Blogs

When CEOs Should Speak Up on Polarizing Issues

Harvard business - Wed, 10/31/2018 - 10:00
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CEO activism, the growing trend of top executives speaking out on sensitive social and political issues, has been labeled the “new normal.” But behind the scenes, executives do not feel in control. They are struggling to anticipate and respond to intensifying pressure from the public, investors, and — above all — their employees.

There are conflicting views of how CEOs should proceed. One survey suggests the public wants chief executives to lead on social change without waiting for the government to act. A separate survey shows public support for corporate engagement on such issues as sexual harassment and equal pay — though not on gun control or abortion. A third survey indicates that brands may be punished for even mentioning President Donald Trump, regardless of whether they are being critical or complimentary.

Companies we work with at BSR, a nonprofit sustainability business network and consultancy, feel trapped: Although every conceivable action carries considerable risk, inaction may not be much of an option, either.

What to do, now that the neutral middle ground has become a quicksand? We have been working with businesses to develop a strategic framework for when to take a stand on social issues. It draws on the work of R. Edward Freeman and others regarding stakeholder theory, which offers a way of examining the interests of all groups affected by an organization — not just shareholders but also customers, employees, governments, suppliers, and communities. We started by studying how distinct stakeholder groups view our corporate clients’ positions on social issues. Here is what we learned.

Companies must consider values, not just shared value. Most companies prefer to prioritize their business interests in line with both fiduciary duty and the shared value approach to corporate responsibility, which connects business success with social good. This would suggest that companies should act only when there is a clear business case and an opportunity for direct action. For example, most would assume that it’s easier and more effective for the CEO to cut a company’s climate emissions than to take a stand on immigration. A CEO could be forgiven for thinking it’s safest to only weigh in on political issues that affect operational and strategic goals, industry dynamics, or a company’s regulatory and policy landscape.

But a company’s exposure to a political issue is also determined by its values. Values are determined by the company’s culture, mission, and voluntary commitments, along with the opinions and beliefs of a range of actors — not just customers but also employees, business partners, and civil society organizations.

We were surprised to find that when business interests and values conflict, values are the dominant variable. That’s why, although focusing on core interests may seem sensible, reality shows it to be untenable. Tech companies, for example, had little to gain strategically by opposing the Trump administration’s family separation policy. But Microsoft and Google found it impossible to remain silent in the face of employee demands for a response to what staff regarded as an assault on company values. The same dynamic may now complicate Google’s plans to re-enter China’s search market. Employee pressure can even drive significant turnover in senior leadership ranks, as happened recently at Nike, which earlier this year was sued for sexual discrimination by several former employees.

Employees are now a company’s most powerful interest group. In many ways, corporate power seems to be high: Companies prioritize shareholder value; union membership rates are at an all-time low; employment contracts for some jobs include nondisclosure clauses as standard features; certain sectors of the workforce are moving toward gig economy jobs with diminishing hourly rates and no health care; other sectors are facing unemployment as jobs are automated. So why are leaders responding so readily when employees pressure them to demonstrate integrity? Workers are freely using the tools of this hyper-transparent era — including petitions and email leaks — to land punishing blows against corporate reputations and finances, in the process emerging as companies’ most powerful interest group. At a time when the U.S. economy seems to be approaching full employment, employees have more influence over whether and how their leaders speak out.

Polarization heightens risk. Companies seem to face the greatest peril when an issue is politically polarizing to customers and has more to do with values than with long-term financial consequences. On Jan. 28, 2017, Uber cut congestion pricing to John F. Kennedy International Airport while New York taxi drivers were protesting President Trump’s new immigration policy; although the move was a financial one on Uber’s part, it was perceived as aligning the company with the “Muslim ban,” leading to the #deleteUber hashtag and to hundreds of thousands of riders deleting their accounts. Keurig faced complaints when it pulled advertising from Sean Hannity’s Fox News show. Delta drew outrage and lost tax breaks when it decided to end a travel discount for the National Rifle Association. Still, Target, after undergoing boycotts and petition drives for implementing a transgender bathroom policy in its stores, said it had suffered no material financial impact.

Companies certainly have tools to parse the views of their customers, but fretting over who is yelling the loudest on Twitter does not offer a firm ground for action. Basing decisions on corporate principles and employee values is a better approach than trying to navigate what is likely to be a broad spectrum of customer sentiment.

Your rhetoric has to be aligned with your dollars. Companies face heightened scrutiny over influence-peddling and corruption, which makes it much harder to decouple public rhetoric and private lobbying efforts. The Center for Political Accountability has called out companies on a range of issues, including contraceptive makers that indirectly fund political officials who aim to limit women’s reproductive rights. C-suite hypocrisy is now a media focus, with funding for business associations a particularly vulnerable flank. Climate activists have long highlighted the gap between the oil and gas sector’s softening rhetoric on climate change and the corporate funding for its trade group, the American Petroleum Institute, which has opposed numerous climate change policies.

Opportunities for direct action may be constrained. Companies are not governments, and their customers are not the electorate. So even when they want to take action, there are concrete limits on what businesses can achieve. Companies can accept or decline business, and they can tackle such issues as diversity and climate change in their own operations, but on pure policy matters like trade or immigration, there’s only so much they can do.

Companies know this well, but they struggle to communicate the limits of their ability to drive systemic social change, which leaves them at risk of raising expectations they cannot fulfill. For example, an incident of discrimination by staff at a Starbucks in Philadelphia led to public outcry against the company, which soon stood accused of helping foster gentrification and systemic racism in the U.S. This was a discouraging development, given that the organization has long mounted efforts to drive collaborative action on race and immigration issues, including a pledge to hire 10,000 refugees.

So the paradoxes multiply. While pressure to enhance shareholder value has not relented, companies are listening intently as they try to balance the needs and demands of a broad range of stakeholders. At the same time, powerful sections of the investment community are amplifying demands that companies move beyond empty posturing to better manage their social, political, and environmental efforts. Amid all the fuss, key shareholders seem to be concluding that prioritizing only profits may be neither smart nor sustainable. Behind the roiling divisions on specific issues, a consensus is emerging among markets, employees, and the public: Companies must fundamentally rethink their interactions with society.

Categories: Blogs

LeadershipNow 140: October 2018 Compilation

Leadershipnow - Wed, 10/31/2018 - 09:59

Here are a selection of tweets from October 2018 that you might have missed:
See more on Twitter.

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Like us on Instagram and Facebook for additional leadership and personal development ideas.

Categories: Blogs

Better Ways to Communicate Hospital Data to Physicians

Harvard business - Wed, 10/31/2018 - 09:00
Dave King/Getty Images

We recently conducted an in-depth study at Lumere to gain insight into physicians’ perceptions of clinical variation and the factors influencing their choices of drugs and devices. Based on a survey of 276 physicians, our study results show that it’s necessary to consistently and frequently share cost data and clinical evidence with physicians, regardless of whether they’re affiliated with or directly employed by a hospital. This empowers physicians to support the quality and cost goals inherent in a health system’s value-based care model. Below, we offer three recommendations for health systems looking to do this.

Insight Center

Assess how data is shared with physicians. The reality is that in most health systems, data sharing occurs in irregular intervals and inconsistent formats. Ninety-one percent of respondents to our survey reported that increasing physician access to cost data would have a positive impact on care quality. However, only 40% said that their health systems are working to increase physician access to such data.

While working directly with health systems to reduce clinical variation, Lumere has discovered firsthand that the manner and type of cost and evidence-based data shared with physicians varies dramatically. While some organizations have made great strides in developing robust mechanisms for sharing data, many do little beyond circulating the most basic data from the Centers for Medicare and Medicaid Services’ patient-satisfaction survey (the Hospital Consumer Assessment of Healthcare Providers and Systems, or HCAHPS).

There are multiple explanations as to why health system administrators have been slow to share data with physicians. The two most common challenges are difficulty obtaining accurate, clinically meaningful data and lack of knowledge among administrators about communicating data.

When it comes to obtaining accurate, meaningful data, the reality is that many health systems do not know where to start. Between disparate data-collection systems, varied physician needs, and an overwhelming array of available clinical evidence, it can be daunting to try to develop a robust, yet streamlined, approach.

As for the second problem, many administrators have simply not been trained to effectively communicate data. Health system leaders tend to be more comfortable talking about costs, but physicians generally focus on clinical outcomes. As a result, physicians frequently have follow-up questions that administrators interpret as pushback. It is important to understand what physicians need.

Determine the appropriate amount and type of data to share. Using evidence and data can foster respectful debate, provide honest education, and ultimately align teams.

Physicians are driven by their desire to improve patient outcomes and therefore want the total picture. This includes access to published evidence to help choose cost-effective drug and device alternatives without hurting outcomes. Health system administrators need to provide clinicians with access to a wide range of data (not only data about costs). Ensuring that physicians have a strong voice in determining which data to share will help create alignment and trust. A more nuanced value-based approach that accounts for important clinical and patient-centered outcomes (e.g., length of stay, post-operative recovery profile) combined with cost data may be the most effective solution.

While physicians generally report wanting more cost data, not all physicians have the experience and training to appropriately incorporate it into their decision making. Surveyed physicians who have had exposure to a range of cost data, data highlighting clinical variation, and practice guidelines generally found cost data more influential in their selection of drugs and devices, regardless of whether they shared in savings under value-based care models. This was particularly true for more veteran physicians and those with private-practice experience who have had greater exposure to managing cost information.

Health systems can play a key role in helping physicians use cost and quality data to make cost-effective decisions. We recommend that health systems identify a centralized data/analytics department that includes representatives of both quality-improvement teams and technology/informatics to own the process of streamlining, analyzing, and disseminating data.

Compare data based on contemporary evidence-based guidelines. Physicians would like to incorporate reliable data into their decision-making when selecting drugs and devices. In our survey, 54% of respondents reported that it was either “extremely important” or “very important” that hospitals use peer-reviewed literature and clinical evidence to support the selection of medical devices. Further, 56% of respondents said it was “extremely important” or “very important” that physicians be involved in using data to develop clinical protocols, guidelines, and best practices.

Health systems should ensure that data is organized and presented in a way that is clinically meaningful and emphasizes high-quality patient care. Beginning the dialogue with physicians by asking them to reduce costs does not always inspire collaboration. To get physicians more involved, analyze cost drivers within the clinical context.

Finally, health systems should keep data and communication simple by developing, communicating, and mobilizing a small number of critical key performance indicators (KPIs). These indicators should reflect the voices of health care customers, including patients, care providers, and payers. In some instances, these will overlap — for example, length of stay, infection rates, readmissions, and likelihood to recommend the provider in the future. Consistent, relevant benchmarks will keep physicians focused on organizational goals.

Our survey results paint a vivid picture: Health systems openly and transparently engage with both employed and affiliated physicians and foster a culture that appreciates data and analytics. Only then will we see improved clinical, operational, and financial outcomes.

Categories: Blogs

To Combat Harassment, More Companies Should Try Bystander Training

Harvard business - Wed, 10/31/2018 - 08:36
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As the wave of #MeToo stories have come to light over the past year, it’s become painfully clear that whatever organizations are doing to try to prevent sexual harassment isn’t working.

Ninety-eight percent of companies say they have sexual harassment policies. Many provide anti-sexual harassment training. Some perpetrators have been fired or fallen from grace. And yet more than four decades after the term “sexual harassment” was first coined, it remains a persistent and pervasive problem in virtually every sector and in every industry of the economy, our new Better Life Lab report finds. It wreaks financial, physical, and psychological damage, keeping women and other targets out of power or out of professions entirely. It also costs billions in lost productivity, wasted talent, public penalties, private settlements, and insurance costs.

So what does work? Or might?

Sadly, there’s very little evidence-based research on strategies to prevent or address sexual harassment. The best related research examines sexual assault on college campuses and in the military. That research shows that training bystanders how to recognize, intervene, and show empathy to targets of assault not only increases awareness and improves attitudes, but also encourages bystanders to disrupt assaults before they happen, and help survivors report and seek support after the fact.

