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30 Sep 2019|by Dina Gerdeman
When Barack Obama was elected president in 2008, some saw it as proof that the color of one’s skin could no longer hold people back from achieving important leadership roles in the United States.
Not true, says Harvard Business School senior lecturer Anthony J. Mayo. “Obama’s election created this false illusion of a post-racial society, where many people thought we had transcended issues of race,” he says. “But that was not the case at all.”
It certainly wasn’t the experience for many of the black business executives included in the book Race, Work, and Leadership: New Perspectives on the Black Experience, co-edited by Mayo, University of Virginia Professor Laura Morgan Roberts, who is a visiting scholar at HBS, and David A. Thomas, president of Morehouse College and a former professor at HBS.
“These African American executives never reported feeling, even during the Obama years, that race was no longer relevant or that we had somehow collectively moved beyond race in the workplace,” Roberts says.
The picture that emerges from the essays in Race, Work, and Leadership echo the same message: Race not only still matters in the American workplace, but it remains a powerful barrier that prevents African Americans from ascending to leadership roles.
The data is indeed bleak. While an increasing number of African Americans are earning bachelor’s and graduate degrees, the number of black people in management and senior executive positions remains scarce and stagnant. Today, there are only three black CEOs of Fortune 500 companies, and not one of them is a woman.
What doesn’t help, the authors say, are recent incidents in the news, including the 2017 white supremacist march in Charlottesville, Virginia, and the 2018 arrest of two black men at a Philadelphia Starbucks after employees called the police to complain they were trespassing, even though they were just waiting for a business acquaintance.
“Given the racist rhetoric and vitriol in the air right now, racism is more prevalent today than we would have hoped,” says Mayo, the Thomas S. Murphy Senior Lecturer of Business Administration. “We’ve made some progress in the workplace, but we still have such a long way to go. It’s more important than ever to discuss what organizations can do about it.”
The book describes the experiences of African American workers and offers advice to black employees who seek to advance in their careers. It also provides these recommendations for companies that are intent on building diverse workplaces:
1. Encourage employees to talk about race
After two fatal police shootings of black men in 2016, Tim Ryan of PwC asked his staff to gather for a series of conversations about race. Two years later, when one of PwC’s own black employees was shot to death by an off-duty police officer, Ryan emailed his employees with a plea to keep talking.
Yet, the explicit discussion of race is considered taboo at many companies, and, more often than not, business leaders remain silent on the issue. That cloak of silence from the top tends to enfold all employees. Ellis Cose, an author of several books about race and public policy, writes that young black professionals who aspire to advance to senior leadership positions typically adopt the strategy of remaining silent about race and inequality to avoid being labeled “agitators.”
In a 2017 study by Sylvia Ann Hewlett and colleagues, 78 percent of black professionals said they have experienced discrimination or fear that they or their loved ones will, yet 38 percent felt it is never acceptable to speak about their experiences of bias at their companies.
All that hushing of the topic can make African American workers feel as if companies are not willing to address their concerns that their talent is being undervalued or squandered, which can leave them feeling less engaged with colleagues, less satisfied with their work, and less loyal to their companies, according to the book.
2. Help white colleagues contribute to the race conversation
Black leaders shouldn’t be the only ones talking about race, the authors say. It’s time for their white colleagues to stop pretending racial tensions don’t exist and start initiating conversations at work, even if they worry about feeling uncomfortable or saying the wrong thing.
“We can’t just rely on the small percentage of black executives who reach the top to wave the flag. That’s an unfair burden,” Mayo says. “If real systemic change is going to happen, it has to come from the white majority who often are in positions that give them greater leverage to change the environment. That being said, white employees may worry about their ability to effectively discuss race, but if they approach it with a sense of openness and learning, they can play an important role in advocating change.”
Managers must learn to create safe spaces at work to have these conversations and let employees know it’s OK to talk about incidents in the news, like police shootings of black people, by asking them, “How does that make you feel?”
“When black employees bring their full identities to work, they bring a set of stories and experiences that can be both painful and powerful, yet it can be hard for them to let their guard down and connect,” Mayo says. “So, creating the psychologically safe environment to have these conversations is important, with managers learning how to provide the proper support during these discussions.”
3. Tackle systemic inequality, starting with the corporate culture
Many organizations have created diversity and inclusion programs in an attempt to recruit and retain more minorities, but the initiatives often fall short, the authors say.
The problem: These programs tend to focus on helping black employees fit into the status-quo culture, rather than eliminating systemic inequality within their organizations. Companies should focus on managing injustice, rather than “managing blackness,” Courtney McCluney and Veronica Rabelo write in their chapter of the book.
Companies can start by using data analytics to assess whether employees feel included on their teams and are treated fairly within their larger organizations. “These surveys should be broken down by demographic categories, including race and gender, to identify certain populations that have a lower engagement or sense of commitment to the organization,” Roberts suggests.
4. Keep confronting racial bias in hiring
Companies should train managers to root out racial bias from their hiring and recruitment processes. They should also invest in retaining black professionals, in part by reinforcing the message that race will not be a barrier to advancement.
“Some of the most difficult conversations about creating racially diverse organizations are getting sidelined.”
That’s especially important today, since inclusion programs have shifted in recent years toward recognizing more forms of diversity—based on gender and sexual orientation, for instance. Employers need to make sure that discussions about race aren’t getting lost as they work to make other groups feel like they belong.
“It’s good that we’re recognizing more forms of diversity,” Roberts says. “But, it seems like we’re talking more generally about belongingness now, and some of the most difficult conversations about creating racially diverse organizations are getting sidelined. We have to make sure we aren’t erasing race from the conversation.”
5. Support employees so that they can be themselves
Research shows that minorities at work feel pressure to create “facades of conformity,” suppressing some of their personal values, feeling unable to bring their whole selves to work, and believing they should nod in agreement with company values, according to the book.
Mayo says creating opportunities for people to bring their authentic selves to work boosts engagement and helps employees contribute more to the organization.
Creating a support network for workers can go a long way. Research shows that when professionals from diverse backgrounds have solid relationships with their managers and co-workers, they’re more satisfied and committed to their jobs. These relationships can grow through day-to-day work interactions, but also through informal get-togethers.
For instance, employees at one consulting company started a book club that focused on black writers and coordinated visits to African American museums and historical sites. And when American Express was looking to gain a better understanding of its African American customers, company officials tapped black employees for their insight, which helped signal that race is important, the authors say.
6. Be mindful of the “mini me” phenomenon
Managers should also check themselves when they evaluate their employees’ performance and advancement potential, taking a hard look at whether they’re choosing a “mini me” when they hand out a plum assignment or consider promotions, Roberts says.
“A lot of managers will say, ‘This guy has potential because he reminds me of myself when I was younger.’ Some people get a pass, and there’s a lower bar to being given an opportunity, while other people have a higher bar based on their identity,” she says. “So, it’s important to be race conscious when evaluating people’s potential to make sure these decisions aren’t biased.”
Once that potential is identified, managers should coach their workers, provide regular feedback, and champion them, showing them they have their backs as they learn and even make mistakes.
“With an underrepresented group, you need to have managers in your corner who are going to have some skin in the game, put themselves out there, and support you in your career, just as they would support your majority counterparts,” Mayo says. “They’re not just going to throw you into the deep end of the pool and expect you to survive on your own. Instead, they’ll stick with you to provide the support you need to succeed.”
