of 82 infants with SMA, 40% of those receiving the drug achieved motor milestones, including sitting crawling and even walking, compared to none receiving the placebo. The FDA stopped the study early because nusinersen was so effective.
Patients and providers greeted approval with near ecstasy, but the celebration was bittersweet. Five days after the FDA approved, the drug, Biogen announced each dose would cost $125,000. Given that patients need six doses in the first year and three per year after that, it means the drug costs $750,000 per patient in the first year and $375,000 annually thereafter.
There are at least 10,000 SMA patients in the United States. A little over half have SMA1 or SMA2 (the more severe forms). If just this segment were treated with nusinersen, the total cost in the first year would be $3.8 billion and the annual cost thereafter would be $1.9 billion. (These figure do not account for administration costs.) The actual total cost will be larger because, since the treatment is effective and SMA patients will hopefully live longer, the number of SMA patients that will require ongoing treatment will increase over time.
While criticism of drug prices should focus on a patient’s ability to afford treatment and on profiteering by unscrupulous pharmaceutical companies, Biogen’s pricing decision signals a larger threat to the U.S. health care system: the cumulative cost of therapies for rare diseases may be impossible to bear.
Many experts have expressed concern over Biogen’s pricing decision. In a report published in December, Geoffrey Porges, an analyst at Leerink, predicted the “Spinraza pricing decision is likely to invite a storm of criticism, up to and including Presidential tweets.” And renowned cardiologist Eric Topol tweeted: “Recurrent biotech theme — #RareDisease A great discovery, spoiled.”
Then there’s Will’s heartbreaking reaction, which I’m sure echoes the sentiments of many touched by SMA. “The Biogen announcement of the cost of nusinersen floored me in every way possible,” he says. “Words cannot describe the sickening feeling I get when I think about it.”
A very promising gene therapy for SMA is on the horizon, which would require only one dose and potentially render nusinersen obsolete. Did such mercenary economics influence Biogen’s pricing decision? We may never know; drug companies are not required to justify their prices.
There are 7,000 rare diseases affecting 25 million to 30 million Americans. The average drug approved under the Orphan Drug Act of 1983 (ODA), which governs rare disease approval, costs $118,820 per year. Assuming a similar cost, if a single drug were approved under the ODA for 10% of rare diseases, the total would exceed $350 billion annually — more than 10% of the total amount that America spends on health care and much more than the health care costs attributable to either diabetes or Alzheimer’s disease and other forms of dementia.
If this seems far-fetched, consider the two drugs for treating Duchenne muscular dystrophy that the FDA approved in the last six months: eteplirsen, which is sold by Sarepta Therapeutics and costs $300,000 annually per patient, and deflazacort, which is sold by Marathon Pharmaceuticals and costs $89,000 annually per patient. However, approval of such costly drugs exposes an uncomfortable truth: scientific discovery has outpaced health care economics.
At the University of Utah, we follow about 150 SMA patients. If each were treated with nusinersen, the cost would be $113 million the first year and $56 million thereafter (not accounting for newly diagnosed patients). Nusinersen’s extreme price is a challenge for any health care system, particularly those like ours with an accountable care organization responsible for large numbers of patients (200,000 children in our case).
Approaches to contend with costly new therapies range from creating expert panels to approve each patient treated to assigning physicians an annual patient quota. None of these strategies is ideal, and each risks creating an adversarial dynamic between physicians, administrators, and patients.
Unless the United States acts now, we will no longer be able afford FDA-approved treatments for rare disease. Hard decisions are already being made. Some insurance companies are limiting access to nusinersen and eteplirsen. Potential repeal of the Affordable Care Act, which prohibits lifetime insurance spending caps, promises to further limit access to care for patients with chronic rare diseases.
Coverage decisions should be based on an understanding of a drug’s value (outcomes relative to the cost). In nusinersen’s case, the impact on the quality of life of SMA infants is indisputable.
In the United Kingdom, the National Institute for Health and Care Excellence (NICE) determines the cost effectiveness, or value, of newly approved drugs based on their impact on quality-adjusted life years. These determinations inform the National Health System’s (NHS) treatment-coverage decisions. In contrast, the FDA is prohibited from considering cost or value in its decision making, and there is no U.S. governmental equivalent of NICE.
The Institute for Clinical and Economic Review (ICER), a small Boston-based nonprofit, has taken a step towards value-based pricing by creating a NICE-like model. Development of a NICE or ICER-like post-approval value review, incorporating appropriate oversight and accountability, would help ensure coverage decisions remain fair and cost-effective, but it won’t be enough. The NHS is likely to impose care rationing because of escalating health and pharmaceutical costs. Any successful plan to manage rising drug costs must address multiple aspects of the problem, including value-based pricing, transparency, drug re-importation, and the reform of the Orphan Drug Act, to name a few.
The FDA and other federal payers, including Medicare, must be empowered to consider drug costs and outcomes, and this process should factor in federal investment in drug discovery. (Ionis and Cold Spring Harbor received federal grant funding to support the early development of nusinersen.)
Federal government payers should also be allowed to negotiate price discounts and re-import drugs (with provisions for adequate quality control). In a disappointing move, President Trump, who had promised to let Medicare negotiate bulk pricing discounts for prescription drugs, abandoned this pledge after meeting with pharmaceutical industry lobbyists and executives.
Pharmaceutical companies must be required to disclose and justify development costs, particularly those seeking the substantial benefits under the ODA. There are numerous examples of pharmaceutical companies taking advantage of ODA provisions to repurpose inexpensive medications for rare diseases, often at extraordinary, unjustified costs. Marathon proposed a price of $89,000 for deflazacort, which is already available in Europe and Canada for $1,000 to $2,000, a 6,000% price increase. (After several members of Congress complained, the launch of the drug was delayed.) Senator Chuck Grassley, chairman of the Senate Judiciary Committee, is rightly leading an inquiry into this practice and other ODA abuses.
A health care system’s goal should be to provide the best patient-centered care. Coverage decisions and resource allocations must prioritize value to patients — not insurers’ or pharma companies’ profits. If we are committed as a society to curing diseases such as SMA, dangling treatments like nusinersen just out of patients’ reach is cruel. Collectively, government, pharma, insurers, hospital systems and physicians all have a role to play in providing access to the right care at justifiable cost.
Amy Gallo, HBR contributing editor, discusses a useful tactic to more effectively deal with conflict in the workplace: understanding whether you generally seek or avoid conflict. Each personality style influences how you approach a particular conflict, as well as how your counterpart does. Gallo talks about how to escape the common pitfalls of conflict seekers and conflict avoiders, so that you can improve your work and your relationships. She’s the author of the HBR Guide to Dealing with Conflict.
Several years ago, colleagues and I were invited to predict the results of a start-up pitch contest in Vienna, where 2,500 tech entrepreneurs were competing to win thousands of euros in funds. We observed the presentations, but rather than paying attention to the ideas the entrepreneurs were pitching, we were watching the body language and microexpressions of the judges as they listened.
We gave our prediction of who would win before the winners were announced and, as we and the audience soon learned, we were spot on. We had spoiled the surprise.
Two years later we were invited back to the same event, but this time, instead of watching the judges, we observed the contestants. Our task was not to guess the winners, but to determine how presenters’ non-verbal communication contributed to their success or failure.
We evaluated each would-be entrepreneur on a scale from 0-15. People scored points for each sign of positive, confident body language, such as smiling, maintaining eye contact, and persuasive gesturing. They lost points for each negative signal, such as fidgeting, stiff hand movements, and averted eyes. We found that contestants whose pitches were rated in the top eight by competition judges scored an average of 8.3 on our 15-point scale, while those who did not place in that top tier had an average score of 5.5. Positive body language was strongly correlated with more successful outcomes.
We’ve found similar correlations in the political realm. During the 2012 U.S. Presidential election, we conducted an online study in which 1,000 participants—both Democrats and Republicans—watched two-minute video clips featuring Barack Obama and Mitt Romney at campaign events delivering both neutral and emotional content. Webcams recorded the viewers’ facial expressions, and our team analyzed them for six key emotions identified in psychology research: happy, surprised, afraid, disgusted, angry, and sad. We coded for the tenor of the emotion (positive or negative) and how strongly it seem to be expressed. This analysis showed that Obama sparked stronger emotional responses and fewer negative ones. Even a significant number of Republicans—16%— reacted negatively to Romney. And when we analyzed the candidates’ body language, we found that the President’s resembled those of our pitch contest winners. He displayed primarily open, positive, confident positions congruent with his speech. Romney, by contrast, often gave out negative signals, diminishing his message with contradictory and distracting facial expressions and movement.
Of course, the election didn’t hinge on body language. Nor did the results of the start-up competition. But the right kinds of non-verbal communication did correlate with success.
How can you send out the same signals—and hopefully generate the same success? At the Center for Body Language, we’ve studied successful leaders across a range of fields and identified several positions which are indicators of effective, persuasive body language.
Early in Bill Clinton’s political career he would punctuate his speeches with big, wide gestures that made him appear untrustworthy. To help him keep his body language under control, his advisors taught him to imagine a box in front of his chest and belly and contain his hand movements within it. Since then, “the Clinton box” has become a popular term in the field.
Holding the ball
Gesturing as if you were holding a basketball between your hands is an indicator of confidence and control, as if you almost literally have the facts at your fingertips hands. Steve Jobs frequently used this position in his speeches.
When people are nervous, their hands often flit about and fidget. When they’re confident, they are still. One way to accomplish that is to clasp both hands together in a relaxed pyramid. Many business executives employ this gesture, though beware of overuse or pairing it with domineering or arrogant facial expressions. The idea is to show you’re relaxed, not smug.
How people stand is a strong indicator of their mindset. When you stand in this strong and steady position, with your feet about a shoulder width apart, it signals that you feel in control.
This gesture indicates openness and honesty. Oprah makes strong use of this during her speeches. She is a powerful, influential figure, but also appears willing to connect sincerely with the people she is speaking to, be it one person or a crowd of thousands.
The opposite movement can be viewed positively too—as a sign of strength, authority and assertiveness. Barack Obama has often used it to calm a crowd right after moments of rousing oration.
The next time you give a presentation, try to have it recorded, then review the video with the sound off, watching only your body language. How did you stand and gesture? Did you use any of these positions? If not, think about how you might do so the next time you’re in front of an audience, or even just speaking to your boss or a big client. Practice in front of a mirror, then with friends, until they feel natural.
Non-verbal communication won’t necessarily make or break you as a leader, but it might help you achieve more successful outcomes.
I help the University of Utah hospital system manage its drug budgets and medication use policies, and in 2015 I got sticker shock. Our annual inpatient pharmacy cost for a single drug skyrocketed from $300,000 to $1.9 million. That’s because the drug maker Valeant suddenly increased the price of isoproterenol from $440 to roughly $2,700 a dose.
Isoproterenol is a heart drug. It helps with heart attacks and shock and works to keep up a patient’s blood pressure. With the sudden price increase, we were forced to remove isoproterenol from our 100 emergency crash carts. Instead, we stocked our pharmacy backup boxes, located on each floor of our hospitals, to have the vital drug on hand if needed. We had to minimize costs without impacting patient care.