Researchers and workplace experts are now exploring how to prevent sexual harassment in companies by translating that approach. The Equal Employment Opportunity Commission in its 2016 task force report encouraged employers to offer bystander training, for one. And New York City passed a law in May requiring all companies with more than 15 employees to begin providing bystander training by April 2019. It could prove a promising, long-term solution.

But culture change is hard — it can take anywhere from months to several years, experts say. It’s much easier to go for the annual, canned webinar training on sexual harassment that checks the legal-liability box. Yet culture change is exactly why bystander interventions could be powerful: the strategy recognizes that, when it comes to workplace culture, everyone is responsible for creating it, every day, in every interaction.

Jane Stapleton, co-director of the Prevention Innovations Research Center at the University of New Hampshire and an expert in bystander interventions, told me about an all-too-familiar scenario: Say there’s a lecherous guy in the office — someone who makes off-color jokes, watches porn at his cubicle, or hits on younger workers. Everyone knows who he is. But no one says anything. Co-workers may laugh uncomfortably at his jokes, or ignore them. Maybe they’ll warn a new employee to stay away from him. Maybe not. “Everybody’s watching, and nobody’s doing anything about it. So the message the perpetrator gets is, ‘My behavior is normal and natural,’” Stapleton said. “No one’s telling him, ‘I don’t think you should do that.’ Instead, they’re telling the new intern, ‘Don’t go into the copy room with him.’ It’s all about risk aversion — which we know through decades of research on rape prevention, does not stop perpetrators from perpetrating.”

When bystanders remain silent, and targets are the ones expected to shoulder responsibility for avoiding, fending off, or shrugging off offensive behavior, it normalizes sexual harassment and toxic or hostile work environments. So bystander intervention, which Stapleton and others are beginning to develop for workplaces, is designed to help everyone find their voice and give them tools to speak up.

It’s all about building a sense of community. “Bystander intervention is not about approaching women as victims or potential victims, or men as perpetrators, or potential perpetrators” she said. “Rather, it’s leveraging the people in the environment to set the tone for what’s acceptable and what’s not acceptable behavior.”

At the most fundamental level, bystander interventions could begin — long before an incident of harassment — with workers having non-threatening, informal conversations in unstressed moments about how to treat each other, how they can help each other do their jobs or make their days better, and practice giving positive feedback. Normalizing talking about behavior and defining respectful behaviors everyone agrees on may make it easier for coworkers to see and give negative feedback if a worker later crosses a line,  Fran Sepler, who for 30 years has worked as a consultant, trainer, and investigator on workplace harassment prevention, told me in an interview. “So when a co-worker tells an offensive joke, it’s easier to say, ‘Remember how we talked, and we all agreed about what’s OK to say at work? That’s not it.’”

In testimony before the EEOC, Sepler suggested organizations create “feedback rich” environments, where middle managers are trained to respond to complaints and issues in an emotionally intelligent way, and where people feel comfortable speaking up and listening, no matter the issue.

In campus settings, bystanders are trained to recognize when a sexual assault may be imminent and intervene by, for instance, disrupting the environment — turning the lights on at a party, or turning the music off — defusing the situation, with humor perhaps, distracting or interrupting a potential perpetrator, drawing a potential target away, or drawing others in.

But disrupting sexual harassment in the workplace requires a very different set of tools. “Too often people let things slide, concerned that if they get involved, it might affect their own career aspirations,” Alberto Rodríguez. supervising attorney for the New York City Commission on Human Rights, told me.

Because careers and reputations can be on the line, Sepler suggests considering a matrix of questions before acting: “Can I have an impact? Is it safe? What is the best strategy given the culture of the organization and my level of influence?”

Bystanders in the workplace can defuse harassing or offensive language or situations with humor, she said, or verbal or nonverbal expressions of disapproval. They can interrupt a situation by changing the subject, or inserting themselves into the situation. “If it’s the first time you hear someone say something offensive, you might try humor as a way of getting their attention, making a caustic remark, or saying, ‘What year is this? 1970?’ as a way of getting their attention,” Sepler said. Even so, she cautioned that bystanders must weigh whether the colleague has the reputation for being a jerk. Another option bystanders could consider is having a conversation after the fact, when tensions have cooled, laying out why the behavior was offensive.

For a harassing boss or someone who holds power over your career or livelihood, where direct confrontation could be riskier, defusion, distraction, or interruption are still possible tools for bystanders in the moment. And after the fact, bystanders can also seek out a supervisor or influencer, make a report, or help a target make a report.

At a minimum, bystanders can always show support to targets, who often feel isolated, humiliated, diminished, and alone after a harassing incident. “Going to someone and saying, ‘I saw how they were treating you. I didn’t like it. Is there anything I can do to help?’ Or, ‘It’s not your fault, let’s go talk with human resources.’ That might be all you can do,” Sepler said. “That’s not nothing.”

Categories: Blogs

4 Analytics Concepts Every Manager Should Understand

Harvard business - Wed, 10/31/2018 - 08:00
Jorg Greuel/Getty Images

Like many professionals, my job doesn’t require expertise in data or analytics. I’m a writer and editor, so I deal with words, not numbers. Still, nearly every knowledge worker today needs to be a regular consumer of data analysis. For example, I need to understand whether and why articles on having a mid-career crisis outperformed ones on receiving feedback or why pieces with particular headlines get more traffic than others.

I also need to be able to read research on the topics I cover and understand whether the findings in those studies are valid and generalizable, and be able to articulate the findings — and their limitations — to you, our readers.

To do all of this, I need a more-than-basic understanding of data analytics. And while the statistics course I took in graduate school was helpful, it didn’t fully equip me to grasp the important concepts and have the conversations I need to around data analysis.

Insight Center

Fortunately, I had the opportunity to talk with some of the best experts in the field — Tom Redman, author of Data Driven: Profiting from Your Most Important Business Asset, and Kaiser Fung, who founded the applied analytics program at Columbia University — about several critical topics when it comes to data analysis. Here are four refreshers from our archives on data analytics concepts that every manager should understand.

Randomized controlled experiments

One of the first steps in any analysis is data gathering. This often happens via a spectrum of experiments that companies do — from quick, informal surveys, to pilot studies, field experiments, and lab research. One of the more structured types is the randomized controlled experiment. Many people, when they hear this term, immediately think of costly clinical trials but randomized controlled experiments don’t have to be costly or time consuming and they can be used to gather data on things like whether a particular customer service intervention improved customer retention or whether a new, more expensive piece of equipment is more effective than a less costly one. In this refresher, Tom Redman helps me understand what it means for a test to be “controlled” and how you make sure it includes an element of “randomization.” The article also addresses questions like: What are dependent and independent variables? And what are the steps to designing and conducting one of these experiments?

A/B testing

One of the more common experiments companies use these days is the A/B test (which is a type of randomized controlled experiment). At their most basic, these tests are a way to compare two versions of something to figure out which performs better. Companies use it to answer questions like, “What is most likely to make people click? Or buy our product? Or register with our site?” A/B testing is used to evaluate everything from website design to online offers to headlines to product descriptions. It’s critical to understand how to interpret the results and to avoid common mistakes, like ending the experiment too soon before you have valid results or trying to look at a dashboard of metrics when you really should be focusing on a few. You can learn more about A/B tests here.

Regression analysis

Once you have the data, regression analysis helps you make sense of it. Of course, there are many ways to analyze the data, but linear regression is one of the most important. It’s a way of mathematically sorting out whether there’s a relationship between two or more variables. For example, if you are in the business of selling umbrellas, you might want to know how many more items you sell on rainy days. Regression analysis can help you determine whether and how inches of rain impacts sales. It answers the questions: Which factors matter most? Which can we ignore? How do those factors interact with each other? And, perhaps most importantly, how certain are we about all of these factors?

Fortunately, regression is not something you typically do on your own. There are statistics programs for that! But it’s still important to understand the math behind it and the types of mistakes to avoid. In this refresher, I explain how regression works and share a common — but often misunderstood — warning against confusing correlation with causation.

Statistical significance

Once you’ve done the analysis, you need to figure out what your results mean, if anything. This is where statistical significance comes in. This is a concept that is also often misunderstood and misused. And yet because more and more companies are relying on data to make critical business decisions, it’s an essential concept to understand. Statistical significance helps you quantify whether a result from an experiment is likely due to chance or from the factors you were measuring.

This is a concept I sometimes struggled to fully understand myself but, fortunately, the average professional doesn’t need to understand it too deeply. According to Tom Redman, who helped out with this refresher, it’s more important to understand how to not misuse it.

While you’re boning up on these four concepts, it would also be helpful to read this overview on quantitative analysis from my colleague, Walt Frick. It is a nice primer on why data matters, picking the right metrics, and asking the right questions from data. There’s also a great chart on correlation vs. causation to help you make decisions about when to act on analysis and when not to.

Lastly, if you’re interested in analytics because you need to consume social science research, I highly recommend this piece from Eva Vivalt, a research fellow and lecturer at the Australian National University. She gives several tips for determining whether the evidence from a study should be trusted.

Data analytics is ultimately about making good decisions. It doesn’t matter what business you are in or what your role is at your company, we all want to — need to, really — make smart, informed, evidence-based decisions.

Categories: Blogs

How to Build Great Data Products

Harvard business - Wed, 10/31/2018 - 06:18

Products fueled by data and machine learning can be a powerful way to solve users’ needs. They can also create a “data moat” that can help stave off the competition. Classic examples include Google search and Amazon product recommendations, both of which improve as more users engage. But the opportunity extends far beyond the tech giants: companies of a range of sizes and across sectors are investing in their own data-powered products. At Coursera, we use machine learning to help learners find the best content to reach their learning goals, and to ensure they have the support — automated and human — that they need to succeed.

The lifecycle of a so-called “data product” mirrors standard product development: identifying the opportunity to solve a core user need, building an initial version, and then evaluating its impact and iterating. But the data component adds an extra layer of complexity. To tackle the challenge, companies should emphasize cross-functional collaboration, evaluate and prioritize data product opportunities with an eye to the long-term, and start simple.

Stage 1: Identify the opportunity

Data products are a team sport

Identifying the best data-product opportunities demands marrying the product-and-business perspective with the tech-and-data perspective. Product managers, user researchers, and business leaders traditionally have the strong intuition and domain expertise to identify key unsolved user and business needs. Meanwhile, data scientists and engineers have a keen eye for identifying feasible data-powered solutions and a strong intuition on what can be scaled and how.

To get the right data product opportunities identified and prioritized, bring these two sides of the table together. A few norms can help:

  • Educate data scientists about the user and business needs. Keeping data scientists in close alignment with product managers, user researchers, and business leads, and ensuring that part of their role is to dig in on the data directly to understand users and their needs will help.
  • Have data scientists serve as data evangelists, socializing data opportunities with the broader organization. This can range from providing the organization with easy access to raw data and model output samples in the early ideation stages, to building full prototypes in the later stages.
  • Develop the data-savvy of product and business groups. Individuals across a range of functions and industries are upskilling in data, and employers can accelerate the trend by investing in learning programs. The higher the data literacy of the product and business functions, the better able they’ll be to collaborate with the data science and tech teams.
  • Give data science a seat at the table. Data science can live different places in the organization (e.g., centralized or decentralized), but no matter the structure having data science leaders in the room for product and business strategy discussions will accelerate data product development.

Prioritize with an eye to the future

The best data products get better with age, like a fine wine. This is true for two reasons:

First, data product applications generally accelerate data collection which in turn improves the application. Consider a recommendations product powered by users’ self-reported profile data. With limited profile data today, the initial (or “cold start”) recommendations may be uninspiring. But if users are more willing to fill in a profile when it’s used to personalize their experience, launching recommendations will accelerate profile collection, improving the recommendations over time.