About the Author
Dina Gerdeman is senior writer at Harvard Business School Working Knowledge. [Image: PeopleImages]
Robotic process automation (RPA), commonly referred to as “bots,” is a type of software that can mimic human interactions across multiple systems to bridge gaps in processes that previously had to be handled manually. RPA software applications can be integrated with other advanced technologies such as machine learning or artificial intelligence. But at the most basic level, they act like super-macros following a detailed script to complete standardized tasks that do not require the application of judgment.
Why Combine RPA and Lean Six Sigma?
Replacing manual work with bots removes the possibility of human error, reduces rework and quality checks, while also increasing accuracy. Bots can work much faster than humans and at any hour of the day so long as the underlying systems are operational. The potential to reduce overhead costs and increase process cycle time is vast. Bots also provide enhanced controls for risk avoidance.
Bots can serve as a foot in the door to gain traction for a quality program. Senior level executives get excited by the potential of this relatively affordable technology. By incorporating a thoughtful Lean Six Sigma (LSS) process review into a company’s bot deployment strategy, quality programs will gain additional visibility and leadership support.
Effective Bot Deployment at Edward Jones
Edward Jones is a financial services firm serving more than 7 million clients in the US and Canada. Their operations division began exploring RPA in 2017 and subsequently implemented their first bot into production in November 2018. Since then, they’ve deployed 17 additional bots, yielding 15 full-time employees in capacity savings, which in turn generated more than a million dollars in cost avoidance. While still at an early stage in this journey, the operations division has developed a structured approach using LSS tools to assess process readiness for automation, minimize or remove non-value-added work steps prior to development (abandonment), and redesign the process to fully leverage the benefits of RPA.
LSS Process Review
Using a questionnaire to begin their intake process, business areas submit critical data regarding process volumes, capacity needs, system utilization and risk level. This data feeds into a prioritization matrix that allows them to decide where to focus energy and time. Once a process is identified for RPA, a member of the quality team engages the business area for a LSS process review using familiar tools such as a project charter, stakeholder analysis, SIPOC (suppliers, input, process, outputs, customers) and process maps.
After thoroughly understanding the process’s current state, the practitioner and corresponding business area redesign the process for robotics. Next, they complete an FMEA (failure means and effect analysis) and business continuity plan to ensure process risk is being adequately controlled. After this LSS process review has concluded, a broad group of experts – including robotics developers, internal audit staff, risk leaders and senior leadership from all impacted business areas – are brought together to jointly review the robotics proposal and agree on a go/no-go decision.
A critical component of this process review is thorough documentation of every step along the way. Using an Excel playbook to organize all the tools in one place enables a smooth transition as the effort moves from the quality team to the robotics development team. Then, this comprehensive documentation is retained by the business area for ongoing maintenance. Specific elements of this documentation include a systems inventory, a record of all sign-off dates and approvals and a business continuity plan for disaster recovery. Having complete documentation enables the business areas to take a proactive approach when faced with upcoming system changes or unexpected work disruptions. It also equips business areas with any data points required for routine internal or external audits.
Deployment Pitfalls to Avoid
There are some specific areas of concern when it comes to RPA.
- Communication: Provide clarity to business areas about what RPA can and cannot do, and what processes fit best with this technology. Without an accurate understanding of the capabilities of RPA, there will be an influx of unsuitable requests for this new technology and, as a result, many disappointed business areas and wasted effort spent putting together their business case. At Edward Jones, the most common misunderstanding was regarding the lack of reading ability for the specific RPA vendor being used. While the bots can recognize characters in static fields, they are not able to interpret characters in an unstructured context. This ruled out many initial RPA requests. Additionally, while comparing RPA to macros was initially an effective way to explain the technology to business leaders that were not knowledgeable about technology development, this comparison created an unfortunate misconception that coding and implementing bots was as fast and easy as creating a macro. Business areas were not expecting development time to take four to six months for what they perceived to be a simple request.
- Change Management: Incorporate thoughtful change management throughout the deployment at all levels of the organization. Leveraging bots will take away manual tasks being completed by employees. Some employees may welcome the automation of monotonous tasks, but others may view this technology as a threat to job security. Supervisors will need to adapt and grow their skills to include oversight of the RPA technology. Strong people leaders often don’t have the same level of competency in the technical space, and they will need to quickly increase knowledge and skill to effectively manage their automated processes. Senior/C-suite leaders will need to consider the inherent risks associated with using RPA, the infrastructure and skills needed to support an RPA program, and how to obtain the needed resources and talent.
- Human Resources: Bots may create job redundancy, creating the potential for job loss reassignment. Engage human resources early to navigate these situations.
- Governance: Balance senior leader involvement so they feel comfortable with automation without extra levels of required approvals that slow the development process down.
- Don’t Force a Problem to Fit the Solution: RPA is not the right solution for every bad process. In the early phase of bot deployment, it is easy to let excitement about the new technology lead to poor choices around when to apply RPA. This leads to disappointing results that could undermine the entire bot deployment. Identify clear criteria regarding when bots are an appropriate solution and use a disciplined approach to evaluate each new process improvement opportunity. Consider non-bot solutions before a final decision is reached.
- Vendor Approvals: Any third-party vendors must permit bots to interface with their systems. Review vendor contracts or have new contracts signed to ensure bots are legally allowed to interact with vendor systems and web sites before beginning development.
- Resource Constraints: Set clear expectations with business areas about the work involved and resources needed to design and implement an RPA solution. The quality team and technical developers do not have the knowledge required about the specific processing steps to complete this work without a subject-matter expert from the business area being heavily involved throughout the project life cycle.
- Results: Heavy focus on capacity savings only tells part of the story. Identify other meaningful methods of communicating value from RPA implementation, such as risk reduction, faster cycle time, improved client experience or increased accuracy.
Case Study: Automating Retirement Disbursements to Charities
An example of an RPA implementation at Edward Jones involves the process of receiving, validating and executing on client requests to send monetary donations from qualified retirement accounts to charitable organizations. Prior to implementing the bot, the Qualified Charitable Distribution (QCD) process required 11 hours of manpower each day to get through the volume of donations – and the number of requests had been doubling each month.
The process had five to 10 errors monthly due to the manual data entry required, which in turn took one to three hours of leader or senior processor time to resolve. A bot was designed and implemented that would validate the original request (quality check) and then enter the appropriate data into a computer screen to issue the check to the selected charity.
Stakeholder Analysis and SIPOC
After the project charter was created and agreed upon by the project Champion and project team, a stakeholder analysis was conducted to identify any additional individuals or business areas that were upstream or downstream of the process or might be affected by a change to the process. These parties were consulted or communicated with throughout the effort to ensure process impacts were understood and considered as the automation opportunity was identified and designed.
Next, a SIPOC matrix was created to understand all the process inputs, including systems, data files and end users. Together, the stakeholder analysis and SIPOC are essential in ensuring all critical components of the process upstream and downstream are identified early in the automation effort so no processing gaps are created during RPA development.
|SIPOC Analysis: SIPOC for the QCD Automation Project|
|Client, branch team||Clilent instructions, intranet form message||Branch team sends form message with client instructions for QCD||Unexcuted client request in the retirement department queue||Retirement support team|
|Retirement support team||Form message, client account information, IRS rules, client request||Retirement associate reviews client request for QCD to confirm eligibility||Validated client request||Retirement support team|
|Retirement support team||Validated client request||Issue check||Executed request, issued check||Client, branch team|
|Retirement support team||Client request, issued check||Close client request on system||Completed client request for QCD||Client, branch team|
Current- and Future-State Process Maps
The next step was to create detailed current- and future-state process maps. The current-state process map must include enough detail to highlight all the data sources required by the process, and where that data must be entered to move the process forward. The future-state map must incorporate all of those critical points, while also accounting for the limitations of RPA technology (inability to “read”) and the advantages of RPA (directly ingesting data files, speed and accuracy).
