Events

It feels like we have been talking about performance management forever. In our conversations, organizations are telling us that performance management practices are not just ineffective; in some instances, they’re painful. In fact, when we recently asked managers in one organization how performance management was handled, our two favorite answers were: “with a pointy stick” and “like it’s 1979.”

Why this is important:

We are at least 7 years into the performance management “revolution”, and yet, many (rightfully) have a healthy skepticism about whether the new approaches are any better than the old. In fact, recent research by McKinsey & Company found that 54% of respondents still don’t believe that performance management has a positive impact.

Despite myriad articles and case studies about simplified ratings (or no ratings at all), separate performance and compensation conversations, real-time feedback and the technologies that support it, agile goal-setting, and coaching and development as a part of performance management, most organizations would admit that performance management is still a struggle.

Today, we’re launching a formal research study, sponsored by Glint, into what organizations are doing with respect to performance practices and how effectives those practices are.

Hypothesis:

Peformance shouldn't just be managed; it should also be enabled.

The premise for this project is that we have moved from an era where organizations only had to concern themselves with performance management to one where enabling performance is equally as important.

In the beginning…

A hundred years ago, performance management was much less complicated than it is today. Organizations were looking for a way to understand the return on their people investment. During the first industrial revolution, as assembly lines and other methods for increasing efficiency made an appearance, people were plugged into those systems and processes.

The worth of an employee was much more easily quantified than it is today. Tasks had a “right” way, and because measures associated with those tasks were objective (e.g., cycle time, number of widgets), it was easy to determine how well an individual performed based on those numbers. It created a transparent and equitable way to compensate employees.

The times, they are a-changin’…

However, we’re not living through the first industrial revolution; we’re living through the fourth. And there are some differences.

First, the work organizations are asking employees to do is different and much harder to measure. There are increasingly fewer ‘right’ ways to do a task because employees are continuously adjusting to changes in both internal and external environments. Instead of a set way of doing things with a set way of measuring things, employees are often left with nebulous job responsibilities and organizations are left with even more nebulous ways of assessing them.

As a result, “performance” has necessarily become less of a technical term. Instead of objective measures, shifting goals and strategies make it necessary to use more subjective measures when appraising employee performance.

Second, employee expectations have also shifted. As our societies continue to evolve toward a knowledge and information economy, compensation has become only one of many factors that keep employees with an organization. Employees now choose roles and tasks, not solely based on compensation, but also on things like how interesting they find the work, whether there is room for growth, opportunities for recognition, and what types of skills they can learn.

These expectations have prompted organizations to supplement traditional performance management processes. They are no longer just worried about the outcome or throughput; if organizations invest in individuals, they also want to measure their propensity to learn and their attitudes as a part of their overall performance.

The result…

As a result of these changes, many organizations have implemented a hodgepodge of old practices that don’t quite fit current conditions, and new practices that are applied haphazardly. As organizations try to blend the old with the new, gaps are introduced that result in frustration and uncertainty, both for the organization and for their employees. We currently see that frustration in the market. Gaps include:

Focusing on management or enablement, but not both

It is likely that during this last performance management revolution that we threw the baby out with the bathwater. Performance appraisals are an important part of how organizations compensate and create fairness, and throwing them out has caused havoc in more than one company.

As we begin to adopt some of the new ways of doing things, it becomes doubly important that we figure out how we fulfill some of the more traditional reasons for performance management. (By the way, if you’ve managed to create performance management practices that balance both of these, we would love to talk to you.)

Treating performance as a stand-alone challenge

Currently, most organizations look at performance and performance management as a separate set of practices and measures. However, how employees perform is ultimately the culmination or result of all other people practices.

This means that incentives, recognition, compensation, wellness programs, career management, coaching and mentoring, and engagement programs impact the performance of the organization. Truly enabling performance means taking a holistic approach to people practices by looking at all parts of the organization and understanding how they impact individuals and their ability (or willingness) to perform.

