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Harvard Business Review
Mindfulness is the ability to stay focused, while being aware of your thoughts and surroundings and being able to recognize and move past distractions as they arise.
In our information-saturated workplaces, this mental skill is becoming as important as emotional intelligence and technical skills. Research shows that people spend almost 47% of their waking hours thinking about something other than what they’re doing, which impairs their creativity, performance, and well-being.
We developed this assessment, in collaboration with Accenture, to help you understand how mindful you are, both at work and in general. It is based on our work at Potential Project conducting mindfulness training for thousands of individuals in organizations around the globe. We will provide you with a rating of your mindfulness and recommendations for improving it.
For each of the questions below, think about your behaviors and thoughts at work and indicate your level of agreement. Please answer honestly and carefully. There are no right or wrong answers.
Although we live in a world that glorifies self-belief and stigmatizes self-doubt, there are really only two advantages to thinking that you’re better than you actually are. The first is when you’re attempting to do a difficult task. Believing that you can do something difficult is half the battle, but if you truly overrate your abilities, then by definition you will fail. The second is fooling others into thinking that you are competent. Most people will be found out eventually, and the personal benefits of faking competence will be offset by the negative consequences for others. For example, deluded leaders may come across as charismatic and talented, but their overconfidence puts their followers at risk in the long run. In contrast, when leaders are aware of their limitations, they are less likely to make mistakes that put their teams, organizations, and countries in danger.You and Your Team Series Difficult Conversations
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And yet — as I demonstrate in my latest book — leaders are not generally known for their self-awareness. Although leadership talent is normally distributed, 80% of people think they are better-than-average leaders. Moreover, with narcissism rates rising steadily for decades, there is no reason to expect future leaders to be more accurate in their self-evaluations, let alone to be humble. Strengths-based coaching, and removing negative feedback from performance appraisals are aggravating the problem, validating leaders’ fantasized talents much like when parents tell their children that they are the brightest and cutest in the world. This is especially likely when leaders are intimidating, or when they surround themselves with sycophantic employees. As a result, leaders are deprived of the very feedback they need to get better.
Whether you manage or coach leaders, or are just trying to provide some feedback to your own boss, here are three simple points you may wish to consider in order to have this difficult (but necessary) conversation with them:
- Tap into their personal motives: Nobody likes to be criticized — especially high-status individuals. However, if you can help leaders understand how they can achieve their personal goals, they will pay attention. The most effective way of doing this is by tapping into the leader’s motives and values. For instance, leaders who are driven by recognition care a great deal about their reputation. Telling them that they are seen as less capable than they think they are will probably mobilize them, even if you allow for the possibility that their reputation is unwarranted. On the other hand, when leaders are driven by power, you will be able to appeal to them by linking the feedback to their performance and career progression: “If you change X and Y, you will be able to outperform your competitors and make it to the top”. In contrast, when dealing with altruistic leaders, your best strategy for delivering negative feedback is to convey that “by changing X and Y, you will be able to harness your team’s potential and improve their engagement and wellbeing”.
- Let the data do the talking: Leaders are not always interested in people, and they often regard psychological matters as fluffy. On the upside, they tend to care about results. A good way to help leaders understand that their self-views and behaviors matter is via 360-degree feedback (360s) and employee engagement In particular, there is ample evidence for the connection between 360s and leadership performance, as well as a leader’s integrity. The use of 360s also enhances coaching and development interventions by closing the “blind-spots” between leaders’ self-views and other people’s views on them. As for engagement, it is arguably the best source of data to evaluate leaders’ effectiveness — other than actual team performance data. For example, a meta-analysis of almost 8,000 business units and 36 organizations shows that increases in employee engagement are associated with better business-unit outcomes, including revenues and profits. Another data-driven approach to making leaders aware of their potential deficits is through scientifically valid personality assessments. When reports focus not just on the bright side, but also the dark side of personality, leaders will be able to understand what their “toxic assets” are. Indeed, dark side personality traits predict leader derailment even in the presence of outstanding technical skills and expertise. From Dominic Strauss-Kahn to Bernie Madoff, there is no shortage of famous case studies demonstrating that brilliant leaders can damage their own and others’ careers when they overuse certain strengths and are unable to tame their undesirable qualities.
- Highlight the downside of self-confidence: A final point to consider is that leaders who are interested in science may be easily persuaded of the virtues of modesty, as well as the adverse consequences of hubris. In other words, there is vast empirical evidence to convince leaders that excessive self-confidence is more problematic than they think. For example, economic studies suggest that overconfidence leads to poor financial decisions and an inability to attend to social cues that highlight one’s mistakes. Financial studies show that overconfidence drives Forbes 500 CEOs to “persistently fail to reduce their personal exposure to company-specific risk”. Business studies show that overconfident entrepreneurs are not just more likely to fail, but also die younger than their more insecure counterparts. By the same token, there is also compelling evidence for the benefits of (moderate) self-doubt. For instance, academic studies suggest that leaders who underrate their abilities tend to be more effective, and broad theories of motivation suggests that self-perceived deficits in competence are pivotal for improving one’s performance. Perhaps most famously, Jim Collins’ seminal analyses of effective executives suggested that the most outstanding leaders are not just relentless and driven, but also humble.
Sadly, these suggestions are not always easily applied. For example, leaders with poor 360s tend to dismiss the value of feedback, which makes them virtually uncoachable. This is one of the fundamental limitations of coaching: it often works with those who need it the least; but it works a lot less with those who need it the most. There are also too many sources of (fake) positive feedback at the disposal of leaders, no matter how talented they are. In that sense, the world of work is not so different from Facebook, though even Facebook has decided to allow users to leave negative feedback on other people’s posts. Ultimately, we need to get better at selecting leaders who are comfortable with their own insecurities and self-doubt. As the great Voltaire noted: “Doubt is not a pleasant condition, but certainty is absurd.”
Every serious technology company now has an Artificial Intelligence team in place. These companies are investing millions into intelligent systems for situation assessment, prediction analysis, learning-based recognition systems, conversational interfaces, and recommendation engines. Companies such as Google, Facebook, and Amazon aren’t just employing AI, but have made it a central part of their core intellectual property.
As the market has matured, AI is beginning to move into enterprises that will use it but not develop it on their own. They see intelligent systems as solutions for sales, logistics, manufacturing, and business intelligence challenges. They hope AI can improve productivity, automate existing process, provide predictive analysis, and extract meaning from massive data sets. For them, AI is a competitive advantage, but not part of their core product. For these companies, investment in AI may help solve real business problems but will not become part of customer facing products. Pepsi, Wal-Mart and McDonalds might be interested in AI to help with marketing, logistics or even flipping burgers but that doesn’t mean that we should expect to see intelligent sodas, snow shovels, or Big Macs showing up anytime soon.Insight Center
- The Age of AI Sponsored by Accenture How it will impact business, industry, and society.
As with earlier technologies, we are now hearing advice about “AI strategies” and how companies should hire Chief AI Officers. In much the same way that the rise of Big Data led to the Data Scientist craze, the argument is that every organization now needs to hire a C-Level officer who will drive the company’s AI strategy.
I am here to ask you not to do this. Really, don’t do this.
It’s not that I doubt AI’s usefulness. I have spent my entire professional life working in the field. Far from being a skeptic, I am a rabid true believer.
However, I also believe that the effective deployment of AI in the enterprise requires a focus on achieving business goals. Rushing towards an “AI strategy” and hiring someone with technical skills in AI to lead the charge might seem in tune with the current trends, but it ignores the reality that innovation initiatives only succeed when there is a solid understanding of actual business problems and goals. For AI to work in the enterprise, the goals of the enterprise must be the driving force.
This is not what you’ll get if you hire a Chief AI Officer. The very nature of the role aims at bringing the hammer of AI to the nails of whatever problems are lying around. This well-educated, well-paid, and highly motivated individual will comb your organization looking for places to apply AI technologies, effectively making the goal to use AI rather than to solve real problems.
This is not to say that you don’t need people who understand AI technologies. Of course you do. But understanding the technologies and understanding what they can do for your enterprise strategically are completely different. And hiring a Chief of AI is no substitute for effective communication between the people in your organization with technical chops and those with strategic savvy.
One alternative to hiring a Chief AI Officer is start with the problems. Move consideration of AI solutions into the hands of the people who are addressing the problems directly. If these people are equipped with a framework for thinking about when AI solutions might be applicable, they can suggest where those solutions are actually applicable. Fortunately, the framework for this flows directly from the nature of the technologies themselves. We have already seen where AI works and where its application might be premature.
The question comes down to data and the task.
For example, highly structured data found in conventional databases with well-understood schemata tend to support traditional, highly analytical machine learning approaches. If you have 10 years of transactional data, then you should use machine learning to find correlations between customer demographics and products.
In cases where you have high volume, low feature data sets (such as images or audio), deep learning technologies are most applicable. So a deep learning approach that uses equipment sounds to anticipate failures on your factory floor might make sense.
If all you have is text, the technologies of data extraction, sentiment analysis and Watson-like approaches to evidence-based reasoning will be useful. Automating intelligent advice based on HR best practice manuals could fit into this model.
And if you have data that is used to support reporting on the status or performance of your business, then natural language generation is the best option. It makes no sense to have an analyst’s valuable time dedicated to analyzing and summarizing all your sales data when you can have perfectly readable English language reports automatically generated by a machine and delivered by email.
If decision-makers throughout your organization understand this, they can look at the business problems they have and the data they’re collecting and recognize the types of cognitive technologies that might be most applicable.
The point here is simple. AI isn’t magic. Specific technologies provide specific functions and have specific data requirements. Understanding them does not require that you hire a wizard or unicorn to deal with them. It does not require a Chief of AI. It requires teams that know how to communicate the reality of business problems with those who understand the details of technical solutions.
The AI technologies of today are astoundingly powerful. As they enter the enterprise, they will change everything. If we focus on applying them to solve real, pervasive problems, we will build a new kind of man-machine partnership that empowers us all to work at the top of our game and realize our greatest potential.
As academic physicians, we do a lot of mentoring. Over the course of our careers, and through our formal research on mentoring within and outside of academia, we’ve found that good mentoring is discipline-agnostic. Whether you’re a mentor to a medical resident or marketing manager, the same principles apply. The best mentorships are more like the relationship between a parent and adult child than between a boss and employee. They’re characterized by mutual respect, trust, shared values, and good communication, and they find their apotheosis in the mentee’s transition to mentor. We’ve also seen that dysfunctional mentorships share common characteristics across disciplines — the dark side of mentoring, which we’ll get into later.
Given how important mentoring is, there’s surprisingly limited guidance about how to become a good mentor. This is perhaps even more the case in the world of management outside of academic medicine — whether it is finance, consulting, or technology — as the path from professional to senior executive requires more than individual success. We offer here an informal set of guidelines for good mentorship — a playbook, if you will, for a game that is very much a team sport. While we draw many of our examples from academic medicine, the lessons are pertinent across disciplines.Choose Mentees Carefully
Effective mentorship takes time. Mentors trade away hours they could use to pursue their own career goals and spend them on someone else’s. Although the prospect of having an energetic, personable junior partner for a multitude of projects is appealing, having the wrong mentee can be painful.
Beware the diffident candidate who expects the mentor to keep the relationship going, or the candidate who insists on doing things their way. A mentee should be curious, organized, efficient, responsible, and engaged. One way to look for these traits is to test prospective mentees. For instance, we often ask mentees to read a book and return within a month to discuss it. Similarly, we sometimes give a candidate a few weeks to write a review of an article in a relevant area. In a business setting, you might ask a prospective mentee to prepare a presentation in their area of expertise, or join you on a sales call or at a strategy offsite and write up their observations. This gives you a good sense of their thinking process, communication skill, and level of interest. If they don’t come back or complete the assignment, you should breathe a sigh of relief — you have avoided taking on a mentee who lacked commitment.