For the QCD process, the client verification step needed to be handled differently for RPA than in the original process. Previously, an employee was comparing client names between the original client request and the account registration referenced in the request to ensure a match. Names can be difficult for RPA to match because the technology doesn’t understand common nicknames that might be used interchangeably with legal names. For example, “Bill” and “William” would flag as a mismatch by the robotic technology, while a human processor would recognize those as referring to the same individual. To avoid large numbers of false positives from the bot flagging mismatches caused by nicknames, an alternative form of identification matching was used, in this case a social security number.
In a typical Six Sigma effort, the goal is to achieve a more streamlined future-state process map with less processing steps and fewer decision points. One key difference between process maps for an RPA effort compared to a more typical Six Sigma improvement effort is that the future-state process maps may contain more, not fewer, steps and decision points. This is normal and shows that the automation capability is being fully utilized to provide a higher level of accuracy. Since the bot processes at a speed much faster than a human can achieve, these additional quality checks do not add to the overall process cycle time. Each decision point with RPA represents a quality assurance checkpoint, allowing for the final output to have higher accuracy than the original process achieved.
Figure 1: QCD Process – Before BPA
Figure 2: QCD Process – After RPA
Once the future automated state has been identified, conduct a risk assessment to understand the risks associated with the current process and how the process risks may be affected by RPA. The largest risk associated with the QCD process was the manual nature of the process and likelihood of human error. This risk was eliminated by using bots.
However, automation adds different types of risks, including system failures and coding errors. By identifying potential risks and using control reports to quickly identify and remediate issues, these risks can be effectively managed.
Business Continuity Plan
The final element of the process review is a business continuity plan, specifically focused on failure of RPA to successfully perform the programmed tasks. Consideration should be given to a failure of the bot itself but also any underlying systems that the bot needs to interact with to obtain data or execute requests. Planning should include how to perform the work if the automation is not operational for a particular timespan as well as how to identify and resolve errors made by the bot if the programming becomes corrupted.
Through this planning exercise, a critical aspect of the QCD process was identified that may have led to future bot failure had it not been remedied. Volumes for this highly seasonal process rise drastically at year end, and a single bot was unlikely to keep up with the work at this peak. Programmers were able to proactively solve this issue by diverting process volume onto three separate bots to stay on top of the surge of work during these high-volume time periods.
The QCD bot was implemented in September 2019 and immediately realized 11 hours of capacity savings with no errors. The total project cycle time from the initial continuous improvement analysis, through the bot design, development, testing and implementation took seven months. Since implementing RPA on this process, 100 percent of the process has been automated with zero errors. Process risk was reduced by one point on a 10-point scale by eliminating human error from manual work steps.
During routine follow-up six months after bot implementation, the project team learned that the benefits received from the automation had grown significantly. The volume of client requests for charitable distributions had increased rapidly, so the bot was now performing work that would have taken 34 hours – or five employees – to complete each day.
Don’t short cut the methodology when leveraging RPA and other new technologies. Technology masks a bad process, so clean up the underlying work steps first to maximize the benefit of RPA.
I’ve written a number of blog posts about regression analysis and I’ve collected them here to create a regression tutorial. I’ll supplement my own posts with some from my colleagues.
This tutorial covers many aspects of regression analysis including: choosing the type of regression analysis to use, specifying the model, interpreting the results, determining how well the model fits, making predictions, and checking the assumptions. At the end, I include examples of different types of regression analyses.
If you’re learning regression analysis right now, you might want to bookmark this tutorial!
Why Choose Regression and the Hallmarks of a Good Regression Analysis
Before we begin the regression analysis tutorial, there are several important questions to answer.
Why should we choose regression at all? What are the common mistakes that even experts make when it comes to regression analysis? And, how do you distinguish a good regression analysis from a less rigorous regression analysis? Read these posts to find out:
- Tribute to Regression Analysis: See why regression is my favorite! Sure, regression generates an equation that describes the relationship between one or more predictor variables and the response variable. But, there’s much more to it than just that.
- Four Tips on How to Perform a Regression Analysis that Avoids Common Problems: Keep these tips in mind through out all stages of this tutorial to ensure a top-quality regression analysis.
- Sample Size Guidelines: These guidelines help ensure that you have sufficient power to detect a relationship and provide a reasonably precise estimate of the strength of that relationship.
Tutorial: How to Choose the Correct Type of Regression Analysis
Minitab statistical software provides a number of different types of regression analysis. Choosing the correct type depends on the characteristics of your data, as the following posts explain.
- Giving Thanks for the Regression Menu: Patrick Runkel goes through the regression choices using a yummy Thanksgiving context!
- Linear or Nonlinear Regression: How to determine when you should use one or the other.
- What is the Difference between Linear and Nonlinear Equations: Both types of equations can model curvature, so what is the difference between them?
Tutorial: How to Specify Your Regression Model
Choosing the correct type of regression analysis is just the first step in this regression tutorial. Next, you need to specify the model. Model specification consists of determining which predictor variables to include in the model and whether you need to model curvature and interactions between predictor variables.
Specifying a regression model is an iterative process. The interpretation and assumption verification sections of this regression tutorial show you how to confirm that you’ve specified the model correctly and how to adjust your model based on the results.
- How to Choose the Best Regression Model: I review some common statistical methods, complications you may face, and provide some practical advice.
- Stepwise and Best Subsets Regression: Minitab provides two automatic tools that help identify useful predictors during the exploratory stages of model building.
- Curve Fitting with Linear and Nonlinear Regression: Sometimes your data just don’t follow a straight line and you need to fit a curved relationship.
- Interaction effects: Michelle Paret explains interactions using Ketchup and Soy Sauce.
- Proxy variables: Important variables can be difficult or impossible to measure but omitting them from the regression model can produce invalid results. A proxy variable is an easily measurable variable that is used in place of a difficult variable.
- Overfitting the model: Overly complex models can produce misleading results. Learn about overfit models and how to detect and avoid them.
- Hierarchical models: I review reasons to fit, or not fit, a hierarchical model. A hierarchical model contains all lower-order terms that comprise the higher-order terms that also appear in the model.
- Standardizing the variables: In certain cases, standardizing the variables in your regression model can reveal statistically significant findings that you might otherwise miss.
- Five reasons why your R-squared can be too high: If you specify the wrong regression model, or use the wrong model fitting process, the R-squared can be too high.
Tutorial: How to Interpret your Regression Results
So, you’ve chosen the correct type of regression and specified the model. Now, you want to interpret the results. The following topics in the regression tutorial show you how to interpret the results and effectively present them:
- Regression coefficients and p-values
- Regression Constant (Y intercept)
- How to statistically test the difference between regression slopes and constants
- R-squared and the goodness-of-fit
- How high should R-squared be?