Second, many data products can be built out to power multiple applications. This isn’t just about spreading costly R&D across different use-cases; it’s about building network effects through shared data. If the data produced by each application feeds back to the underlying data foundations, this improves the applications, which in turn drives more utilization and thus data collection, and the virtuous cycle continues. Coursera’s Skills Graph is one example. A series of algorithms that map a robust library of skills to content, careers, and learners, the graph powers a range of discovery-related applications on the site, many of which generate training data that strengthen the graph and in turn improve its applications.

Too much focus on near-term performance can yield underinvestment in promising medium- or long-term opportunities. More generally, the criticality of high-quality data cannot be overstated; investments in collecting and storing data should be prioritized at every stage.

Stage 2: Build the product

De-risk by staging execution

Data products generally require validation both of whether the algorithm works, and of whether users like it. As a result, builders of data products face an inherent tension between how much to invest in the R&D upfront and how quickly to get the application out to validate that it solves a core need.

Teams that over-invest in technical validation before validating product-market fit risk wasted R&D efforts pointed at the wrong problem or solution. Conversely, teams that over-invest in validating user demand without sufficient R&D can end up presenting users with an underpowered prototype, and so risk a false negative. Teams on this end of the spectrum may release an MVP powered by a weak model; if users don’t respond well, it may be that with stronger R&D powering the application the result would have been different.

While there’s no silver bullet for simultaneously validating the tech and the product-market fit, staged execution can help. Starting simple will accelerate both testing and the collection of valuable data. In building out our Skills Graph, for example, we initially launched skills-based search — an application that required only a small subset of the graph, and that generated a wealth of additional training data. A series of MVP approaches can also reduce time to testing:

  • Lightweight models are generally faster to ship and have the added benefit of being easier to explain, debug, and build upon over time. While deep learning can be powerful (and certainly is trending) in most cases it’s not the place to start.
  • External data sources, whether open source or buy/partner solutions, can accelerate development. If and when there’s a strong signal from the data the product generates, the product can be adapted to rely on that competitive differentiator.
  • Narrowing the domain can reduce the scope of the algorithmic challenge to start. For example, some applications can initially be built and launched only for a subset of users or use-cases.
  • Hand-curation — where humans either do the work you eventually hope the model will do, or at least review and tweak the initial model’s output — can further accelerate development. This is ideally done with an eye to how the hand-curation steps could be automated over time to scale up the product.

Stage 3: Evaluate and iterate

Consider future potential when evaluating data product performance.

Evaluating results after a launch to make a go or no-go decision for a data product is not as straightforward as for a simple UI tweak. That’s because the data product may improve substantially as you collect more data, and because foundational data products may enable much more functionality over time. Before canning a data product that does not look like an obvious win, ask your data scientists to quantify answers to a few important questions. For example, at what rate is the product improving organically from data collection? How much low-hanging fruit is there for algorithmic improvements? What kinds of applications will this unlock in the future? Depending on the answers to these questions, a product with uninspiring metrics today might deserve to be preserved.

Speed of iteration matters.

Data products often need iteration on both the algorithms and the UI. The challenges is to determine where the highest-value iterations will come from, based on data and user feedback, so teams know which functions are on the hook for driving improvements. Where algorithmic iterations will be central — as they generally are in complex recommendation or communication systems like Coursera’s personalized learning interventions — consider designing the system so that data scientists can independently deploy and test new models in production.

By fostering collaboration between product and business leaders and data scientists, prioritizing investments with an eye to the future, and starting simple, companies of all shapes and sizes can accelerate their development of powerful data products that solve core user needs, fuel the business, and create lasting competitive advantage.

Categories: Blogs

Research: When Getting Fired Is Good for Your Career

Harvard business - Wed, 10/31/2018 - 06:05
Blaise Hayward/Getty Images

Most leaders are, deep down, afraid of failure. But our 10-year CEO Genome study of over 2,600 leaders showed almost half (45%) suffered at least one major career blow-up — like getting fired, messing up a major deal, or blowing an acquisition. Despite that, 78% of these executives eventually made it to the CEO role.

We conducted additional research on 360 executives, analyzing their careers in depth. While all of them experienced a variety of setbacks, 18% of executives in this dataset faced what many view as the very worst-case scenario: getting fired or laid off. Most of them lost their job at a relatively senior point in their career (only 17% were in their first decade in the workforce at the time they were let go).

What we found is that being fired or laid off doesn’t necessarily have catastrophic effects on leaders’ prospects. We also found that leaders can do some specific things to make sure that a major setback doesn’t become a career-killer.

The good news: 68% of executives who had been let go landed in a new job within six months. An additional 24% had a new job by the end of one year. Even better? 91% of executives who had been fired took a job of similar or even greater levels of seniority.

We even found some signs that the experience of losing a job — when handled the right way — might even make one a stronger candidate for future roles.  In our study, when the interview process included expert third-party assessors engaged by employers to prevent hiring mistakes, 33% of executives who had been previously fired were recommended for hire — compared to 27% of candidates who had never been fired.  Experienced hiring managers know that setbacks are inevitable and want to see how individuals have handled failure in the past. The riskiest hires are the ones who are untested by failure. Executives who have faced failure and learned from it can demonstrate resilience, adaptability, and self-awareness prized in leaders.

About the Research

This article is based on research conducted over 10 years in support of our 2018 book The CEO Next Door. ghSMART has assembled a data set of assessments of over 18,000 C-suite executives across all major industry sectors and company sizes. Each executive assessment includes detailed career and educational histories; performance appraisals; and information on patterns of behavior, decisions, and business results. This data was gathered through structured 4-5 hour interviews with every executive.

That said, executives who had been let go were also more likely to receive a strong “do not hire” recommendation than those who were never fired (46% vs. 36%), indicating that the reason why someone was removed from a role and the way in which they processed that experience did impact their future career potential.

Leaders whose careers soared — not sank — after this setback, did three things differently:

Looked facts in the face… without shame. Those who deflect ownership and instead point to external factors or blame others for failures on their watch don’t do as well. Our data shows that candidates who blamed others cut their chances of being recommended for hire by one-third. Strong performers own their mistakes, and describe what they learned and how they adjusted their behavior and decision making to minimize the chances of making the same mistakes in the future. Having several different types of career blow ups does not derail you. Repeating the same blowup over and over does.

While they own their mistakes, they do so without guilt or shame. Executives who saw their mistakes as failures were 50% less successful than those who took a more learning/growth-oriented approach.

Taking ownership without shame enabled these executives to show themselves as likeable and confident in the interview process for the next role qualities proven to increase chances of getting the job. Analysis of ghSMART assessments by Kaplan and Sorensen showed that the more likable leaders had higher odds of getting hired for any leadership position. Our research with SAS found that highly confident candidates were 2.5 times more likely to be hired.

Leaned on their professional network to get the next job: Candidates were twice as likely to find a job through a professional network than via recruiters or personal network (59% vs. 28%). While friends may be eager to help and lend their sympathetic ear, ultimately the most powerful support comes from those who have seen the results you can deliver based on their direct working experience with you. Search firms have a wide exposure to available positions but typically play it safe and may be reluctant to put their credibility on the line with their client by presenting a candidate who had been fired before. Proactively reaching out to former bosses, colleagues, customers, or peers for whom you have delivered before proves more fruitful than golfing with friends from university or blasting your CV to the recruiting world — although those most eager do all three.

Relied on their experience: 94% of those who landed a new job within 6 months had prior experience in that industry. Hence, one would be well advised to get experience across 2-3 industries early in one’s career, so that if one gets fired, there are multiple industries to rebound into rather than being pigeonholed.

The most important advice both for those looking to rebound and to prevent getting fired in the first place: Pick jobs in the “bull’s eye” of your skills and motivations.

We hope this offers some hopeful news both to people who’ve been let go, and to managers who are in the position of needing to let someone go. One third of the leaders in our CEO Genome study took too long to make people changes — often with damaging consequences for themselves, their teams, and the executive who is poorly fit to the job. If you are agonizing over the need to move someone out of your team, worried about destroying their career, hopefully this research helps you make the right decision for the wellbeing of your whole team and gives you the tools to support the person you are moving out to help them land in the right next opportunity.

We also hope this is useful research for everyone suffering from the fear of failure. While mistakes and career setbacks are painful, a much bigger mistake, according to our data is not taking risks. When we analyzed careers of executives who got to the top faster than average, what set them apart was taking risks to take messy jobs or smaller jobs that nobody wanted or taking on big leaps that felt way over their head.

More than 20 years of advising and coaching leaders has shown us that when you try to achieve something meaningful, you’ll face blow-ups from time to time. What matters more, is that you address the failure as an opportunity for growth. It can be a real travesty when, by playing defense throughout their careers, so many of us miss a chance to grow to our full potential and to live more meaningful lives.  In the words of Oliver Wendell Holmes “Many people die with their music still in them.”

Categories: Blogs

Chinese Activists Are Using Blockchain to Document #MeToo Stories

Harvard business - Tue, 10/30/2018 - 10:00
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One of our main jobs when teaching and advising students who are thinking of founding blockchain companies is to get them to question whether or not their idea actually requires it. Data integrity is the main benefit conferred by blockchain technology, and a few questions can help determine whether that’s a particular problem for a given business or use case:

  1. If the data that my business collects is corrupted, how much do people suffer?
  2. Do outsiders (perhaps hackers) have incentives to distort or change the data that my business is based upon?
  3. How much does my business depend on other people being able to trust the data on which it is built?

Take for example, a digital currency — the first use-case for blockchain. There, if data is corrupted or distorted by outsiders, people lose real money, and the outsider who corrupts the data gains money, making such attacks plausible and to be feared. Therefore, no one will adopt a digital currency unless they can trust their data will not be corrupted or distorted. In other words, there’s at least a plausible reason why you’d want blockchain technology managing currency transactions.

However, all too often blockchain startup ideas don’t really need blockchain. Their data really isn’t that valuable or unique in a way that gives outsiders sufficient economic incentives to launch attacks to try and corrupt or otherwise change it. That’s why a recent use of blockchain technology in China in response to the #MeToo movement is so interesting.

In late 2017, increasing number of stories were being shared on Chinese social media surrounding sexual harassment and abuse of position in Chinese universities. At first, the movement was called woyeshi, the Chinese spelling of “Me Too.”  The Chinese government and technology platforms made repeated attempts to filter out such stories by censoring a variety of hashtags and keywords that campaigners used on Weibo and Wechat. First, woyeshi was censored, and then #MeToo, and finally “Rice Bunny”, which has the same pronunciation as “Me Too” in Chinese. As a result, campaigners turned to blockchain technology to record their stories under the name “Every Snowflake.” This website simply uses a blockchain ledger process to record stories about sexual harassment.

This is a use-case that fulfills the three criteria outlined above. Victims desperately want to not be censored; other parties have a deep interest in censoring them; and people can only find value in stories of discrimination if they have not been censored. “Every Snowflake” is a compelling case where blockchain helped people overcome a real problem of data integrity.

However, this project also highlights some of the challenges of using blockchain technology.

The general weakness of using blockchain lies in its interface with other technologies and the rest of the world. I’ve written before about blockchain’s  “last mile problem.” In this case, the “last mile” challenge comes from the fact that it is still possible to restrict access to data built on the blockchain — for example, by banning the website that displays it.

Last, perhaps the biggest challenge to our privacy lives in the fact that digital data usually lives forever unless someone makes strenuous efforts to delete it. Blockchain is even more extreme; it nearly guarantees the data lives forever. Corrections can’t be made. Stories can’t be modified. This raises challenges. What do libel suits look like when records can’t be deleted from the blockchain? What about the “right to be forgotten” that is built into privacy policy in some countries? In the case of sexual harassment, these aren’t just questions of protecting the accused. What if a victim comes to regret making a statement publicly and wants to withdraw it, perhaps to protect their privacy or even their safety?