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Consider the case of a partner in a major consulting firm who told us of how he struggled with his first mentoring relationship. A young gun (let’s call him Sam) wanted to join the partner’s team, which was helping a client with a difficult human resources problem. Sam appeared keen, ambitious, and enthusiastic. He emailed constantly, asking about the position and reiterating how much he wanted to join this team. “He reminded me of a younger version of myself, and I thought I could groom him to be a superstar,” the partner recalled. Unfortunately, Sam proved to be a disaster. He showed up late to meetings, never turned in reports on time, and didn’t get along well with the offsite team. When the client finally complained, the partner had no choice but to take Sam off the project. Rather than being apologetic, Sam criticized the manager for cutting him loose. “I realized I had made a huge mistake, but only too late,” the partner told us. Sam could certainly talk the talk, but he didn’t have the commitment, organization, or motivation necessary to succeed.Establish a Mentorship Team
The exclusive, one-on-one relationship of mentor and mentee, long the norm, was ideal for a time when both parties stayed put in one institution or devoted to a single mission. That time has passed. Professionals in business and academia are highly itinerant, moving from one project or institution to another. Moreover, faculty and managers alike are under constant and growing time pressure. As a result, most mentors today share responsibility with others for the growth of a mentee. It makes sense: Few senior-level people have the time or range of expertise to serve as a solo mentor. Having a handful of co-mentors also gives mentees a fallback position if the relationship with their primary mentor fizzles.
Mentees should work with mentors to create a mentorship team, with members selected for their various areas of knowledge, such as subject matter expertise or career advice. The individuals chosen need to work well together and with the mentee. The primary mentor should function as the go-to person, providing mentees with moral, career, and institutional support, ranging from choosing a project focus, to helping build a network, to strategizing for success.
The concept of mentorship teams has slowly started to spread through management. A recent HBR article (“Your Career Needs Many Mentors, Not Just One,”) advanced the concept of mastermind groups, or a personal board of directors, a clear allusion to mentorship teams. Inherent in each of these brain trusts is the notion that the myriad skills and knowledge needed in business are difficult to acquire from a single individual. Indeed, firms such as Credit Suisse now employ a multiperson mentorship strategy when assigning new analysts to projects. An analyst needs much more support than a single staffer can provide, and will only grow more fluent in a firm’s culture and language through guidance from key figures across the organization. A young analyst we spoke with, who is soon to become an associate, described their experience in this way: “What I learned in onboarding was only 40% of what I needed to be successful. By having several key people, from staffers to VPs, assigned to me early in my career, I was able to gain the other 60% quickly.”Run a Tight Ship
The mentor role needn’t take an excessive amount of time. Establishing firm and clear ground rules with mentees can improve efficiency.
To begin, clarify what your mentee expects from the relationship, match it against your expectations, and reach consensus. You may have misapprehension as to the mentee’s long-term goals, while the mentee may have an exaggerated notion as to what services you will provide. Such misunderstandings are costly, in terms of time and tranquility. These differences should be resolved explicitly and early in every mentoring relationship. In our experience, the most successful relationships are ones where the mentee fully understands and shares their mentor’s vision for success.
Establish a cadence for communication. Most mentors want to keep up with major developments in their mentees’ work, but dislike unscheduled phone calls or a flood of emails for minor issues. We avoid this by telling mentees we will meet in person monthly to discuss issues in depth. If an unexpected or time-sensitive issue arises outside of this meeting, we expect an email or call that is on-point, with questions framed to facilitate “yes” or “no” answers. For this to work, the mentor and mentee have to be disciplined about keeping their scheduled meetings. For example, we know of a junior associate in an international banking firm who described communicating with his VP every two weeks, regardless of where in the world they were. “I remember once being in Geneva while he was in China. We were both working on different projects,” the associate told us. “But because we had that time slotted on our calendars, I made it a point to reach out to him to see if he still wanted to speak. I shouldn’t have worried. As I was writing my email, an invitation from him popped up for a phone call.”
Finally, make it clear that accountability isn’t optional. Effective mentors educate mentees about the standards of the profession — and ensure they live up to them. If a mentee produces second-rate or tardy work, both the mentee’s and mentor’s reputations suffer. Deadlines must be honored, commitments to projects kept, and appointment times adhered to. Mentees must respect mentors’ time. Essential mentee behaviors include setting up an agenda ahead of meetings and assuring that mentors have adequate time in advance to review any related materials. (In academia, that would include giving mentors a week or two to look at a draft of a manuscript or grant proposal.)
Part of assuring accountability involves making sure that mentees understand that they are, in effect, your student. They should expect and welcome constructive criticism. Mentees must also understand that repeating the same mistakes is unacceptable and that a single egregious error, such as data fabrication or plagiarizing, may end the relationship — or worse.Head Off Rifts…or Resolve Them
It’s not uncommon for mentors and mentees to have a falling out. What seemed like a perfect pairing on the surface may wind up being a total mismatch. Sometimes this becomes obvious suddenly. For example, an associate in a consulting firm told us of their decision to not take an overseas assignment because of family issues. Rather than receiving support from their mentor (who was also their boss), they got an angry call the next day. As the mentee told us, “He thought my giving up this opportunity was a huge mistake — that this was how he got his break, and that I was being dumb for putting family first. I certainly did not see it that way, and was shocked that he felt so strongly about it.”
At other times, either the mentor or the mentee may be completely unaware that there is a rift. For example, we know of a mentee who was having academic difficulties and told their mentor they were thinking about quitting. The mentor responded with advice on how to get a leave of absence. The mentee was despondent, but hid it: They had actually hoped for additional resources to ease their workload, but was uncomfortable about directly asking for it.
In some cases, there’s nothing to be done. Usually, though, it’s possible to avoid or repair problems. Mentors must recognize that disagreements and misunderstandings are almost inevitable in these relationships and that the mentor, not the mentee, is responsible for avoiding or repairing rifts. Smart mentors do not allow sores to fester or spats to escalate. They intervene early to keep the relationship on track. For instance, in the second example above, the mentor could have created an open, cards-on-the-table relationship that would have encouraged the mentee to be more honest about their needs, or at least inquired about the underlying issues behind the mentee’s challenges before suggesting a leave of absence.Don’t Commit Mentorship Malpractice
Because mentors are in the dominant position in the relationship, it’s easy for them to wield their power inappropriately – even if they’re not fully aware of it. Such “mentorship malpractice,” as we called it, has negative career consequences for both parties. Next time you look in the mirror, professionally speaking, ask yourself whether you’re guilty of any of these behaviors – and if you are, stop them immediately:
- Taking credit for your mentees’ ideas or usurping lead position on their projects
- Insisting that your mentees advance your projects rather than allowing them to develop their own work
- Handcuffing your mentee to your timeline, slowing their own progress when you are slow to get back to them
- Discouraging your mentees from seeking other mentors, which may stoke your ego but isolate them from broader learning and recognition
- Allowing mentees to repeat common self-destructive mistakes — what we call “mentee missteps” — without reining in such behavior
A mentor’s accumulated wisdom and expertise must be passed on to the next generation. Good mentors make this process conscious, discussing challenges and satisfactions of mentorship with mentees. While the actual moment of transition from mentee to mentor varies according to circumstances, the mentor must feel that the mentee has achieved real expertise and has a coping, generous personality to make this leap. Often, some event within the mentor’s area — a retirement, a new grant, or a major project — creates the need for a new mentor to join the ranks.
Here’s how a colleague described her experience:
“When we took on another fellow, my mentor was swamped. He asked me if I was ready to be the new fellow’s primary mentor. I knew how my mentor went about mentoring me, felt ready, and agreed to do it.” As it turned out, her mentor had her back. “I shouldn’t have worried. He immediately suggested to serve as a co-mentor, ensuring I was comfortable in the role while guiding and grooming our fellow. As co-mentor, he gave me feedback about how best to run meetings with my mentor, provide advice on work-life balance, ensure discipline, and identify growth opportunities. He showed me just how much joy mentoring can bring.” This, perhaps, is the most valuable lesson of them all.
Many companies’ all-white, all-male executive teams make it quite clear how well corporate diversity efforts aimed at women and racial minorities are faring. Harder to discern is how firms are doing on the inclusion of lesbian, gay, bisexual, and transgender individuals. LGBT employees do not necessarily make their sexual orientation known in the workplace, and thus are sometimes considered an “invisible” minority.
In the U.S. and Europe, approximately 20% of LGB employees experience discrimination at work. Transgender employees typically report higher rates of discrimination, perhaps because they are more visibly gender nonconforming. In a 2014 study by an advocacy group, a majority of LGBT employees reported that they had overheard jokes about gay or lesbian people, and one-third said they felt compelled to lie about their personal life in the workplace.
To better understand the causes and consequences of homophobia in the workplace, we conducted a study of gay and lesbian auditors in the Big Five audit firms in France. The challenge of tackling LGBT inclusion is particularly crucial in professional service firms, in which work interactions are key to the functioning of the organization. We chose to focus on audit firms for two reasons. One is what sociologists call the predominance of men: The Big Five firms in France employ roughly 50% women overall, but this proportion shrinks to 20% at the partner level. The second is that there are clearly agreed-upon norms about what auditing entails: ensuring a firm’s activity follows accounting rules and is meeting social and financial expectations. This focus on norms influences the perception of behaviors and gender within the firm. In other words, auditors are expected to follow norms themselves as they ensure that norms are followed by the firms they audit.
We conducted in-depth interviews with 18 gay and lesbian auditors, and followed up with them over the course of two years. Our data was collected at a time when the French government was passing a gay marriage law that had polarized public opinion and triggered months of protests. Our study unveiled subtle forms of homophobia and the identity struggles experienced by gay and lesbian auditors.How Homophobia Can Be Commonplace at Work
The good news is that our study revealed no obvious discrimination against the 18 gay and lesbian employees. The bad news is that almost all of them reported hearing a number of comments or jokes aimed at sexual minorities in the work context. Previous psychology research has shown that in comparison to workers who are not out, employees who are open about their sexuality tend to experience higher job satisfaction and better relationships with their managers. Most of the auditors we studied kept their sexual identity hidden from their coworkers. They felt that doing so could prevent them from suffering overt discrimination, but could also allow their colleagues to assume that using homophobic slurs is “harmless.”
Our subjects were reluctant to reveal their sexual identity for fear of being judged. Auditors are regularly rated by their peers and managers, so being harshly judged by colleagues could have negative career consequences. Beyond the prospect of being the subject of overt discrimination, LGBT employees were afraid of losing control of information about their sexual identity, by being talked about by colleagues, for example, or being the object of office rumors.
To hide their sexuality, gay and lesbian auditors lied constantly about their personal life while at work. Since they worked long hours, they spent a significant share of their time concealing part of their identity and feeling insecure during personal discussions. Something as mundane as a discussion about dinner plans for Valentine’s Day can be difficult for employees who are not out. Should they tell the truth? Should they lie by omission? Or should they plainly and simply lie about it? Each option is risky. More generally, gay and lesbian auditors reported a constant social discomfort, as they needed to repeatedly decide whether to disclose or to conceal their sexual identity, and in the latter case, decide how to conceal it.Why the Rhetoric of Corporate Performance Can Be Damaging
We observed that the rhetoric of performance in the workplace is consistently associated with virility and heteronormative masculine values. This has been noted by researchers in a variety of professional service firms, such as investment banking, consulting, and auditing. Because homosexuality is prejudicially thought to diverge from those values, it is considered at odds with performance. Several of our respondents reported their discomfort when they heard their manager or colleagues shout “This is not some faggot’s audit!” (“C’est pas un audit de PD!”) as a way to signal the importance and significance of the mission and to encourage strength and combativeness among team members.
Because of this association between performance and virility, some employees engaged in extreme demonstrations of their masculinity when they felt it was threatened, and to reassert their commitment to achievement at work. For example, they made overtly sexist comments, demeaning the behavior of other male colleagues as “effeminate.”Making Professional Service Firms More Welcoming to LGBT Staff
To fix the problem of workplace homophobia, managers should be on the lookout for toxic performance rhetoric, and they should certainly stop using such rhetoric themselves.
Mentoring, while an imperfect solution to diversity issues, can play a role. We observed that in the global firms’ UK offices, just on the other side of the Channel, there were more active networks for mentoring LGBT employees. The challenge for such schemes is to actually find LGBT employees who are out at the most senior level to act as mentors.