- How to interpret a model with a low R-squared
- Adjusted R-squared and Predicted R-squared
- S, the standard error of the regression
- F-test of overall significance
- How to Compare Regression Slopes
- Present Your Regression Results to Avoid Costly Mistakes: Research shows that presentation affects the number of interpretation mistakes.
- Identify the Most Important Predictor Variables: After you’ve settled on a model, it’s common to ask, “Which variable is most important?”
Tutorial: How to Use Regression to Make Predictions
In addition to determining how the response variable changes when you change the values of the predictor variables, the other key benefit of regression is the ability to make predictions. In this part of the regression tutorial, I cover how to do just this.
- How to Predict with Minitab: A prediction guide that uses BMI to predict body fat percentage.
- Predicted R-squared: This statistic indicates how well a regression model predicts responses for new observations rather than just the original data set.
- Prediction intervals: See how presenting prediction intervals is better than presenting only the regression equation and predicted values.
- Prediction intervals versus other intervals: I compare prediction intervals to confidence and tolerance intervals so you’ll know when to use each type of interval.
Tutorial: How to Check the Regression Assumptions and Fix Problems
Like any statistical test, regression analysis has assumptions that you should satisfy, or the results can be invalid. In regression analysis, the main way to check the assumptions is to assess the residual plots. The following posts in the tutorial show you how to do this and offer suggestions for how to fix problems.
- Residual plots: What they should look like and reasons why they might not!
- How important are normal residuals: If you have a large enough sample, nonnormal residuals may not be a problem.
- Multicollinearity: Highly correlated predictors can be a problem, but not always!
- Heteroscedasticity: You want the residuals to have a constant variance (homoscedasticity), but what if they don’t?
- Box-Cox transformation: If you can’t resolve the underlying problem, Cody Steele shows how easy it can be to transform the problem away!
Examples of Different Types of Regression Analyses
The final part of the regression tutorial contains examples of the different types of regression analysis that Minitab can perform. Many of these regression examples include the data sets so you can try it yourself!
- Linear Model Features in Minitab
- Binary Logistic Regression: Predicts the winner of the 2012 U.S. Presidential election.
- Multiple regression with response optimization: Highlights features in the Minitab Assistant.
- Linear Regression: Great Presidents by Patrick Runkel and my follow up, Great Presidents Revisited.
- Linear regression with a double-log transformation: Examines the relationship between the size of mammals and their metabolic rate with a fitted line plot.
- Nonlinear regression: Kevin Rudy uses nonlinear regression to predict winning basketball teams.
- Orthogonal regression: Carly Barry shows how orthogonal regression (a.k.a. Deming Regression) can test the equivalence of different instruments.
- Partial least squares (PLS) regression: Cody Steele uses PLS to successfully analyze a very small and highly multicollinear data set.
by Martha Lagace
All of the most valuable firms in the world today are platforms, starting with Apple, Microsoft, Google and Amazon. But platforms do not evolve in predictable ways, and there is a lot that managers and entrepreneurs can learn about past, present, and future platform strategies.
To shed light on the challenges and opportunities posed by digital platforms, The Business of Platforms: Strategy in the Age of Digital Competition, Innovation, and Power is a new book by Harvard Business School Professor David B. Yoffie and coauthors Michael A. Cusumano and Annabelle Gawer.
Across seven chapters the authors explain the fundamentals of platforms, different strategies and business models, common errors, and platform battlegrounds of the future that involve competing technologies and implications for organizations. There is advice for traditional firms looking to build or join platforms, as well as for entrepreneurs and startups. The authors discuss issues of power and of managing privacy, fairness, and public trust.
Martha Lagace: What trends are you seeing around platforms?
David Yoffie: The first question one must ask is: Are platforms the dominant business model of the twenty first century? Today, the world’s largest taxi company (Uber) owns no cars; the world’s largest provider of accommodations (Airbnb) owns no real estate; and the world’s largest retailer (Alibaba) owns no inventory.
Modern platform thinking has been evolving for the past 30 years. Academic and practitioner interest in the subject was initially stimulated by the explosive growth of the Microsoft Windows operating system. The real value of Windows, we learned, was not about the product, per se, but the applications written by independent software vendors. As a result, most of the early research on platforms was focused on what we call today innovation platforms.
With the emergence of Amazon, eBay, and other firms in the late 1990s and early 2000s, it was clear that a very different kind of technology platform was emerging, which we call transaction platforms. These platforms have their antecedents going back thousands of years to bazaars, but technology has enabled platforms to be globally scalable, which had never previously been possible.
While many people lump innovation and transaction platforms together, we argue that they are very different animals. Furthermore, in the last 10 years, we have also seen a new type of platform company emerge, which we call hybrids. A hybrid is a company that has both an innovation and a transaction platform operating simultaneously within the organization. In some cases they’re deeply linked. In other cases they are simply separate pieces of an organization that operate under a corporate umbrella. For example, Google Search is a classic transaction platform that connects end users to advertisers, and the Android operating system is a classic innovation platform that enables third parties to write new applications that create value for Android phones.
“While many people lump innovation and transaction platforms together, we argue that they are very different animals.”
We argue in The Business of Platforms that hybrids like this will become more important over time. Even if you’re running a pure transaction platform today, you may see the opportunity to create open interfaces—APIs, or application programming interfaces—that enable third parties to build on your platform. Even highly focused transaction platforms like Uber have opened up APIs to enable third parties to add value. This is an inevitable trend of digitization.
Lagace: In your research, you identified 209 platform failures between 1995 and 2015 and about 45 successful firms for the same period. What are drivers of success?
Yoffie: The most important driver of success is network effects. Network effects create the opportunities to scale at incredible speed and the potential for winner-take-all or winner-take most businesses. But network effects are not enough. This is a common misconception, that any business with strong network effects will produce a winner-take-all outcome. The evidence suggests that simply isn’t true. Network effects are a necessary but not sufficient condition.
Beyond network effects, successful platforms make it hard for their users to multihome. Multihome means users can participate on multiple platforms at the same time. In the old days, it was hard to use both a Windows PC and a Mac because of incompatibilities. Whenever there are switching costs, multihoming is hard, which makes it complicated for firms or individual users to switch from one platform to another.
The next criterion we identify is relatively homogenous products and a lack of identifiable niches. The more heterogeneous the market, the more fragmented it inevitably becomes, which lowers the likelihood of a winner-take-all outcome.
Lastly, the truly successful firms in a platform world tend to have meaningful supply-side scale economies. Markets with large economies of scale generally have higher barriers to entry, and they are more likely to tip.
Lagace: Since most platform launches fail, what mistakes should managers and entrepreneurs avoid?
Yoffie: We see four common problems across the data. The number one problem is how to price the product. The vast majority of platforms require subsidies on one or both sides of the platform for some period of time. Failure to get that pricing right inevitably leads to decline. You can see examples in businesses like ridesharing. The first player in the space was a company called Sidecar that never was able to figure out the right pricing to drive market demand or attract new drivers to the platform. Sidecar ended up a casualty of both Uber and Lyft’s aggressive pricing policies.
A second common mistake is the failure to build, establish, and maintain trust. Platforms by their very nature require two unfamiliar parties to do business with each other, which means they may not know each other and have no reason to trust each other. Without trust, many transactions will never materialize. A crucial feature of any platform is enabling and creating a trust environment allowing independent parties to feel comfortable that they’re not putting their business, operation, or personal wealth at risk.