This type of arbitrary and unpredictable inflation is not sustainable. And it’s not the way things are supposed to work in the United States. Isoproterenol is a drug that is no longer protected by a patent. Theoretically, any drug company should be able to make a generic version and sell it at a competitive cost. We should have had other options to buy a competitors’ copy for $440 or less. But that’s not happening like it should. The promise of generic medications is getting further from reality each day. As the U.S. Senate considers President Donald Trump’s choice to head the Food and Drug Administration, now is the time refocus efforts on generic drugs.How generics are supposed to work
The 1984 Drug Price Competition and Patent Term Restoration Act gave pharmaceutical companies exclusive protections for innovating a new drug. If they brought a new therapy to life, they enjoyed patent protection to effectively monopolize the market. That was the payoff for shouldering the high risk and high costs of developing new drugs.
But once the patent and the exclusive hold on the market expires, the legislation encouraged competition to benefit consumers. Any drug company would be able to manufacture non-brand name versions of the very same drug, so-called “generics.” And for a while, the system worked well.
Not anymore. The system intended to reward drug companies for their innovations, but eventually protect consumers, is systematically being broken. Drug companies are thwarting competition through a number of tactics, and the result is high prices, little to no competition, and drug quality problems.The ways companies stop generics
One of the ways branded drug manufacturers prevent competition is simple: cash. In so-called “pay for delay” agreements, a brand drug company simply pays a generic company not to launch a version of a drug. The Federal Trade Commission estimates these pacts cost U.S. consumers and taxpayers $3.5 billion in higher drug costs each year.
“Citizen petitions” offer drug companies another way to delay generics from being approved. These ask the Food and Drug Administration to delay action on a pending generic drug application. By law, the FDA is required to prioritize these petitions. However, the citizens filing concerns are not individuals, they’re corporations. The FDA recently said branded drug manufacturers submitted 92% of all citizen petitions. Many of these petitions are filed near the date of patent expiration, effectively limiting potential competition for another 150 days.
“Authorized generics” are another tactic to limit competition. These aren’t really generic products at all; they are the same product sold under a generic name by the company that sells the branded drug. Why? By law, the first generic company to market a drug gets an exclusivity period of 180 days. During this time, no other companies can market a generic product. But the company with the expiring patent is not barred from launching an “authorized generic.” By selling a drug they’re already making under a different name, pharmaceutical firms are effectively extending their monopoly for another six months.
Another way pharmaceutical firms are thwarting generics is by restricting access to samples for testing. Generic drug makers need to be able to purchase a sample of a brand-name product to conduct bioequivalence testing. That’s because they have to prove they can make a bioequivalent product following the current good manufacturing practices (CGMP) standard. These manufacturers don’t need to conduct clinical trials like the original drug company did.
But the original drug developer often declines to sell drug samples to generics manufacturers by citing “FDA requirements,” by which they mean the agency’s Risk Evaluation and Mitigation Strategies program. The idea behind this program is a good one: give access to patients who will benefit from these personalized medicines, and bar access for patients who won’t benefit and could be seriously harmed. However, brand drug makers are citing these requirements for the sole purpose of keeping generics from coming to market.Problems with generic drug makers
Although makers of a branded drug are using a variety of tactics to create barriers to healthy competition, generic drug companies are often not helping their own case. In 2015, there were 267 recalls of generic drug products—more than one every other day. These recalls are for quality issues such as products not dissolving properly, becoming contaminated, or even being outright counterfeits.
A few high-profile recalls have shaken the belief that generic drugs are truly the same. In 2014, the FDA withdrew approval of Budeprion XL 300 — Teva’s generic version of GlaxoSmithKline’s Wellbutrin XL. Testing showed the drug did not properly release its key ingredient, substantiating consumers’ claims that the generic was not equivalent. In addition, concerns about contaminated generic Lipitor caused the FDA to launch a $20 million initiative to test generic products to ensure they are truly therapeutically equivalent.
In some cases, patent law also collides with the FDA’s manufacturing rules. For example, the Novartis patent for Diovan expired in 2012. Ranbaxy received exclusivity for 180 days for the first generic product. However, due to poor quality manufacturing, Ranbaxy couldn’t obtain final FDA approval for its generic version. The FDA banned shipments of Ranbaxy products to the United States. Ranbaxy ended up paying a $500 million fine, the largest penalty paid by a generic firm for violations.
Due to these protracted problems with the company that had won exclusivity, a generic product did not become available until 2014. The two-year delay cost Medicare and Medicaid at least $900 million. Ranbaxy’s poor-quality manufacturing also delayed other key generic products like Valcyte and Nexium. Ironically, it was Mylan—involved in its own drug pricing scandal over its EpiPen allergy-reaction injector—that filed the first lawsuit to have the FDA strip Ranbaxy of its exclusivity. Mylan made multiple attempts to produce generic products but was overruled in the courts.Ways to Fix the System
Pharmaceutical firms are currently using a set of tactics to make their temporary monopolies semi-permanent. Eliminating these tactics will not be easy. Still, doing so will fulfill the deal that policy makers offered to drug makers and consumers: a temporary monopoly on sales to help pay for drug development.
First, restrictive distribution programs need to be stopped. Generic companies must also be allowed to purchase samples of these medications to conduct bioequivalence studies. (One measure to close these loopholes already has bipartisan support.) Next, pay-for-delay agreements should be eliminated as well as a corporation’s ability to issue citizen petitions with the intent of delaying generic competition.
Encouraging and enforcing high-quality standards for medications must also be an industry imperative. To create transparency around drug quality, the FDA has proposed a system of letter grades for manufacturers. In an economic study, one official notes that lack of transparency “may have produced a market situation in which quality problems have become sufficiently common and severe to result in drug shortages.”
Another way to achieve greater transparency in medication quality is to change the product labeling laws. Labels should disclose the medication’s manufacturer. Currently, hospitals and pharmacies don’t always know which company actually made the product. This makes it difficult to base purchase decisions on quality.
Generic medications can provide great benefits for patients and health systems when there is adequate competition and quality. But their promise is unfulfilled, and it’s costing consumers. By eliminating restrictive distribution schemes, pay-for-delay, and citizen petitions as well as providing more transparency around quality, hospitals, clinicians, lawmakers, and the new leaders at the FDA have a clear opportunity. They can start to reverse rising health care costs and ensure quality medications are accessible to the American people.
As artificial intelligence algorithms infiltrate the enterprise, organizational learning matters as much as machine learning. How should smart management teams maximize the economic value of smarter systems?
Business process redesign and better training are important, but better use cases – those real-world tasks and interactions that determine everyday business outcomes – offer the biggest payoffs. Privileging smarter algorithms over thoughtful use cases is the most pernicious mistake I see in current enterprise AI initiatives. Something’s wrong when optimizing process technologies take precedence over how work actually gets done.
Unless we’re actually automating a process – that is, taking humans out of the loop – AI algorithms should make people’s jobs simpler, easier, and more productive. Identifying use cases where AI adds as much value to people’s performance as to process efficiencies is essential to successful enterprise adoption. By contrast, companies committed to giving smart machines greater autonomy and control focus on governance and decision rights.
Strategically speaking, a brilliant data-driven algorithm typically matters less than thoughtful UX design. Thoughtful UX designs can better train machine learning systems to become even smarter. The most effective data scientists I know learn from use-case and UX-driven insights. At one industrial controls company, for example, the data scientists discovered that users of one of their smart systems informally used a dataset to help prioritize customer responses. That unexpected use case led to a retraining of the original algorithm.
Focusing on clearer, cleaner use cases means better and more productive relationships between AI and its humans. The division of labor becomes a source of design inspiration and exploration. The quest for better outcomes shifts from training smarter algorithms to figuring out how the use case should evolve. That drives machine learning and organizational learning alike.
Five dominant use case categories emerge when organizations pick AI-empowered people and processes over autonomous systems. Unsurprisingly, these categories describe how intelligent entities work together to get the job done – and highlight that a personal touch still matters. Depending on the person, process, and desired outcome, AI can make the human element matter more.
Alexa, Siri and Cortana already embody real-world use cases for AI-assistantship. In Amazon’s felicitous phrasing, assistants have skills enabling them to perform moderately complex tasks. Whether mediated by voice or chatbot, simple and straightforward interfaces make assistants fast and easy to use. Their effectiveness is predicated as much on people knowing exactly what they need as algorithmic sophistication. As digital assistants become smarter and more knowledgeable, their task range and repertoire expands. The most effective assistants learn to prompt their users with timely questions and key words to improve both interactions and outcomes.
Where assistants perform requested tasks, guides help users navigate task complexity to achieve desired outcomes. Using Waze to drive through cross-town traffic troubled by construction is one example; using an augmented-reality tool to diagnose and repair a mobile device or HVAC system would be another. Guides digitally show and tell their humans what their next steps should be and, should missteps occurs, suggest alternate paths to success. Guides are smart software sherpa whose domain expertise is dedicated to getting their users to desired destinations.
In contrast to guides, consultants go well beyond navigation and destination expertise. AI consultants span use cases where workers need either just-in-time expertise or bespoke advice to solve problems. Consultants, like their human counterparts, offer options and explanations, as well as reasons and rationales. A software development project manager needs to evaluate scheduling trade-offs; AI consultants ask questions and elicit information allowing specific next step recommendations. AI consultants can include relevant links, project histories and reports for context. More sophisticated consultants offer strategic advice to complement their tactical recommendations.
Consultants customize their functional knowledge– scheduling; budgeting; resource allocation; procurement; purchasing; graphic design; etc. – to their human client’s use case needs. They are robo-advisers dispassionately dispensing their domain expertise.
A colleague is like a consultant but with a data-driven and analytic grasp of the local situation. That is, a colleague’s domain expertise is the organization itself. Colleagues have access to the relevant workplace analytics, enterprise budgets, schedules, plans, priorities and presentations to offer organizational advice to colleagues. Colleague use cases revolve around advice managers and workers need to work more efficiently and effectively in the enterprise. An AI colleague might recommend referencing and/or attaching a presentation in an email; which project leaders to ask for advice; what budget template is appropriate for a requisition; what client contacts need an early warning, etc. Colleagues are more collaborator than tool; they offer data-driven organizational insight and awareness. Like their human counterparts, they serve as sounding boards that – who? – help clarify communications, aspirations and risk.
Where colleagues and consultants advise, bosses direct. Boss AI tells its humans what to do next. Boss use cases eliminate options, choices and ambiguity in favor of dictates, decrees and directives to be obeyed. Start doing this; stop doing that; change this schedule; shrink that budget; send this memo to your team.
Boss AI is designed for obedience and compliance; the human in the loop must yield to the algorithm in the system. Boss AI represents the slippery slope to autonomy – the workplace counterpart to an autopilot taking over an airplane cockpit or an automotive collision avoidance system slamming on the brakes. Specific use cases and circumstances trigger human subordination to software. But bossware’s true test is human: if humans aren’t sanctioned – or fired – for disobedience, then the software really isn’t a boss.
As the last example illustrates, these distinct categories can swiftly blur into each other. It’s easy to conceive of scenarios and use cases where guides can become assistants, assistants situationally escalate into colleagues, and consultants transform into bosses. But the fundamental differences and distinctions these five categories present should inject real rigor and discipline into imagining their futures.