Mentors can help junior employees navigate the implications of disclosing or concealing their identity and help them obtain organizational support. For example, one of our respondents who was being sent abroad for a work assignment explained how the firm supported his partner in his job search. Being part of a network of employees based on this invisible attribute is also a way to reveal one’s sexual identity in a dispassionate way.
Much remains to be done for professional service firms to address the challenges of invisible minorities. Rethinking those firms’ culture should be first on the agenda.
Six months ago, at your request, your boss agreed to put your name forward for a new position that works directly with the CEO. Weeks went by, and you heard nothing. Then someone else got the job. When you asked your boss about it, he gave a long, confusing explanation for why the CEO considered you a strong candidate but “had to go another way.”
Last week, you bumped into the CEO in the hall. She pulled you aside and asked why you never raised your hand for the new job, confessing that she wasn’t very happy with the person in the role. As she was talking, you knew one thing for certain: Your boss lied to you. What now?
There are two ways to handle deceit from above: reactively or proactively. If you are in reactive mode, stay calm and be constructive. Breaks in trust are infuriating and hurtful, but they don’t entitle you to flame out, throw a fit, or stomp around rolling your eyes. Try to keep the steam from coming out of your ears.Reactive Actions
Do a cost/benefit analysis. Once you spot deceit, you have to choose between the lesser of two evils. If you confront your boss, you may poison the relationship forever. The same may be true if you go to someone else in the firm, such as HR or your boss’s boss. Think before you act, gossip, or complain. Have a hard conversation with yourself. Do you want to keep your job? Confrontation or sounding an alarm is not a good way to do that. But if changing jobs is not out of the question, it may make sense to directly address the deceit.
Turn the situation around. Before you engage in a hard conversation, try to understand the motivations your boss may have had. Is he trying to be discreet about a pending merger (which is morally understandable), or is he trying to hide a series of illegal kickbacks (morally repugnant)? Perhaps what feels like deceit to you is actually an attempt by your boss to protect you. Never confront your boss alone if you suspect laws have been broken; always consult an attorney first.Further Reading
Have the hard conversation. Never corner or ambush your superior. If you choose to clear the air, provide a face-saving escape. Avoid labeling the deceit as such, and do not be accusatory. Put on your curiosity hat — remember, you might learn something. Use language such as “I might be seeing this the wrong way” or “I understand that there may have been circumstances that prevented you from sharing all the details with me.” Ask for an explanation of recent events that gave you the impression that you were not receiving an accurate portrayal of what’s been happening. To go back to the opening example, after the CEO pulled you aside, you might choose to relate that conversation to your boss and inform him that you avoided any discussion of previous opportunities — but also expressed enthusiasm about the chance to help her out in the future.Proactive Actions
Be explicit about your moral code. Dan Ariely, best-selling author and Duke University professor, conducted research in which college students were asked to solve math problems and grade their own results. There was a bit of cheating. In later rounds of the experiment, the researchers asked students to recall the Ten Commandments before engaging in the exercise. There was no cheating in those rounds. “This result was very intriguing,” observes Ariely. “It seemed that merely trying to recall moral standards was enough to improve moral behavior.”
Similarly, Sreedhari Desai, of the University of North Carolina’s Kenan-Flagler Business School, found in her research that displaying a virtuous quote can “reduce the chances that you’ll be asked to do bad things.” So consider taking this simple step. Add a moral quote, such as “Success without honor is worse than fraud,” to your email signature line or in a framed print on your desk. The more you talk about, and live by, your principles, the harder it will be for others to treat you in a morally ambiguous manner.
Build strong relationships. If you have good relationships with your colleagues and become known as someone who sweats the details and always follows up, it will be harder to sustain a falsehood in front of you.
Pay attention. Carefully read memos and presentations that your boss and others circulate, and ask yourself if they fit logically with the messages your boss is giving you. By paying attention, you will be able to spot deceit earlier. If you begin to suspect deceit, document it. Write down specific examples, save copies of documents, and see whether your gut instincts hold up when listed in black and white. But don’t show anyone…yet.
There is a downside to this strategy: If you push it too hard, or run around all day long with a “gotcha notebook,” you may become known as a person who can be incredibly tiresome to work with. But there’s plenty of room in the middle. Situational awareness is a skill that takes practice, looking, and listening. Focus on the benefits of developing the skill, not on your boss’s wrongdoings.
If, after taking these steps, you find your boss lying to you again, it may be time to move on. A friend of mine once realized that her boss was highly supportive to her face but actively critical of her in private. In short, he was her enemy, and he was lying about it. It didn’t take her long to decide that there was no upside for her in confronting, or accusing, her boss, so she quietly and methodically made a plan to leave the company, and ended up with a much bigger job at a competitor nine months later. While it can feel unfair to have to make a career decision because of a morally deficient boss, doing so can sometimes lead you in the right direction, if a bit faster than you otherwise would have preferred.
It doesn’t take a tremendous amount of training to begin a job as a cashier at McDonald’s. Even on their first day, most new cashiers are good enough. And they improve as they serve more customers. Although a new cashier may be slower and make more mistakes than their experienced peers, society generally accepts that they will learn from experience.
We don’t often think of it, but the same is true of commercial airline pilots. We take comfort that airline transport pilot certification is regulated by the U.S. Department of Transportation’s Federal Aviation Administration and requires minimum experience of 1,500 hours of flight time, 500 hours of cross-country flight time, 100 hours of night flight time, and 75 hours of instrument operations time. But we also know that pilots continue to improve from on-the-job experience.
On January 15, 2009, when US Airways Flight 1549 was struck by a flock of Canada geese, shutting down all engine power, Captain Chelsey “Sully” Sullenberger miraculously landed his plane in the Hudson River, saving the lives of all 155 passengers. Most reporters attributed his performance to experience. He had recorded 19,663 total flight hours, including 4,765 flying an A320. Sully himself reflected: “One way of looking at this might be that for 42 years, I’ve been making small, regular deposits in this bank of experience, education, and training. And on January 15, the balance was sufficient so that I could make a very large withdrawal.” Sully, and all his passengers, benefited from the thousands of people he’d flown before.Insight Center
- The Age of AI Sponsored by Accenture How it will impact business, industry, and society.
The difference between cashiers and pilots in what constitutes “good enough” is based on tolerance for error. Obviously, our tolerance is much lower for pilots. This is reflected in the amount of in-house training we require them to accumulate prior to serving their first customers, even though they continue to learn from on-the-job experience. We have different definitions for good enough when it comes to how much training humans require in different jobs.
The same is true of machines that learn.
Artificial intelligence (AI) applications are based on generating predictions. Unlike traditionally programmed computer algorithms, designed to take data and follow a specified path to produce an outcome, machine learning, the most common approach to AI these days, involves algorithms evolving through various learning processes. A machine is given data, including outcomes, it finds associations, and then, based on those associations, it takes new data it has never seen before and predicts an outcome.
This means that intelligent machines need to be trained, just as pilots and cashiers do. Companies design systems to train new employees until they are good enough and then deploy them into service, knowing that they will improve as they learn from experience doing their job. While this seems obvious, determining what constitutes good enough is an important decision. In the case of machine intelligence, it can be a major strategic decision regarding timing: when to shift from in-house training to on-the-job learning.
There is no ready-made answer as to what constitutes “good enough” for machine intelligence. Instead, there are trade-offs. Success with machine intelligence will require taking these trade-offs seriously and approaching them strategically.
The first question firms must ask is what tolerance they and their customers have for error. We have high tolerance for error with some intelligent machines and a low tolerance for others. For example, Google’s Inbox application reads your email, uses AI to predict how you will want to respond, and generates three short responses for the user to choose from. Many users report enjoying using the application even when it has a 70% failure rate (i.e., the AI-generated response is only useful 30% of the time). The reason for this high tolerance for error is that the benefit of reduced composing and typing outweighs the cost of wasted screen real estate when the predicted short response is wrong.
In contrast, we have low tolerance for error in the realm of autonomous driving. The first generation of autonomous vehicles, largely pioneered by Google, was trained using specialist human drivers who took a limited set of vehicles and drove them hundreds of thousands of kilometers. It was like a parent taking a teenager on supervised driving experiences before letting them drive on their own.
The human specialist drivers provide a safe training environment, but are also extremely limited. The machine only learns about a small number of situations. It may take many millions of miles in varying environments and situations before someone has learned how to deal with the rare incidents that are more likely to lead to accidents. For autonomous vehicles, real roads are nasty and unforgiving precisely because nasty or unforgiving human-caused situations can occur on them.
The second question to ask, then, is how important it is to capture user data in the wild. Understanding that training might take a prohibitively long time, Tesla rolled out autonomous vehicle capabilities to all its recent models. These capabilities included a set of sensors that collect environmental data as well as driving data that is uploaded to Tesla’s machine learning servers. In a very short period of time, Tesla can obtain training data just by observing how the drivers of its cars drive. The more Tesla vehicles there are on the roads, the more Tesla’s machines can learn.
However, in addition to passively collecting data as humans drive their Teslas, the company needs autonomous driving data to understand how its autonomous systems are operating. For that, it needs to have cars drive autonomously so that it can assess performance, but also assess when a human driver, required to be there and paying attention, chooses to intervene. Tesla’s ultimate goal is not to produce a copilot, or a teenager who drives under supervision, but a fully autonomous vehicle. That requires getting to the point where real people feel comfortable in a self-driving car.
Herein lies a tricky trade-off. In order to get better, Tesla needs its machines to learn in real situations. But putting its current cars in real situations means giving customers a relatively “young and inexperienced” driver — although perhaps as good as or better than many young human drivers. Still, this is far riskier than beta testing, for example, whether Siri or Alexa understood what you said, or whether Google Inbox correctly predicts your response to an email. In the case of Siri, Alexa, or Google Inbox, it means a lower-quality user experience. In the case of autonomous vehicles, it means putting lives at risk.
As Backchannel documented in a recent article, that experience can be scary. Cars can exit freeways without notice, or put on the brakes when mistaking an underpass for an obstruction. Nervous drivers may opt not to use the autonomous features, and, in the process, may hinder Tesla’s ability to learn. Furthermore, even if the company can persuade some people to become beta testers, are those the people it wants? After all, a beta tester for autonomous driving may be someone with a taste for more risk than the average driver. In that case, who is the company training their machines to be like?
Machines learn faster with more data, and more data is generated when machines are deployed in the wild. However, bad things can happen in the wild and harm the company brand. Putting products in the wild earlier accelerates learning but risks harming the brand (and perhaps the customer!); putting products in the wild later slows learning but allows for more time to improve the product in-house and protect the brand (and, again, perhaps the customer).
For some products, like Google Inbox, the answer to the trade-off seems clear because the cost of poor performance is low and the benefits from learning from customer usage are high. It makes sense to deploy this type of product in the wild early. For other products, like cars, the answer is less clear. As more companies seek to take advantage of machine learning, this is a trade-off more and more will have to make.
We live in a digital economy: a virtual environment that has changed the rules of doing business and made disruption the norm. It has put customers, not companies, in charge. And it has transformed workforce dynamics as the “born digital” millennials come to prominence in the workplace.
This age is ripe with opportunity. Organizations can now engage with customers and employees like never before, and the virtual environment holds the potential to drive operational efficiencies, save time and money, and open the exploration of new commercial avenues. When it’s far cheaper to build an app than a manufacturing plant, there are greater returns to be gained for significantly lower investment. Gartner predicts 41 percent of enterprise revenue will come from digital business by 2020—almost double what the percentage was in 2015 (Gartner, 2016). For the Googles, Ubers, and Facebooks of the world, facing these challenges and realizing and exploiting these opportunities are second nature. But for traditional firms, they’re a whole new world.Read more from Korn Ferry:
- How to Develop Leaders Who Can Drive Strategic Change
- Preparing for the Future of Talent Acquisition
To understand what digital leaders do differently, Korn Ferry not only drew on broad research into business change but also interviewed leaders who are driving transformation at some of the world’s most successful organizations. This revealed five essential leadership and organizational capabilities: discipline and focus, agility, connectivity, openness and transparency, and empowerment and alignment.