A third mistake is mistiming the market. It’s possible to be too early, which is not often the big problem, but it is more problematic to be too late. This is because of the power of network effects and the power of platforms to scale very quickly. Even if a firm has a better product, if it is too slow in developing customers on each side of the platform, it can still lose out. A great example was Microsoft’s failed efforts in smartphones. Microsoft built a very good operating system for smartphones, but it could not crack the market because its product came out five years after the iPhone and four years after Android. By then, there were already hundreds of thousands of applications written for the other operating systems. Even though Microsoft may have had the best of the three operating systems, it didn’t matter because it was simply too late.
The fourth common mistake is hubris. When firms are very successful in the early stages of a platform they often think the market has tipped and they don’t need to worry about competition and new technology. They lose their paranoia. The reality is, even in markets with strong network effects, it’s possible for competitors to overturn a leader’s advantage.
Lagace: What advice do you have for conventional firms looking to explore platforms?
Yoffie: There are three potential strategies. You can belong to an existing platform, buy a platform if time to market is critical, or build one if you want to control your ecosystem.
None of these strategies are without risk. Belonging to a platform is a way to quickly participate in a platform market. The challenge is to avoid the problem of “hold up” by the platform itself—that is, how do you prevent the platform from extracting most of the value? How do you prevent it from observing what you do and then simply copying it? Nonetheless, belonging to a platform is a way to engage in a platform market quickly at relatively low cost and learn the tools of the trade. In the book, we explore a number of “belong” strategies which have delivered excellent results.
Buying a platform is a higher risk, higher cost strategy, but it accelerates engagement in platform businesses. For some companies, it may be the best way to get the talent and culture required to operate a platform. The example we use in the book is Walmart trying to compete with Amazon. Walmart largely failed in the platform retail business for 20 years. Its acquisition of Jet.com, however, let Walmart aggressively expand the top line of its platform revenue and bring in a team that understood platforms. Although still far behind Amazon, Walmart’s acquisition of Jet.com finally turned Walmart into a serious online competitor.
Lastly, the hardest problem in responding as a conventional firm is trying to build your own platform. To be honest, very few firms have been successful. A lot have tried. It is something large, established firms under the right circumstances need to put on the agenda as an option they might pursue. In the book, we discuss General Electric’s efforts to build their Predix platform. Predix was clearly going to be a multiyear, maybe multibillion dollar investment and one that was increasingly difficult for GE to afford. But it’s a great example of recognizing the potential that platforms can create even within a very traditional, industrial business. We think the basic design of Predix was heading in the right direction, but the challenges in execution have been severe.
Lagace: A central concern of The Business of Platforms is the double-edged sword nature of platforms and its impact on business.
Yoffie: Platforms really are double-edged swords. They are some of the most valuable, efficient ways to organize commerce, and they are also a potential source of violence, disinformation, antitrust abuse, worker abuse, racism, misogyny, and the list goes on. In other words, the fundamental challenge we see in platforms is that they are vehicles for good as well as evil. And the vast majority of platforms in the last 10 years were only focused on the good and not on the potential for evil.
There are two theories about how to think about platforms today. We clearly are in one camp and not the other. One theory is that digital platforms are like the public square. Anybody should be allowed to do anything: it’s a world of free speech, and let the buyer beware.
The other theory is that these are environments that reflect the values and philosophy of the companies themselves. They are not a public square, and companies therefore have roles and responsibilities to their communities. Platforms have to maintain the efficiency on one hand and reduce the potential for evil on the other. This is a controversial position.
We write about a number of different elements of this problem. One, obviously, is the antitrust problem that has become a big issue in the current US elections. We argue that once these firms become dominant, many have engaged in bullying behavior. Some of these actions were perfectly legal when the companies were small. But these same actions became unnecessary (and in some cases illegal) when the big platforms became dominant. Nonetheless, leading platform firms have been slow to adjust to nonbullying behavior. A lot of the antitrust problems could go away if they could internally think of themselves as a dominant player, rather than continue to operate as if they were entrepreneurs trying to build the business from scratch.
“Twitter, YouTube, and Facebook … are going to have to find ways to curate, ways to say certain kinds of activities are unacceptable, and if users are not happy, they should just go to another platform.”
Probably the most controversial thing that we discuss in the book is the question of whether platforms need to be curated. Curation would try to eliminate disinformation, fake news, promotion of violence, and so on. Is it up to the platform to prevent that activity from occurring? Should it be done by third parties or by members of the platform community policing themselves? Facebook, for example, has about 30,000 people working on curation of the Facebook platform. The problem is there are more than 2.5 billion users. Thirty thousand people, even with the help of AI and sophisticated big data algorithms, simply are not able to catch up.
We argue that curation is going to need to become more important. There will be costs associated with it, but ultimately it’s about maintaining and establishing trust. If the platform loses the trust of one or both sides of the market, it will disappear. And ultimately it’s the platform’s responsibility to ensure that their users can trust the platform itself.
Yes, it is a philosophical change in approach. These are companies that were built as the town square, with the philosophy of “we don’t need to worry about this misuse because the ecosystem will take care of itself.” Potentially restricting free speech is anathema to many of the users as well as many people inside the company.
It is a wrenching problem. If you look at Twitter, YouTube, and Facebook, the three biggest platforms where this has become a serious problem, all three of them are struggling to address this challenge. Our argument is that they are just postponing the inevitable. They are going to have to find ways to curate, ways to say certain kinds of activities are unacceptable, and if users are not happy, they should just go to another platform. But that does mean giving up some potential revenue, which is also difficult for a public company to do.
About the Author
Martha Lagace is a writer based in the Boston area.
by Michael Blanding
Nearly a third of US patents rely directly on government-funded research, says Dennis Yao. Is government too involved in supporting private sector innovation—or not enough?
Innovation has always relied, to some degree, on government support. But a recent study suggests that public funding might be even more influential than it seems.
“Nearly a third of US patents rely directly on US government funded research,” says Dennis A. Yao, Lawrence E. Fouraker Professor of Business Administration and co-head of the Strategy Unit at Harvard Business School.
Consider that between the 1950s and 1980s, Uncle Sam’s spending on research and development (R&D) rose fivefold from less than $20 billion to more than $100 billion a year, about equal to corporate R&D spending.
“If more inventions are building on federal grants, it suggests that support is becoming more important to research generally.”
Since then, corporate spending has continued to rise, while government funding has leveled off. By 2016, businesses accounted for 69 percent of all R&D spending, while the US government provided just 22.5 percent, according to the Congressional Research Service. Higher education, nonprofits, and nonfederal government entities contributed the remaining 10 percent.
“The question that naturally arises is, ‘What is the role of government in fostering innovation within this changing environment?” Yao says.
Its role remains significant, according to new research by Yao and several colleagues. Despite spending relatively less, the government funds innovations that really matter to the American economy.
The research, published in the journal Science in June, was spearheaded by University of California, Berkeley, engineering and business professor Lee Fleming, and also included University of Connecticut law professor Hillary Greene, Guan-Cheng Li of Berkeley, and Boston University strategy professor Matt Marx.
Who’s funding patents?
To get a handle on how government funding fuels innovation, the researchers took advantage of new patent data from the US Patent and Trademark Office, which recently began including patent filers’ acknowledgments in its database. Those acknowledgments usually cite funding sources, which helped researchers identify patents sponsored by government agencies, such as the National Science Foundation (NSF) or the National Institutes of Health (NIH).
