Recent Research on #EmployeeEngagement (Part 1)

The understanding of employee engagement, which has been studied extensively in recent years, has taken on new urgency in the current labor market environment. Organizations that do not understand the fundamentals of employee engagement may find themselves dealing with unmotivated, underappreciated, and dissatisfied employees who may be spending their free time searching for better opportunities. Two recent studies seek to bring order to the vast research on engagement, and to explore the role of employee engagement in the formation of the employee-organization relationship. For purposes of this overview, the definition of the “Utrecht Group” (Wimar Schaufeli and associates) will be used:

A positive, fulfilling, work-related state of mind characterized by a sense of vigor towards, dedication to, and absorption in work activities.

The first study, The Meaning, Antecedents and Outcomes of Employee Engagement: A Narrative Synthesis (Bailey et al., 2017), a literature review is performed to answer three questions:

  • How has engagement been defined and theorized?
  • What antecedents are associated with engagement?
  • What evidence is there that engagement is associated with employee morale and performance?

The study begins with a master class in structuring and executing a literature review. Anyone familiar with research in the social sciences will have come across many literature reviews–but this article is unique in the level of description and analysis of the research and review process that is provided. Key to the process is the narrative evidence synthesis method of planning, structured search, evaluation of material against agreed eligibility criteria, analysis and thematic coding, and finally reporting. An initial search resulting in 712,550 records was reduced through this process to 38 items with theoretical/conceptual models; 172 empirical papers; and 4 meta-analyses. The following is a brief recap of discoveries of this analysis.

How has engagement been defined and theorized?

The authors found six headings into which study definitions could be grouped:

  • Personal role engagement: the individual’s cognitive, emotional, and physical expression of the authentic self at work;
  • Work task or job engagement: the Utrecht Group’s definition of engagement quoted above;
  • Multidimensional engagement: a distinct and unique construct consisting of cognitive, emotional and behavioral components that are associated with individual role performance;
  • Engagement as a composite attitudinal and behavioral construct: research featuring measures of cognitive, emotional, and behavioral engagement;
  • Engagement as management practice: an emerging field of inquiry with no firmly established definition or conceptualization; and
  • Self-engagement with performance: defined as the individual’s sense of responsibility for and commitment towards performance.

The predominant definition of engagement is that of the Utrecht Group (noted above) which was adopted in 86% of the studies reviewed. After the definitions, five principal theoretical frameworks utilized in the studies were discussed:

  • The Job Demands-Resources (JD-R) framework was utilized in 38% of the studies reviewed. The JD-R framework distinguishes between resources (job-related or personal) and job demands. Resources energize employees and lead to engagement, while demands which require additional effort can lead to disengagement, and thus, negative outcomes.
  • In Social Exchange Theory (SET) relationships between employees and employers are based on reciprocity: when employees feel they are being treated well, they respond with higher levels of engagement.
  • Conservation of Resources theory suggests that employee engagement can be driven by the provision of resources;
  • Broaden-and build theory argues that engagement can occur when individuals experience positive emotions, which create the space for a broader range of thought-action repertoires; and finally,
  • Kahn’s engagement theory, which is based on the premise that engagement is influenced by meaningfulness of work, psychological safety, and experienced availability.

Antecedents of Engagement

The authors reviewed 155 empirical studies of antecedents to engagement, and found five main headings:

  • Individual Psychological States: the most studied attributes included self-efficacy, resilience, and personal resources were found to be positively associated with engagement.
  • Experienced job-design-related factors: multiple studies showed positive associations between job resources (supervisory and colleague support, feedback, and autonomy) and engagement.
  • Perceived Leadership and Management: multiple studies found a positive association between transformational leadership and engagement.
  • Individual perceptions of organizational and team factors: perceived organizational support, organizational identification, and team-level climate and communication were shown to be positively associated with engagement.
  • Organizational interventions or activities: some studies noted associations between training and development programs and engagement.