Discipline and Focus
Organizations that successfully transform with the digital world have a clear vision of what digital means to them. They define their desired outcomes, and they focus relentlessly on achieving them. Such organizations do so by prioritizing the things that drive the most value—customers and talent, data, and products—and then they are disciplined in their execution. They decide quickly what to invest in, and then draw on their strengths to make these investments efficiently, effectively, repeatedly, and at scale.
Digitally sustainable organizations are agile: They think fast, decide fast, execute fast, fail fast, learn fast, and scale fast. Agile businesses run planning and execution in parallel, investing in scenario planning so they can act promptly when opportunities arise. They are also prepared to take risks. They create solutions based on what they already know and evolve them as customer feedback comes in. This means streamlining reporting lines, engaging a wider group of stakeholders from the outset, sharing ideas and plans before they’re fully formulated, and seeking input along the way. They launch several projects at once to see what works and what doesn’t, and then make rapid decisions about what to invest in and what to stop investing in.
Agile organizations are connected organizations. Connected businesses create ecosystems made up of networks of people, from both within and outside of the organization, who can drive change. These organizations are no longer concerned about defined roles, instead focusing on shared objectives and metrics to deliver on specific projects. Ideas and input come from all sides and segments and across all stakeholder groups. Everyone involved actively collaborates with the outside world, co-developing solutions with clients, partners, and sometimes even competitors.
Openness and Transparency
People must collaborate, solve problems, and think creatively to meet customer expectations in the digital economy. This means everybody has a voice. Open businesses understand that brands are now public property. Customers and employees can find out anything they want about any business—and pass judgment on it—at the click of a mouse or the touch of a screen. Open organizations thrive in this climate by being deliberately transparent about their ethics, responsibilities, decisions, and practices. They leverage their own IP whenever possible but are also happy finding and applying IP from outside sources when needed or when more cost-effective.
Empowerment and Alignment
In the digital economy, value is found in three assets: people (both customers and employees), data, and products. Successful organizations put power into the hands of the people closest to these assets: Marketing, HR, and customer operations have power over customers and talent; IT has power over data; and R&D has power over products. Organizations can empower all employees, from the board to the front line, by aligning them to the same three things: what the business stands for, what it’s trying to achieve, and how goals are being implemented. This enables people to make the right decisions in the moment, without the need for continuous guidance.
Graphic above based on Korn Ferry’s “Superior Performance Model (SPM).
Like the industrial revolution 250 years before it, the digital revolution has transformed the time we live in. It has taken us into a new age and changed the meaning of value.
In the industrial age, value came from machines. With the digital revolution, value comes from technology, data, and algorithms. But now and in the future, value will come from people (Jean-Marc Laouchez et al., November 2016). People bring the creativity and discipline needed to understand and use technology to bring about transformational change.
But for organizations to harness these qualities in their people, they need to inspire them to bring their all to the cause of digital sustainability. This means moving away from traditional power structures, toward open, transparent, and connected structures and organizational cultures that encourage innovation and experimentation.
That’s how to build a business that’s fit for the digital economy. That’s how to be truly digitally sustainable.
Adapted from Korn Ferry’s “Rebuilt to Last: The Journey to Digital Sustainability.” To learn more about driving digital sustainability UP, click here.
One of the many things managers worry about is employees breaking the rules. Evidence suggests that such behavior is widespread, and it can have devastating consequences. Companies have tried many different ways to limit unethical behavior, from creating codes of conduct to implementing ethical training. But these interventions are often criticized for being ineffective. This may be because they’re too direct.
We tend to think of unethical behavior as intentional, in that employees consciously choose to break rules. Sometimes this is true, but sometimes it is not. Research has shown that unethical behavior frequently arises unconsciously, from workers’ unchecked, automatic inclinations.
There are two ways we process information and make decisions: Type 1, our quick and automatic responses to a situation, and Type 2, our deliberative and reflective reasoning. Type 1 processes do not require much effort or working memory, which is why they are our “default” system for making decisions — unless we’re able to actively turn to Type 2 processes. Type 1 processes are also the ones that frequently (though not always) serve our egocentric or hedonic interests — such as, for example, the temptation to take money that is not justifiably earned — while Type 2 processes serve as a self-control function that can override such tendencies.
We wondered whether routine work influences an employee’s tendency to break the rules by activating more Type 1 processes. Does doing the same task over and over trigger automatic decision making and make employees more likely to behave unethically? And would activating Type 2 processes help reduce rule breaking? Our research, published in Organization Science, found that working on the same task may lead to more rule breaking, while switching back and forth between even a few tasks may lead to less.
Many jobs require individuals to do repetitive tasks, but the order is often flexible. For example, a radiologist might need to read three X-rays, three MRIs, and three ultrasounds. A data entry clerk might need to enter three insurance claim forms, three appeal forms, and three reimbursement requests. In each case, there are task A’s, task B’s, and task C’s. The employees could finish all the task A’s before moving on to B’s and C’s, so that there is less switching among tasks (e.g., AAABBBCCC). Or they could switch more frequently (ABCABCABC), having more “sequential variety.” We thought the latter might force employees to be more cognitively alert and deliberative, which could lead them to behave more ethically simply by avoiding automatic, self-interested decision making.
Our first study looked at data on employees who process mortgage applications in a Japanese bank. The work was designed so that employees were assigned to process one stage of an application at a time. Throughout the day, they might be assigned to work on the same stage across many applications or on different stages, depending on the system dynamics. We analyzed 17,161 observations, across 101 employees, from June 2007 to December 2009. As a measure of rule breaking, we looked at whether employees abided by the lunch policy and came back from their one-hour lunch break on time.
We examined the relationship between employees’ task variety (i.e., the number of different stages they worked on before lunch) and how much time they took for lunch. Controlling for different factors, such as workload, we found a negative relationship between the variety of stages completed before lunch and the propensity to take a longer lunch than allowed. When people worked on different tasks in the morning, they were less likely to return late from lunch than people who worked on the same tasks.
Because this doesn’t imply a causal relationship, we conducted three laboratory experiments. We enlisted 403 participants (202 online panel participants, representing the general population in the U.S., and 201 lab participants in the UK and the U.S., who were mostly students). We asked them to solve a series of math, verbal, and spatial problems. In all experiments, one group saw these problems organized by category (low variety); the other group saw the problems mixed together (high variety). In one of our studies, once participants finished these questions, we assessed their default mode for making decisions (Type 1 or Type 2) using a measure called the Cognitive Reflection Task (CRT). The CRT consists of three questions to test whether someone answers intuitively or deliberately.
We then gave participants a second set of questions — and an opportunity to cheat. Once the question appeared on the screen, the correct answer popped up as well, unless the participant pressed a certain key on their keyboard. They were told that this happened due to a glitch in the system, and that they should press the key to prevent the correct answer from appearing, otherwise we would not know whether they knew the correct answer. (In another experiment, participants could scroll down to see the correct answer, though they were explicitly told not to do so.) Participants were paid based on the number of correct answers they gave, so they had an incentive to look at the correct answer.
We found that participants in the high-variety group in Round 1 were less likely to cheat in Round 2 than those in the low-variety group. The CRT scores showed that the high-variety group used more-deliberative decision making, suggesting that seeing a variety of questions (as opposed to organized blocks of questions) activated a deliberative mindset that led to less rule breaking.
These results point to a relatively simple way to support rule compliance at work. Changing the order in which employees perform routine tasks may promote rule following more easily than changing people’s motivations.
However, our findings, and this advice, should be interpreted with caution. Our studies dealt with relatively simple tasks — we don’t know with certainty that the effects carry through to complex tasks. Other research has found that switching between tasks can hurt performance, at least in the short run, and that the greater cognitive load involved can make people feel depleted and therefore more prone to unethical behavior. It might be that, with complex tasks, the costs of switching outweigh the benefits of task variety. Future research should empirically explore these questions.
We advise managers to consider the context of their teams’ work. Designing employees’ work to incorporate more variety may be more effective for promoting ethical behavior when tasks are low to moderately complex, and when the transition from one to another is not overwhelmingly difficult. There might also be moments when the work environment is changing, and uncertainty is already high, that may make switching between tasks too costly. Managers should experiment with how they design tasks and be prepared to monitor the effects.
Picture this. You are the newly promoted vice president of business development at an oil company. Your first assignment is to land an oil field services contract abroad. The process is arduous, negotiations are tough, and you’re working against a tight deadline. When you submit a tender to the foreign government, they advise you that there is little likelihood of winning the contract unless you hire a consultant of their choosing. Now what?
This is just one example of pressures that unfortunately are all too common in business. Nobody wakes up in the morning and says, “I’m going to become a white-collar criminal today.” But when there’s money on the table, the wrong behavior can emerge. Consider Volkswagen cheating on its diesel emissions, Wells Fargo’s fraudulent accounts, and the bribery fiasco at GlaxoSmithKline (GSK).
The onus for ethical behavior falls first to the employee. But it’s also the responsibility of the company to cultivate a culture that shuns corner-cutting and prevents it from accumulating into major scandals, ones that damage the credibility of the business, endanger jobs, and threaten the entire enterprise.
So how do you know whether your company is positioned to help you — or hurt you — as you encounter gray-area decisions in your work? Here are five questions to ask:
Do your company’s incentives match its policies?
Most companies talk a good ethics game and even make their goals public. But it is the employee incentives that really matter. For example, compensation tied solely to landing a contract invites abuse of the system. Compensation should be tied to broad-based outcomes and include things such as customer satisfaction and product knowledge, in addition to success at closing deals. If there is a disconnect, that is a red flag.
Consider the case of GSK. Despite having solid internal anti-corruption rules in place, the pharmaceutical giant wound up facing criminal investigations for bribing doctors and foreign officials, eventually paying a $489 million fine. Partly to blame was GSK’s compensation policy for its sales representatives, which linked bonuses to individual sales performance.
At first glance, this policy looks reasonable. Yet it resulted in a corporate mentality focused on making the sale at any cost. With bonus checks riding on the number of GSK prescriptions written by doctors sales reps visited, it may have seemed all too easy to slip cash under the doctor’s table for a chance to boost sales volume. In the wake of the scandal, GSK changed its incentive policy to evaluate employees who work with customers on a wider variety of metrics, including technical knowledge, quality of service, and adherence to company values.
Do you feel like you change who you are when you’re at work?
It’s natural to put on a different front when you’re at work. You’re a professional in a professional setting. But if you feel like a substantially different person at work than at home, beware. A serious disconnect between your values and those of your company may lead you to justify business choices that harm shareholders, consumers, or other employees.
Take the culture that seems to have bred corner-cutting at Volkswagen. The tightly-controlled automotive company fostered a mentality where the lower ranks faced immense pressure to achieve the company’s business objectives. The CEO of Volkswagen from 1993 to 2002 was famous for his willingness to demote or fire employees who failed to meet expectations. His successor frequently berated poorly performing employees.
The punishing, pressure-cooker work environment meant that Volkswagen engineers were apparently loath to say no or admit failure to superiors. Many of these engineers may have been honest, upstanding citizens in their communities, but the pressure to succeed at work led them to game the system.
Who gets promoted?
Are people who cut corners rewarded with promotions at your company? Ethical behavior has to be led by example, and promoting people who ignore ethics when expedient for them tells everyone that the company wants results and it does not really care how they are obtained. A company could have a terrific ethics policy, but actions speak louder than words on paper. If those who are breaking the rules are rewarded, employees quickly learn that the rules are meant to be broken.
Wells Fargo, for example, discouraged sham-account fraud. In ethics workshops, employees were specifically warned not to create fake accounts and credit cards to boost sales numbers. But a recent class action suit alleges that Wells Fargo actively promoted people who stole customer identities, opened sham accounts, and pressured customers into purchasing unwanted or unnecessary accounts. An environment that rewards such conduct is a breeding ground for unprincipled behavior.
What’s the tone from upper management?
Do the C-suite executives emphasize a win-at-all-costs mentality? Do they talk more about maximizing profits and hitting quarterly numbers, or do they talk more about optimizing value for the long term? The right tone from the top helps set the right goals for the organization.