“Previously, it was possible to figure out what patents came directly out of government research labs,” Yao says. “Now we can see what patents came indirectly from government support as well.”
That includes patents that were supported by federal grants and patents that relied on previous patents or publications that the government funded, directly or indirectly. (Yao and his colleagues’ research was itself funded by an NSF grant.)
By examining a database of all patents filed since 1926, the team found that the percentage of patents that involved government support has risen steadily. While government R&D spending as a percentage of gross domestic product has declined since the mid-1980s, the percentage of patents that received any government support rose from 12 percent in 1980 to a high of 30 percent by 2011 before falling slightly to 28 percent since then.
“If more inventions are building on federal grants, it suggests that support is becoming more important to research generally,” Yao says.
Yao and his colleagues also examined patent citations of previous patents to find out how past inventions influenced future innovations. Among patents granted to companies in 2010, those that benefited, directly or indirectly, from federal largesse were cited 6.33 times, on average, in the next five years, compared to 4.42 citations for patents that didn’t receive government help.
The results held even when researchers compared patents that involved similar technology, were filed around the same time, or had a similar number of inventors. In those cases, government-funded inventions received 3.39 more citations, on average, than those without.
“This result suggests that government-funded patents are more important, reinforcing the idea of government-funded innovation as a driver for the economy,” Yao says.
Who benefits from government funding?
Companies, which filed the vast majority of the patents that Yao and colleagues studied, benefited most from government money, not lone inventors or academic institutions. Startups were particularly dependent on government-funded research, relying on federally supported research for some 35 percent of all patents they filed.
“Startups were particularly dependent on government-funded research…”
While the paper doesn’t explicitly examine why government-funded patents are so important, Yao speculates that government institutions, relative to companies, tend to fund broader scientific initiatives that are more likely to lead to more novel discoveries.
Government funding is paying off
Taken as a whole, the paper provides a strong rationale for the government to continue—if not increase—its level of investment in scientific research.
“In the political environment, research funding is frequently a target for cuts,” says Yao, noting that voters are more likely to feel the immediate consequences of shrinking human services than the long-term benefits of research spending, whose outcomes might be years away. “Voters don’t get as angered about such cuts.”
The research can’t predict what would happen if the US government slashed funding significantly. But the study shows that, at least for now, government funding, dollar for dollar, fuels innovation more effectively than non-government spending.
“The data certainly suggest that the current level of government funding of research is paying off,” says Yao. “Maybe we could get even more of a benefit if we spent more.”
About the Author
Michael Blanding is a writer based in the Boston area.
I want to share with you my 7 Cs for coronavirus survival if you’re a manager or a leader. This message is also available on video.
- Calm. Your folks, your employees, your customers, your suppliers, are going to be looking to you as a leader to project a sense of calm through this difficult, uncertain situation.
- Confidence. You have to be calm, but not still-water calm. You have to project confidence that you’re going to be able to see this through successfully, with a minimum amount of hurt to the company, but also to all of the stakeholders who are relying on your leadership to get them through the difficult days and months ahead.
- Communication. You have to relentlessly communicate, communicate, communicate. This is to avoid rumors developing that muddy the waters. But when I’m talking about communication, I’m also talking about a strategy for communication. You need a sense of order in which to communicate decisions and priorities, but also have rapid communication to the entire body of constituents—not delays over hours or days or, even worse, weeks. Silence is absolutely the worst possible thing that you allow to happen, because that’s when the rumor mill develops.
- Collaboration. You are not going to know all the answers; no one expects you to. This is a time for you to call on the resources, the capabilities of all of your employees, all of your team members, and bring them together in taskforces, sub-taskforces, and potentially have a role for everyone in which they feel they can contribute to overcoming the uncertainty, overcoming the crisis. Engaging employees in this way will also reduce that rumor mill, give confidence to them that they will then project in turn to the people who are relying on them as their managers for direction.
- Community. All of us live in communities. Our factories are in communities, our colleges and universities are in communities. We are leading by example, not just within our organizations, but within our broader communities. And especially since we’re talking here about an infectious virus, it’s extremely important that we set an example, model behaviors that are community friendly and supportive.
- Compassion is extremely important at this time. We may rise to the occasion if we’re fortunate to have a good team around us, but there are many people in our organizations who are depending upon us, who are not necessarily that resilient. And they need to be given the compassion to express their concerns. So, think of someone in your organization who has elderly parents in a fragile state of health. They’re going to be doubly concerned about relatives at this time when the virus is potentially affecting the most vulnerable and medically challenged in our communities. If they want time off, if they want to work from home, if they need to have a little bit of space to look after their family members, please consider giving that to them. Compassion at a time of crisis is a very important manifestation of leadership.
- Cash. The most obvious commercial C of the 7 Cs is Cash. Cash is king at a time of crisis, and everything needs to be done to look both short term and long term at the financial health of the organization. After all, your employees, suppliers, and customers are depending upon you to lead, not just emotionally but also prudently with respect to the long-term finances of the organization. Whatever you can do to conserve cash is going to be critical, because that’s what’s going to determine whether your employees are going to be paid next week.
Shifting to remote work raises many questions for managers and employees, especially when it happens quickly as a result of a crisis.
Prithwiraj “Raj” Choudhury, the Lumry Family Associate Professor of Business Administration in the Technology and Operations Management Unit at Harvard Business School, studies how location and geographic mobility affect worker productivity and innovation. His research also examines how companies benefit by allowing employees to work remotely.
Choudhury answered questions from participants in a recent installment of “Office Hours,” an Instagram series (@HarvardHBS) in which Working Knowledge makes experts available to Instagram users to ask questions about their research.
What’s the most surprising thing you’ve learned in your research?
Choudhury: One of the most surprising things I’ve realized is how, in our personal and social lives, we use a lot of digital tools for communication. But in work, we still tend to use face-to-face meetings.
How does location or geographic mobility affect innovation?
Choudhury: Knowledge is often locked in a geography, and when a worker moves from one geography to the other, knowledge is often transferred and recombined with local knowledge.
What’s the best place to be most productive?
Choudhury: That’s an interesting question. I feel the best place is where you get the most psychological satisfaction and that can be very different for every person.
What can organizations that haven’t made the change to remote work do, since they are behind?
Choudhury: Identify workers and tasks that can be done remotely, easily, comparatively, and then learn from these [experienced] remote companies, like GitLab and Zapier, who have mastered these processes to make remote work, work.
More tips for remote workers
How the coronavirus is changing everything we know about how to get work done.
Many parents are working and caring for kids at home. How can managers set expectations?
Choudhury: It’s a great question. I feel managers should show a lot of empathy in allowing people to find their rhythm and settle down and the manager should also adjust their own personal timelines for when to expect stuff to get done.
How can I avoid the temptation to procrastinate when I work remotely?
Choudhury: We all do that, so don’t feel bad about it. I feel the key is to set alarms and find a routine that works for you, so that you can get stuff done even when you have kids around and life is not normal.
Do you think companies will stick with remote work post-pandemic?
Choudhury: Companies might be tempted to go back to work as usual, but some workers might enjoy the flexibility in this timeframe and might start demanding flexible work as a long-term solution.
Doesn’t making employees work remotely save on utility expenditures?