Outcomes of Engagement

The outcomes of engagement were explored under two headings, Performance and Morale. Not surprisingly, ample evidence exists in multiple studies demonstrating the positive relationship between engagement, better performance, and morale. The most critical conclusion of this meta-study is that evidence suggests that engagement is associated most strongly with job satisfaction and organizational commitment.  Specific recommendations supported by the author’s analysis include:

  • Job designs that allow for autonomy and feedback on performance;
  • Ensuring that workers have sufficient and appropriate resources;
  • Leadership that is positive and authentic; and
  • Enhancing individual resilience and personal resources.

Furthermore, there is some limited evidence that interventions can positively impact engagement levels, and that there may be ways for employers to develop and enhance engagement. Evidence on this last point is limited, however, and it is hoped that interventions to improve engagement will be the focus of future studies.

In a future blog post, I’ll be recapping the findings from the Eldor and Vigoda-Gadot article noted below.


Bailey, C., Madden, A., Alfes, K., & Fletcher, L. (2017). The Meaning, Antecedents and Outcomes of Employee Engagement: A Narrative Synthesis. International Journal of Management Reviews, 19(1), 31–53.

Eldor, L., & Vigoda-Gadot, E. (2017). The nature of employee engagement: rethinking the employee–organization relationship. International Journal of Human Resource Management, 28(3), 526–552.

Fun with #Prototyping!

As part of an ongoing project, I have been prototyping pieces of a new recognition program I’m preparing to roll out. I have been meeting with people one on one to test one of the most critical components of my plan, involving motivation and sustainment. I knew going into these interviews that I would learn a lot, but I wasn’t initially prepared to deal with the amount of content generated that was not directly related to the piece of my plan that I was testing.

One of the challenges I’ve experienced in prototyping sessions is keeping people on topic. Even with a very simple A/B design to test a response to a change in conditions, there are a lot of questions and comments, many not related to the exact component I am testing. What I have learned is the Power of the Parking Lot. Now, when I start my Prototyping test, I make sure that I have a parking lot prominently posted on either a whiteboard or easel, so that I can capture all the off-topic ideas that are generated in the course of the test.

Now that I am nearly done with my tests, I plan to bring together small groups of test participants to review all the ideas surfaced in my prototype tests. These ideas can then drive another round of tests, or perhaps be integrated directly into my overall plan.

So, when you start meeting with people to prototype parts of a larger plan:

  • Be prepared with a parking lot to capture ideas that are not directly related to your test;
  • Keep your subject focused on the content you are testing by letting them know that you can capture all of their off-topic ideas for later discussion; and
  • Bring test participants back together to review all the ideas generated in your tests.

My Approach: Creating solutions that incorporate the unique context of the organization

In an earlier post, I wrote about the challenge of staying in the problem space and not jumping to solutions too quickly. One should keep in mind that there are no easy or obvious solutions out there—if there were, they would have already been successfully implemented. Along with this, one should also be cautioned against generic, off-the-shelf solutions, particularly those sold by the innumerable management gurus whose books litter the (few remaining) bookstores. Generic solutions aren’t going to solve your problems—every organization has different processes and a different culture, both of which must be considered when designing solutions.

The most effective solutions will have two characteristics: they will be specific to the exact challenges faced by the organization, and the solutions will be a joint creation of the designer and the organization members. In my recent work, I’ve created an opportunity tree that’s helped me focus on the specific challenges faced in my organization. Armed with that detailed knowledge, I have reviewed ideas with organization members, to generate solutions that are desirable and workable in the context of the organization. Prototype testing of those ideas has allowed me to further refine and rework my solution, and with a little more testing, I hope to be able to offer a sustainable solution that is tailor-made to the context of my target population.

My Approach: Surfacing Assumptions

The third stage of the Design Thinking Process calls for Ideation, that is, identifying new solutions to the problems surfaced in the previous stage in the process. Before proceeding to the next stage of Prototyping, however, the designer needs to examine the assumptions underlying each of the proposed solutions. One solution can be founded on many assumptions, and any one of those assumptions, if proven false, could invalidate a proposed solution, or at the very least, point the way to rethinking a solution. One potential challenge, however, is that there can be many different assumptions built into a proposed solution—so many that it’s impossible to test them all. The key is to identify the assumptions that are most critical to the success of the solution—the assumptions that have the potential to render a proposed solution unworkable.