Missing the perspective of the employee

Most modern performance management practices have been conceived of by leaders of organizations and management consultants. Strangely, a lot of organizations limit upstream feedback to engagement surveys and the occasional 360. In the case of performance management, we think employees are in a unique position to tell us what would be useful to them in order to perform better. As a part of this study, we will be asking them.

Ignoring inherent bias

Performance management processes as implemented in most organizations are inherently biased. Most processes are largely subjective, no matter how many times a year a conversation is conducted. While a manager’s and peers’ opinions are important and valid to appraise performance, new technologies and access to new data can provide additional information that may create more fairness in the process and provide the organization with much more information about who is performing well at what tasks and in what instances.

We want to explore that further.

Why we care:

It seems like everywhere we look folks are talking about employee experience (EX). In fact, a global 2018 study of five hundred CHROs, found that 83 percent of organizational leaders believe a positive employee experience is crucial to the organization’s success.¹

Why is this the case? Some folks mention the hyper-competitive talent market and the expanding need for innovation. However, an equally critical reason is financial: many believe there is a clear connection between employee experience and customer experience (which should then drive revenue).

While this makes sense intuitively, there are still many unanswered questions:

1. What, exactly, comprises employee experience?
2. What is the relationship between employee experience and employee engagement?
3. How does employee experience impact customer experience (CX)?²
4. What is the measurable impact of employee experience on customer experience?

Understanding the answers to these questions will allow leaders to make much more strategic employee experience investments.

This is why we are launching a new research initiative, sponsored by Medallia, focused on these questions. We have already begun our analysis of existing literature and are actively looking to interview organizational leaders (is that you? Email us!) who can share their stories (the good, the bad, and the ugly) of how they have used employee experience to impact customer experience.

Hypotheses:

There is not a clear definition of employee experience. For example, some believe that employee experience is the result of connection, meaning, impact, and appreciation that employees find in their jobs – and builds on the foundations of culture and engagement³. Others see employee experience as being more akin to customer experience – using technology to make employee life more personal, predictive, and seamless⁴.

Though neither of those definitions of employee experience are aligned, they are different from employee engagement, which itself does not necessarily have a clear definition. For example, some⁵ defined employee engagement as the harnessing of organization member’s selves to their work roles. Others,⁶ stated it is a positive fulfilling, work-related state of mind that is characterized by vigor, dedication, and absorption. And, yet another academic⁷ defined it as an “employee’s willingness and ability to contribute to company success by freely giving the extra effort on an ongoing basis.”

Finding clarity on the differences and similarities of employee experience and engagement is our starting point.

Despite the competing definitions, research^8,9 indicates that both employee engagement and experience influence customer experience and satisfaction, but the way they do that may be different. To better understand where and how organizations should invest, we need to have a framework for thinking about all of these concepts.

In addition, we believe there are insights that can be drawn from the customer experience world,¹⁰ such as thinking about experience as both static (e.g., a specific point-in-time or interaction) and dynamic (developing collectively over time), that can be applied to our understanding of employee experience.

Finally, we believe that organizations where employees can take action on employee experience and engagement insights tend to see better customer experience. To create a culture that enables these actions, organizations need to consider desired behaviors, leadership activities, information sharing protocols, decision-making rights, incentives and technology.

This Project:

Some of the ideas this research project will explore include:

Please take a few moments to share your comments with us!

Why is this important?

Research shows that the best performing organizations use advanced people analytics. For example, research from Sierra Cedar shows that mature people analytics organizations have a 79% higher return on equity and research from the Corporate Leadership Council (part of CEB / Gartner) reveals that these organizations have 6% higher gross profit margin.¹

To realize these results, organizations need many things (e.g., capable people data analysts, strong relationships with HR and the business, and many others), one of which is technology. To meet that demand, many technology vendors have entered the market. Our recent analysis shows that there has been a 145% growth in the number of people analytics vendors in the market over the course of the last ten years. For anyone trying to make a technology purchase, it can be quite difficult to understand the landscape or providers, their offerings, and the relative benefits and drawbacks of each. Further, our current review of articles and literature reveals there is relatively little research published on this topic to date.