Nonetheless, “Every Snowflake” hints at the possibilities of blockchain in our “post-truth” world. Not every interesting idea or business proposal requires the blockchain. But where data integrity is essential, it can be transformative.

Categories: Blogs

Stop Initiative Overload

Harvard business - Tue, 10/30/2018 - 09:50

Rose Hollister and Michael Watkins, consultants at Genesis Advisers, argue that many companies today are taking on too many initiatives. Each manager might have their own pet projects they want to focus on, but that trickles down to lower level workers dealing with more projects at a time that they can handle, or do well. This episode also offers practical tips for senior-level leaders to truly prioritize the best initiatives at their company — or risk losing some of their top talent. Hollister and Watkins are the authors of the HBR article “Too Many Projects.”

Download this podcast

Categories: Blogs

How One Hospital Improved Patient Safety in 10 Minutes a Day

Harvard business - Tue, 10/30/2018 - 09:00
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Most modern health care improvements seem to involve expensive technology and an uncomfortable amount of change management. But clinical and nonclinical staff at the Rotterdam Eye Hospital have improved patient care and raised staff morale at a very modest cost: 10 minutes a day and a special deck of cards.

Members of the hospital’s design thinking team were inspired by something they saw when they boarded a KLM Airline flight: During a pre-flight huddle of the cabin crew, team members introduced each other and then asked each other two questions on flight safety.

When they got back to Rotterdam Eye Hospital, the managers asked themselves why couldn’t they add a similar feature to their own “team-start” huddles? After all, in some ways, the situations were similar: A group whose members may not have worked together before must form a close-knit team quickly and execute their duties in a way that meets the organization’s guidelines to the letter.

Insight Center

To test the idea, hospital managers developed a special patient-safety card game that encouraged coworkers to work together more easily and reinforced their knowledge of core safety and patient care principles. (One of us, Roel, designed and ran the initiative; the other, Dirk, studied it.

Now, a number of other hospitals and long-term care organizations in the Netherlands have started playing the card game too. In 2016 and 2017, a nursing home and a rehabilitation center from Zorgpartners Midden Holland near Rotterdam also adopted the “team-start” huddle and card game and have seen similar improvements in patient care and staff morale.

Here’s how it works:

At the start of every shift, the team members get together for a brief “team-start.” Each team member rates his or her own mood as green (I’m good), orange (I’m okay but I have a few things I’m concerned about) or red (I’m under stress). The rest of the team doesn’t need to know that you’re under stress because you’re having a dispute with your landlord or you are worried about your ill toddler. How you feel, however, is important because it affects how you should be treated.

Next, the team leader asks if there is anything in particular the team needs to know to work more effectively together that shift: For example, “Is there a delay in public transport so we can expect patients to be late for their appointments?,” or “Is there a patient with some kind of special need coming in?”

Sharing the answers or results generated by the card questions and activities with the group ensures that the insights stick.

That’s it.

This routine might not sound like the makings of a significant advance, but Rotterdam Eye Hospital has experienced some significant improvements in service quality since it introduced the card game in 2015. First, the hospital’s performance on its patient-safety audits has risen, and caregiver job satisfaction has improved substantially, moving from 8.0 to 9.2 on a 10-point scale after staff began playing the game. The nursing home and rehabilitation center reported similar results.

The staffers have observed a variety of other gains as well. For instance, the game has encouraged team members to get to know each other better, and patients are reassured when team members are familiar with each other. (We conducted interviews with staff members in the hospital, nursing home, and rehabilitation center, and conducted an informal survey after the initial exercise.)

“The main advantage for me is that I know who I am working with today. Now I know their names and how they are doing,” one doctor said.

Other staff members gained a deeper understanding of the reasons behind certain protocols. “I now understand the importance of some patient safety measures more, and now I know how I contribute to them,” one cleaning person from the rehabilitation center said.

Finally, everyone gained a deeper understanding of the significance of their own job — not always easy in a centralized organization. “I now feel part of the caregiver team,” one nutrition assistant said. “I know now I am not only providing food but am part of making a patient feel safe.”

The game has also encouraged more sharing between members of the staff, particularly between people who often don’t have very many occasions to talk to each other such as cleaning people and doctors. One case in point: A question from the card game about what someone should do if he or she found medicine lying around prompted a cleaning person to mention that she kept finding pills in a patient’s bed, alerting the doctor to the fact that the patient was not taking the prescribed medicine.

Rotterdam Eye Hospital has also introduced the game to other members of the World Association of Eye Hospitals in the United Kingdom, Australia, and Singapore.

Although the game is not expensive to run, it does require management to do the following:

Design the particular card game you need. The card game must be tailor-made for your own culture and focused on your current challenges. A hospital, for example, might stress medication safety and hand hygiene, while a nursing home might focus on understanding the vulnerabilities of the elderly and end-of-life care. Each patient experience card game consists of at least six themes.

Make a commitment to the game. It won’t work if teams play only some of the time.

Require everyone on the team to participate. The game works because everyone knows that he or she is in the same boat and may be put on the spot tomorrow. And we mean everyone — not only the inpatient and outpatient teams but even people in HR and Finance.

We sometimes act as if health care organizations are big machines. But the fact is that the quality of health care depends ultimately on the collective performance of many small teams. The “team-start” huddle and patient experience card game suggests that performance can improve once we take into account the full perspective and emotional needs of the people who are actually delivering that care. The game is a great first step toward building that awareness.

Categories: Blogs

Power Sales Performance by Harnessing Analytics - SPONSOR CONTENT FROM TABLEAU

Harvard business - Tue, 10/30/2018 - 08:30

How often is your sales team making important decisions based on gut feel? Are you sure that deal will close this quarter and was it optimally priced? Are your sales resources allocated properly to drive growth?

In my experience, when sales organizations make major decisions and plans based on gut feelings, there are costly consequences. One company missed its fourth-quarter forecast by a significant amount and had to reset all quotas for the next year, delaying quota distribution by several weeks. Another sales team relied too heavily on experience and judgment to make pricing decisions for large deals and left millions of dollars on the table. One company failed to leverage its data on relative productivity of sales reps across geographies and inefficiently allocated scarce sales resources to the right growth opportunities.

In a world where data is everywhere, too many companies fail to take advantage of the power of data and analytics to fuel sales performance improvement.

Why does this happen in so many companies? Historically, sales has been labeled an art. Selling revolves around people, and with that comes emotion, beliefs, opinion, and the careful management of relationships with customers, partners, and others within the sales organization. Accessing data, and figuring out what to do with it, has been a difficult endeavor. However, with more modern business intelligence platforms emerging, and easier access to sales performance data, the application of science to selling has become a key differentiator in managing the sales organization. Companies that embrace data and analytics as the foundation for sales planning and performance management will achieve breakthrough improvement in sales productivity.

What could this look like? I’ve seen several use cases where advanced analytics have been applied to sales:

• Improved pricing and discounting: Many sales reps and leaders are time-constrained and haven’t been trained to effectively apply data analytics to pricing decisions. Oftentimes, it’s faster and easier to just offer the same pricing to customers or use the floor of the discount matrix to speed up the customer buying process. Typically, sales reps don’t know that other reps in their organization have achieved higher prices for the same deals with similar customers. This is an area where data and analytics can yield several points of margin improvement. With an advanced analytics platform mining all historical sales data, sales leaders can see where they are pursuing suboptimal pricing and challenge sales teams to reconsider their deal structures.

• Better forecasting accuracy: Sales leader judgment can be an important ingredient in forecasting deals, but human judgment often fares far worse than analytical models in assessing the likely outcome of deals and sales teams. The data does not lie. By leveraging data points on opportunities (e.g., the customer’s historic buying behavior, sales rep performance, product type, and sales stage), a predictive model can actually deliver a more accurate forecast than traditional “roll-up” processes can. Using these types of analytical models can also save countless hours in management meetings trying to analyze human judgment and adding “manager overrides” to lower-level forecasts.

• Reduced customer churn: Armed with a comprehensive profile of customer behaviors (e.g., support incidents, attendance at training classes, and website engagement), sales reps and/or customer success managers can more accurately identify at-risk customers and take preventative actions to prevent churn. Marketing outreach can also be tailored to target at-risk customers and increase overall engagement.

Establishing data and analytics as a foundation within the sales organization isn’t easy. Getting there requires leadership to invest time and resources into acquiring the right data, systems, and people to build these new capabilities. In my experience, it’s vital to build the right Sales Operations function with the charter and resources necessary to prepare and analyze data, synthesize the analysis into effective action plans, and drive change management across sales. These leading Sales Operations teams bring deep insight into performance improvement opportunities and become trusted advisors to leaders throughout the company. All of this is built on a solid foundation of data, from governance to preparation to analytics and reporting.

One Brand's Success in the "Science" of Selling

LinkedIn applied data and analytics to empower its sales teams with insights that drove success. Before, the company stored close to a petabyte or more of sales data using internal databases, Google Analytics, Salesforce.com, and third-party tools. One analyst serviced daily sales requests from over 500 salespeople, creating a reporting queue of up to six months, which left team members questioning their performance and the status of customer relationships.

The business analytics team adopted a new BI platform to centralize customer data and used dashboards to track performance and predict churn. To support even deeper analysis, they also leveraged predictive models in the BI platform to forecast churn—empowering sales to increase customer success within at-risk accounts. This has created a more proactive sales cycle and increased revenue. Michael Li, Senior Director of Business Analytics, said, “We decided to focus on how to scale the BI solution that we built and really provide the scalability and empower our sales team to get what they need in time. It became a one-stop shop for sales people to get what they need in a very self-service way.”

Today, 90 percent of LinkedIn’s sales force accesses the BI solution weekly. By tracking overall sales performance and digging deeper to understand the customer experience, sales now identifies when customers increase product usage and can proactively connect around opportunities to increase overall spend and avoid account churn.

Setting up the right processes, systems, and people to acquire, prepare, and analyze key sales data will enable better decision-making for any sales organization. By putting data at the center of your approach to sales planning and performance management, you will also be able to realize a breakthrough in growth and productivity.

Enabling the “Science of Selling”

Building a new capability to harness the power of analytics in sales begins with clean, prepared, and well-managed data. This data must come from a widely-adopted CRM system and should be analyzed by a robust, modern analytics platform. And as mentioned above, the right analytically-minded Sales Operations staff need to be in place to understand the data, glean insights from analysis, and recommend effective actions for sales leaders to take to improve performance.

1) Start with clean data
Enterprises already know the pain of disparate data sources, siloed departments, and legacy software—a broken infrastructure that hinders performance, growth, and development. Scaling advanced analytics enterprise-wide means having consistent definitions and sales practices. This also requires activating staff who will ask the right questions of data, perform analytics, and discern what must happen next.

2) Enable sellers with the right solutions
Globally, how is your CRM system being used? Is your account and opportunity hierarchy defined and structured the same way across teams—does “closed won” mean the same thing to your commercial sales team as it does to your enterprise team, to your teams in the UK and Australia, for example? Setting definitions and hierarchies within your CRM is a best practice that leads to cleaner data. Embrace an analytics platform with the capability to connect to your CRM and other data sources, which has intuitive data-prep tools and optimizes advanced analytics to provide a single source of truth. Then you can take advantage of modern business intelligence capabilities and scale quickly.

3) Hire inquisitive, driven, tech-savvy talent
Beyond standardization of data analytic definitions and processes, you need the right talent in place to set your organization up for success. Your sales operations staff are trusted advisors to the business and should have a seat at the table to support sales planning and resource optimization. For a true ROI in Sales Operations, they should not be relegated to back-office reporting but instead should have the organizational support and technology resources to apply advanced analytics. The right people, empowered with the right analytics platform, and backed by the right data, drives sale performance improvement.