To take a single example from my own work, I had discovered that, quite reasonably, people wanted more public recognition of their successes. As part of one of my solutions, I included public recognition via Yammer, but recognized that I was merely assuming that recognition via Yammer would be valued. In prototype testing, though, I received mixed results on that proposition, and therefore had to rethink that part of my solution.

I had prototyped that part of my solution as a single item, to determine if it would work—and the great thing about prototyping is that in this case, the feedback opened the door to other ideas that would achieve the desired result.

My Approach: Developing Empathy

In the course of their work, OD practitioners and consultants will be engaged by business leaders to solve problems. These leaders may come to the table with facts, their perceptions, data from internal sources, and, inevitably, their own prejudices about how a business, and the people driving the business, should work. In what, then, will the practitioner’s solutions be grounded?

Solutions to the organizational opportunities that arise from people must be found within the people themselves. No solution can be successful or sustainable if it is not grounded in the needs, behaviors, and circumstances that form the foundation of the work environment. At all costs, the practitioner must avoid using stereotypes or depersonalized constructions of the users for whom the solution is being designed. Shortcuts like mere numbers or market segmentation data won’t allow the practitioner to get to the heart of the problem to be solved.

My experience in problem solving has led me to talking to people, in interviews and round tables, to help me understand exactly what they are thinking, and most importantly, doing. By talking to people, and observing how they work and what they themselves experience, I have been able to experience their challenges through their eyes. Developing empathy for end users leads to a deeper understanding of how and why they work the way they do. Experiencing work as others do opens the door to genuinely insightful problem-solving.

This doesn’t, however, need to mean that there is no room for hard data in the problem-solving process. I have used “big data” in the form of function-wide learning reports, to help understand where learning gaps exist that I can explore through interviews and observations. Bringing together insights based on empathy and data analytics lays the foundation for sustainable solutions that meet the needs of all stakeholders.

My Approach: Drawing and Mapping the Way to Clarity

When I was first asked to use a visual tool as part of a Design Thinking project, my first response was, “I can’t do this—I just don’t have the skills to draw out anything that would be useful.” I can’t draw, I don’t have any particular ability to create anything visual at all—I just don’t have that capability. My skill is writing—I can research and write about anything, and I’m always tempted to think I should try to leverage whatever skills I think I have.

The root of my challenge here is that I was thinking too literally—since I can’t draw, I can’t use visual tools. It took someone more perceptive than I to help me see beyond this supposed limitation. Recently, in a workshop, I was using the online tool to create a Story Map, a kind of flow chart, of a process that I was putting together. One of the instructors came over and said, “You know, you’re drawing right now.”


That was all it took to unlock my thinking—I suddenly realized that I drew things out all the time to help me understand them. I’ve sketched out an Input/Output model to help understand the components of a proposed dashboard, and how those elements fit together:


I’ve learned to use Mind Mapping (and a nifty tool called The Brain) to lay out diagrams to pull together and organize ideas:


And I draw out academic models all the time, just to help me understand them better, and to help me gain insights. I recently wrote about the Job Demands/Resource Model, in an earlier blog post—it wasn’t until I drew the model out that I really started to make sense of the connections in the model:

JDR Model

In all of these examples, I’ve intuitively used some sort of a visualization to get me closer to understanding and gaining insight from whatever I was working with. But I would never have said that that was what I was doing. Sometimes it just takes a little nudge, like the one I got in my workshop, to open your mind–and remind you of what you’ve been doing all along.

My Approach: Using theory as inspiration

Since I was first exposed to Design Thinking, I have always gone back to Tim Brown’s Change by Design for ideas and inspiration. Brown (President and CEO of IDEO, and the leading exponent of Design Thinking) has written in his book the definitive guide to the application of Design Thinking to both product and process problems. Now that I am starting to think about prototyping solutions for my DOEC project, I’ve gone back to Brown to get some inspiration from the basic prototyping principles he lays out.