Trust is implicit in all five categories. Do workers trust their assistants to do what they’ve been told or guides to get them where they want to go? Do managers trust the competence of bossware or that their colleagues won’t betray them? Trust and transparency issues persist regardless of how smart AI software becomes, and they become even more important as the reasons for decisions become overwhelmingly complex and sophisticated. One risk: these artificial intelligences evolve – or devolve – into “frenemies.” That is, software that is simultaneously friend and rival to its human complement. Consequently, use cases become essential to identifying what kinds of interfaces and interactions facilitate human/machine trust.
Use cases may prove vital to empowering smart human/smart machine productivity. But reality suggests their ultimate value may come from how thoughtfully they accelerate the organization’s advance to greater automation and autonomy. The true organizational impact and influence these categories may be that they prove to be the best way for humans to train their successors.
Imagine you’re a middle class American, with an average education and average skills. You’re employed. What are the chances that next year you’ll vault into the top third of earners?
It depends quite a bit on the company you work for.
For middle-skilled, middle class workers at low-paying firms, the chance of moving into the top third of the income distribution was just 0.6%, according to a recent paper analyzing U.S. Census data from 1990 to 2013. For middle-skilled, middle class workers at middle-paying firms, the chances of moving up the following year were 2.6%. But for middle-skilled middle class workers at high-paying firms, the chance was substantially better: nearly 12%. (The paper divides earners, skillsets, and firms up into thirds. So “high-paying” means the top third of firms, “middle-paying” means the middle third, and “low-paying” the bottom third. The same is true for skills. I use “middle class” to refer to the middle third of earners.)Related Video The Other Kind of Inequality, Explained Pay gaps are rising between companies more than within them. See More Videos > See More Videos >
Where you work matters, not just for how much you make, but for your economic mobility — how much you rise or fall in income over the course of your lifetime. If that sounds obvious, consider how often conversations about economic mobility leave companies out entirely, instead focusing on education, skills, or geography.
The new paper — by John Abowd of the U.S. Census Bureau, Kevin McKinney of the California Census Research Data Center, and Nellie Zhao of Cornell — adds to a growing literature connecting how well different firms pay to rising income inequality across wealthier economies. In a recent Harvard Business Review article, Stanford’s Nicholas Bloom argued that this between-firm inequality explains most of the increase in inequality between Americans since 1980, and is caused by an increasingly winner-take-all economy.
Abowd and his co-authors used standard statistical techniques to estimate how much of a worker’s earnings are attributable to employee-specific characteristics (e.g., skills, experience, etc.) and how much are attributable to the firm where they work. They also control for numerous relevant factors, from gender and ethnicity, to part-time vs. full-time, to the strength of the labor market in each year. The part attributable to the worker should be a measure of skill, and the part attributable to firms should measure how well different firms pay, independent of who they hire.
“We show that a typical worker of any skill type would benefit from working at a middle-paying firm relative to a low-paying firm,” the authors write in the paper. “But it is the workers of any skill type employed at high-paying firms who benefit the most.” Hence middle class workers of average skill are a bit more likely to move up in the earnings distribution if they work at a mid-paying firm, relative to a low-paying one. But the big difference is between working at a high-paying firm vs. everything else.
Moreover, the researchers found that once workers find those high-paying firms, they stay there. “Once you’re fortunate enough to find a job at a top paying firm, you get the benefits of that, independent of your position in the skills distribution,” said Abowd, “and you’re much more likely to stay put. If you’re fortunate enough to find one of these jobs, you’re probably not going to quit it.”
For Abowd, the mystery is what enables firms to sustain high wages. “They’re the most successful firms in their industries in many cases,” he said. And through some combination of timing, luck, intellectual property, valuable assets, and the right combination of employees, they have created a moat that competitors struggle to cross. In economics, that’s called a mystery; in the field of strategy, it’s called success.
The worrying thing is the growing gap between firms that have figured out a strategy that supports decent wages, and those that haven’t. A few firms seem to be doing well, and paying well, while the rest fall further behind. Some argue that this productivity gap is the result of too little competition; however, a nascent-but-growing body of research attributes it to technology.
In March, Andy Haldane, the Bank of England’s chief economist, offered another explanation for the growing gap between the most productive UK firms and the rest. “For the same reason most car-owners believe they are above-average drivers, most companies might well believe they have above-average levels of productivity,” he said in a speech at the London School of Economics. In other words, many executives do not realize how poorly they’re managing their firms.
And management does matter, not just to the success of companies but for the growth of entire economies. It may have at least some role in determining economic mobility for employees, too. Individuals’ chances of climbing the economic ladder over the course of their lifetimes depends in part on where they work. And whether that firm has the strategy, the business model, and the values that enable it to pay high wages depends in part on how well it is managed.
In the traditional media industry, some outlets differentiate themselves through quality, but social media hasn’t gotten there yet — there is no “New York Times of social media.” The modern landscape for newspapers and books resulted from centuries of evolution, but “new media” hasn’t yet developed such strong brands and categories.
However, although there aren’t any dominant players, there are social network companies seeking to stake out “high-quality” territory. The most common approaches are to specialize in either high-quality information, or to specialize in deep, emotional relationships. Of course, people do use existing comms and social software to manage quality information and close relationships — the beloved chat app Slack is widely used by couples and families, for example. But Slack is generally aimed at the enterprise market and doesn’t specialize in intimate relationships. Similarly, Facebook doesn’t specialize in purveying journalism, even though almost every news company posts articles on Facebook.
Although many companies have come and gone in this space, the problems they’re trying to solve have recently become urgent. They’re urgent both for the public, which is increasingly aware of social media’s pitfalls — from privacy issues, to trolling, to viral political propaganda — and for social platforms themselves. Indeed, Mark Zuckerberg himself just posted a long letter on his Facebook profile vowing to support community leaders who use Facebook as a platform, strengthen the news industry, and so on (though this letter also had its critics).
Could specialized social media handle these functions better than the dominant players? What might a high-quality social media platform look like? How about a “warmer” or “more vulnerable” platform? How about a “luxury” or “intellectual” platform? How about “trade publication social media” — or a platform that serves non-professional yet well-defined niches? And of course: What’s the business model for any of the above?
It’s proven hard to solve these problems partly because of metrics: It’s hard to identify and measure the factors that lead to high-quality information or connection. In fact, it’s difficult to identify and measure quality in media of any kind.
Technologists often discuss the problem of “vanity metrics.” Vanity metrics are methods of measuring ROI that make product-builders feel good (or make them look good to funders), but don’t ultimately lead to awesome products. In journalism, for example, the pageview is a much-maligned metric. Many publishers count an article’s success by the number of times a page is loaded (partly because many ads are sold based on pageviews) — yet many people argue that pageviews are a vanity metric. Indeed, journalists discontented with the pageview model write articles with titles like “Pageview journalism is killing us,” and refer to the Pageview Industrial Complex.
This conversation recently flared up around Medium, a publishing platform with many social platform features, after it laid off 50 people in January. Medium’s founder, Ev Williams, wrote publicly that the layoffs were inspired by Medium’s decision to move away from an ad-supported business model, because “people who write and share ideas should be rewarded on their ability to enlighten and inform, not simply their ability to attract a few seconds of attention.” In other words, Williams concluded that ad-supported models were encouraging both product designers and creators on the Medium network to focus on pageviews, and that was bad.
In support of Williams’ announcement, one of Medium’s investors, M.G. Siegler at G.V., wrote:
2 billion words written on Medium in the last year. 7.5 million posts during that time. 60 million monthly readers now. Pageviews galore. So step 2 is simply to slap some banner ads on the site, while step 3 is to profit, right? The reality — perhaps hard to see in the midst of such numbers — is that it behooves no one to simply continue down a path if you know the end result isn’t ultimately going to be successful. And so, the prudent yet extremely difficult move is to swallow your prideful metrics and course correct.
… Numbers — even insanely impressive numbers — can deceive. They can deceive when the goal is not actually to build the site with the most pageviews on the internet…. It’s not enough to simply be big. That’s part of the equation, to be sure. But just as vital is continuing to innovate on core product and experience while also building a sustainable model to make sure that all sides (publishers and readers) are deriving value — actual value — from the content, for the long-term.
Many other social media platforms are monetized through ads and their views, which makes them vulnerable to the same problems Siegler describes above: Prideful metrics and pressure to scale. And so, just like Medium, there’s widespread pushback against those metrics among companies that envision building social networks to deliver deep value over the long term. In fact, some companies resist this pressure by refusing to take venture money at all, since venture funders can sometimes put pressure on companies to scale fast.
So what are the metrics for high-quality social media?
In the digital content publishing world, I often direct people to the free ebook “The New World of Content Measurement,” published in 2014 by the combined content marketing agency + platform Contently. (I wasn’t involved in the production of that ebook, but it’s still good!) The ebook identifies both vanity metrics, and metrics that content companies can try if the goal is to deliver long-term ROI. These longer-term metrics are: 1) “Engaged Time” (a reader’s attention, measured by things like scrolling and highlighting); 2) “Readers and Returning Readers” (number of readers coming back to the content, and their engaged time across sessions); and 3) “Average Finish” (the percentage of visitors who finish reading the story).
Can these content metrics be applied to social media? Some work across both content and social (for example, Returning Users and Engaged Time). Yet these metrics, while arguably better than pageviews, can still lead product-builders astray. For instance, a digital media product might have a high Engaged Time because it’s addictive, rather than because people get deep and long-term value from it.
So: What metrics could measure thoughtfulness, warmth, harmony, or the value of ideas that emerge from a conversation? Perhaps limiting the amount of information that users disseminate through a platform can reduce noise and encourage users to see the act of sharing as valuable. Accordingly, one strategy is to limit users to posting one link per day. Of two companies that have tried this, one of them, This., has folded; the other, Catchpool, is still operating. (Both launched in 2014.)
Another way of thinking about noise reduction is to force users to apply to the network, or to focus on specialized material — “trade publication social networks,” if you will. Quibb, for example, both requires users to apply and bills itself as “a professional network to share industry news and analysis” within the tech industry. (Full disclosure: Quibb is a former client of mine.)
Alternatively: If users invest a lot of time helping a community, if they volunteer to maintain or moderate it, or if they pay a subscription fee to support it, then it’s clearly valuable to them, and those metrics are hard to hit but not hard to measure. There are some old-school digital communities that survive on models like this, such as MetaFilter, a community website founded in 1999. MetaFilter used to support itself on Google AdSense, but changes in Google’s algorithm forced it to look for another model in 2014, and now subscriptions are a critical part of MetaFilter’s business model.
Then there’s software like Mightybell, which launched in 2011 to support many niche, focused social networks. Founded by Gina Bianchini, who previously partnered with Marc Andreessen to found Ning (early software for niche communities), Mightybell enables community creators to monetize their communities as they see fit. It offers customizable tools for that — for example, a community creator might wish to use subscriptions, or she might wish to use sponsorships, and Mightybell’s software can support either or both of those options.
In this way, Mightybell seeks to align its business model with the business incentives of users who create and maintain small, devoted communities. As Bianchini said to me by phone, “As a platform for identity and interest networks, it’s our job to make community creators a lot of money. That’s pretty different from targeted ads as a business model. We aren’t a centralized social media feed that tries to be all things to all people.”