RedThread Research is excited to announce our newest research initiative on the people analytics technology landscape. This research is being supported by PAFOW and Insight222.

Hypotheses:

While it may certainly be the case that better performing organizations make the investment in advanced people analytics, we believe that every organization has a lot to learn from a more sophisticated, and data-driven approach to enabling their people.

The growth in the number of vendors in the people analytics technology market within the last 10 years has been exponential. These vendors offer a dizzying array of capabilities and there is an offering in every area of talent management (talent acquisition, performance management, learning, strategic workforce planning, etc.).

The capabilities and the ways these vendors interact is confusing to many, hindering customers’ abilities to understand and buy from the market and vendors’ ability to differentiate themselves. The market needs a clear framework that explains the different vendors, their capabilities, the needs of the leaders, and where the market is going.

This Project:

We will dive into the people analytics vendor landscape in detail. Our intention is to assess the current state of the people analytics technology market, analyze vendors in the market, and understand practitioners’ needs.

More specifically, we will examine the following topics:

Why is this important right now?:

One of the most common questions we get is, “How can our learning function show impact?” Though the more useful question is “How can learning functions actually have impact?” the enduring nature of the question indicates learning functions feel pressure to tie learning to the business, using numbers. And a lot hinges on getting the answer right – not least L&D reputation and budgets.

Measuring the impact of learning has always been difficult. It requires measuring the knowledge and skills of individuals, and measuring how what individuals know affects the overall performance of the organization.

And it’s even more complicated today. Different types of learning methods, an emphasis on skills that aren’t easily measured with a multiple choice assessment, new tools that allow employees to dip in and out of learning at will, and a general recognition that learning also happens as a natural part of work, complicates the process of how to have (and show) learning impact.

And, unfortunately, the 20+ learning measurement models and the many thousands of articles written about ROI are barely helpful in this new reality.

Today, we’re launching a formal research project into how organizations can (and more importantly, should) measure the impact of their employee development.

Hypothesis:

The premise driving this project is a simple one: Traditional mindsets and methods of measuring learning impact hobble the organization – not just the L&D function – the organization.

We must rethink how we show learning impact to account for new tools, metrics, data sources, and learning methods. This is a bold statement, we realize. Two quick examples to illustrate how what we've done is no longer sufficient:

Primarily measuring courses.

Almost all organizations (and every single learning measurement model we could find) use the course or initiative as the unit of analysis. We measure everything from what the course cost and how well people liked it to its return on investment, and perceived impact on business.

While measuring courses is our “safe space,”, it creates challenges. Among these: new types of learning are hard to isolate, particularly as learning becomes more integrated with the work itself. We no longer have complete control over the content, tools, and experiences that employees use in their development efforts. If we’re only measuring courses or initiatives that we are responsible for, we’re missing the myriad other things that impact employee development and readiness.

Measuring only courses or L&D initiatives shortchanges the organization by drawing focus away from a broader definition of employee development. This in turn keeps us from enabling key activities outside our direct control that could vastly increase the effectiveness of the workforce.

Over-focusing on conformity.

Back in the early days of the efficiency movement, Taylor established training as one of the most important things organizations could do to improve worker efficiency, as measured by output . Since then, organizations have been built with a focus on efficiency.

And L&D has been built to serve that focus: efficiently teaching employees to do the same tasks in the same way in hopes of realizing efficiency (productivity) gains. This approach no longer works (if it ever did). Most organizations tell us that innovation and agility are increasingly important in their increasingly competitive environments. Neither agility nor innovation are inherently “efficient,” which means L&D's focus on developing an efficient workforce is disconnected from the workforce the organization now needs.

In a world where the half-life of a workplace skill is between 2.5 and 5 years , workforces must adapt to changing market conditions, often acquiring skills that we often aren’t aware of yet. Effective learning focuses less on making sure that employees learn the same things in the same way, and more on creating the right conditions so employees have the tools, content, and connections they need to move business forward.