When I think about how I might start prototyping solutions, I’m going to keep in mind Brown’s admonition that early prototypes should be “fast, rough, and cheap.” Why? Because the greater the investment in an idea, the more committed one becomes to it. The whole point of prototyping is to learn quickly from iterative experiments: the prototyping process creates the opportunity to discover new ideas that can be further built out in successive iterations. Well taken, also, is the point that prototypes should only involve as much time and effort as necessary to generate good feedback that can drive ideas forward.

I’ve also taken prototyping inspiration from Lim and Stolterman’s article on the anatomy of prototypes. One of the ideas that they explore is that of the prototype as filter: a prototype can be used to explore certain aspects of a design idea by filtering to specific qualities. Rather than prototyping a complete solution, it is possible to filter the solution down to specific components that can be tested individually. Therefore, the best prototype is the one that filters to the specific qualities the designer wants to explore.

As I approach my design prototypes, I will therefore keep an eye out to experiments that are quick and easy to put together, and that are designed to explore specific components of my overall solution.


Brown, T. (2009). Change by Design. New York: HarperCollins.
Lim, Y.-K., Stolterman, E., & Tenenberg, J. (2008). The anatomy of prototypes: Prototypes as filter, prototypes as manifestations of design ideas. ACM Transactions on Computer-Human Interaction, 15(2), 1–27.

Working Out Loud to Reframe the Question

I think I am getting to caught up going around and around in my problem space. I am caught in a cycle that’s leading me nowhere, as I consider how change plays out in my work group. I get stuck on the challenges that arise with change management where incomplete information is transmitted at the beginning of the change process. Change information communicated from senior leadership will differ in quality, depending on the circumstances: sometimes more or less information will be available at the outset, because the change is a work in progress. Perfect information about organizational changes will probably never be possible, because organizational change is a dynamic process. 

How did I get here? By asking, “Why is change management so hard here?” I think what I need to do is completely reframe the problem. In Tom and David Kelley’s book Creative Confidence, five techniques for reframing problems are laid out:

  1. Step back from obvious solutions: if the solution is obvious or simple, maybe you are solving the wrong problem.
  2. Alter your focus or point of view: shifting your focus to the viewpoint of another stakeholder can open up new insights on the problem.
  3. Uncover the real issue: how much time have I spent thinking the problem was one thing, when it’s entirely possible that it’s something else?
  4. Look for ways to bypass resistance or mental blocks: framing a problem in an entirely new way can help people accept new solutions to old, seemingly intractable problems.
  5. Think about the opposite: Flipping the question around can help think about problems in new ways.

The problem I have been trying to think through, “Why is change management so difficult?” needs to be reframed–how about “What can we do to make change management easier?” That’s a very different question, that could potentially lead to an easier path to solutions. Maybe that’s still not the best reframing of the problem, but I think that’s the direction I need to go.

My Approach: Staying in the Problem Space

The Design Thinking methodology, based in the deep understanding of the end-user experience, can illuminate complex and difficult problems. As with any problem-solving discipline, however, there are challenges inherent in the process that must be anticipated and resolved. Of the many potential challenges, there are three related to staying in the problem space that designers must be cognizant of and address:

  • As the discovery process begins to revel the contours of the problem, there can be an overwhelming temptation to jump in with solutions. The problem is there to be solved, right? So why wait? The solution is to take a step back, and be ready to acknowledge that if the answers were easy, they would already have been implemented. Dive deep, and seek a holistic understanding of the problem.
  • Groupthink on a problem-solving team can be deadly, as it can shut down ideas that haven’t been expressed. Team leaders need to create an open environment for exploration that enables team members to freely express their thoughts and ideas.
  • Finally, misdiagnosing the problem can result in failure. Designers and teams must dig deeper into their challenge, and expose and account for all the factors that can impact the problem.

Leaders of Design Thinking projects must enter the problem space fully aware of the potential challenges noted above, and be ready to focus effort on building a deep and holistic understanding of the opportunity being explored. This deep and holistic understanding will enable the designer to develop the empathy needed to move into the next problem-solving steps.

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