To leverage data analytics to prosper as a modern sales organization and bring more science to your selling, visit the Tableau Sales Analytics Solutions page. This one-stop resource for all things data and sales, will support new and better possibilities for your sales operations.

Categories: Blogs

Myths of the Gig Economy, Corrected

Harvard business - Tue, 10/30/2018 - 08:00
Nattapol Poonpiriya/Getty Images

Every day there are news stories about the so-called gig economy where workers contribute part or full-time labor — not as employees with benefits, but as independent contractors. Dara Khosrowshahi, the CEO of Uber, the ride-sharing giant, proudly declared on September 10 that “very few brands become verbs”. The same week Upwork, a platform for hiring freelancers, filed for an IPO, as did Fiverr, which boasts that it offers a “freelance services marketplace for the lean entrepreneur.” Indeed, the gig economy has not only turned millions of Americans into contractors, but it’s given the more successful entrepreneurs the tools to grow even faster. A fast-moving startup can secure talent as it needs it, outsource more quotidian tasks like payroll, and stay lean and mean; indeed, I see entrepreneurs employ this approach through my work at EY supporting creative, successful startups.

But there are lots of myths about gig work, whether full-time or part time. It’s growing, but not as much as you think, and in ways that may be very different than you imagine. It might even be better for older executives than recent grads. Here are a few myths worth dispelling.

Myth No. 1: Millennials love to gig. There is a common perception that somehow the millennial generation just loves part-time, gig employment. But a recent study by EY found a more complicated picture: Sixty percent of millennials — those born between 1981 and 1996 — were not involved in the gig economy at all, and only 24% report earning money from the gig economy. In fact, the percentage of millennials with full-time careers is rising at a brisk clip from 45% in 2016 to 66% in 2018, according to the data we collected. That reflects a growing economy that’s offering more full-time employment, but it also shows a generation that may want the same thing as their parents: Steady jobs with a clear advancement track and benefits such as health insurance and paid time off.

Myth No. 2: We’re all going to be giggers. The size of the gig economy and how fast it’s growing also seem to be over-imagined at times. The measurements can vary a lot and so can the predictions for how much it’s likely to expand. Back in 2013, a much-touted survey suggested that by 2020 — just over a year from now — a whopping 40% of the workforce would be so-called contingent workers, a number that would include contractors, temps and the self-employed. But here are the facts: the best estimates according to the Gig Economy Data Hub, a joint project of Cornell University’s Institute of Labor Relations and the Aspen Institute, put the percentage at around 30%. That’s a lot and it’s growing. But don’t think the world as you know it is completely disappearing. Only about 10% of workers rely on gig arrangements for their full-time jobs. And on-demand services where you get your next gig from an app like Lyft or Task Rabbit represent an even smaller percentage of gig workers. In fact … less than 1% of workers have used online platforms to arrange work in the past month. Most workers are still grabbing extra hours the old-fashioned way — tending bar or temp work on the side — not by being digitally summoned.

Myth No. 3: Gig is better. In our 2018 EY Growth Barometer, an annual global survey of middle market company leaders, we found some movement away from part-time and gig hiring. Most companies are still committed to full-time hires for all of the advantages that bestows — loyalty, retained knowledge, institutional memory, stealing top talent from the competition. In many cases, you have jobs in which the worker is integral to a team or needs to be supervised. That’s why so many of the entrepreneurs I know use the gig economy where they can, but they also have a deep and abiding interest in hiring great, full-time talent. A gig-based businesses can’t transmit “a culture” in a traditional sense. “You have individuals doing things you have no supervision of, other than the work itself,” said D. Quinn Mills, a professor of business administration at Harvard Business School, in an interview. Mills noted that while the gig economy can benefit companies and is likely to expand, it’s not for every business.

Myth No. 4: Gig work is unfulfilling. There’s a perception that gig jobs are dead-end jobs. Not true. Consider Jody Greenstone Miller who has had a stunning career from the White House to the Walt Disney Company. The Los Angeles lawyer-turned-entrepreneur is the co-founder and CEO of Business Talent Group (BTG), which pairs high-end talent with high-end expertise in areas such as finance, operations, and mergers and acquisitions at companies such as Pfizer, Kraft, and MasterCard. Miller said in an interview that her that stable of top talent wants “to be able to choose who we work with and what we work on.” This lines up with EY’s recent findings. On a global basis, according to our 2018 Growth Barometer, a lack of skilled talent is a bigger headache for US companies than for those in other countries, with 25% of US survey respondents citing this as a challenge to growth compared to 10% of their counterparts elsewhere. With U.S. unemployment at a historic 40-year low, there just aren’t the numbers of suitably qualified people in the talent pool to hire.

Lisa Hufford, a consultant author of Navigating the Talent Shift, has worked with gig talent for years. She’s seeing first-hand that while the gig economy isn’t the answer to all problems, it can help startups meet their talent needs at lower costs and help mature companies grow. It can also be a surprising boon to baby boomers and Generation Xers. “We were raised at a time when there weren’t a lot of options, and now there are so many choices,” says Hufford, a member of Generation X, in an interview. “For people who didn’t grow up that way, it can feel overwhelming. I like to help people navigate that shift. They realize they have a lot of skills that companies want and a lot of options. It’s kind of cool.”

Categories: Blogs

Your Team Doesn’t Need a Data Scientist for Simple Analytics

Harvard business - Tue, 10/30/2018 - 07:00
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Arthur Nielsen, market research pioneer and founder of the Nielsen Corporation, once said, “The price of light is less than the cost of darkness.” As data proliferates across the enterprise, this observation by Nielsen is rendered even more relevant, because data represents the unlit fuel that has the potential to light the darkness, but which often lacks the spark of analytics that enables us to see.

The mission of enabling data analytics in today’s enterprise is hobbled by the lack of the requisite skills in the marketplace, including: advanced statistics/mathematics, new analytics methodologies, advanced systems analysis, business fundamentals, regulatory and legal understanding, and general IT technical and data architecture skills.

To cope with the shortfall in market supply, companies need to better leverage their existing talent. Having founded a data management company and worked with hundreds of organizations over the past 20 years to execute their information management and analytics initiatives, I’ve found the groups that are able to successfully utilize their company’s analytics technologies often take the following approaches:

Build a team. One strategy is to take the team approach to cross-pollinate and commingle the required skillsets; bringing together a diversity of skills and backgrounds from within your organization to achieve a common goal is a highly effective method.

Insight Center

Start by identifying the characteristics and needs of your organization’s environment. For example, highly complex product and service environments will require domain experts or subject matter experts. Simpler product environments will require experts in operations, logistics, and supply chain. Formulate teams that reflect your particular needs, and consciously design your team’s framework and composition to transfer skills across functional or organizational boundaries.

Find the supporting players. I suggest going outside your department in order to lay the foundation for functional analytics initiatives. It will be productive to search across your organization for a few relevant skillsets that will enable your team to make use of the data available:

  • Data analytics experts: They understand the basics of analytics and can navigate between what’s possible and what’s relevant, using the latest methodologies and technologies available.
  • Data experts: They understand the data formats, the layout and content, especially the data schema and interrelationships.
  • Data architects: They know how data is stored and architected, including the plumbing that connects them. The perfect theoretical analytical approach can crash ignominiously when it takes an impossible amount of time to simply access the data. Particularly in these days of heady cloud adoption, one should be sensitive to latencies involved in moving data to and from the cloud.
  • IT technology and process experts: They understand the nature of the data flow and operational processes. They play an important role in leveraging available IT tools to access data while being aware of key issues.
  • Records managers: They are the curators of business records, both physical and digital. They know the locations of important documents and how they are categorized and catalogued.

Seek creativity and curiosity. The foregoing is a good start at convening a team of diverse skill sets in order to enable, if you will, “analytics for the rest of us.” However, there is one set of essential traits to be found in your team that will drive the initiative. Seek individuals who are innovative, frugal, and creative, who produce maximum results with minimal resources. In data analytics, such combinations of creativity and flexible thinking can make a huge difference in producing actionable results, while reducing time, effort, and costs.

For example, I spoke with one data analyst at a payments processor who claimed to predict riots with a high level of accuracy in the wake of the Ferguson unrest. One would have thought it was from comprehensive analyses of complex demographics and collections of red-flag news indicators of social discontent. It wasn’t. He simply tracked the sales of riot-related components such as crowbars and flammable fluids from major hardware outlets and looked for spikes in purchases that exceeded a certain threshold.

This combination of creativity and curiosity is difficult to teach but essential to effective analytics. Finding team members with such characteristics can make all the difference.

Make the data usable. Given that you’re unlikely to find an abundance of individuals with exceptional data management skills, it’s necessary to employ methodologies and technologies that present data in an accessible, visual, and intuitive fashion.

This has been demonstrated in our first-hand experience using internal enterprise data already under management for compliance and legal purposes to identify the “go-to” people in an organization. Rather than conducting complex analyses of high performance metrics, dictated by the type of role or function, and customized for each department or region, we used graphical analysis to discover a much easier proxy to get to the same approximate result: We analyzed individuals’ inbound communications to assess the frequency of questions and from how high up the organization they came, and then analyzed the outbound communications to assess the frequency of answers and to how high up the organization they went. The go-to people lit up like a fireworks display.

Note that this approach identified the top performers regardless of function or role, and took a fraction of the effort required in more traditional approaches. It is the technology that can make analytics tasks more intuitive and visual, thereby reducing the need for deep technical or statistical skills.

Consult legal and compliance stakeholders. Finally, in order to ensure that your analytics initiatives are in compliance with legal requirements and new privacy regulations such as GDPR and the California Consumer Privacy Act, it’s advisable to consult the right legal and compliance stakeholders:

  • Legal and Compliance Managers: They understand at a high level what data can be stored, and how they can be used, while minimizing the risk of running afoul of legal and regulatory guidelines.
  • Regulatory Data Managers: They understand which data is retained or deleted due to regulatory obligations, which can increase or reduce capabilities, and possibilities in data analytics projects.
  • Data Protection Officers: A new and timely role, these privacy experts can help analytics stay on the right path and avoid triggering penalties from incoming and expanding privacy regulations.

Lighting the Path Ahead

Data analytics is a powerful and promising source of competitive advantage. To enable such a strategy in the face of a difficult shortfall of the requisite talent in the marketplace, one must fall back on developing existing employees through cross-training and cross-pollination of team members and experts.

To embark on this strategy, we shouldn’t wait for that singular blazing torch-bearer to light the darkness. It is more pragmatic to help the rank-and-file member to become a candle, and from the collective light, illuminate the darkness.

Categories: Blogs

4 Ways to Pressure-Test Strategic Decisions, Inspired by the U.S. Military

Harvard business - Tue, 10/30/2018 - 06:05
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Every leader wants to avoid major strategic mistakes, but, in a complex world, it’s hard to anticipate all the forces that might impact your goal. It’s vital to find weaknesses in your strategies before you implement them — and developing a rigorous process to do so.

The ability to poke holes in one’s own strategies is something the U.S. military has practiced and refined over centuries. Rick served in the U.S. Army for 35 years, retiring as a Lieutenant General, and has seen this firsthand. In the heat of battle, strategic planning that’s incomplete or simply wrong causes leaders to revert to on-the-spot decision making. While sometimes necessary, making it up as you go is more often associated with failure — and loss of life — and is often a symptom of ineffective or inaccurate anticipation of competitive moves or environmental shifts.

The same is true in business, and the techniques the military has honed can help executives anticipate problems and change course when necessary.

Build situational awareness

Simply put, situational awareness (SA) is achieved after a soldier has deliberately assessed an environment from various vantage points and has ensured that all potential perspectives have been captured.

In the business world, things are fuzzier — there are no landscapes, buildings, or troop movements to scan. But it’s still crucial to make sense of the environments in which we operate and foresee how different factors will affect our decisions.