For example, at General Motors, the ignition switch problem stayed buried for a very long time — so long that lives were lost because of it. Some of the casualties could likely have been prevented, if not for the apparent fear of reporting bad news up the chain of command.
Toshiba’s recent accounting fiasco provides another lesson about tone at the top. Facing “too embarrassing” losses in the midst of the financial crisis, Toshiba’s then-president ordered his staff to “get it done like your life depends on it.” Here, “it” reportedly meant using fraudulent accounting tactics to sweep the company’s losses under the rug and generate artificial gains. These practices continued under executive leadership that stifled disagreement with superiors and, all told, led to $1.2 billion in inflated profits.
Does your company cover for employees in ethical lapses?
Accountability is important. Anyone who takes unethical shortcuts should be held responsible when their behavior is discovered. If a company stands behind employees who have behaved unethically, that’s an indication of a weak ethical stance.
Some employees at Siemens believed that they were acting for the good of the company when they offered bribes to win foreign contracts, but when the bribery was discovered they found out the hard way that those contracts were neither for the good of the company nor their careers. The company sought claims against those employees. That set the right signal about accountability.
Prosecutors will often give cooperation credit – and in some cases even decide not to prosecute the corporation – if the names of those involved in the illegal behavior are disclosed. Nonetheless, a company’s fear of reputational damage might lead it to conceal its employees’ unethical conduct. In the Walmart bribery scandal of 2002, for example, fear of reputational fallout allegedly led the company to prematurely shut down its investigation into bribes paid by its employees to government officials in Mexico. In this case, how the firm reacted to employees who acted unethically was a telling signal.
So what should you do if you answer these five questions and don’t think your company’s ethics are up to standard? First, ask yourself if you are in a position to drive change. Can you be a positive influence and help lead changes like aligning incentives, developing ethical goals, or making sure people who cheat the system are not rewarded with promotions or bonuses?
If the answers to those questions are no, and your circumstances allow it, take a job at a more ethical company. Building a career of positive productivity and learning is hard enough in a company that helps you along.
The water industry is using digital technologies and analytics to derive more value from its physical assets. The need for this sector to change and evolve could not be greater: The organizations that manage water supplies around the world are facing critical issues, and water scarcity is chief among them.
Because of changes in our lifestyles, including increased consumption of grain, meat, and cotton clothes, growth in water consumption per capita has doubled over the last century. And demand is increasing. According to a 2016 report from the UNEP-hosted International Resource Panel, water demand will outstrip supply by 40% by 2030. During the same period, according to the World Economic Forum, water infrastructure faces a huge $26 trillion funding shortfall. If not addressed, water scarcity will squeeze food and energy supply chains, and stall economic growth.
To help solve this problem, organizations are using digital technologies and data analytics to improve leak detection. According to the World Bank, the world loses about 25-35% of water due to leaks and bursts, and the annual value of this non-revenue water — water produced and lost by utilities — is $14 billion. Organizations are also using these tools to improve maintenance, infrastructure planning, water conservation, and customer service (including repair efficiencies and pricing).
Although members of the water industry have found success using digital technologies and analytics, they’ve also faced challenges when trying to transform the roles and mindsets of their employees and their internal- and customer-facing processes. But those that have managed to integrate their technological advances with two other key elements — people and processes — have created more than data; they’ve also created value for their enterprises and society.
People: Good leaders know that using and interpreting data is not only a search for insights; it’s also about enlisting the hearts and minds of the people who must act on those insights.
The challenge is that employees are used to doing things in a certain way, and aren’t always quick to change. For example, despite the social and efficiency value of using predictive analytics to prevent water leaks, many utility managers view themselves as heroes for responding after the leak has occurred. As one U.S. executive explains, “Most current practice is to wait for the service-failure event and judge performance by reacting to it, because the utility doesn’t get credit from regulators or the media for preventing leaks that the public doesn’t know about.”
Regulatory incentives often exacerbate this behavior. In many parts of the world, the increased operational and infrastructure costs are simply passed on to consumers. In other regions, however, (e.g. Australia, Israel, the U.K.), regulators steeply fine utilities for inefficiencies – and it’s no coincidence that a number of utilities in these countries have been leaders in adopting new digital tools.
But even with proper incentives, there are still challenges. For example, many U.S. utilities have installed smart meters — an investment that can easily surpass $60 million in cities with 150,000 water connections, or about 15% of average annual utility revenue and water rates. But after making this investment and charging consumers for it, there were false alerts about leaks, which caused expensive repairs and claims processing. The law of unintended consequences was also alive in operations: because of the initial problems, the field transmissions group distrusted the data — even after the IT problem was diagnosed and resolved – and therefore required additional training to assuage their doubts.
This is why it’s imperative to change roles, break down silos, and adopt new decision support systems when implementing new technologies. A water authority in Australia, which deployed a software solution for improving network efficiency, is a case in point. Its managerial team first formed a working group of personnel from business units across the organization — from retail and asset management to planning and maintenance crews. The group met weekly and by doing so they recognized that the software detected faulty incidents and provided a focal point to collect information (e.g., types of problems, magnitude, location, etc.) to make better decisions in other areas of the business. As a result, they created procedures that shortened the average repair cycle by 66%, saving millions annually.
Longer term, the information allowed the team to make more focused investments based on types and frequency of problems in each zone, and the ability to compare — and negotiate better terms with — vendors based on quality and performance.
Processes: As with other sectors, water utilities are going through a shift from treating users as connections who pay bills, to customers that have needs, habits, and strong opinions if things go wrong. And data analytics is enabling them to provide faster and more effective responses. “We can compare the efficiency in each of the six sectors making up our network and evaluate the response time it takes to identify potential damage, ensuring faster repair times,” an executive at one of Romania’s leading water utilities told us. “As well as smarter insights, the event management system ensures better managerial attention to continuous improvement in our operations and service to customers, and helps to prevent large-scale damage from hidden leaks.”
But in order to achieve those outcomes, the Romanian utility had to change its organizational processes and metrics. The utility had to re-define company metrics goals and create weekly and monthly processes for reviewing performance-against-goals. The software provided relevant data — e.g., the start time of a leak and when it was fixed, based on real-time information, not when reports were submitted. But it was new customer-facing processes such as setting repair-cycle targets and comparing performance-against-goal by region, which created a healthy sense of internal competition and led to more productive behaviors.
These issues aren’t unique to the water industry; they’re also relevant to companies in other industries that are using data and digital tools that are increasingly available.
For example, sales is the focus of potentially big improvements via new tools that can provide better lead generation, forecasting, and targeting. But in order to take full advantage of these tools, sales organizations will need to change their compensation incentives, internal processes, and the skill sets of their staffs, among other things.
More generally, while most current talk about big data seems to assume the replacement of physical assets by digital technologies, a larger and more impactful trend is the use of online tools to improve physical asset utilization in off-line businesses, as in the water industry. In that context, the role of data is not to make a manager sound analytical. Its role is to help make better decisions and drive value for the company. And you can’t do that only with technology or analytics, no matter how good they are.
Many leaders are now aware of the dangers of collaboration overload and collaboration-tool overload in the workplace. The evidence continues to mount that, for many organizations, the costs associated with meetings, emails, IMs and other forms of workforce collaboration now exceed the benefits.
But what can get lost in the eye-popping statistics around excess email and meetings is this: Collaboration overload is almost always a symptom of some deeper organizational pathology and rarely an ailment that can be treated effectively on its own. Attempts to liberate unproductive time by employing new tools (for example, Microsoft Teams, Slack, Box) or imposing new guidelines and meeting disciplines will prove fruitless unless steps are taken to deal with the underlying organizational illness. Companies that have successfully combatted the excesses of overload have done so by focusing on the root causes of unproductive collaboration—and not merely the symptoms—in devising the cure.
Meetings, emails, IMs and other workplace interactions don’t just happen; they are a by-product the company’s organization. They reflect attempts by managers and employees to get work done within the confines of prescribed structures, processes, and norms. In our experience, unhealthy collaboration most often stems from two underlying organizational maladies: organizational complexity and a “collaboration for collaboration’s sake” culture.Organizational complexity
As companies grow, they naturally add new dimensions to their organizations. A single-product enterprise, for example, might add new products, focus on new customer segments, or even enter new geographic markets. Each of these additions necessitates more interactions between stakeholders in order to make and execute critical decisions.
Complexity increases geometrically with the number of new functions, products, customers, geographies or other nodes added to an organization. Adding a new geography to an organization, for instance, will require that managers in this new territory coordinate with representatives from various functions, product teams, and customer support groups to get work done. In short order, the number of nodes involved in decision making and execution explodes, resulting in more meetings, more emails, more IMs and more hours devoted to collaboration. Calls for fewer meetings and emails—even from the very top—will do little to stem the tide of interactions brought about by organizational complexity.A “collaboration for collaboration’s sake” culture
On its face, more collaboration is a laudable goal. After all, two heads are almost always better than one. But left unchecked, calls for greater collaboration can lead to a culture of “collaboration for collaboration’s sake,” undermining productivity.
Take meetings, for instance. If meetings become the norm for how work gets done in an organization, an individual employee can do very little. If an individual employee is invited to a meeting—particularly by his or her boss—he or she has little choice but to attend or risk offense. Over time, meetings become a status symbol—that is, the more meetings to which an executive is invited, the more important he or she is assumed to be. Even worse, meetings can become a substitute for effective leadership communication. Rather than taking the time to share the specifics discussed in a meeting with subordinates who did not attend, some leaders opt to invite an army to every meeting. As bosses fail to cascade vital information following important meetings, employees come to believe that they need to attend every meeting or risk missing out. So, what starts out as a well-intentioned drive for inclusiveness turns into a downward spiral of more meetings and wasted time. No attack on collaboration overload can be effective unless it addresses cultural norms such as these head-on.Addressing the root causes
But it doesn’t have to be this way. Bain research, conducted with the support of the Economist Intelligence Unit, found that the most productive companies—namely, the top quartile in our study’s sample of 300 large corporations worldwide—lose 50% less time to unnecessary and ineffective collaboration than the rest. The best companies save more than half a day a week for all of their employees (vs. less productive counterparts) by reducing organizational drag – all those factors that slow the organization down. But they don’t drive workforce productivity by attacking the symptoms of collaboration overload. Instead, they take steps to address the underlying causes:
Simplify the operating model. A company’s operating model encompasses its structure, governance, accountabilities, and ways of working. It determines how many nodes need to be activated in order to make and execute critical decisions. A complex operating model produces too many nodes and collaboration overload; a built-for-purpose operating model significantly reduces unproductive collaboration, liberating organizational time.
When Brazilian investment firm 3G Capital acquired Anheuser-Busch in 2008 to form AB InBev, it dramatically reduced the number of executives involved in making key decisions. The firm removed several layers of management, flattening the organization. And it established new ways of working in which all senior executives at AB InBev work around a common conference table. Supply chain leaders are expected to interact with marketers, for example, to solve complex problems in real time rather than rely on armies of subordinates and hours of review meetings. By streamlining the operating model, AB InBev dramatically reduced the number of interactions required to get work done, reducing costs and accelerating decision making and execution.
Align the organization. Even when an organization’s structure is lean by most accounts, it can be misaligned. As a result, it may take more interactions than it should to get work done. In technology, for example, sales can be highly complex, involving generalist sales makers, product specialists, technicians and the like. If each of these groups is organized differently, then the number of interactions required to make a sale can balloon.
Dell Technologies is a case in point. When leadership examined the number of interactions required to make a typical sale at Dell, it found that 11 people were typically involved, representing generalist account executives (organized by industry vertical), product specialists (organized by product) and technicians (organized by product and geography). Two nearly identical sales to similar types of customers in the same region who are buying similar products could involve completely different teams of individuals, making it challenging for teams to grow accustomed to working together. By moving to a geographic structure for sales makers, product specialists, and technicians, Dell cut the number of interactions required to make a customer sale by half (on average) and increased the percentage of familiar teams, further bolstering sales productivity. The company accomplished all of this without sacrificing account coverage in any way.