From this philosophy emerges a service model for community creators. This is also expressed in Mightybell’s customizable features, which each community creator can turn on and off — and that means that the ideal metrics might differ from community to community within Mightybell. For example, Mightybell creators can enable their community members chat in different ways; a creator can choose photos, text messages, videos, or any combination of the three. “The future of shared interest and identity is allowing community creators to customize the platform to enable new connections,” Bianchini told me.
Ultimately, the social platform software that wins territory like “the best information” or “the deepest relationships” may not scale to a billion users — and that might be okay. It may stay small, or scale one small community at a time.
Employee burnout is a common phenomenon, but it is one that companies tend to treat as a talent management or personal issue rather than a broader organizational challenge. That’s a mistake.
The psychological and physical problems of burned-out employees, which cost an estimated $125 billion to $190 billion a year in healthcare spending in the U.S., are just the most obvious impacts. The true cost to business can be far greater, thanks to low productivity across organizations, high turnover, and the loss of the most capable talent. Executives need to own up to their role in creating the workplace stress that leads to burnout—heavy workloads, job insecurity, and frustrating work routines that include too many meetings and far too little time for creative work. Once executives confront the problem at an organizational level, they can use organizational measures to address it.
In our book Time, Talent and Energy, we note that when employees aren’t as productive as they could be, it’s usually the organization, not its employees, that is to blame. The same is true for employee burnout. When we looked inside companies with high burnout rates, we saw three common culprits: excessive collaboration, weak time management disciplines, and a tendency to overload the most capable with too much work. These forces not only rob employees of time to concentrate on completing complex tasks or for idea generation, they also crunch the downtime that is necessary for restoration. Here’s how leaders can address them.Excessive collaboration
Excessive collaboration is a common ailment in organizations with too many decision makers and too many decision-making nodes. It manifests itself in endless rounds of meetings and conference calls to ensure that every stakeholder is heard and aligned. Many corporate cultures require collaboration far beyond what is needed to get the job done. Together, these structural and cultural factors lead to fragmented calendars and even fragmented hours during the day. Our research found that senior executives now receive 200 or more emails per day. The average frontline supervisor devotes about eight hours each week (a full business day) to sending, reading and answering e-communications—many of which shouldn’t have been sent to or answered by those managers.
Burnout is also driven by the always-on digital workplace, too many priorities, and the expectation that employees can use their digital tools to multitask and power through their workloads. Multitasking turns out to be exhausting and counterproductive as we switch back and forth between tasks. The costs of context switching are well documented: switching to a new task while still in the middle of another increases the time it takes you to finish both tasks by 25%. A Microsoft study found that it takes people an average of 15 minutes to return to an important project after an e-mail interruption.
Companies can begin to address the collaboration overload problem by adjusting organizational structures and routines. One easy step is to look at the number of nodes in the organization. These are intersections in the organizational matrix where a decision maker sits. A proliferation of nodes is a sign of unnecessary organizational complexity, and nodes act as organizational speedbumps, slowing down the action and stealing organizational time and energy.
Companies can also systematically examine how people go about their work. You can, for example, zero-base meeting calendars to determine which meetings are really necessary, how frequently they should be scheduled, how long they last and who really needs to attend. You can also look at how you staff teams. Instead of isolating star players by distributing them across teams, companies can often get better results by putting the high-energy, high-achieving players together on the same squad and having them tackle the highest priority work.
In addition to formal organizational changes, leaders can reduce burnout and raise enterprise productivity through softer interventions. For example, by adopting agile principles, leaders can motivate and energize teams, and give individual team members a way to own the results. With Agile approaches, teams focus on fewer, more critical activities. Initiative backlogs are used to set priorities, and the team reprioritizes the list whenever they add new tasks. This provides a mechanism for sustained focus on the most important priorities and constant pruning of less important ones. Projects are time-boxed and focused so that there is more doing and less energy-draining process.
Executives can also work on culture and coaching. Leaders can help establish new cultural norms around time and make clear that everyone’s time is a precious resource.Weak time-management disciplines
In most large organizations today, the demand for collaboration has significantly outpaced the development of tools, disciplines and organizational norms to manage it. Most often, employees are left on their own to figure out how to manage their time in ways that will reduce stress and burnout. They have limited ability to fight a corporate culture in which overwork is the norm and even celebrated. And few employees have the power—or temerity—to call off unnecessary meetings.
But company leaders can do something. The first step is to get a handle on the problem. While executives like to measure the benefits of collaboration, few have measured the costs. But there are useful tools to measure how employee time is spent and how that affects burnout and organizational productivity. Ryan Fuller, the cofounder of a workplace analytics start-up acquired by Microsoft, notes that executives often simply do not know how much time employees spend on activities that contribute to enterprise productivity, nor do they know how much time is lost or spent on less productive activities. His company’s product is now marketed as Microsoft Workplace Analytics and provides one way to estimate how employee time is spent.
Using data from such tools, you can map the places in your organizations where too much time is spent in meetings, emails, or online collaboration. With this information you can target changes in specific groups and functions to reduce the organizational drag that drains productivity and leads to burnout. Our data suggest that most executives have an opportunity to liberate at least 20% of their employees’ time by bringing greater discipline to time management. Equally important, doing so gives employees back control over their calendars. We find that one of the greatest sources of organizational energy is giving employees a sense of autonomy. It pays to give people back control of their days. It also helps to avoid micromanaging, which is another contributor to stress.Overloading of the most capable
Employee workloads have increased in many organizations in which hiring has not matched growth; companies overestimate how much can be accomplished with digital productivity tools and rarely check to see if their assumptions are correct. The overload problem is compounded for companies because the best people are the ones whose knowledge is most in demand and who are often the biggest victims of collaboration overload. In one company we studied, the average manager was losing one day a week to email and other electronic communications and two days a week to meetings. The highly talented managers will lose even more time to collaboration as their overwork earns them more responsibility and an even larger workload.
The same workplace analytic tools that can measure how much employee time is lost to unproductive activities can also measure the excess demands on the time of the best managers, enabling their bosses to redesign workflows or take other steps to avoid overload and burnout.
Everyone knows the human toll of burnout. Unchecked organizational norms insidiously create the conditions for burnout—but leaders can change them to make burnout less likely. Giving people back the time to do work that drives the company’s success will pay huge dividends by raising productivity, increasing productive output and reducing burnout. Everybody wins.
The McKinsey Global Institute, in conjunction with FCLT Global, recently released research stating that long-term-oriented companies perform better than those that focus on short-term results. While a laudable effort in principle, measuring a company’s tendency to make myopic operating and investing decisions is fiendishly complex. Getting the measurement right is central to providing convincing evidence on the debate over short-termism.
FCLT and McKinsey rely on readily available and machine-readable accounting data to measure myopia. However, such coarse data doesn’t capture how widely practices can vary between individual companies. This can lead to faulty estimations of companies’ myopia.
In its research, McKinsey classified a company as short-term-oriented, or myopic, in its decision making if the company was associated with: (1) low investment, indicated by a lower ratio of capital expenditure to depreciation; (2) poorer earnings quality, measured as higher accruals to revenue; (3) margin growth without revenue growth, captured as the difference between earnings growth and revenue growth; (4) unsustainable earnings growth, indicated by the difference between earnings-per-share (EPS) growth and growth in reported earnings; and (5) the incidence of companies beating or missing EPS targets by less than two cents.
Of these, the last indicator is perhaps the most likely to accurately capture a company’s short-termism. If a company has beat or missed its EPS targets by less than two cents, that means the company has nipped and tucked its quarterly results just enough to meet the target EPS number it committed to analysts. This measure has been validated by extensive academic research. But the other indicators probably pick up legitimate differences in how companies in the sample operate, as opposed to whether they are myopic.
For instance, McKinsey considered a smaller ratio of capital expenditure to depreciation to indicate short-term thinking, because it’s assumed that short-term companies will invest less, and less consistently, than other companies. But a smaller ratio could also indicate that: A firm has enough capacity built up and does not want to overinvest; a firm has recently outsourced its production, and therefore needs to spend less on capital expenditure; a firm has improved its operating efficiency, and therefore needs lower capital expenditure than before; or a firm relies more on short-term operating leases, which are not captured by the capital expenditure number, to provide for its capacity needs.
Similarly, considering greater accruals (which represent the difference between reported income and operating cash flows) to measure short-term orientation has its difficulties. It assumes that a smaller proportion of cash flows in earnings indicates a myopic firm. However, higher accruals can reflect either innocuous aspects of certain business models, such as in the construction industry, where the time lag between earning income and realizing cash is long, or that growing firms retain higher working capital to meet greater current and future customer demand.
McKinsey’s margin growth measure classified firms that report higher earnings growth than revenue growth as myopic. However, firms can efficiently increase margin growth without much revenue growth by managing to squeeze out their fixed costs to service the same level of output. So this measure may mislabel efficient companies as myopic.
Finally, McKinsey considered increases in earnings-per-share growth without earnings growth as unsustainable, and therefore an indicator of myopia. On the surface, this measure looks reasonable. But note that the difference between EPS growth and earnings growth is the reduction in the number of shares outstanding in the company. In essence, the measure labels firms with large share repurchase programs as myopic. Are all share repurchases myopic? No. What if concentrated market power of a few companies in an industry has made these companies more profitable than usual? Repaying such profits to shareholders through share repurchases is better than misinvesting that cash to diversify into unrelated businesses in which management has no expertise or overinvesting in projects that may not return cost of capital.
As I said earlier, measuring a company’s short-term orientation is incredibly tricky. A number of factors can confound any conclusions based on coarse data. What would better measures be? Based on my research and teaching, I believe there are five important aspects of a business’s decision making to consider. These are by no means exhaustive or bulletproof, but they are more likely to measure a company’s myopic orientation because they don’t solely rely on aggregate data that ignores individual differences across companies.
R&D spending. McKinsey was correct in looking at investment. However, it’s important to look closely at a company’s R&D spending, its R&D projects, and returns on such R&D. Myopic companies are more likely to invest in patents that pay off quickly, but in smaller amounts and for shorter periods of time, than long-term companies, which are more likely to invest in moonshot projects.
Corporate culture. I have worked on research that has found that a strong company culture is associated with lower levels of myopic decision making, better productivity, and innovation. One way to gauge this is in how a firm treats its workforce in bad times. For instance, Home Depot, despite a painful housing market–led recession, retained most of its hourly workers and their benefits in 2008–2009. Home Depot’s stock performance in the subsequent years has been stellar. Our research considered several other ways to measure corporate culture, such as collecting anonymous employee feedback on websites like Glassdoor, conducting interviews with retired or former executives at the firm, and noting the firm’s involvement in scandals. Evidence of a negative culture would be a strong indicator of a short-term company.
Compensation structure. Many compensation plans reward managers for higher earnings and higher stock prices, as opposed to rewarding them for adding long-term value to the firm. Incentivizing managers for growth routinely leads to expansion through overvalued acquisitions. These acquisitions increase growth without increasing value, which indicates myopia. But if firms pay managers for adding real value (stock returns or earnings that adjust for the cost of capital), it would indicate that the compensation committee is rewarding long-term value instead of short-term growth.