One way to build one’s situational awareness is to talk through alternate realities. Although this sounds like science fiction, alternative realities are basically hypotheticals. We think X will happen, but what if Y or Z happens?

At Merck, where Jay served as Chief Strategy and Business Development Officer and President of Emerging Businesses, “alternate realities” were used to prevent “team think,” which frequently occurs when organizations believe the conventional view of a situation is the correct one.

To develop better situational awareness, start by forming  teams and tasking them to develop alternatives based on different views of the same situation. For example, what if a new competitor enters the market earlier than expected? What could they do that would surprise and/or outmaneuver us? What if they are delayed; what types of things might they do to try to recover and penetrate the market more quickly? Could any of their actions be extreme or desperate? What actions could and should our team consider mitigating or blunting the risk in these alternate scenarios?

The next step is to compare these hypotheticals collectively and then determine what counter measures will have the most impact.

 Most importantly, make sure to consider specific “triggers” that would indicate one or more of the alternative scenarios is unfolding. Agreeing on these triggers up front is useful because they prospectively define specific thresholds for change in action or direction. Once identified, you should track these triggers regularly on a dashboard that all senior team members see. This eliminates or greatly reduces debate when course changes become necessary and urgent. Then, make sure that group leaders complete an SA assessment regularly and discuss the alternate scenarios and triggers during each business review.

Small investments of time can result in new insights about your organization’s readiness, and your leaders’ acumen, that would have gone unnoticed until crisis.

Develop an outside-in perspective

This is another technique that’s routine in the military and can highlight unique but under-leveraged capabilities or untapped sources of competitive advantage. Think of aircraft. For a long time, the military used planes primarily to increase visibility of topography and troop movements, but starting in the early 1900s, the military began using planes to delivery ordinance and to conduct warfare. What are your organization’s aircraft?

Frequently, these are ancillary assets or capabilities that are often considered to be a “cost of doing business.” These could include a controlled global supply chain, unique abilities to test compounds, proprietary communication channels with key constituents, unique manufacturing machinery, etc. Think to yourself: In future scenarios, could any of these become new lines of business? If your environment changes unexpectedly could any of them help you to adapt?

In companies, an outside-in perspective can help shape an honest view of your organization’s strengths (and weaknesses). Customers can be a great source for this and forming a strategic advisory council is another option.

Game it out

Another practice is war-gaming, and there is often no substitute for putting real people into the mix to see how they react. Even complex AI simulation, while helpful, can lack the variability and ingenuity of human creativity. The US Military has become an expert in preparing for combat operations using war games.  Most notable is the establishment of the National Training Center in the Mohave Desert in California where the US Army conducts live, force-on-force battles to refine its capabilities.

At Merck, war-gaming exercises around critical decisions were used frequently. The best way to do this is to assign high performing managers to lead “opposing” teams, which should be made up of individuals with expertise across relevant functional areas. Before the exercise, make sure to prepare a background that  outlines the general challenge and provides specific information and data. A best practice is to task the line area most responsible for the situation with organizing and leading the overall exercise — and to make sure that each group presents their findings at the end. Incentivizing “opposing” teams for success will help ensure a robust simulation. For example, consider inviting a senior leader to judge the readout, and offering a cash bonus or team recognition for the winning team, or both.

Form diverse, strategic groups

Finally, form strategic initiatives groups, and populate them with people who can analyze problems from various perspectives.

At Merck, the strategic initiative group often came up with alternate decisions and actions on key business issues.  In one case, the choice to position a new product as second line treatment versus trying to displace a well-accepted initial therapy turned out to be uniquely advantageous, helping achieve a launch that far exceeded expectations.

Categories: Blogs

Workplace Posting Requirements for Remote Workers – Ask #HR Bartender

Hr Bartender - Tue, 10/30/2018 - 02:57

(Editor’s Note: Today’s post is brought to you by our friends at Poster Guard, a division of HRdirect and the leading labor law poster service that gets your business up to date with all required federal, state and local labor law postings, and then keeps it that way — for an entire year.  Enjoy the article!)

Remote work is more than just a passing fad. In a study by AND CO and Remote Year, more than 23 percent of the remote workers they surveyed said their organization is fully distributed. And technology tools like Slack are helping remote workers collaborate on projects.

But it raises the question, how do organizations communicate with employees when it comes to topics like workplace compliance postings. I know we need to be focused on the work, but we also need to make sure all employees know their rights as required by federal, state, and local law.

I had the opportunity to speak with Ashley Kaplan, senior employment law attorney for HRdirect about this issue. Ashley leads the expert legal team for Poster Guard® Compliance Protection. On a personal note, I’ve known Ashley for years and I’m thrilled to share her knowledge.

Even though today’s post is sponsored, please remember that Ashley’s comments shouldn’t be construed as legal advice or as pertaining to any specific factual situations. If you have detailed questions, they should be addressed with your friendly neighborhood labor and employment attorney.

Ashley, before we talk about the posting requirements for remote workers. It might be good to discuss, in general, the current posting requirements for organizations.

[Kaplan] Sure. All employers must post federal, state, and local (if applicable) postings. The mandatory federal posters include:

  • Equal Employment Opportunity (EEOC)
  • Occupational Safety and Health Act (OSHA)
  • Family and Medical Leave Act (FMLA)
  • Uniformed Services Employment and Reemployment Rights Act (USERRA)
  • Fair Labor Standards Act (FLSA)
  • Employee Polygraph Protection Act (EPPA)

In addition, there could be up to 15 additional state-specific posters, depending upon what state you’re in … and up to 10 additional posters for city/county compliance. Oh, and don’t forget there are additional posters for government contractors and certain industries. The topics for these state, local, and industry-specific postings include minimum wage, fair employment, child labor, unemployment insurance, workers’ compensation, expanded family/medical leave rights, smoking in the workplace, electronic cigarettes, human trafficking, and more.

For HR pros who just read that list and are saying to themselves, “I have no idea if I have the right posters up!” is there a government site that will tell them everything they need?

[Kaplan] Sadly, no. The postings are issued by multiple different government agencies. Believe it or not, HR professionals have to visit each agency’s site to find out posting requirements. There are 175 different agencies responsible for issuing more than 370 posters at the federal and state level. Add to that the approximately 22,000 local jurisdictions that have the authority to issue their own postings. That’s a lot of follow-up and unfortunately, these agencies aren’t required to coordinate efforts.

Okay, so potentially HR pros have several sites to check. But do posters really change that often?

[Kaplan] Surprisingly, they do. Our Poster Guard legal team monitors posting changes and has found that there are approximately 150 state-specific post changes per year, with half of them requiring mandatory updates. I’m sure that big changes, like minimum wage increases, most businesses are aware of. But businesses need to pay attention to the small changes too because the government isn’t required to notify businesses when those changes happen. Also, be aware that mandatory posting changes are issued throughout the year, not just in January. 

I honestly don’t remember labor law posters being so complex. How do current labor law posting requirements impact remote workers?

[Kaplan] By law, you’re required to provide these mandatory notices to ALL employees. That includes remote workers such as employees who work from home, offsite, on the road, at mall kiosks, in mobile service units, out in the field, and at construction checkpoints.

Does this mean that HR needs to send remote workers full-size laminated posters to hang in their spare bedrooms/home office?

[Kaplan] No, but it does mean that employees need to receive notices. Although the regulations don’t specify the format — paper or electronic — organizations are responsible for communicating the same information to your remote workers as those onsite. For employees who work on computers as part of their jobs, we recommend electronic delivery of postings, where workers can download, view and acknowledge receipt of all required postings. This satisfies your obligation to communicate their rights, as covered in the mandatory federal and state notices.

That raises another question about what information should an employee receive. If a company has remote employees who work in different states, which posting requirements should they follow? Those from the state where the company is headquartered or the state where the employee works?

[Kaplan] Unfortunately, it’s not always clear which state laws apply in this instance. Most basic employment rights — such as minimum wage, overtime and safety issues — are governed by the laws where the employee performs the work. However, depending on how your company is structured, your out-of-state employees may be covered by both states’ laws. Because it depends on so many factors, we recommend you provide both sets of state-specific postings to remote workers in this situation. 

What if an organization has some employees who work from home, but they report to the office headquarters occasionally. Do they still need to send posters electronically to the remote worker?

[Kaplan] The law isn’t 100 percent definitive on how frequently a remote employee must access the physical wall posters to be covered.  However, FAQs published by the U.S. Department of Labor (DOL) suggest that, if an employee reports to a company’s physical location at least three to four times a month, the physical postings at the business are adequate. If not, the DOL recommends electronic delivery.

Last question, there could be people thinking, “Labor law posters aren’t a big deal. If we don’t have them, we’ll just get a warning.” What’s the penalty for businesses who are not in compliance?

[Kaplan] Recently, the amount for federal posting fines increased to more than $34,000 per violation, per location. State and local fines range from $100 to $1000 each. But the real price tag comes in terms of lawsuits or investigations.

An agency could be on-site for a number of reasons, such as an immigration issue, OSHA inspection, wage and hour audit, or EEOC complaint. The first thing they will do is look for up-to-date postings, and non-compliance can negatively impact the outcome of the investigation.

The real danger is with employment litigation. A missing or outdated posting can impact damages and can even ‘toll’ or extend the statute of limitations. And as your readers know, the statute of limitations can often be an employer’s best friend in defending claims.

A HUGE thanks to Ashley for sharing her experience with us. If you want to learn more about how to make sure your posting requirements are up to date, I hope you’ll check out PosterGuard. Today’s technology makes providing remote workers with their postings easy. They also guarantee their work against government posting fines. Right now, they’re offering HR Bartender readers a discount to try their Poster Guard Compliance Protection service. Just use the code SC28549 at checkout to receive 25 percent off their compliance protection service, and the two products they have for remote workers. The code expires on December 31, 2018.

Compliance matters. It’s important to the organizational bottom-line. And when employees – regardless of whether they work remotely or in the office – know that organizations are transparent about their rights, it creates trust and engagement.

P.S. Mark your calendars! I hope you’ll join me and the Poster Guard team on Wednesday, November 7, 2018 at 2p Eastern for a TweetChat about trends and best practices of working with remote workers. Follow the HRdirect Poster Guard Twitter account (@hr_direct) for more details.

Image captured by Sharlyn Lauby while exploring the Wynwood Wall Art District in Miami, FL

The post Workplace Posting Requirements for Remote Workers – Ask #HR Bartender appeared first on hr bartender.

Categories: Blogs

When We Make All (or Most of) the Money

Harvard business - Mon, 10/29/2018 - 12:19

From the Women at Work podcast:
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Women are increasingly supporting our families financially. It can feel empowering to be the sole or primary earner, but many of us feel pressure to be both an ideal worker and an ideal mother. We hear from a woman who supports a stay-at-home husband and three sons.

Then, Alyson Byrne fills us in about the research on women as financial providers — for example, the more we financially contribute, the better our psychological well-being. (Yay.) She has tips on managing the professional side and the personal side of being the chief breadwinner. And Maureen Hoch, Women at Work’s supervising editor, shares her experience of being her family’s primary earner.

Guest:

Alyson Byrne is an assistant professor at the Faculty of Business Administration at Memorial University of Newfoundland.

Resources:

Fill out our survey about workplace experiences.

Email us here: womenatwork@hbr.org

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

Categories: Blogs

When Companies Should Invest in Training Their Employees — and When They Shouldn’t

Harvard business - Mon, 10/29/2018 - 09:00
Photodisc/Getty Images

According to one industry report, U.S. companies spent over $90 billion dollars on training and development activities in 2017, a year-over-year increase of 32.5 %. While many experts emphasize the importance and benefits of employee development — a more competitive workforce, increased employee retention, and higher employee engagement — critics point to a painful lack of results from these investments. Ultimately, there is truth in both perspectives. Training is useful at times but often fails, especially  when it is used to address problems that it can’t actually solve.