The traditional mindsets and methods learning functions have used to show impact are inhibiting progress. How and what you measure matters – not just to L&D, but to the organization .

This Project:

This project will look at how organizations and thought leaders are rethinking learning impact. Specifically, we'll be exploring the following topics:

This is a tough problem and we’re looking for people with strong opinions about it. As with all research projects, we’ll be taking a much more collaborative approach to this project. Specifically, we’ll:

Ask you to engage in the process. Throughout the project, there will be short polls, invitations for interviews and roundtables and other opportunities for you to offer your input. Please do! The more heads working on this problem, the better.

Publish our results as we go along. Instead of one massive report after 6 months of work, we will be sharing our findings throughout.

We welcome comments from the getgo! Please comment, share with others interested in learning measurement / analytics, tell us where we're wrong, suggest people we should talk to!

Why this is important right now:

Research abounds showing the positive impact of diversity – and gender diversity in particular – on an organization’s outcomes. For example, a recent McKinsey study showed 47% higher return on equity for companies with women on executive committees.¹

However, women are unique in that they are the only historically disadvantaged group who make up nearly 50% of the workforce. Despite that, they are woefully underrepresented at top levels. Fewer than 5% of S&P 500 CEOs are women and only 26% of senior management positions are occupied by women.²

To address this, organizations have recently invested in unconscious bias training in droves. However, it is not at all clear that unconscious bias is the villain. One large-scale analysis of more than 80 research studies and 17,000 individuals found no reliable relationship between measures of unconscious bias and actual behavior.³ And even if unconscious bias did affect behavior in some cases, simple awareness cannot remove implicit bias. It cannot be trained away. Diversity training, in fact, is one of the least effective methods to promoting diversity and inclusion.⁴ It may even make matters worse.⁵

Hypotheses:

Exclusion from informal professional networks has been identified as one of the greatest barriers to career success.⁶ One multinational study of over 240,000 men and women found that while 81% of women report some form of exclusion at work—astonishingly—92% of men don’t believe that they are excluding women at all!⁷

However, research shows that men’s and women’s networks do not seem to follow consistent patterns, revealing that solving the problem is not so as easy as simply identifying new ways in which women should build their networks. Instead, we believe organizations may need to re-think work partitioning, training, mentoring, sponsorship programs, and collaborative technologies to create opportunities for professionals to develop effective working relationships built on understanding and trust.

To that end, RedThread Research is excited to announce our new research initiative on how women use their networks to advance in organizations and the potential opportunity for technology to amplify those network behaviors. This research is being supported by GSV AcceleraTE. The final research report will be previewed at the 2019 ASU GSV Summit, April 8-10 in San Diego, and published shortly thereafter.

This Project:​

This research will focus on identifying how women can more effectively use existing opportunities, overcome factors that hinder performance, examine the role of technology, and make recommendations on what can be done by women and men as individuals, and organizations as the system in which people work, to improve women’s likelihood to rise in companies.

More specifically, we will examine the following topics:

Participate:

The above list represents our initial hypotheses as to what the study will cover. However, one of our core values at RedThread is collaboration and we need you to be a part of the process. We are collaborating with Dr. Inga Carboni, Associate Professor of Organizational Behavior at the College of William and Mary, to conduct interviews now through the end of March. If your organization is doing anything interesting on this topic, we encourage you to reach out to us and share your input at [email protected].

We are currently looking for folks to participate in our research around these topics:

• How organizations help women advance in their organizations
• How organizations help women build and develop important professional relationships inside and outside their organizations
• How organizations are helping women design their networks intentionally
• The importance of women’s networks and relationships in enabling them to advance within the organization
• The role or potential opportunity of technology to democratize or accelerate women effectively using their networks

If you have an interesting story to share about the topics above, wish to participate in an interview, or have recommendations, please contact us.