Choudhury: If companies allow workers to live anywhere, they might save real estate costs, rental costs, electricity costs, and that might be huge if the company is based in a major metro.
What are the biggest obstacles for companies that want to allow remote work?
Choudhury: I feel the biggest obstacle is changing the organizational processes for how communication and coordination happens, but also the mindset of managers in thinking that people will not shirk and will be responsible.
Has coronavirus changed your remote work research at all?
Choudhury: I’ve started multiple projects, especially trying to understand how companies and workers are scrambling to adjust to this new way of working in a very short period of time.
How will operations change after COVID-19?
Choudhury: Many workers are picking up tools, such as Zoom and Slack, in this period. And even when they go back to physical work, they might use these tools for coordination and communication.
30 Mar 2020|by Dina Gerdeman
Welcome to the new world of remote work, where employees struggle to learn the rules, managers are unsure how to help them, and organizations get a glimpse into the future!
With more people working remotely right now, many of us have experienced a videoconference interrupted by barking dogs or hungry kids demanding snacks, punctuated, perhaps, by cabinet doors slamming and ice makers grinding in the background. We all understand, of course—we’re living it, too.
Welcome to the new world of remote work, pandemic style.
Before the coronavirus hit, 5.2 percent of US employees reported telecommuting most of the time, while 43 percent worked from home at least some of the time. Now, with the pandemic shuttering workplaces, that figure has skyrocketed globally.
But remote work during this bizarre time, with so many people scrambling to get their work done while sharing close quarters with shut-in kids, spouses, and pets, is certainly not business as usual, even for work-from home veterans. While some of the typical remote work rules apply, others don’t. Business leaders need a new game plan.
We asked Harvard Business School professors to provide practical advice for managing large-scale, long-term remote work at a time when many employees are not only distracted by the commotion in their homes, but are shaken by the crisis unfolding outside their doors.
“Managers should make the call on high-level priorities, so employees can focus on their best work.”
Here are 10 ways that leaders can support employees who are working remotely during an unprecedented and uncertain time:
1. Communicate clearly and be decisive
Business leaders have already had to make difficult decisions, such as closing offices or eliminating travel, but now they should express in black-and-white terms how employees’ work priorities should change as a result of these business disruptions.
If certain non-essential tasks are too difficult to pull off from home, take them off the table or at least put them on a back burner for now, and let workers know which projects should be prioritized, says HBS Senior Lecturer Julia Austin, who provides leadership coaching to companies.
“While now is a time to foster trust and delegate, you don’t want people debating about whether they should or shouldn’t do a major project. All that time questioning what to do will impact productivity,” Austin says. “Managers should make the call on high-level priorities, so employees can focus on their best work.”
At a time when many business leaders can’t gather their staffs in the same room, they need to “show up” on videoconference or in email to update workers regularly about how their companies are pivoting to weather this crisis and are protecting employees worried about their jobs, says HBS professor Tsedal Neeley, the Naylor Fitzhugh Professor of Business Administration, who has researched how to fix broken global teams.
“They may not be able to completely reassure workers about what will happen tomorrow, but they can provide a glimpse of the big picture from their perspective,” says Neeley, who is writing a case about a leader of a US company whose entire China operation was shut down and has seen no revenue, with thousands of employees home, since November.
2. Lead by example
Managers should model the behavior they want to see in others. If they say employees can leave the office or avoid travel, but the manager keeps popping into the workplace and hitting the road, workers may feel guilty staying home.
“Leaders underestimate how much what they do is mirrored by their employees,” Austin says. “Hypocrisy degrades them. Employees not only want to be told what to do, they want their managers to follow through on everything they’re saying, so they don’t feel pressure to keep up or start questioning their own performance.”
3. Be extra flexible
The beauty of classic remote work is the breathing room for employees to take a walk, throw in a load of laundry, or start dinner, all while getting more work done by avoiding unnecessary office meetings and traffic-snarled commutes.
But right now, with offices, schools, and day cares closed, those time-on-your-side benefits have evaporated for many remote workers who no longer have the house to themselves and are struggling with the tremendous challenge of focusing on work while balancing the demands of family members.
So, this period requires a new frontier of flexibility, the professors say. Managers should ask employees what challenges they face and allow workers the freedom to choose their own best windows of time to get work done, whether at the crack of dawn, late at night, or in two-hour shifts with breaks throughout the day.
“Managers should yield to the expertise and knowledge of their subordinates and let them decide the best times and ways for them to work right now,” Neeley says.
If the team is working on a project that is time-critical, one option is to ask employees about their availability so everyone knows not to expect an immediate response during certain chunks of the day. And, if a manager starts sending out emails on Sunday mornings because that’s her own best time to work, she should make it clear that her subordinates need not reply until Monday.
“Employers should understand the fundamental shift in employees’ lives and recognize that they have to radically alter their work expectations.”
4. Adjust work expectations
With business practices changing as the result of widespread remote work, some workers have too much to do and others have too little, and some may have a tougher time getting work done than others. Whenever possible, managers should trust workers to make decisions about what they can and cannot accomplish, Neeley says.
And based on input from employees, managers may want to evaluate each employee’s workload and ability to handle the work under the current circumstances and shift projects around as needed, Austin says.
In some cases, it might even be appropriate for employers to decrease workloads for now and reevaluate when working hours should return to normal, says Lakshmi Ramarajan, the Anna Spangler Nelson and Thomas C. Nelson Associate Professor of Business Administration.
Her research suggests that employer expectations can create conflicts between employees’ personal and professional identities, decreasing their performance and commitment.
“Employers should understand the fundamental shift in employees’ lives and recognize that they have to radically alter their work expectations until this crisis winds down,” Ramarajan says. “An employee with young kids at home, or someone taking care of elder relatives, or a worker needing to focus on their own physical and mental health as a result of the situation will not be able to do a 40-hour workweek.”
More tips for remote workers
Unsure of your footing when it comes to working at home? Remote work expert Prithwiraj Choudhury answers all your questions.
Wikimedia, the nonprofit organization behind Wikipedia, is telling staff and contractors they can work 20 hours per week and still get paid for 40. “Work is not the only thing on people’s minds right now. Their families, their bills, childcare and school closures, the economy … we are all trying to manage a lot,” CEO Katherine Maher wrote. “It is unreasonable and unrealistic to expect someone to be fully present, eight hours a day, when they have a three-year-old with crayons drawing on the wall, or an elderly parent who needs help navigating the stairs.”
On the flip side, some employees are working more than usual now—partly to prove they’re still plugging away when they can’t be seen. “There’s this pressure to say to your supervisor, ‘Yes, I’m here!’ by making yourself super available at all hours,” Austin says.
Managers should discourage workers from being “heroes,” Austin says. “If an employee is cranking at home because he’s good at it, but his colleagues are struggling, don’t start assigning all the work to him,” she says. “Managers should be patient and give people time to catch up, so you’re not adding pressure to anyone’s plate.”
5. Rethink meetings
Managers should understand that some employees can’t do back-to-back phone or online meetings all day long. “People are still spending too much time in meetings, even though our work and lives have changed significantly,” Austin says.
If your office has a meeting-heavy culture normally, consider scaling back the total number and length of meetings, Austin says. Could you reduce a get-together that typically lasted an hour in the office to a 30-minute huddle on Zoom if the meeting leader sticks to a clear agenda?