Set a zero-based time budget. One discipline that we have seen work to reduce the number of unnecessary meetings is to create a fixed meeting time bank in which all new meetings are funded out of the current bank. To start, determine the total amount of time currently dedicated to meetings by level in your organization. Then place a ceiling on that total. Now, for every new meeting an executive requests to schedule, ask (or require) him or her to remove some other meeting of equivalent (or greater) time. At the very least, this approach will highlight the total time devoted to meetings in your company. Over time, it may enable your organization to lower the ceiling and liberate countless hours of unproductive time.
Require business cases for new initiatives. When a company makes a major capital investment, senior management nearly always demands some form of business case—that is, an explicit statement of the expected benefits from making the investment weighed against the costs. New initiatives often demand hours of senior leadership time and can involve hundreds of meeting hours each month for the organization. Yet time investments of this sort are rarely held to the same standard as those involving financial capital. As a result, initiative overload is a common complaint at most companies. Perhaps more insidious, initiative overload can be a leading factor contributing to collaboration overload. By requiring that concrete business cases be developed for all initiatives that demand the time of senior leadership, an organization can slow the growth of new initiatives and winnow the existing set of initiatives to those that demonstrate clear benefits in excess of their organizational cost.
Provide real-time feedback. In some instances, it is possible to modify an organization’s cultural norms by providing its leaders with real-time data on the load they are placing on their teams as a result of the emails they send and meetings they schedule. Microsoft Workplace Analytics and other applications now make it possible to provide executives with regular feedback on the (often unintended) costs of collaboration. Over time, executives can modify their own behavior in response to this feedback—for example, eliminating unnecessary meetings, reducing the number of attendees at meetings, shortening meetings, reducing the use of “reply all” in email. Such self-policing can save thousands of hours each year, reducing collaboration overload.
There is much to like—and dread—about collaboration in the workplace. We have all grown weary of the needless meetings, unnecessary emails and other unproductive interactions associated with collaboration at work. Excess collaboration saps energy and leaves employees with too little time to complete their work during the day, forcing too many workers to spend time playing catch-up after hours and on weekends. But it is possible to capitalize on the benefits of collaboration while reducing its ill effects. Doing so requires examining the whole organization—its structure, processes and cultural norms—and treating the root causes of collaboration overload and not merely finding new, inventive ways to manage the symptoms.
Each year major business media outlets rank CEOs based on their performance. The few who win awards and earn the highest ranking become superstar CEOs — they gain visibility and higher social recognition, and they may even earn higher compensation. Award-winning CEOs also tend to capitalize on their fame by assuming more board seats and writing books.
But for every happy award-winning CEO, there are many more CEOs who did not win. We wanted to know how these rankings affect CEOs who don’t get the top spot. If awards can influence the behaviors of CEOs who win, could they also influence the behaviors of their competitors who don’t?
We conducted a study to investigate this question. Looking at CEO awards granted by Business Week, Financial World Gold/Silver Awards, Forbes, Chief Executive, and Harvard Business Review, we identified over 200 superstar CEOs of S&P 1500 firms in the U.S. from 1996-2010. We considered a CEO to be a “superstar” if he or she won an award or was included in a ranking of top CEOs. We then identified their competitors among S&P 1500 firms – these are CEOs of firms that are similar in size and have similar product offerings as the superstar’s firm. The average number of competitor firms for each superstar CEO firm was 24, and there were 1,450 competitor CEOs in our sample.
We hypothesized that competitor CEOs’ firms would undertake more and/or larger acquisitions in the four years after a peer had won a CEO award (i.e., post-award period), compared to the four years before (i.e., pre-award period). We believed that when CEO gained high social recognition and visibility from an award, it would motivate their competitors to look for ways to enhance their own social recognition and visibility in the short term. Since acquisitions are heavily covered by mass media, undertaking more or larger acquisitions can bring social recognition and visibility to CEOs.
Acquisitions also enable a firm to grow much faster than it would organically. Corporate growth can enhance top executives’ social status, and larger firms tend to pay their CEOs more than smaller firms. So acquisitions can help competitor CEOs bolster their social recognition and visibility, as well as their compensation.
We found that competitor CEOs’ firms conducted 22% more acquisitions in the post-award period than in the pre-award period. This suggests that if a competitor CEO firm made five acquisitions in the pre-award period, such a firm would undertake six acquisitions in the post-award period. Moreover, we found that if a firm spent $100 million on acquisitions in the pre-award period, it would increase its acquisition spend to $256 million in the post-award period.
We also investigated how different CEOs responded to missing out on awards. We created a model to estimate each CEO’s chance of winning an award, based upon firm characteristics (such as firm size, accounting performance, stock performance, advertising intensity), CEO characteristics (such as gender, age, and tenure), and the number of acquisitions conducted in the prior two years. Not surprisingly, we found that “runner up” CEOs – or those who would seem more likely to win but didn’t – were associated with the biggest increases in the number and value of acquisitions conducted in the post-award period. This suggests that “runner up” competitor CEOs may feel worse about losing out on an award than other competitor CEOs.
If competitor CEOs use acquisitions to make up for their loss, as our data suggests, then what can we expect for the quality of those acquisitions? We found that acquisitions conducted by CEOs after losing awards had a more detrimental effect on firm accounting performance than those conducted in the pre-award period. Specifically, acquisitions conducted by competitor CEO firms in the post-award period negatively influenced return on assets more than those conducted by the same firms in the pre-award period. In addition, acquisitions conducted in the post-award period were received more negatively by stock market. This suggests that these acquisitions were rushed through without sufficient due diligence.
Our findings have three important practical implications. First, as shareholders and board directors assess whether an acquisition is a good or bad move, they need to investigate the CEO’s motivation behind it. In particular, they need to pay attention to the timing of when a CEO is proposing an acquisition deal. For example, our study would suggest that if it is not long after the CEO’s peer won a prestigious award, the proposal may be driven by the CEO’s personal desire and could have adverse consequences for the firm.
Second, our findings highlight the potentially negative effect of CEO awards. CEO awards can be used to reward those who have done a great job, and can incentivize non-winner CEOs to work harder and deliver better financial performance. Yet, personal desire for achieving high social recognition and visibility may also motivate the non-winners to undertake strategic actions, such as acquisitions, that can harm shareholder value. Further, there are a lot more non-winners than winners, and the potential negative effects of such awards may outweigh their value.
Third, our research highlights the importance of paying attention to CEOs’ emotions after something substantial happens to their peers. This study indicates that CEOs may become envious if their peers achieve greater social recognition and visibility. Such envious feelings may drive CEOs to engage in intensive acquisitions or other strategic moves that may benefit their own interest but may harm shareholder value. Our findings suggest that board directors may need to play a role in preventing CEOs’ emotions from influencing major firm strategic decisions.
It is important to point out that we did not directly measure the psychological process behind how CEOs reacted to not winning an award. Yet, our findings consistently indicated that they strive for higher visibility in the business community through intensive acquisitions.
Leaders and their teams often pride themselves on their ability to deal with an onslaught of decisions. But the reality is they often end up making rapid-fire calls on issues big and small and wasting their time. They and their organizations would be better served by an approach that treats decisions as a deliberately structured workstream.
Consider the experience of one of the world’s largest footwear manufacturers, whose leaders engaged in an exercise that others can use to revamp the way they make decisions. In its fast-changing industry, big challenges loomed on many fronts. Computer-driven, automated manufacturing that could make reshoring of factories feasible threatened to redraw the supply-chain map. Advanced materials and new construction methods were bringing far greater complexity to manufacturing processes. Product innovations (such as sensors in athletic shoes to detect incipient injury) could add additional layers of complexity. And like all organizations, the manufacturer also faced a steady stream of more mundane challenges: how to comply with product specifications from customers, improve yields at underperforming sites, or refurbish corporate headquarters.
All such issues require decisions — and in some cases, a series of decisions — that differ in magnitude, urgency, and complexity. But in the culture of firefighting that had developed at the company, decisions were treated in isolation or in response to day-to-day developments in the business. Moreover, managers and teams were unsure who owned what decisions, constantly kicking them upstairs and putting more demands on the senior team. As a result, the team found itself handling everything from big-picture questions like how much to invest in the “factory of the future” to far-less-momentous issues like equipment purchases to improve the throughput of a single production line.
Recognizing that ensuring high-quality decisions would require a disciplined process, the executive team embarked on an exercise designed to create a repeatable process for prioritizing decisions and determine the right methodology for each. It consists of these four steps:1. Compile a list.
Create a list of the decisions likely to arise in coming months, without regard for their significance — everything from major capital investments to promotions to when to hold the next all-hands meeting. Although most large organizations may have defined processes for this, rapidly-changing situations, short-term crises, and urgent needs from customers can overwhelm the team’s agenda. Often they also fail to consider the behavioral aspects of team dynamics — for example, how various members exert their power to get their issues on the agenda. Dynamics between teams can come into play as well: For example, how does a senior regional team interact with the global team?
For the footwear manufacturer, the exercise turned out to be less straightforward than it initially appeared. Using a time horizon of 12 months, members of the senior team offered lists that differed widely. Disagreement emerged about which decisions fell within the specified time frame. Many members listed numerous issues that they expected to bubble up from within their functions. And it soon became clear that little agreement existed about who owned which decisions in the company.
But once the team had compiled the list and become aware of all the decisions members felt needed to be addressed, they could remove duplications and combine similar decisions into more coordinated, larger decisions. For instance, the list included a decision about embarking on a process-innovation strategy and one about bringing the production process closer to the customer. The process-innovation question was then rolled up into a larger decision about a broader customer-centric strategy.2. Understand their characteristics.
Ultimately, some 26 decisions emerged from the first step. The team then characterized them according to four criteria — magnitude, organizational complexity, analytical complexity, and subject-matter challenge — and used a point system to assign each decision a score.
For magnitude, the metrics included size of capital investment or operational expenditure and time to expected benefits; the greater the investment or longer the time-to-benefit, the higher the point score. Measures of organizational complexity included number of stakeholder groups involved, their degree of alignment, degree of power, and the degree of effort required to achieve alignment, with point scores escalating accordingly. Measures of analytical complexity included quality of relevant data, degree of uncertainty, number of alternatives, and degree of clarity in measures of value, again with escalating point scores. Measures of content challenge included the team’s degree of familiarity with the business or technical issues involved; the less familiarity, the higher the score.3. Sort them into three categories.
Based on the scores that resulted, the team could assign each of the 26 decisions to one of three categories, each of which requires a distinct decision-making process:
Strategic. These highest-scoring decisions, entailing a great deal of both organizational and analytical complexity, are usually the relatively small number of decisions that will determine the long-term direction of the company. For the footwear manufacturer, these strategic decisions included where and how to deploy automation and the location of factories for proximity to customers. Such decisions require addressing complex organizational challenges such as multiple, often-conflicting stakeholders with differing values, experiences, or cultural needs. Further, these decisions also have considerable analytical complexity such as large, often-incomplete data with considerable ranges of uncertainty.
Strategic decisions usually require the most time and attention of senior teams as well as a rigorous, comprehensive, and uniform decision-making process. Such a process frames the question accurately, generates multiple alternatives (including hybrids of two or more alternatives), generates a wide range of information from experts inside and outside the organization, identifies values and trade-offs, uses sound reasoning (not “gut feel”) that takes uncertainty and risk into account, and concludes with a commitment to action.
Significant. These decisions score in the middle range, require a sound business case, and together can add up to considerable investment. Typical significant decisions include such issues as sourcing, new products, and make-or-buy IT investments. The decision-making process may not require an in-depth application of each step in the strategic-decision-making process. Rather the process should be tailored, depending on the nature of each significant decision.
For significant decisions that are organizationally complex but involve little analytical complexity, the process should focus on the best means for bringing people along and getting buy-in. For the footwear manufacturer, choosing an approach to ERP implementation represented such a decision.
Significant decisions characterized by a high degree of analytical complexity but low organizational complexity require leading-edge data capture and cleansing, as well as the right value-focused analytics. For the manufacturer, that included decisions about energy and water solutions as part of the company’s drive for sustainability.
Quick. These decisions score low on both organizational and analytical complexity and may be addressed by defining procedures that describe the approach needed or that have well defined rules, regulations, checklists, and the like. How to deal with a production process that is drifting out of spec falls into this category. These quick decisions can often be delegated to lower levels in the organization, freeing time for the senior team to focus on strategic and significant decisions.