Overly optimistic financial statements. Myopic companies may be more likely to minimize the expenses and liabilities they report on their financial statements. By spinning their accounting performance, they may postpone having to make hard strategic decisions. Consider three examples. First, several companies with pension plans understate their pension expense and pension liability because they assume that actuarial estimates of pension liability are smaller than what an outside party, such as an insurance company, would assign to take over that liability, and that financial assets in their pension plans will earn greater future returns relative to what is widely regarded as feasible. Acknowledging that the pension plan is severely underfunded would likely prompt timely steps to either cut pensions or lower the plan’s risk in other ways.
Second, many companies understate their health care obligations to employees because they assume that the annual long-term health costs will eventually increase by only 5%, even though the actual increase over the last decade has been closer to 9%. Again, acknowledging reality might force hard, but timely, decisions on restructuring employee benefits.
Third, firms understate their depreciation expense because they assume that their long-lived assets will retain their worth over the long term — even though technological change increasingly makes them obsolete. Such misplaced optimism potentially masks underinvestment in technology needed to keep up with the competition.
Creative accounting measures. Similarly, a good indicator for myopia is a company’s use of performance measures that are not compliant with generally accepted accounting principles, as it may effectively spin the financial results. For example, the pervasive use of EBITDA (earnings before interest, tax, depreciation, and amortization) to reflect a company’s performance assumes that the company can operate without having to pay for these costs (I, T, and DA). As Warren Buffett warns, companies that rely on EBITDA are likely spending every dime that comes in and leaving no resources to replace existing capacity to counter competitive threats.
McKinsey and the FCLT have made a major contribution by refocusing our attention on the harmful consequences of short-termism in corporate America. However, we are more likely to make real progress in this debate if we get the measurements right.
I recently conducted a study with a large, multinational company to figure out how to increase employee engagement. After the data collection was complete, I ran the data analysis and found some intriguing results that I was excited to share with the firm. But a troubling result became apparent in my analysis: This organization had rampant discrimination against women, especially ambitious, passionate, talented women. Although this result was based on initial data, and was not particularly rigorous, I was convinced that managers at the collaborating organization would like to hear it so that they could address it.
I couldn’t have been more wrong. In a meeting with the company’s head of HR and a few members of his team, I first presented my overall results about employee engagement. In my last few slides, I turned the presentation toward the results of the gender discrimination analysis that I had conducted. I was expecting an animated conversation, and perhaps even some internal questioning into why the discrimination was occurring and how they could rectify it.
Instead, the head of HR got very angry. He accused me of misrepresenting the facts, citing data from his own records that showed men and women were equally likely to be promoted. In addition, he had never heard from anyone within the organization that gender discrimination was a problem. He strongly believed that the diversity practices his team had championed were industry leading, and that they were sufficient to ward off gender discrimination. Clearly, this topic was important to him, and my findings had touched a nerve.
After his fury (and my shock) was over, I reminded him that the data I presented was just initial pilot data, and should be treated as such. Perhaps if we were to do a more thorough assessment, I argued, we would find that the initial data was inaccurate. In addition, I proposed that a follow-on study that focused on gender discrimination could pinpoint which aspects of the diversity policies were working particularly well, and that he could use these insights to further advocate for his agenda. We landed on a compromise: I would design and run an additional study with a focus on gender discrimination, connecting survey responses to important outcomes such as promotions and turnover.
A few months later, the data came in. My data analysis showed that my initial findings were correct: Gender discrimination was happening in the company. But the head of HR’s major claim wasn’t wrong: Men and women were equally likely to be promoted.
The improved data set allowed us to see how both facts could be true at the same time. We now had detailed insights into which employees were — and, more important, were not — being promoted. Although ambitious, passionate, and talented men were being promoted, their female counterparts were being passed over for promotion, time and again — effectively being pushed out of the organization. That is, the best men were being promoted, but not the best women. Those women who were being promoted were promoted out of tokenism: They weren’t particularly high performing, and often reached a “natural” ceiling early on in their careers due to their limited abilities.
We also now had data on the specific kind of advancement opportunities male and female employees received to learn new skills, make new connections, and increase their visibility in the organization. Compared with their male counterparts, passionate women were less likely to get these kinds of chances.
Armed with this new data, I was invited to present to the head of HR again. Remembering our last meeting, I expected him to be upset. But we had a very different conversation this time. Instead of anger, the data I presented was met with concern. I could place the fact of men and women being equally likely to be promoted in a fuller context, complete with rigorous data from the organization. We had a lively debate into why this asymmetry between men and women existed. Most important, we concluded that the data he measured to track gender discrimination was unable to provide him with the necessary insight to understand whether gender discrimination was a problem.
He has since appointed a task force to tackle the problem of gender discrimination head-on, something he wouldn’t have done if we hadn’t collected the data that we did. This is the power of collecting thorough data in your own organization: Instead of making assumptions on what may or may not be occurring, a thoughtful design of data collection practices allows you to collect the right data to come to better conclusions.
So it’s not just about the data you have. Recall the famous Sherlock Holmes story about the dog that didn’t bark; existing data blinds us, and it is important to shift the focus away from readily available data. Crucially, not having the right data is no excuse. In the case of the head of HR, not hearing about gender discrimination from anyone in the organization allowed him to conclude that women did not face discrimination. Think about what data is not being collected that may help embed existing data in a richer context.
Next time someone angrily challenges your data, there are a few steps you can take. First, try taking their perspective: Understand why your counterpart is responding so forcefully. In many cases, it may simply be that they really care about the outcome. Your goals may even be aligned, and framing your data in a way where their goals are achieved may help you circumvent their anger.
Second, collect more data that specifically takes their criticism to heart. Every comment is a useful comment. Just as a fiction author can’t be upset when readers don’t get the point of what they are trying to say, a researcher must understand how their research is being understood. What is the upset recipient of your analysis responding to, and how can further data collection help you address their concerns?
Third, and last, view your angry challenger not as an opponent, but as an ally. Find a way to collaborate, because once you have their buy-in, they are invested in the joint investigation. As a result, they will be more likely to view you as being part of the team. And then you can channel the energy that prompted their fury for good.
We don’t usually consider praise from others to be a bad thing. When a colleague compliments our work or agrees with our opinions, we take reassurance — at least one person supports us.
Of course, CEOs, who are often subject to high levels of ingratiation by senior managers, may suspect that some of the flattery they receive is not 100% sincere. And yet they may not realize just how insincere it is. Our research suggests that, far from showing a subordinate’s support, flattery could be associated with the opposite: backstabbing. Moreover, our findings show that CEOs who are women or racial minorities may be particularly at risk.
Flattering one’s boss can feel demeaning, and since senior managers tend to have high opinions of their own abilities, we suspected that they would particularly dislike having to bring themselves to suck up to their boss. We hypothesized that ingratiation could lead to feelings of resentment, which in turn could make ingratiators more likely to criticize the CEO behind their back.
To investigate this, we collected survey data from CEOs and top managers at large and midsize U.S. public companies over a three-year period, as well as on journalists with whom the managers reported having communicated. We had completed responses from 3,895 CEO–top manager relationships over the three years, representing a 36% response rate. Our surveys allowed us to measure the top manager’s ingratiation toward the CEO, their resentment of the CEO, and subsequent communications with journalists.
This data confirmed our expectation. Not only did ingratiation increase the likelihood that managers would feel resentment toward the CEO, but it also increased the likelihood that they would make statements that reflected negatively on the CEO when communicating with journalists. These negative statements included both direct criticism and subtle forms, such as noting that the “board is picking up the slack” or that the CEO “recognizes their lack of experience.”
The size of the effects was large: A one-standard-deviation increase in compliments to the CEO was associated with an average increase in resentment of between approximately one and a half and two points on a two-point scale (depending on the survey item). This difference corresponded to going from disagreeing with the statement “I can’t help but feel some resentment toward [the CEO]” to agreeing with it. As we expected, this increased resentment led to higher levels of criticism of the CEO with journalists — a two-point increase in resentment was associated with approximately a doubling in the levels of criticism.
While ingratiation had negative implications on average across all CEOs, our research revealed that the penalty tended to be especially severe for women and racial minority CEOs. Specifically, we found that white male managers seemed to particularly resent having to ingratiate a female or a racial minority boss, and were more prone to then criticize that CEO with a journalist.
While there is evidence of barriers that make it harder for females and racial minorities to reach upper-level managerial positions, our research indicated that women and racial minorities who do reach the CEO positions continue to face additional burdens in leading their firms. These specific disadvantages are subtle and may be hard to even detect; the CEOs may not be aware that they are being criticized by the white male managers who are flattering them. The fact that white male managers often make up the majority of a female or racial minority CEO’s direct reports further increases the likelihood that they will be criticized.
Disturbingly, the CEOs may be completely in the dark about the identity of these backstabbers. Why would a CEO expect that a manager who seems particularly supportive, offering flattery and agreement to their face, would be the very ones saying bad things behind their back? Since journalists typically withhold source names, a CEO is likely to have a very hard time working out who it was that was making the negative comments.
One potential limitation of our study is that we focused only on relations between top managers and their CEOs. However, since ingratiation occurs throughout organizational levels, it may have other negative consequences for the firms beyond those we examine. While we have yet to examine it, we would suspect that firms with cultures that encourage ingratiation as a way for employees to get ahead may be particularly prone to backstabbing between those colleagues. Ingratiation at lower levels of the organization may then contribute to further problems that impact the CEO’s ability to effectively lead their firm.
Overall, our study offers a warning to CEOs. In an age where managers are increasingly being encouraged to actively build relations with important others, often through ingratiation, CEOs are likely to receive a substantial amount of praise. While it may be pleasing to receive this flattery, it may not be a good indicator of overall managerial support. In fact, our findings suggest that the CEOs who tend to receive high levels of flattery and agreement from their managers are particularly prone to being socially undermined by those very same individuals.
Marion Barraud for HBR
There’s a lot of advice out there about how to make meetings more efficient and productive. And while it’s true that leading focused, deliberate conversations is critical to organizational performance, meetings aren’t just about delivering results. There’s another outcome that leaders should be paying more attention to: creating a quality experience for each participant.
What is a quality experience in a meeting? I define it as when employees leave feeling more connected, valued, and fulfilled. Of course, you should still be focused on achieving the meeting outcomes, but thoughtful meetings and productive ones don’t have to be at odds.
I’ve worked with managers and project leaders to create these kinds of experiences. We begin by asking people to reflect on their best team experience and answer two questions: What does a powerful group look like? What does it mean to be powerful in a group?
The second question typically elicits answers like these:
- “I never left anything important unsaid. When I spoke, I felt like I was being heard, and I believed that what I said had an impact.”
- “It felt like I was really a member of the group. Everyone seemed genuinely interested in each other and in what was going on in our lives.”
- “I knew that I added value, both in the meetings and outside of them.”
In other words, each group meeting added to the experience of being a productive, valued member of the group.
Here’s what I’ve seen leaders do to create that quality experience:Related Video What to Do Before Ending Any Meeting Closure is important. See More Videos > See More Videos >
Work hard on being present. Take adequate time to prepare so that you can be available and attentive before and during the meeting. If you’re running late because of another meeting or still thinking about how to conduct this meeting, you’ll be preoccupied and not truly available for anyone who wants to connect.
Preparation allows you to relax about leading the meeting and pay more attention to “reading the room” — noticing how people are doing as they walk in, and throughout the meeting.You and Your Team Series Meetings
- The Seven Imperatives to Keeping Meetings on Track How to Design an Agenda for an Effective Meeting Do You Really Need to Hold That Meeting?