One of the simplest ways to trim meetings is to move to email, Slack, and other writing-based tools for information-sharing and idea-gathering, and call meetings only for decision-making, says Austin, who has written about how to master team meetings. “Meetings should be reserved for getting things done,” she says.
At the same time, Neeley notes that for some organizations, additional contact with staff and more meeting-based communication may be necessary now, particularly in the early days of adjusting to the remote work world. Research shows that informal conversation benefits remote employees, so she advises managers to devote time during meeting calls to connecting with staff on a personal level, for instance, by asking how everyone is holding up.
“It can be harder to pay attention to a long meeting online versus face-to-face.”
Afterward, managers should articulate key outcomes of the meeting using other media like email. “It can be harder to pay attention to a long meeting online versus face-to-face, so some form of redundant communication would be helpful so things don’t slip through the cracks,” Neeley says.
6. Move to more asynchronous work
Given the disruption to the 9-to-5 workday, employers should decrease “synchronous” work that employees perform simultaneously and increase “asynchronous work” that workers can do on their own time in a Google doc, Slack, or email, says Prithwiraj Choudhury, whose research shows companies often benefit when employees work remotely. Choudhury is the Lumry Family Associate Professor in the Technology and Operations Management Unit.
“The crisis accentuates what remote companies already understand—that work does not need to happen at the same time,” says Choudhury. “People can wake up in different time zones and cities, open documents, and get going.”
Those who are new to remote work also need to change their mindset about how quickly to expect responses and learn to practice patience, he says.
“If you post a message in Slack, trust that people will be responsible and come to it when they can,” he says. “It doesn’t hurt to throw your question in the deep, dark water and wait a few hours. We will all learn that things don’t have to happen right this instant. This is the new norming that needs to happen.”
7. Accept that productivity will probably suffer
Choudhury’s research shows productivity often increases with remote work. But now, with workers who have never operated this way scrambling to get up to speed while dealing with the anxiety of the virus and distractions at home, this period is not the best litmus test for measuring the productivity of remote work, Choudhury says.
In fact, companies may need to face the hard truth that productivity could suffer by at least 10 to 20 percent in the short term, Austin says. “I have a client who hung a sheet in his basement because it was the only way he could hide from his kids. And his kids were still handing him notes under the sheet during our call,” she says. “With that happening everywhere, productivity is bound to suffer.”
Ramarajan says business leaders should send this message: We get it—this isn’t easy. Take care of yourself and your families first. And since employees are concerned about the global health and economic conditions affecting their job security, employers should also reassure them they won’t be penalized if productivity drops, whenever possible. This will generate greater long-term commitment to organizations, she says.
“Great leaders will share their own struggles about adjusting to their partners being on conference calls in the next room,” Austin says. “People often think that everyone else has it figured out except them. They’ll be relieved to know this isn’t easy for anyone.”
8. Focus on outcomes rather than monitoring activities
Supervisors who lack experience managing remote workers might seek to keep close tabs on employees—asking them to keep their webcams on all day or alert managers when they take quick breaks. Or they might send emails at 4:45 p.m. to test whether workers are still online. Neeley says this type of micromanaging, which was found, for example, in a Wall Street Journal editor’s leaked memo, sends a hidden message to workers: We don’t trust you.
“The crisis accentuates what remote companies already understand—that work does not need to happen at the same time.”
“It’s terribly intrusive and tone deaf,” says Neeley. “Managers who don’t see the people they’re managing are struggling. They feel like they’re losing control, and their insecurities are creeping in.” She urges managers to let go of commanding by fear and trust they’ve hired competent people who aren’t slacking off.
One caveat: While most workers thrive with a hands-off approach, Choudhury’s research suggests that junior workers who are new to a company may need additional supervision and guidance while working remotely.
But in general, rather than monitoring every move employees make, companies should establish work goals and measure individual productivity based on output, he says.
“If you’re on a team in a traditional company, one imperfect measure of productivity is showing up to work every day,” Choudhury says. “Now companies don’t see their workers, so the immediate priority should be to make productivity more objective and measurable to the person, so you don’t worry people are free-riding.”
9. Take time to empathize
It’s a terrible, uncertain time, and managers need to acknowledge the obvious. After all, employees are worried not just about keeping their jobs and how their business is faring, but about the welfare of their families and friends, their personal finances, and even the logistics of squeezing in a germ-harrowing run to the grocery store.
Managers might want to give employees space to talk with each other, offer support, and listen.
“Now, more than ever, teams need empathy and to feel like you are all suffering together,” Austin says. “Everyone is dealing with a crisis that is very real. Managers should show their vulnerabilities by saying, ‘We’re all feeling this.’ After 9/11, crying with my coworkers was one of the most transformational moments in my career. Work teams may bond over this current crisis.”
10. Let workers blow off steam
With many employees feeling anxious and isolated, companies could set up attendance-optional social events online—coffee breaks, lunch gatherings, happy hours, cooking and crafting classes, talent shows, and even meet-the-pet sessions.
Knowing that workers are bound to feel some screen fatigue these days, business leaders should encourage self-care by allowing employees to take breaks, naps, and walks between work calls.
“A manager can say, ‘It’s 3 p.m., and it’s been a tough week. Take the rest of the afternoon off and spend time with your loved ones.’ You’d be meeting people where they are by recognizing that everyone is stressed out,” Neeley says.
While this period of remote work isn’t normal, Choudhury says, the silver lining is that many business leaders who have long been resistant to the idea of remote work may open their eyes for the first time to its benefits, including happier workers, less need for office space, and, for some, a possible bump in productivity over the long haul, once the virus settles down.
“Now that you’ve opened the door to adopting a remote work culture, it may be hard to go back,” Austin says. “My prediction is that there will be a higher demand for more remote-friendly software solutions, a lot of empty space in office parks, and more workers looking for remote roles.”
Managers are always claiming, “People are our most important asset.” But deep down, they can’t shake the feeling that employees are costs. Big costs. And they treat them that way. Quarterly earnings off? Cut the perks, rein in training, and downsize. This strategy may increase earnings in the short term, but it’s myopic. Recent studies suggest that layoffs actually destroy shareholder value. And our research shows that treating employees like the assets they are—by investing in their development—boosts returns over the long term.
For years now, our research has measured the effect of spending on employee education and training—a “cost” that is buried in general and administrative expenses—on the stock prices of 575 publicly traded firms. We created four hypothetical portfolios (one each for years 1997 through 2000) consisting of between 20 and 40 companies that invested at roughly twice the industry norm in employee development in each of the previous years (1996 through 1999). We followed the performance of these portfolios through 2001. Their returns were robust and in line with a growing body of empirical research showing that organizations that make extraordinary investments in people often enjoy extraordinary performance on a variety of indicators, including shareholder return.
In December 2001, we decided to put our money where our research was and created a live portfolio of companies that spend aggressively on employee development. In its first 25 months since inception, that portfolio has outperformed the S&P 500 index by 4.6 percentage points (2.2% versus a decline of 2.4% for the index). In January 2003, we expanded our investment strategy by launching two additional live equity portfolios made up of similar development-oriented companies. The results speak for themselves. While past performance is never a guarantee of future results, and while it is always possible to lose money, each of these three portfolios outperformed the S&P 500 by 17% to 35% in 2003. (See the exhibit “The People Payoff.”)
The People Payoff
How are you investing in your most important asset?