All upper-tier teams face all three categories of decisions. The kind of decision doesn’t necessarily correlate with where in the organization it should be addressed but with the appropriate way to solve it.4. Understand the timing.
Once the decisions were defined and categorized, the footwear manufacturer’s senior team could see clearly when each needed to be addressed. By defining time horizons of three, six, and nine months, the team could defer decisions that were not immediately needed and address them at the appropriate point. For example, the team determined that key promotions, which would take into account the change-management abilities of candidates, needed to be addressed ahead of ERP implementation strategy.
When teams consider and score the decisions they face in terms of organizational and analytical complexity, the majority of decisions usually turn out to be classified as significant. Further, with a mechanism in place for characterizing decisions in terms of organizational and analytical complexity in the future, the team can treat decisions as a workflow, which they can periodically review and update. And by defining the most efficient and effective process for dealing with them, the team can free more time for attention to strategic, high-impact decisions. The appropriate delegation of decisions can free even more time. In the case of the footwear manufacturer, the CEO could assure team members that a whole cluster of decisions could be comfortably taken at the departmental level instead of requiring the approval of the entire senior team or him.
Understanding where to focus and when is one of the most important things a senior team can do. As the leadership team of the footwear manufacturer learned, creating and managing a decision agenda is one of the fastest and most efficient ways to do it.
Sixty percent of employees don’t believe they have the opportunity to do what they do best every day at work, according to the 2017 State of the American Workplace report. Sadly, one common explanation for this is that their boss is too busy doing it for them. In our ten-year longitudinal study on executive leadership, among 2,700 leaders, 67% struggled to let go of work from previous roles. As leaders rise in organizations, they have a strong tendency to take the work that made them feel successful along with them. The resulting organizational compression — the compacting effect of leaders playing too low — leaves direct reports constrained from having impact, feeling less satisfaction from their job, and then forced to work lower than their role, too.
If you are feeling like your boss is more involved in your job than you’d want, you obviously aren’t alone. But the fact that it’s common doesn’t mean you have to accept it. Whether you report to the CEO or a first-level supervisor, it’s in both of your best interests to thrive in your own jobs, not other people’s. While the notion of confronting your boss may feel intimidating, the results can be more promising than you think. Because most leaders, especially those higher up in organizations, don’t get great feedback from those they lead, it can be refreshing to have someone volunteer it. And though frustrating, there could be any number of explanations for your boss’s behavior. Here are five things you can do to help guide your boss back to doing their own job, freeing you to do yours.
Test for awareness by clarifying expectations. You shouldn’t assume your boss is even aware how involved they are in your job. Start by getting aligned on expectations. Ask your boss to share what contribution they expect from you and what they see the scope of your role to be. If their answer aligns with your views, you know they are unaware of their over-involvement. However, if their answer suggests a much narrower scope than you understood your role to entail, justifying their level of involvement, then the conversation you need to start with is about mismatched expectations about what your job actually is.
Aligned or not, the conversation opens the door for you to share your expectations, as well. Let them know how the degree of their involvement makes you feel. If you both agree on the scope of your role, discuss specific examples where they have been overly involved, and how you felt that work was yours to do. If you’re not aligned on the scope of your role, then share why you feel their more narrowed definition doesn’t allow you to grow and contribute to your full potential and satisfaction.You and Your Team Series Difficult Conversations
- Don’t Let Frustration Make You Say the Wrong Thing How to Handle Difficult Conversations at Work Create a Culture Where Difficult Conversations Aren’t So Hard
Ask if you’re falling short. Your boss’s excessive involvement in your job could be a form of veiled feedback, stifling though it might feel. Ask if there is something about the way you are performing the role that they find inadequate. If they jump into “reassuring” mode, telling you they think you’re doing a great job, this opens the door for you to share an example of why you are asking. I recently encouraged the Chief Marketing Officer in one of my client organizations to take this approach with her boss, the CEO. He prided himself on being a former marketer, though it had been more than a decade since he’d done it. Whenever she presented new brand campaigns to him, he enthusiastically jumped in with “suggestions” that replaced her direction with his. He enjoyed the process so much he failed to see how demoralizing it was for her. When she expressed how his involvement made her feel devalued, embarrassed in front of the team, and unimportant, he felt horrible. Beginning the conversation about her rather than him allowed him to discover the disconnection, and led to a productive conversation about how to change his behavior.
On the other hand, if your boss does indicate he is disappointed in your performance, then address that. Let them know that you want to excel in the job, and are troubled they feel the only way to get the work done is for them to do it themselves. Ask your boss to consider offering you feedback and coaching when your work doesn’t meet expectations, rather than jumping in and doing it for you. Whether they are disappointed or not, they may not realize how intrusive their “help” feels. Starting by asking for calibration allows them to invite reciprocation.
Point out the unintended consequences. Your boss’s unwanted involvement has further-reaching consequences than they likely realize. It makes you both look bad. As was the case with the CMO above, everyone on the team watched the CEO’s compressive behavior play out. In one of my diagnostic interviews, one person said, “Well, we all know who the real CMO around here is anyway.” She was able to bring that to his attention as part of their conversation. Regardless of the impetus behind it, your boss’s excessive involvement in your job isn’t a legitimate solution. It suggests they’d rather do your job than their own. It makes them appear as if they don’t trust you. The compression of their involvement in your job has a cascading effect, leading you to become overly involved in work below your level. Most consequently, if they are overly involved in your job, they’re likely doing it to other direct reports as well, compromising the performance of the entire team. While their intentions may be good — such as trying to be helpful, to demonstrate tangible value, or to “pitch in and help out” — the unintended consequences far outweigh any “help” they are offering.
Find alternative solutions together. Help your boss get clear on what their involvement is intended to achieve. It could be that they enjoy your job more than they enjoy their own, especially if they used to have it. It could be they think they’re better at it than you, and they may well be more experienced than you. As such, they may fear your work is making them look bad. It could be they want to feel needed as a boss, so they are jumping in as a way to feel useful to those they lead. Any one of these needs has a legitimate foundation. But meeting that need by overly involving themselves in your role isn’t a strategic way to meet any of these needs.
There is a legitimate level of involvement a boss should have in the work of those they lead. For example, they need to be kept informed. They can sometimes offer additional expertise to strengthen results. Whatever the reason, negotiate with your boss to find a mutually satisfying and reasonable level of involvement that meets both of your needs.
Don’t wait. Letting toxic resentment accumulate could be dangerous. The longer you wait, the more you are likely to start ascribing motives to your boss and concocting reasons to explain their behavior. In the case of my client above, the CMO had reached such a boiling point when she came to me, she was literally headed into the CEO’s office to rage, “Why the hell do you have me here? If you want to be the damned CMO, just take the job! But stop humiliating me with your passive-aggressive ‘suggestions’ everyone knows are really corrections.” Clearly, that would have been a disaster.
With the best of intentions, leaders often play beneath their level, overly involving themselves in the work of those they lead. Don’t assume your boss is aware they’re doing it, or why. Do yourself, and your boss, the favor of helping them get back into their own swim lane, and allowing you to thrive within yours.
Managers who can’t seem to pick a course of action — or who constantly change their minds – can be maddening. You’re left spinning your wheels, or abruptly switching directions, and your team’s credibility across the organization is likely to suffer. So how can you help a wishy-washy boss make decisions? If your manager isn’t willing to steer, is it OK for you to take the driver’s seat?
What the Experts Say
Reporting to an indecisive boss is an unquestionably “challenging and frustrating situation,” says Sydney Finkelstein, the Director of the Leadership Center at the Tuck School of Business at Dartmouth College and author of the book, Superbosses: How Exceptional Leaders Manage the Flow of Talent. “It drives you crazy because without direction, you’re not sure what to do.” In addition to the daily annoyance, you might also have concerns about your professional prospects, says Nancy Rothbard, the David Pottruck Professor of Management at the University of Pennsylvania’s Wharton School. “From a career aspiration standpoint, you worry that your reputation will suffer,” she says. “If your boss isn’t being taken seriously in the organization, are you, by extension, seen as ineffective?” Here are some strategies for coping if your boss is chronically indecisive.
Diagnose the situation
According to Finkelstein, the first step is to “figure out what is behind the behavior.” Pay attention to what’s going on in your boss’s work world because it will “give you some clues” as to why they’re acting the way they are. Try to have empathy. “It could be that his own boss smacked him down the last time he went out on a limb.” It could be that he’s wary of your organization’s “blaming culture.” Or perhaps your manager’s inability to move forward is due to his “inexperience or naturally risk-averse” disposition. As you diagnose the problem, it’s critical to do a “gut check” to ensure that you’re not “overestimating your boss’s indecisiveness or misinterpreting it,” he says. Ask yourself if “there might be a method to your manager’s madness. For example, “Is it possible your boss isn’t telling you how to do every little thing because he is waiting to see if you step up?” Rothbard agrees. “As a subordinate, you don’t necessarily have all the information,” she says. “There could be all kinds of reasons why your boss is having trouble making a decision.” And indecision is sometimes defensible. “If an issue is hard and complicated, rushing to judgment is not a good thing. Sometimes your boss needs to be more thoughtful.”
If you determine that the root of the problem is your boss’s insecurity, it’s your job to “lend [your manager] confidence” by being an “extremely competent and trustworthy” direct report, says Finkelstein. Think of it as “an opportunity for you to help your boss see a way forward.” If the indecisiveness stems from the fact that the decision is complicated and the answers unclear, Rothbard recommends acting as “a sounding board — someone who’s willing to discuss and weigh the pros and cons of various actions.” Ask good questions; provide relevant, useful data; and offer your perspective.
When you have a strong opinion about how the decision should go, but your boss is still stuck in “analysis paralysis” — take a different approach. “Giving your boss more data to pore over will not necessarily help him move forward,” Rothbard explains. In these cases, “you need to help your boss sort through the information” and then offer “a clear rationale for your recommendation.” It’s also helpful to “enable your boss to delegate to you without formality,” says Finkelstein. You could say something like, “I have been thinking a lot about this and there are a few ways we could address the issue. Can I give one or two of them a shot and then report back to you with my progress?” Taking charge of the situation removes the decision-making burden from your boss. “It’s much easier for your manager to choose between Door Number One or Door Number Two than it is to take action versus do nothing.” The goal, he says, is to “ease [your manager] into empowering you.”
Talk to your boss
Depending on how receptive your manager is to feedback, it might be worth having an honest and respectful conversation about how her wishy-washiness impacts you and the rest of the team. Don’t be aggressive or confrontational, says Rothbard. “Signal that you know your boss’s intentions are good. Your tone should say, ‘We’re in this together.’” She suggests broaching the subject with a line like, “I’m concerned that because we said one thing in the past and now we seem to be going back on it, it’s affecting morale.” The conversation should be constructive and one-on-one, Finkelstein adds. It’s always wise to “offer people a face-saving way to deal with problems.” That said, if your relationship with your boss is shaky and/or they’re not particularly open, trying to discuss her indecisiveness “could be seen as an aggressive” move.
Another way to speed up the decision-making process is “to form a coalition,” comprised of people “with whom you have a reasonably good relationship” and “who have influence over your boss,” says Finkelstein. “Don’t spill your guts,” and, of course, don’t complain. Simply “ask for their advice” on what to do. He suggests saying something like, “I’m trying to figure out the best way to accomplish the goals of our team. Do you have any ideas?” If several people agree on a course of action, that’s further impetus for your boss to follow the recommendation.
Having an indecisive boss is not only hard on your day-to-day productivity, it’s also bad for your “internal reputation and career development,” says Finkelstein. Without a record of achievement, “What have you got to show on your resume?” If you come to the conclusion that your manager’s woolliness is harming your professional potential, Rothbard advises you “distance yourself and protect yourself” from your boss’s behavior by “developing your relationships and network internally.” She also suggests cultivating “mentors in other parts of the organization. You need people who have your back.” If the problem persists, you might also want to consider moving on.