Many well-intended leaders view training as a panacea to obvious learning opportunities or behavioral problems. For example, several months ago, a global financial services company asked me to design a workshop to help their employees be less bureaucratic and more entrepreneurial. Their goal was to train people to stop waiting around for their bosses’ approval, and instead, feel empowered to make decisions on their own. They hoped, as an outcome, decisions would be made faster. Though the company seemed eager to invest, a training program was not the right way to introduce the new behavior they wanted their employees to learn.

You and Your Team Series Learning

Training can be a powerful medium when there is proof that the root cause of the learning need is an undeveloped skill or a knowledge deficit. For those situations, a well-designed program with customized content, relevant case material, skill building practice, and a final measurement of skill acquisition, works great. But, in the case of this organization, a lack of skills had very little to do with their problem. After asking leaders in the organization why they felt the need for training, we discovered the root causes of their problem had more to do with:

  • Ineffective decision-making processes that failed to clarify which leaders and groups owned which decisions
  • Narrowly distributed authority, concentrated at the top of the organization
  • No measurable expectations that employees make decisions
  • No technologies to quickly move information to those who needed it to make decisions

Given these systemic issues, it’s unlikely a training program would have had a productive, or sustainable outcome. Worse, it could have backfired, making management look out of touch.

Learning is a consequence of thinking, not teaching. It happens when people reflect on and choose a new behavior. But if the work environment doesn’t support that behavior, a well-trained employee won’t make a difference. Here are three conditions needed to ensure a training solution sticks.

1. Internal systems support the newly desired behavior. Spotting unwanted behavior is certainly a clue that something needs to change. But the origins of that unwanted behavior may not be a lack of skill. Individual behaviors in an organization are influenced by many factors, like: how clearly managers establish, communicate, and stick to priorities, what the culture values and reinforces, how performance is measured and rewarded, or how many levels of hierarchy there are. These all play a role in shaping employee behaviors. In the case above, people weren’t behaving in a disempowered way because they didn’t know better. The company’s decision-making processes forbid them from behaving any other way. Multiple levels of approval were required for even tactical decisions. Access to basic information was limited to high-ranking managers. The culture reinforced asking permission for everything. Unless those issues were addressed, a workshop would prove useless.

2. There is commitment to change. Any thorough organizational assessment will not only define the skills employees need to develop, it will also reveal the conditions required to reinforce and sustain those skills once a training solution is implemented. Just because an organization recognizes the factors driving unwanted behavior, doesn’t mean they’re open to changing them. When I raised the obvious concerns with the organization above, I got the classic response, “Yes, yes, of course we know those issues aren’t helping, but we think if we can get the workshop going, we’ll build momentum and then get to those later.” This is usually code for, “It’s never going to happen.” If an organization isn’t willing to address the causes of a problem, a training will not yield its intended benefit.

3. The training solution directly serves strategic priorities. When an organization deploys a new strategy — like launching a new market or product — training can play a critical role in equipping people with the skills and knowledge they need to help that strategy succeed. But when a training initiative has no discernible purpose or end goal, the risk of failure is raised. For example, one of my clients rolled out a company-wide mindfulness workshop. When I asked a few employees what they thought, they said, “It was interesting. At least it got me two hours away from my cubicle.” When I asked the sponsoring executive to explain her thought process behind the training, she said, “Our employee engagement data indicated our people are feeling stressed and overworked, so I thought it would be a nice perk to help them focus and reduce tension.” But when I asked her what was causing the stress, her answer was less definitive: “I don’t really know, but most of the negative data came from Millennials and they complain about being overworked. Plus, they like this kind of stuff.” She believed her training solution had strategic relevance because it linked to a vital employee metric. But evaluations indicated that, though employees found the training “interesting,” it didn’t actually reduce their stress. There are a myriad of reasons why the workload could have been causing employees stress. Therefore, this manager’s energy would have been better directed at trying to determine those reasons in her specific department, and addressing them accordingly — despite her good intentions.

If you are going to invest millions of dollars into company training, be confident it is addressing a strategic learning need. Further, be sure your organization can and will sustain new skills and knowledge by addressing the broader factors that may threaten their success. If you aren’t confident in these conditions, don’t spend the money.

Categories: Blogs

Working with a Colleague Who Feels That the World Is Against Them

Harvard business - Mon, 10/29/2018 - 08:09

Some people love to play the victim. Nothing is ever their fault and everyone around them is out to get them. Having a coworker like this can take a toll on you. So what’s the best way to protect yourself? How can you help your colleague change their mindset? And how do you handle the emotional toll of working with this person? 

What the Experts Say
Working alongside someone who always feels like a victim “is an inherent downer,” says Holly Weeks, a lecturer at the Harvard Kennedy School and author of Failure to Communicate“You feel stuck,” she says. “You see this person walking towards you and your heart sinks.” Perhaps the biggest challenge in dealing with a colleague who has this mentality is “the negativity” that this person exudes, says Amy Jen Su, managing partner of Paravis Partners and coauthor of Own the Room. “When you are busy, the last thing you need is to be around someone who views the world as glass half empty,” she says. Still, you’re not helpless. “The one thing you can control is your response,” Su says. Here’s some advice on how to deal with this decidedly difficult colleague.

Be empathetic
To begin, recognize that your colleague’s perpetual victimhood “is not about you,” says Su. “So don’t take it personally.” Try to reserve judgment. “Compassion helps,” she adds. “Notice that this person views the world differently than you do. And it must be hard to live every day in victim mode.” Weeks recommends trying to “shift how you see the person,” and then “adjusting your psychological reaction in any way that helps.” Be empathetic. Remember: your colleague is not purposely trying to make you crazy. “It’s like when you hear that your plane’s takeoff is delayed. You can dwell on it and get angry, or you can cool your jets and try not to let it bother you,” says Weeks. Your objective is not “necessarily to view your colleague with sympathy, but to be neutral.”

Be positive
Next, think about how you’ll “protect yourself from absorbing your colleague’s toxic behavior,” says Su. A little self-preservation is in order. She recommends spending time with colleagues who provide a “counterbalance” to this difficult one. “You need to surround yourself with people who bring you energy, lift you up, and who are positive forces.” When you have to spend time with this person, find ways to decompress afterward, whether it’s taking a walk, meditating, or listening to music. And, importantly, even if this particular colleague rubs you the wrong way, try to find something about this person to like, says Weeks. “Find different facets to them,” she advises. Don’t focus on their “freaked out, whiny, and paranoid side.” Look for commonalities — at the very least, you’re both committed to your organization.

Provide a counter narrative
Dealing with a colleague like this can be mentally exhausting — especially if you’re regularly listening to the person’s complaints. But you don’t have to “be passive in this recital of woe,” says Weeks. Instead, “shift this person’s focus away from the bogeyman” by “offering a counter narrative” to that version of reality. Say, for instance, your colleague grouses about a boss who they perceive as giving them more work than anyone else on the team. She suggests saying something like, “I know it’s stressful. I bet the boss is doing it because you’re so competent and reliable and doesn’t think it will put a strain on you.” Your response isn’t patronizing, rather it’s showing an alternative way of seeing the situation. Remember: your goal is to help the person “choose a different mindset.”

Offer validation
Offering validation can also be helpful in these circumstances, says Su. “Validation is often the missing link for people like this,” she explains. “They don’t feel seen or heard and so they think, ‘If I complain” — or play the victim — “I will get some acknowledgment and some appreciation.” She says that sometimes these people just need positive reinforcement that they’re not getting elsewhere. Don’t be disingenuous, of course, but “if the compliment is well-deserved it might quell the noise.” This doesn’t mean that you endorse their complaints, rather that you recognize their positive accomplishments. 

Propose solutions
Another possible response to your colleague’s litany of complaints is to offer solutions to problems, says Su. “This person may be complaining because they have an unspoken need that’s not being addressed,” she says. In this case, you should “go into coach mode. Say, ‘Are there expectations you have that others may not be aware of?’ Or: ‘I hear you are upset about XYZ, let’s brainstorm ways to resolve it.’” Your goal, according to Weeks, is to focus “not on your colleague’s feelings,” but on the professional challenges. Empower your colleague and “brace yourself around the issues,” she says. Whatever you do, don’t “encourage the dynamic” of constant carping. If nothing more, your colleague will realize that you’re not fun to grumble to and will likely lose interest in the conversation.

Be direct with your colleague
The prospect of confronting a colleague about their behavior can invoke profound feelings of dread. “But if this person is taking a toll on business results, you need talk to them about the impact they’re having,” says Su. Be gracious and considerate. “Say: ‘You are a leader on this team. I can see you’re under stress, but when you complain, it brings the team down. Can you be more mindful of what you’re telegraphing?’” Your aim is to show your colleague that “their mood has a ripple effect.” Your tone and word choice are critical here, according to Weeks. “If you say, ‘You’re paranoid and you whine a lot,’ your colleague is not going to hear it.” Instead, focus on the behavior they should be exhibiting not the behavior you wish they’d stop.

Talk to your boss
It might also be worthwhile to talk to your manager about the situation. The decision to go to your boss, however, is not straightforward, says Su. “In some ways, if you complain to the boss, you’re becoming this person,” she says. But if you believe that your colleague’s conduct is “taking a toll on the team or having a negative impact on the business,” you need to speak up. Don’t center the conversation around “personalities,” says Weeks. Rather, “talk in terms that are useful” to your boss. “Make it about the work.” You might say, for instance, that this person is distracting. The goal is to “frame the issue in a way that your boss realizes this is not the dynamic they want in the office.”

Set limits
Finally, make your boundaries clear. “If this person is always coming by your desk to vent, you need to set new rules of engagement,” says Su. Don’t be rude or disrespectful. But be upfront about your limits. “Go quiet and use you your body language to signal that you don’t want to get into it.” Even if “you feel like you can’t fix the situation, you can at least contain it,” adds Weeks. “As soon as you see the person coming, say, ‘I have about six minutes to talk.’” It’s not a perfect strategy, but “at least you won’t have to suffer very long.” Your goal is to be “neither a doormat nor an enabler.”

Principles to Remember

Do

  • Demonstrate empathy and compassion for your colleague.
  • Try to shift your colleague’s focus away from complaining by offering solutions to their problems.
  • Talk to your colleague about their behavior and the effect it’s having on the team. Your aim is to show your colleague that their mood has a ripple effect.

Don’t

  • Encourage the dynamic with a colleague who is constantly carping. When you don’t join in, this person will realize you’re not fun to grumble to.
  • Let the negativity drag you down. Surround yourself with colleagues who bring you energy, lift you up, and who are positive forces.
  • Be a doormat. Be upfront about your boundaries and set limits on how much time you’re willing to spend with this person.

Case Study #1: Find something to like about this person and focus on solutions
Duke Greenhill, Vice President of Creative & Strategy at J.O., an advertising agency in Fort Worth, Texas, once worked closely with someone who lived in perpetual victimhood. The employee — we’ll call him Sam — worked in the account services department.

Sam whined a lot, recalls Duke. “The world, fate, God, Yaweh, chance, luck, you name it…they were all conspiring against him. Sam also felt everything was personal, and probably had a healthy dash of narcissism. His every response began with ‘But.’”

In the beginning, Duke tried to be compassionate. He reflected on the things he liked and admired about Sam. “Sam wasn’t bad [at his job] by any stretch of the imagination,” he says. “He was driven and tenacious.”

But Duke admits that this initial approach was maybe a little too soft. “I was, perhaps, overly empathetic — read: enabling — at first, and so Sam began bringing his woes directly to me.”

Duke felt he needed to take action, especially because he knew all too well the dangers of playing the victim. “I used to be [like] Sam in some ways and so I told him about my own similar experiences,” he says. “I also showed him at every opportunity that people/life/the world are not black or white. Through metaphor and everyday examples, I think I helped him see things differently.”