Demonstrate empathy. People associate attention with caring — your attention matters. Observe, listen, ask thoughtful questions, and avoid distractions and multitasking. Empathy is a learned skill that can be practiced by simply setting aside your phone and computer for two to three hours each week and really listening to someone. Meetings can be your primary place to hone this skill.
Set up and manage the conversation. Ask the group for permission to deliberately manage the conversation. It’s important to establish some guidelines about distraction. Ask people to:
- avoid using technology unless it is pertinent to the topics
- avoid any distracting behavior — verbal or nonverbal
- listen and respect people when they’re speaking
- invite others to speak if their view needs to be heard
Include enough time on every topic to allow broad participation. This means having fewer agenda items and more time allocated to each topic. As a target, put 20% fewer items on your agenda and allow 20% more time for each item.
Slow down the conversation to include everyone. I like the idea of social turn-taking, where you have a sense of who has or hasn’t spoken and whether the conversation is being controlled or dominated by one or more people. You don’t need to set this up as a rule, but you can model it as an inclusive style of conversation, so people become more likely to notice who hasn’t spoken yet.
To implement this practice, call on people gently and strategically. By gently, I mean make it feel and sound like an invitation — not some method of controlling participation. By strategically, I mean think through, during your preparation, who needs to be part of the discussion for each topic. Ask yourself:
- Who would be great at starting the conversation?
- Who is affected by the outcomes and therefore needs to be asked for their view?
- Who is most likely to have a different view?
- Who are the old hands who might sense whether we are making a mistake or missing something?
Check in with people at specific times. Begin each meeting with a question: “Does anyone have anything to say or ask before we begin?” Ask it deliberately and with a tone that signals that this conversation matters to you. And then wait. Pausing conveys that you’re not interested in getting to someplace other than right here, right now — that this conversation matters. Don’t spoil your pauses by making remarks about the lack of response or slowness of a response. People often need a few moments to reflect, find something to say, and think about the best way to express it. Just wait.
Once people realize that you are willing to pause, they’ll become more aware, and when they have a question, they won’t worry that they are slowing down the meeting.
High-quality conversations with broad participation allow people to get to know each other in ways that lead to friendship and collaboration. It’s the act of being with other people in an attentive, caring way that helps us feel that we are all in this together. Crafting a quality experience in your meetings takes time, but it’s worth it.
Curiosity has been hailed as one of the most critical competencies for the modern workplace. It’s been shown to boost people’s employability. Countries with higher curiosity enjoy more economic and political freedom, as well as higher GDPs. It is therefore not surprising that, as future jobs become less predictable, a growing number of organizations will hire individuals based on what they could learn, rather than on what they already know.
Of course, people’s careers are still largely dependent on their academic achievements, which are (at least partly) a result of their curiosity. Since no skill can be learned without a minimum level of interest, curiosity may be considered one of the critical foundations of talent. As Albert Einstein famously noted, “I have no special talent. I am only passionately curious.”Insight Center
- The Age of AI Sponsored by Accenture How it will impact business, industry, and society.
Curiosity is only made more important for people’s careers by the growing automation of jobs. At this year’s World Economic Forum, ManpowerGroup predicted that learnability, the desire to adapt one’s skill set to remain employable throughout one’s working life, is a key antidote to automation. Those who are more willing and able to upskill and develop new expertise are less likely to be automated. In other words, the wider the range of skills and abilities you acquire, the more relevant you will remain in the workplace. Conversely, if you’re focused on optimizing your performance, your job will eventually consist of repetitive and standardized actions that could be better executed by a machine.
But what if AI were capable of being curious?
As a matter of fact, AI’s desire to learn a directed task cannot be overstated. Most AI problems comprise defining an objective or goal that becomes the computer’s number one priority. To appreciate the force of this motivation, just imagine if your desire to learn something ranked highest among all your motivational priorities, above any social status or even your physiological needs. In that sense, AI is way more obsessed with learning than humans are.
At the same time, AI is constrained in what it can learn. Its focus and scope are very narrow compared to that of a human, and its insatiable learning appetite applies only to extrinsic directives — learn X, Y, or Z. This is in stark contrast to AI’s inability to self-direct or be intrinsically curious. In that sense, artificial curiosity is the exact opposite of human curiosity; people are rarely curious about something because they are told to be. Yet this is arguably the biggest downside to human curiosity: It is free-flowing and capricious, so we cannot boost it at will, either in ourselves or in others.
To some degree, most of the complex tasks that AI has automated have exposed the limited potential of human curiosity vis-a-vis targeted learning. In fact, even if we don’t like to describe AI learning in terms of curiosity, it is clear that AI is increasingly a substitute for tasks that once required a great deal of human curiosity. Consider the curiosity that went into automobile safety innovation, for example. Remember automobile crash tests? Thanks to the dramatic increase in computing power, a car crash can now be simulated by a computer. In the past, innovative ideas required curiosity, followed by design and testing in a lab. Today, computers can assist curiosity efforts by searching for design optimizations on their own. With this intelligent design process, the computer owns the entire life cycle of idea creation, testing, and validation. The final designs, if given enough flexibility, can often surpass what’s humanly possible.
Similar AI design processes are becoming more common across many different industries. Google has used it to optimize cooling efficiency with its data centers. NASA engineers have used it to improve antennae quality for maximum sensitivity. With AI, the process of design-test-feedback can happen in milliseconds instead of weeks. In the future, the tunable design parameters and speed will only increase, thus broadening our possible applications for human-inspired design.
A more familiar example might be the face-to-face interview, since nearly every working adult has had to endure one. Improving the quality of hires is a constant goal for companies, but how do you do it? A human recruiter’s curiosity could inspire them to vary future interviews by question or duration. In this case, the process for testing new questions and grading criteria is limited by the number of candidates and observations. In some cases, a company may lack the applicant volume to do any meaningful studies to perfect its interview process. But machine learning can be applied directly to recorded video interviews, and the learning-feedback process can be tested in seconds. Candidates can be compared based on features related to speech and social behavior. Microcompetencies that matter — such as attention, friendliness, and achievement-based language — can be tested and validated from video, audio, and language in minutes, while controlling for irrelevant variables and eliminating the effects of unconscious (and conscious) biases. In contrast, human interviewers are often not curious enough to ask candidates important questions — or they are curious about the wrong things, so they end up paying attention to irrelevant factors and making unfair decisions.
Lastly, consider a human playing a computer game. Many games start out with repeated trial and error, so humans must attempt new things and innovate to succeed in the game: “If I try this, then what? What if I go here?” Early versions of game robots were not very capable because they were using the full game state information; they knew where their human rivals were and what they were doing. But since 2015 something new has happened: Computers can beat us on equal grounds, without any game state information, thanks to deep learning. Both humans and the computers can make real-time decisions about their next move. (As an example, see this video of a deep network learning to play the game Super Mario World.)
From the above examples, it may seem that computers have surpassed humans when it comes to specific (task-related) curiosity. It is clear that computers can constantly learn and test ideas faster than we can, so long as they have a clear set of instructions and a clearly defined goal. However, computers still lack the ability to venture into new problem domains and connect analogous problems, perhaps because of their inability to relate unrelated experiences. For instance, the hiring algorithms can’t play checkers, and the car design algorithms can’t play computer games. In short, when it comes to performance, AI will have an edge over humans in a growing number of tasks, but the capacity to remain capriciously curious about anything, including random things, and pursue one’s interest with passion may remain exclusively human.
Project Apollo Archive/NASA
In January Google ended Project Titan, an initiative to blanket the earth in Wi-Fi with the help of solar-powered drones. It was the latest in a series of Google’s moonshot projects being closed. With the announcement, some in the media concluded that the Google moonshot was essentially dead.
“Moonshots” is the term favored by the company’s exploratory arm, known as X, which states on its website: “Our mission is to invent and launch ‘moonshot’ technologies that we hope could someday make the world a radically better place.”
The notion of moonshots is a hugely appealing idea, whether you are an enterprise working on a market innovation, a nonprofit organization tackling societal problems, or a government trying to govern better. Whatever our sector or focus, we need to be able to think big and execute on those ideas successfully, otherwise we are stuck making incremental advances.
But moonshots are high cost and high risk, as the name suggests. They sometimes seem to be a special domain reserved for superhumans and misguided optimists. How can we get the moonshot formula right to unlock this approach to groundbreaking innovation? And how can your company get it right if even Google can’t seem to make its moonshot factory work?
For starters, we can learn something by looking at how the original NASA moonshot worked.
NASA’s moon effort got under way in May 1961, with President John F. Kennedy declaring that the United States would put a man on the moon within the decade. At the time, those charged with achieving the goal had questions as to whether it could be done. Eight years and $24 billion later ($150 billion in today’s terms), Neil Armstrong set foot on the moon as 600 million people watched on their televisions. The landing has been called the greatest technological achievement in human history.
Clearly, this was a moonshot, figuratively as well as literally. On the surface it seems as though the NASA project miraculously accomplished the near impossible. But when you look more closely, you see that there was nothing wildly speculative or fantastical about it. In fact, it was done mostly with common sense and grit. Such an approach can apply to your organization and its largest ambitions.
Here are some lessons from NASA’s moonshot:
Channel existing energies. When President Kennedy set the moon initiative in motion, the U.S. space program had already been under way for two years, and Project Mercury had recently sent men into space. Kennedy wasn’t charting a new path from scratch; he was channeling existing capabilities for a desired outcome, with a focused goal. To create moonshots that work, do not start from the drawing board. Give direction, ambition, and urgency to initiatives already in the works.
Don’t be prescriptive. When Kennedy set the goal, he outlined concrete terms (put a man on the moon and get him back safely) and gave a deadline (do it by the end of the decade). Beyond that, he left it open as to how NASA would achieve the goal. NASA’s employees debated the best way to do it at each step. Was it to blast off a ship from Earth? Assemble it in space? Send a separate lunar module down to the moon while the spaceship itself orbited? Each decision potentially meant the difference between success and failure; crucially, the decisions were left to those who were closest to the challenges and could answer them best. To create moonshots that work, set out the what and the when, and leave the how to those closest to the problem.
Take small steps in the service of big ideas. NASA’s moonshot was a series of 23 small-scale, individual missions. From 1961 to the 1969 lunar landing, 12 Gemini missions and 11 Apollo missions took place, each with its own teams, roadmaps, goals, successes, and failures. This allowed NASA to concretely measure outcomes each step of the way, while creating firewalls between them to contain losses in the event of failure. The best moonshots string together a series of much smaller projects or goals in the service of one big vision.
Get return on your investment as you go. Kennedy was clear from the outset that the real ROI for the lunar project would come from beating the Soviet Union in the space race. But each additional mission served to underscore U.S. superiority over the Soviets in space, effectively giving the U.S. return on its investment along the way. For these types of projects, develop them so that the returns don’t pay out only at the end.
Don’t go it alone. Although NASA employed around 35,000 people and had a team of some of the best engineers in the world during the Gemini and Apollo years, 12,000 corporations were involved in making the moon project happen. The Saturn V rocket alone was built by three different companies. NASA leveraged every possible partner to build a vast ecosystem of subject matter experts working toward the same goal. Get the best possible expertise from outside the building to add to your own core expertise.