Principles to Remember
- Engender trust and confidence by being an extremely competent, high-performing employee who’s willing to serve as a sounding board.
- Take the lead by helping your boss sort through information and then offering a clear recommendation.
- Seek out colleagues who have influence over your boss and ask for their advice on how to handle the situation.
- Take your boss’s behavior personally. Try to figure out what is behind the indecisiveness.
- Be aggressive or confrontational if you decide to talk to your boss about their behavior.
- Stay too long under a boss who can’t make a decision. It’s bad for your internal reputation and long-term career development.
Case Study #1: Seek advice from others and uncover the root of your boss’s indecisiveness
Early in Alexi Robichaux’s career, he worked under a boss—“Frank”—who suffered from “episodic” indecisiveness.
“At times, he could be very decisive, but there were many other times when he just couldn’t make up his mind and it was extremely frustrating,” Alexi recalls. “I was junior in my career, and I blamed myself. I thought I must be doing something wrong and must not be equipping him for success.”
But Alexi was determined to improve the situation. “I realized I could either choose to be a victim or try to help him move forward.”
Alexi’s first coping strategy was to seek advice from other senior leaders in the organization who had a longer history with Frank. “I asked them, ‘What am I missing?’” One colleague told him that Frank was “passionate” about the company and product design but lacked managerial experience. “Frank was very skilled but he was used to being the artist not the boss.”
That perspective helped Alexi to understand the root of the indecisiveness and to see that he and Frank were actually quite similar. “We are both intuitive thinkers, rather than systematic or rational ones,” he says. “I’m not even sure myself how I make decisions, and so I felt more empathy for Frank. We both wanted what was best for the organization.”
Not long after that, Frank, Alexi, and the rest of the team were embroiled in a strategic challenge. The team had created a new product, but “we were limited by technology at the time — the cloud infrastructure wasn’t very developed — and our solution wasn’t elegant.”
Frank hemmed and hawed about whether the product was ready to go to market. “It was never a ‘no.’ It was ‘Let me think about it some more. I’ll get back to you.’”
The team grew more and more aggravated. But, because Alexi appreciated his boss’s strong design aesthetic and perfectionist tendencies, he decided to show Frank that the product was the best it could be under the circumstances.
After each meeting with the engineering team, Alexi sent Frank detailed updates. He described what was discussed as the pros and cons of various scenarios. “I needed to show him that we had the best technical minds in the company working on this and that we weren’t being lazy; we were just limited by technology.”
Ultimately Frank agreed with the assessment and the product went to market.
Today Alexi is cofounder and CEO of BetterUp, the San Francisco-based company that connects employees with certified, executive-level coaching.
Case Study #2: Build trust and consider talking to your boss about their behavior
Several years ago, Kyle Libra was the first employee at a fast-growing software startup. His boss, “Charlie,” was indecisive about pretty much everything.
“Charlie once asked me to extend a job offer to a candidate, which I did. And then he came back a few days later and told me that we should try to go back and offer her less money,” recalls Kyle. “He also wanted to be involved in every little design decision, but he often changed his mind. One day he’d want us to make the buttons [on our product] slightly rounded; two weeks later, they needed to be perfectly square.”
Difficult as this was, Kyle was sensitive to Charlie’s situation. “He was a first-time CEO, and I think he was overwhelmed by all the things he had to do,” he says. “I tried to put myself in his shoes and think about things from his perspective.”
Kyle knew he needed to gain Charlie’s trust, while also demonstrating that the constant mind-changing was having a negative impact on the team. First, he provided Charlie with analytical customer feedback that indicated the company’s product launches were well received. This was meant to reassure Charlie that the team knew what it was doing.
Next, he talked to Charlie about his behavior. “It wasn’t personal, but I tried to be as direct as possible,” he says. Once again, he used data to prove his point. “I showed him a graph of the organization’s engineering output, and showed how his lack of decision-making was hurting their efficiency. They can’t do their jobs if he’s holding them up.”
Kyle succeeded in getting Charlie to delegate more. “Over time Charlie saw that things were running smoothly and trusted us to make good decisions,” he says.
Kyle left the company after two years and is now an internet product manager at Work Market, the New York City-based company that connects businesses with freelancers.
The venture capital industry is beginning to take a good, hard look at a new financial instrument coming out of the bitcoin community — Initial Coin Offerings, or ICOs. Also known as “token sales,” this new fundraising phenomenon is being fueled by a convergence of blockchain technology, new wealth, clever entrepreneurs, and crypto-investors who are backing blockchain-fueled ideas. ICOs present both benefits and disadvantages, as well as threats and opportunities, to the traditional venture capital business model.
Here’s how an ICO typically works: A new cryptocurrency is created on a protocol such as Counterparty, Ethereum, or Openledger, and a value is arbitrarily determined by the startup team behind the ICO based on what they think the network is worth at its current stage. Then, via price dynamics determined by market supply and demand, the value is settled on by the network of participants, rather than by a central authority or government.Insight Center
- Business in the Era of Blockchain Sponsored by Accenture How technology is transforming transactions.
Venture capitalists, who generally have been standoffish to the ICO phenomenon, are now becoming more interested in it for a number of reasons. One is profits — cryptocurrency investors made some massive returns in 2016, with cryptocurrencies from Blockchain startups Monero and NEM both seeing 2,000% increases in value. For example, the cryptocurrency used for the Ethereum network, called Ether, saw its value double in just a few days in March 2017. Yes, in three days, people who invested in Ether doubled their investment. Those investors can opt to cash out to a fiat-backed currency, or wait for the cryptocurrency to continue to rise (or fall). Volatility is a two-way street. While the price of Ether has been rising, Bitcoin has dropped 20% to $1,000 dollars from a record $1,290 on March 3, 2017.
The second reason VCs are becoming more interested in ICOs is because of the liquidity of cryptocurrencies. Rather than tying up vast amounts of funds in a unicorn startup and waiting for the long play — an IPO or an acquisition — investors can see gains more quickly, and can pull profits out more easily, via ICOs. They simply need to convert their cryptocurrency profits into Bitcoin or Ether on any of the cryptocurrency exchanges that carry it, and then it’s easily converted to fiat currency via online services such as Coinsbank or Coinbase.
What traditional investors don’t like about any of this is the regulatory uncertainty; the high valuations and over-capitalization; the lack of control over financials, strategy, and operations; and the lack of business use-cases. And like any industry, the ICO arena has had its fair share of outright scams, pump and dumps, and blatant Ponzi schemes. However, much of the criminal activity is now being mitigated by self-organized, crowdsourced due diligence in the community, as well as by external parties such as Smith and Crown, a research group focused on cryptofinance, and ICO Rating, a ratings agency that issues independent analytical research on blockchain-based companies.
At least one VC firm is moving into cryptocurrencies. Blockchain Capital is set to raise its third fund via a digital token offering in the first-ever liquidity-enhanced venture capital fund (where people can invest without locking their money up for years on end) via a digital token called BCAP.
ICOs are the Wild West of financing — they sit in a grey zone where the U.S. Securities and Exchange Commission (SEC) and many other regulatory bodies are still investigating them. The main problem is, though, that most ICO’s don’t actually offer equity in start-up ventures; instead, they only offer discounts on cryptocurrencies before they hit the exchanges. Therefore, they don’t fit into the current definition of a security, and are technically outside of traditional legal frameworks. Secondly, they are global instruments — not national ones — and they are funded using bitcoin, ether and other cryptocurrencies that are not controlled by any central authority or bank. Anyone can invest, and they can even do so pseudo-anonymously (it’s not impossible to find out who people are, but it’s not easy, either). Currently, there’s no Anti-Money Laundering (AML) law or Know Your Customer (KYC) framework, though some companies are working on that. One example is Tokenmarket, a marketplace for tokens, digital assets and blockchain-based investing, that has teamed up with the Stock Market of Gibraltar to offer KYC- and AML-compliant ICOs.
Detractors of these new funding schemes scream for structure and protection, point out the scams, demand more control, and say that without equity, investors don’t have enough skin in the game. Meanwhile, proponents retort that there’s a real need for freedom to invest outside the accredited system, which sees the wealthy getting wealthier. They argue that the door needs to close on the domination of Sand Hill Road in Silicon Valley and other VCs and investors in the tech industry who have been making massive returns on the backs of entrepreneurs for far too long.How Blockchain Works
Here are five basic principles underlying the technology.1. Distributed Database
Each party on a blockchain has access to the entire database and its complete history. No single party controls the data or the information. Every party can verify the records of its transaction partners directly, without an intermediary.2. Peer-to-Peer Transmission
Communication occurs directly between peers instead of through a central node. Each node stores and forwards information to all other nodes.3. Transparency with Pseudonymity
Every transaction and its associated value are visible to anyone with access to the system. Each node, or user, on a blockchain has a unique 30-plus-character alphanumeric address that identifies it. Users can choose to remain anonymous or provide proof of their identity to others. Transactions occur between blockchain addresses.4. Irreversibility of Records
Once a transaction is entered in the database and the accounts are updated, the records cannot be altered, because they’re linked to every transaction record that came before them (hence the term “chain”). Various computational algorithms and approaches are deployed to ensure that the recording on the database is permanent, chronologically ordered, and available to all others on the network.5. Computational Logic
The digital nature of the ledger means that blockchain transactions can be tied to computational logic and in essence programmed. So users can set up algorithms and rules that automatically trigger transactions between nodes.
For blockchain startups, ICOs are a win-win — they allow startups to raise funds without having equity stakeholders breathing down their necks on spending, prioritizing financial returns over the general good of the product or service itself. And there are many in the blockchain community who feel that ICOs are a long-awaited solution for non-profit foundations that want to build open-source software to raise capital. Non-profits usually hold about 10-20% of the total cryptocurrency they issue; as Ethereum did in their ICO in 2014, with 20% going to the development fund and the remaining going to the Ethereum Foundation. This is so they have a vested interest in building more value, as well as having reserves for growth in the future. (As of March 2017, the market capitalization of the ether token was more than $4 billion.)
The market cap for bitcoin is now close to $20 billion, and half of that is allegedly owned by less than one thousand people, who are called “bitcoin whales.” Many of them are in China, but there are also hedge funds and bitcoin investment funds who hold massive amounts of bitcoin. Most made their money early on by buying or mining bitcoin when it was still under $10 (in the early days of 2011-2013). It’s now worth approximately $1,1200 per bitcoin. These “bitcoin whales” are currently the ones who make or break many of the ICOs. Some of the enormous profits they have made in bitcoin are being channeled back into innovation, as many of them seek to diversify holdings, as well as support the ecosystem in general.
More than $270 million has been raised in ICOs since 2013, according to Smith and Crown (not including the $150 million raised in The DAO scandal, which was returned to investors). Since 2013, there’s been about $2 billion invested in blockchain and bitcoin startups from the VC community. ICOs are becoming more and more popular for startups seeking to get out of self-funding, bootstrapping starvation mode and avoid being locked in by venture capitalists, watching their own equity drown in a sea of financing rounds. ICOs are dominating the overall crowdfunding charts in terms of funds raised, with half of the top 20 raises coming from the crypto-community.
In a recent conversation, MIT scientist and author John Clippinger described the vast potential of this new movement to me as such:
One way of thinking about a crypto-asset is as a security in a startup, which begins with a $10 million valuation and becomes a $10 billion dollar entity. Instead of stock splits, the founding crypto-asset gets denominated in smaller and smaller units; in this case 1,000 to one. Here, everyone in the network is an equity holder who has an incentive to increase the value of the network. All of this depends upon how well the initial crypto-asset and its governance contract are designed and protected. In this instance, good governance, e.g. oversight, yields predictability, security, and effectiveness, which in turn creates value for all token holders.
Just as venture capitalists are taking a hard look at this new phenomenon, so should we all. It’s not just about the money that can be made; it’s also about funding blockchain projects and, in the near future, other startups and even networks, as Clippinger noted. We now have a way to easily fund open source software, housed under foundations rather than corporations, that can truly drive faster innovation. Right now, blockchain technology is at the stage where the internet was in 1992, and it’s opening up a wealth of new possibilities that have the promise to add value to numerous industries, including finance, health, education, music, art, government, and more.