Duke also focused on helping Sam change his perspective by asking him to think about possible solutions to the challenges he faced. “I told him: ‘Don’t come to me with problems and complaints unless you also come to me with at least one potential solution/reframing,’” he says.

Over time, Sam complained less and also proactively began to try to solve his own problems. He also stopped playing the victim as often. He has since moved on to another company. “I hear that Sam is doing well,” says Duke.

Case Study #2: Talk to your colleague about the impact his mood has on the team
Christian Rennella, the CEO of oMelhorTrato — a South American company that helps customers find and compare prices of credit cards and insurance services — has recent experience working with someone who felt the world was out to get them.

About six months ago, his company hired an engineer in the field of artificial intelligence. In many ways, the employee — we’ll call him Ethan — has worked out very well. “The progress he has made has been spectacular,” he says. “Thanks to Ethan, we have been able to automate a large part of our processes and that has helped us grow.”

But Ethan has also proved to be a challenging personality. “It always seemed that he was the victim and that he was never to blame — whether the imagined culprit was within the company or in the larger world of AI,” says Christian. “He had a constant tendency to focus on what happened around him rather than his own work.”

At first, Christian wasn’t sure what to do. But upon reflection, he realized that the behavior was having a negative impact on others. “I saw that the rest of the team also noticed Ethan’s complaints and it was an uncomfortable situation at times.”

Christian decided to talk to Ethan. He wanted to show him that his negativity and victim mindset affected others. “So, in a one-on-one meeting, I highlighted the various times in which he played the victim,” he says.

Christian’s tone was respectful and considerate. “I told him that instead of looking for excuses, what we need from him is to look for solutions.” He also explained that he was making the team uncomfortable.

Ethan didn’t realize that he was having that kind of impact, according to Christian. “He took what I said to heart — and he’s made many adjustments,” he says. “His personality has changed for the better.”

Categories: Blogs

Using Bundled Payments to Improve the Patient Experience

Harvard business - Mon, 10/29/2018 - 08:00
Hero Images/Getty Images

In 2013, The Center for Medicare and Medicaid Innovation launched the Bundled Payments for Care Improvement (BPCI) initiative, a program that proponents hoped could rein in health care costs by “bundling” payment for the full gamut of services that comprise an episode of care. The model certainly seemed like a good bet, as it would reward hospitals for reducing the cost of soup-to-nuts care for any of 48 conditions and penalize them for overruns. Indeed, bundled care for hip and knee replacement has been a dramatic success with clear savings and no increase in emergency department visits, readmissions, or 30-day mortality.

However, our research suggests that bundles may not work as well for other types of conditions. That doesn’t necessarily mean that the problem lies with the bundled payment model itself. Rather, we think it could lie with the fragmented nature of the patient journey in a dysfunctional system, which is exposed by medical bundles’ lack of impact. But before delving into that diagnosis, let’s step back and look at the research.

Insight Center

With our colleagues John Orav and Jie Zheng, we used Medicare claims from 2013 through 2015 to identify admissions for the five most common medical conditions covered under the Medicare bundled payment initiative: heart attack, heart failure, pneumonia, chronic obstructive pulmonary disease, and sepsis. We calculated the costs of each “episode” — the hospitalization plus all costs in the 90 days post discharge — for hospitals that joined BPCI as well as hospitals that didn’t join (our control group). We then looked to see whether costs dropped more in the BPCI hospitals than the control hospitals after the program started. Overall, the average Medicare payment per episode of care across the five conditions — about $24,000 — dipped just a few hundred dollars, a statistically insignificant amount. In addition, there was no difference in the change over time based on whether hospitals were or weren’t participating in the program. We also didn’t find any differences in clinical complexity, length of stay, emergency department use or readmission within 30 or 90 days after hospital discharge, or death within 30 or 90 days after admission between the intervention and control hospitals. In short, for these five common medical conditions, bundled payment had no impact on costs or clinical outcomes — at least in the program’s first year.

We don’t know exactly why bundles were successful for hip and knee replacements, but not for medical conditions. Perhaps all the hospitals that signed up for the hip and knee bundles were much more motivated than the hospitals that signed up for the medical bundles. Or perhaps we just need to wait longer to see an impact of bundling on a wider range of conditions.

However, we suspect that these patterns reflect the complexity and fragmentation of the patient journey for common medical conditions as a cause and shed light on not only how we might help hospitals succeed under bundles, but how we might also improve patient experience.

Hip and knee replacements are discrete, pre-planned events with a fairly standardized and consistent patient journey, from pre-operative evaluation to scheduled OR date to post-operative rehabilitation, and with a single “captain” of the ship. The surgeon performing the operation is ultimately responsible for the entirety of that patient’s clinical course. For the patient too, there is an obvious point person before the admission, during the hospitalization, and after discharge. Most patients who have had a total joint replacement could tell you the name of their surgeon even years after the procedure, often with great fondness.

Medical admissions follow an entirely different course. Consider what happens to a patient coming to the hospital with a heart failure exacerbation. She certainly did not plan the admission, and may have no pre-existing relationship with the clinician she sees in the hospital. She sees the emergency department physician who happens to be on duty that day, and depending on clinical severity, bed availability, and the call schedule of the residents and interns if she’s in a teaching hospital, could end up admitted to a general medical service, hospitalist service, cardiology service, medical intensive care unit, or cardiac intensive care unit. Her care team could change daily, including the nurses and nursing assistants. During her stay in the hospital she may see cardiologists, internists, and nephrologists, as well as physical therapists, pharmacists, social workers, and discharge planners. At discharge, she may or may not be scheduled to come back to see anyone that was involved in her inpatient care, depending on where she wishes to establish or maintain cardiovascular follow-up, and there is likely no post-discharge protocol for follow-up and rehabilitation, nor formal relationships with the nursing facility or home health agency to which she is discharged.

To improve this patient’s journey though the health care system — and increase the chance that bundled payments can help her achieve better outcomes and help the system lower its costs — we first need to understand the journey. Patterns of care are heterogeneous for medical conditions compared with discrete elective surgeries. And perhaps the overwhelming complexity and fragmentation of the patient journey for most unplanned medical admissions explains both why medical bundles are hard, and why they are so very important.

The early failure of medical bundles is a window into the disjointed, piecemeal health system most of our patients (and clinicians themselves) experience. Even the first step for hospitals electing to participate in BPCI for a medical condition — trying to figure out who needs to be around the table to discuss improving care across the clinical episode — is not an easy one.  But rather than discourage us from using bundles as a way to improve care, this complexity makes it all the more critical to use mechanisms like bundled payment programs to incent health systems to change the paradigm. Hospitals can and should design and implement standardized clinical pathways and provide more coordinated, efficient care for medical conditions, and bundling may be a powerful policy mechanism to help get us there.

The five years of experience we have had with BPCI seems like a sufficient time to have learned a lot about it. And perhaps with more time and greater incentives hospitals will be better able and more willing to make the changes needed in care delivery for medical bundles to be effective and to create a better experience for patients. But for now, we are only scratching the surface, and there is much more to learn about the use of bundling for different conditions and different patients. Indeed, bundling is just one in a series of policy innovations that Medicare and others are experimenting with to move us past traditional fee for service. The road to better policy will be long and winding.  We can only hope that on the way we will discover much about more efficient care, and most importantly, ways to both control costs and improve outcomes that matter to patients.

Categories: Blogs

Higher Wages Aren’t Enough to Turn Mediocre Jobs into Good Ones

Harvard business - Mon, 10/29/2018 - 07:43
Image Source/Getty Images

Facing a tight labor market as the holiday shopping season approaches, many retail companies will undoubtedly consider following the lead of Amazon, which recently announced that it is raising its minimum hourly wage for all of its U.S. employees, including those working at Whole Foods stores, to $15 — $7.75 above the federal minimum wage.

Higher wages are good for retail and other low-wage service workers. So, we applaud Amazon’s decision and hope others will do the same. Higher wages are also necessary for many companies that are stuck in a vicious cycle of bad jobs, bad operations, bad customer service, low productivity, and high costs. But higher wages alone are not enough to break this vicious cycle. Unless accompanied by other changes, higher wages will likely reduce company profits and will not turn bad jobs into good ones.

Drawing on the concept of “efficiency wages,” some economists argue that higher pay can by itself improve performance by enabling companies to attract and retain better people and by motivating employees to work harder. But without other changes, we expect these benefits to be small. As one of us has witnessed first-hand while working at a large retailer, even highly skilled and motivated workers will not be able to be as productive as expected because the company’s operational systems got in their way, wasting rather than maximizing their skills and enthusiasm.

We see roadblocks like this all the time and, if you do any store shopping, so do you. For example:

  • Constant display changes that take hours to set up and break down — hours that could have been spent on much-higher-value work like helping customers and trying out process improvements.
  • Last-minute promotion or delivery changes that require managers to spend their time on last-minute schedule changes, which then disrupt employees’ lives and drive absenteeism, turnover, and understaffing, all of which increases the likelihood of errors.
  • Employees who are not empowered to improve their work or solve customer problems. They need management approval for even the smallest things, such as accepting a return or making a price change. When they have an idea for improvement, they are shut down by a manager who is already overwhelmed with all the firefighting she or he has to do.
  • Equipment and technology — such as scan guns, refrigerators, and training or scheduling software — that frequently breaks down, forcing employees to spend hours on the phone with help desks or just go without critical equipment for days or weeks.
  • Stores overwhelmed by a daily stream of directives from headquarters, dozens of sales reports to read, and 100+ management tools to use.

Raising the minimum wage won’t make any of these obstacles go away. It just means companies are wasting their employees’ time and paying more for it. In addition, these obstacles will likely hurt motivation and increase turnover by reducing workers’ sense of achievement, pride, and meaning.

Higher wages may not even allow companies to meet workers’ basic needs if companies are not offering livable take-home pay, predictable schedules, and clear career paths.

Take-home pay. More than hourly wages, workers care about take-home pay. The U.S. Bureau of Labor Statistics cited $23,210 as the median annual wage for a retail salesperson in 2017, but that assumes a regular 40-hour week. In service industries like retail and fast-casual dining, that’s rarely the case. It is not uncommon to have more than half the employees working part-time and even so-called full-timers aren’t usually guaranteed 40 hours a week. Part-time hours might make sense for high school or college students looking to make extra money, but in 2017, the median ages of a retail salesperson and a cashier were 36 and 26. These are people who need a living wage to support themselves and their families.

Companies don’t always realize how few hours their employees work; at one organization, executives told us that they were surprised that most of their hourly employees worked fewer than 15 hours per week and earned under $10,000 a year. So for companies thinking about raising wages, setting targets for actual take-home pay and tracking progress in that regard can help ensure that their workers are earning a living wage.

Predictable schedules. Apart from the instability that comes from not knowing what your pay will be week to week, it’s challenging trying to plan childcare, transportation, and the rest of your life when you get your schedule only a few days in advance, as is the case for many service workers. It’s also expensive. Companies known for offering good jobs provide schedules three to four weeks in advance and new legislation in places including California and Seattle is prompting others to follow suit. Companies that adopt this practice will not only be better employers; studies have shown that stable retail schedules can also drive sales and labor productivity.

Career paths. Today’s take-home is important to workers — but so is tomorrow’s. The best employers offer workers the opportunity to develop new skills, demonstrate their abilities, and move up the ranks, securing a better financial future for themselves and their families. For example, good jobs companies like Costco and QuikTrip promote almost exclusively from within for field positions, giving workers a clear path to higher pay and increased responsibility. Companies that want to attract and retain better workers will find that creating such paths is something their employees care a lot about.

Higher wages will not lead to higher performance for companies or good jobs for workers if companies do not fix their systems. If they create a system that increases the productivity, contribution, and motivation of employees, then higher wages will be one of the several forces driving high performance and good jobs. Luckily, we know a lot about the ingredients of that system.

Categories: Blogs

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