Continually communicate progress. When it undertook the moon project, NASA transformed itself from a secretive government agency into a public relations and marketing machine, leveraging not only its own public affairs staff but also those of partners like IBM and Boeing to help get the word out. They did this with the understanding that U.S. taxpayers, who were the ultimate stakeholders, needed to understand and care about the mission and its progress. Make sure to tell your story well to the people who matter most.
If you look at some of the big successes of our day — the iPhone, Amazon Web Services, SpaceX — you see similar approaches at work. (SpaceX, taking a page from NASA’s playbook, just announced that it will fly tourists around the moon in 2018.). These projects, and the organizations that run them, are not about miraculously mastering wild technologies, but about harnessing existing knowledge, expertise, and energy in the service of some great goal.
The times call for bold solutions to big problems and big opportunities. We need moonshots. Even more, we need moonshots that work. Making that happen should not be impossible. It should only be a matter of understanding the correct steps to take and following through.
With unemployment rates in most developed nations at the lowest levels since the Great Recession, and with new skill sets required to keep pace with head-spinning technological advances, it’s no surprise the talent acquisition environment is incredibly competitive.
In a new Korn Ferry Futurestep global survey of more than 1,100 talent acquisition professionals, 54 percent said it’s harder to find qualified talent now than it was just one year ago. The same study found that identifying people with the right skills in a rapidly changing market is the top issue impacting recruiting.Read more from Korn Ferry:
- How Organizations Can Thrive in the Digital Economy
- How to Develop Leaders Who Can Drive Strategic Change
Although the type of organization, the sector of the industry, and geography, among other factors, determine how challenging it is for an organization to recruit talent, it’s clear that the changing global economy has created a demand for new jobs, new skills, and new capabilities, leaving organizations scrambling to find the best workers to fill positions.
But it’s not just technology and markets that are changing—workers are changing too. The survey revealed that talent acquisition professionals can’t rely on what worked in the past when recruiting top talent today. Five years ago, compensation (i.e., salary and benefits) was the top reason why a candidate chose one employer over another, respondents said. Today, culture is the number one reason why candidates choose an employer.
But the future will likely bring a new set of candidate expectations. Talent acquisition executives predict “workplace flexibility” will be the top reason why candidates choose an employer five years from now. This flexibility goes well beyond workers’ hours and location, to the very nature of the employee-employer relationship.
That is part of another shift in the talent landscape: the move from a full-time employee base to contingent workers. Seventy-five percent of survey respondents reported that they use a contingent workforce on either a regular or an as-needed basis, and the numbers of those workers are expected to grow substantially in the years ahead.
As talent acquisition professionals work to adapt to the changing priorities of candidates, they must also focus on the attributes and skills needed to fill the toughest positions. Survey respondents indicated the most difficult roles to fill today are in sales, research and development, and information technology, and filling them is only going to become more difficult.
The pace of technological and marketplace change will continue to create demand for new skill sets and brand-new job categories. Candidates with the right skills will be looking for organizations that provide flexible working arrangements and a congenial working culture. They might agree to be available via their mobile devices at all times of the day and night, but in return, they expect to work from home and take time off during the day when the need arises.
Demographics suggest the talent shortage will become more acute in the years ahead. Between 2015 and 2025, the 167 million workers entering the workforce will barely outpace the 166 million workers retiring (McKinsey & Company 2015).
In the face of these challenges, it is crucial that talent acquisition become more intertwined with all the functions of the business. In order to stay competitive, leaders must understand where talent needs will arise throughout the organization, and talent acquisition professionals must map a talent management plan to support the overall goals of the business.
This plan can take a blended approach to talent management that includes an effective campus recruitment operation, a robust contingent workforce, a strong social media presence targeted at workers’ needs, a powerful employee brand, and an effective training and leadership development program.
Organizations that implement a blended approach, provide flexible work structures, and give workers what they want from their employers will be best positioned to win the talent acquisition game.
Adapted from Korn Ferry’s “The Talent Forecast.” To learn what talent acquisition leaders can tell us about tomorrow’s workplace, click here.
Differentiation should be a prime motivator of any strategy; firms should always look to find an edge. But too often CEOs find themselves stuck in what I call an innovation plateau. They fall into chronic sameness, an inertia driven by a feeling that they must focus on cost, even cheapness, to remain competitive.
A main indicator of how widespread this plateau has become is the decline in corporate investment in R&D, the invisible infrastructure that supports true innovation. Investment in fundamental science, the R, has dropped from more than 2% of U.S. GDP in the 1970s to 0.78% today. The less science, the fewer ideas for new businesses.
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If this myopia is going to change, CEOs need to be able to recognize when their strategic inertia is staring them in the face. In my research and consulting work, I have identified four symptoms that should warn executives that they are stuck on an innovation plateau. The four are born of good intentions, but ultimately they are self-destructive:
Obsession with low-cost reduction programs. Rather than paying attention to the numerator (increasing revenues), CEOs focus on the denominator (reducing costs). The excuses I hear for this imbalance are pretty simple: Executives say they want to grow the “quotient,” and attacking the cost side is always the easiest and quickest way to achieve it. I describe this symptom as akin to organizational anorexia. What’s striking is that this symptom is so widespread that firms resisting the race to the bottom now stick out in the crowd. Deere & Co — founded almost two centuries ago, and consistently the leader in what it does — have people dedicated entirely to “imagining” the future. Lean is a powerful management tool, but having the “exact” number for efficiently doing the “work” of today jeopardizes the future by not having “extra” people thinking on it. Efficiency is not innovation.
Obsession with listening to the customer. Almost all customers want their products to be as inexpensive as possible. So firms try to respond to this by delivering the value that they think their customers want. But great CEOs understand that the responsibility of defining greatness is the firm’s, not the customer’s. As Steve Jobs was fond of asking, Am I really going to ask customers if they want an iPad?
Obsession with incrementalism. The benefits of compounded marginal gains can be substantial. “Small ball” can be effective in the short term. But when asked about the future, CEOs almost always talk about their current portfolios. By what percentage will they rise or fall? Radical innovation, when a new dominant design emerges that can lead to a step-change in a company’s fortunes, is often absent in their agendas.
Obsession with acquisitions. When failing to innovate, CEOs acquire talent. Apple spending $3 billion on Beats, or Facebook paying around $19 billion for WhatsApp — this to me is indicative that the companies found themselves stuck on the innovation plateau. I have observed that the more innovative a firm is, the fewer acquisitions it makes. It develops the talent inside, focusing on a few great things. Jobs invested $150 million in developing the iPhone; Tim Cook has invested almost seven times that in Didi Chuxing. That is the tale of Apple during growth-driven-by-innovation, and Apple during innovation stall-out.
How do firms overcome the innovation plateau? Firms are discovering that customers don’t always want to shop on price — exploiting an emotional relationship can help escape the race to the bottom. Natura, a Brazilian cosmetics firm, produced a mother-baby product line that undercut Johnson & Johnson’s leading position in the baby market by linking Natura’s products with the Shantala method, a popular technique in Brazil for strengthening the bond between mother and infant through massage. The campaign allowed Natura to compete with Johnson & Johnson on something other than price.
Deepening the science behind the business, focusing on discovering higher-value market segments through new products and in new industries, and looking to expand globally will all keep the top line growing. For example, the small dairy cooperatives Tatua and Westland in New Zealand developed specialized ancillary products such as complex lipids and the world’s first goat milk with a long shelf life. Rather than trying to make the cheapest steel in the world, the Basques (of Basque Country in Spain) make steel for spacecraft. If firms trading in commodities such as steel and milk can climb the value chain, any company should have the imagination to discover global, high-value markets for its expertise — and remain buoyant even in a world of seemingly fleeting competitive advantage and strategic inertia.
Recent research by economists Anne Case and Angus Deaton documents a dramatic rise in mortality rates among working-class white people in the U.S. The immediate causes of these “deaths of despair,” as the pair refer to them, are often factors like drug abuse, health problems like diabetes, and suicide. But these issues stem from a larger epidemic of job insecurity for Americans without a college degree, creating a sense of untethered hopelessness among millions of people. The problem is widespread enough that it led, in 2015, to the first overall decline in U.S. life expectancy since 1993.
The fact that people’s health and emotional well-being are so closely tied to the absence of steady work is striking. Yet what matters here is not just job insecurity; it’s also what we might call the culture of insecurity: the growing conventional wisdom that precarious employment is inevitable. Many Americans can narrate the decline of the social contract, the collapse of the kinds of jobs their grandfathers held for decades before retiring and getting the gold watch. Survey data reflects this sentiment as well: According to Pew, most Americans are convinced that jobs have become more precarious than they were 20–30 years ago, and predict that it will get worse.
These kinds of cultural proverbs, as they are repeated and shared among us, tell us which kinds of emotions are appropriate responses and which are not. If job insecurity is all that we can expect, for example, we learn that resistance is not just futile. It is akin to cursing the wind: misguided, blind to what everybody knows, even illegitimate.
So despair is not due just to a lack of work — it stems from insecurity’s emotional trap, which extends far beyond the workplace.
My research, involving men and women who experience varying levels of job insecurity, suggests that the dampening expectations they have for employer commitment requires them to moderate the kinds of feelings they allow themselves to have in the event of a layoff. This is especially true for less-educated workers, who are most likely to say they could lose their jobs in the next year.
Take the example of Gary*, a former construction manager I interviewed. Grieving after he lost his job, along with his crew and other managers at his company, he noted that “it was the biggest mistake I ever made.” His mistake? “Putting [his] livelihood and career into their hands” — that is, trusting the firm that hired him.
Gary’s inward focus is not uncommon. American workers often blame themselves for being let go and adopt emotional strategies that serve to suppress their own ire and outrage. Many resign themselves to being without work as just “the way things are today.” They tell themselves that getting fired is a new opportunity; they express empathy and understanding for the employer’s point of view; they remind themselves that they did not like or want the job anyway. While some workers are angry (and they are more likely to be angry when they perceive unfair treatment), negative feelings are often viewed as less culturally justifiable in an era when letting people go is, as one woman told me, “just what you would do.”
“And that’s okay, they’re there to make money,” Martha* said, even as she related a hair-raising account of being fired to make room for the boss’s lover. Said another person I interviewed, “It’s just what you would expect.”
Something troubling happens when people become resigned to this inevitability, beyond lost wages, routine, and a sense of purpose. In order to deal with the emotional fallout of being betrayed on the job, workers construct what we might consider a “moral wall” between work and home. At home, they brace themselves against the insecurity they largely accept in the workplace, striving to fend it off when it comes to family and friends. It’s as if people say, “We might not be able to rely on our employers, but surely, in our intimate lives, we can count on each other.”
Yet when they set unreasonably high expectations at home, it can lead to a certain brittleness, an inability to bend or handle inevitable ups and downs. Less-advantaged workers in particular are fervent about the sacredness of intimate relationships and the inviolable duty they command. When people close to them fail to live up to these standards, it can lead some to give full vent to the anger they do not allow themselves when it comes to employment.
In other words, when people have no way of addressing failed commitments at work, they double down on the importance of commitment in other parts of their lives. And when those commitments don’t meet their expectations, despair can grow.
Gary, for his part, has a live-in partner but has been married and divorced twice. “The hurt that’s been caused to me by a lack of commitment on the part of other people — marriage can be tossed out like a Pepsi can,” he said. Let down by others at work and home, it is only at home that Gary permits himself to feel betrayed, because when it comes to work, remember, he blames himself.
The bitter paradox, of course, is that job insecurity is not inevitable. Economists have shown that downsizing does not necessarily lead to higher productivity or shareholder value. Some researchers have suggested that in the coming automation revolution, machines could refine tasks without eliminating whole jobs. Change may be imminent, but its contours are hardly inevitable, depending instead on how we approach it. Denmark, the Netherlands, and other EU countries where union density is higher than in the U.S. have taken important steps, including worker retraining and more-generous unemployment compensation, to balance worker needs for stability and employer needs for flexibility. Dubbed “flexicurity,” these provisions were strained by the Great Recession but contributed to stronger economic performance by the Nordic countries. In fact, the working-class deaths of despair uncovered by Case and Deaton in the United States, a country that has uniquely embraced downsizing as a management tactic, have not been found in other rich nations.
Gary’s story, and those of others I spoke with, gives us clues to the causes of deaths of despair. Uncertainty about the availability of good, steady work is an emotional hit, one that both limits people’s capacity to respond on the job and amplifies their response at home.
So when we talk about work today, we have to talk about it in the context of an unrequited contract, our collective acquiescence to the notion that work can no longer be counted on. When people are left out in the cold by their employers, they steer their yearnings for commitment toward other arenas, such as their personal relationships with friends and family. Yet these yearnings often end up making their intimate lives more fraught, as high expectations meet human frailty. This can lead to even more sorrow and betrayal. Despair makes sense when all we’ve allowed people — and all they allow themselves — is the cultural acceptance of their own abandonment.
*Gary and Martha are pseudonyms
Last month, a Tesla employee criticized the company in a Medium post, spurring a public exchange between the employee and Elon Musk, Tesla’s CEO. In November, an IBM employee resigned by posting an open letter to CEO Ginni Rometty, in response to an open letter that Rometti had written to President Donald Trump.
Many leaders expect to be challenged by employees in the privacy of their offices, but there are greater risks when it happens online, in public. Others may pile on, a CEO’s response may be taken out of context, and comments may live on in perpetuity. A CEO’s personal reputation, which is one of a company’s most valuable assets, may be at stake. Employee critics can be far more damaging than outside commentators, due to their insider’s perspective, access to sensitive information, and greater degree of credibility.
Social media has become an important employee communications tool that leaders should embrace. Employees are more likely to view socially active CEOs as good communicators and listeners, as open and accessible, and as more inspiring. But it’s important to know how to handle criticism, should it occur. Taking a few steps can help CEOs prepare for constructive exchanges with employees online.
Foster internal dialogue. Employees want to have a dialogue with their CEOs, but only 17% of the employees we surveyed globally rated communication from and with their chief executives highly. To better engage with their workforces, leaders need to find ways to hear people’s concerns. CEO roadshows to locations around the world, offices hours, intranet forums, and even informal conversations (like Google’s “TGIF” chats in the cafeteria) help staff feel heard, help leaders keep a pulse on sentiment, and can foster online loyalty among employees down the road.
Typical employee concerns include things such as layoffs, outsourcing, reduced benefits, and so on. These create the perception that CEOs sacrifice employees’ well-being for profit or personal benefit. Effective CEOs need to be aware of these pain points and meet regularly with employees to explain, course correct, or defend. If the conversations don’t happen internally, they will eventually surface externally, at a higher cost.
Listen externally. Social media tracking is a more than $2 billion industry, offering products that monitor everything from when an employee posts something to how many views it gets and whether it’s picked up by traditional media. Investing in the right technology can help companies track how they’re being portrayed online and find the posts that demand attention.
Reach and context are important data points to monitor. For example, one company escalates any critical posts from employees with Twitter followings of more than 10,000. The day’s news cycle and trending online conversations can also carry an employee post from obscurity to prominence. Companies should set objective indicators of risk that can help them decide whether to respond to criticism. They should also plan the steps they will take in different scenarios.
Only respond to criticism when necessary. Responding to all employee criticism isn’t feasible or advisable. Determining whether, when, and how to respond requires judgment and sensitivity to the nuances of the situation. CEOs should partner with communications, HR, and legal to assess the following:
- Who is the employee? What is their standing with the company? What might be their objectives in posting, and what are they looking for in a response? An employee who speaks out after being overlooked for promotion may not be receptive to a constructive exchange. On the other hand, an employee in good standing who uses social media to raise genuine concerns about a new corporate policy may offer the CEO a chance to clarify and bring the employee onboard.
- Is a CEO response likely to draw even more attention to the issue? Getting more attention is not necessarily a bad thing, but it is important to consider. When a Yelp employee complained about the cost of living in the Bay Area and asked the CEO, Jeremy Stoppelman, for a raise in a post on Medium, she was terminated within a matter of hours. This action, and Stoppelman’s Twitter response, amplified the coverage. The employee’s post has been recommended 3,400 times and has received nearly 1,400 comments, and the story was picked up by outlets including Forbes, Fortune, and Business Insider. It ignited a global conversation on the minimum wage, corporate social media policies, and freedom of speech. While the CEO’s response likely drew more attention to the original post, not responding might have sent the wrong message. Instead, Stoppelman added to the conversation by expressing sympathy, sharing his efforts to support affordable housing, and outlining the company’s efforts to create jobs in markets with lower costs of living. When CEOs do respond, their replies should be straightforward and timely to avoid providing more fodder for criticism.
- Is the employee’s claim factually accurate? If not, should the CEO correct it? What is the risk of letting the misinformation go uncorrected? Untrue statements on the internet can do significant reputational damage. When a Reddit employee opened an “Ask Me Anything” thread by falsely reporting that he had been laid off for no reason, the CEO responded personally, clarifying that the employee had been fired, not laid off, and cited the specific reasons for his termination. Recognizing that such a claim would spark widespread unease across the employee base, the CEO chose to nip it in the bud. But if the falsehood has not been widely viewed, doesn’t adversely impact the company’s reputation, or is clearly ludicrous in nature, many companies will choose not to reply.
- What platform was the post on? Does it offer built-in protections to keep dialogue constructive? Some social media channels are lower risk than others. Official employer review sites like Glassdoor are guided by community rules and are rigorously monitored. The site limits exchanges to one review from an employee and a single response from a CEO or company, thereby preventing unproductive back-and-forth. CEOs are active on Facebook (56%), Twitter (36%), and LinkedIn (27%), among other sites. These sites allow criticism of CEOs and other public figures, but prohibit threats, harassment, and hate speech directed at them. They also offer direct messaging, which CEOs can use to respond to employees privately rather than publicly. CEOs may not wish to respond to complaints on personal blogs or industry chatrooms, where there is limited monitoring.
If the decision is to reply to employee criticism, CEOs should remember that a response over social media is not just a response to the critical employee — it’s a message to everyone who comes across it, including potential shareholders, customers, and employees.
As a general rule, simplicity and humility go a long way. The tried-and-true formula — thanking employees for feedback, acknowledging their frustration, and laying out measures to address the situation — is illustrated in this open letter from Danny McKinney, CEO of Satellites Unlimited. This method is frequently deployed by CEOs across social channels.
Interacting with employees online shouldn’t be viewed as a threat so much as an opportunity. When online conversations are positive, they can make CEOs visible, accessible, and likable. When not-so-positive, they can provide CEOs with valuable employee perspective and a chance to create shared understanding.
It is hard for anyone to be against the idea of inclusive prosperity. Of course the bounty produced by economic growth should be broadly shared. But the devil is in the details, and when people advocate for inclusive growth they don’t always have the same things in mind.
Some, for example, are inspired by Thomas Piketty, who seems to have singlehandedly set a new agenda for economics research. This group focuses on reducing the disturbing inequalities in individuals’ incomes and wealth.
Others, like the Legatum Institute, think of prosperity less in financial terms and more as overall well-being, and focus on measuring and growing all its components in societies around the world.
A third group takes a more managerial approach; and that’s the one we want to focus on here. When Eric Beinhocker and Nick Hanauer took on the topic, they put it this way: “Prosperity in a society is the accumulation of solutions to human problems.” By emphasizing solutions as the engine of growth, Beinhocker and Hanauer wanted to cast capitalism as a force for prosperity (as the system that churns out the most constant stream of superior ones). But their way of thinking about prosperity also offers direction for any managers who want to work harder to make the world better off: your mission is to imagine, develop, and launch more life-improving solutions, especially the kinds of goods and services that improve ordinary people’s lives. Businesses have a variety of social responsibilities, but the essential one—and the main reason that private enterprise is given license to operate—is to innovate.
We’d like to add a wrinkle to Beinhocker and Hanauer’s argument. If we’re thinking about prosperity in broad terms, then we should also recognize it isn’t just the solutions themselves that improve quality of life – it’s also engagement in the act of solving. Participating in the satisfying work of innovating enriches lives by endowing them with purpose, dignity, and the sheer joy of making progress in challenging endeavors. Imaginative problem-solving is part of human nature. Participating in it is essential to the good life – and no elite minority should have a monopoly on that.
So this raises the question: How do we enable more people to get involved in solving problems? Every person is capable of creative thought and action. Great managers know how to tap that superabundant resource, and they recognize that pooling creative energy usually accelerates progress. Many minds make lighter work.
But for this to happen broadly, more organizations need to recognize that their innovation mandate is not just to design new products and services, but also to redesign how work gets done. The digital age gives us a tremendous opportunity to do that – but also comes with its own challenges and risks. How businesses continue to develop and deploy information and communications technologies will profoundly affect whether prosperity is inclusive or exclusive. At their best, today’s increasingly capable machines enable and empower people to collaborate more effectively, and they make learning from experience scalable. Collaborative platforms allow people to combine their measurements and observations of large-scale phenomena (such as water quality), while advances in machine learning, artificial intelligence, and sheer computational power extend the powers of human intellect just as earlier technologies amplified human strength.
But at their worst, smart machines have the potential to marginalize human contributions, automating cognitive work and leaving society with, as Bill Davidow and Michael Malone vividly phrased it, “hordes of citizens of zero economic value.” The situation creates huge responsibilities for politicians, educators, executives, and others to manage the transition and the hardships that may come with it.
We find ourselves, therefore, at an important crossroads. The technologies our species is developing might either hold the keys to unlocking human potential — or to locking it up more tightly than ever. Indeed, they could even transform what we think of as human potential, given the startling new combinations of technological and human capabilities being devised. (No need to wait for Elon Musk’s Neuralink. As DARPA’s Arati Prabhakar has described, the merging of humans and machines is happening now. )
Clay Christensen likes to remind innovators of the importance of remembering the essential “job to be done” by their offerings – what is it that customers “hire” your product or service to do for them? In that spirit, what is the “job to be done” by the practice of management itself? What is the job that society needs to get done that it turns to competent managers to do? Increasingly, that job is not only to produce better goods and services more efficiently, but to organize individuals to collaborate and create together in unprecedented ways. The business leaders who get that job done will be those who make the most of human potential, and manage to make prosperity inclusive.
This post is the first in a series leading up to the 2017 Global Drucker Forum in Vienna, Austria – the theme of which is Growth and Inclusive Prosperity.