Good Science - Good Practice
Jamie Madigan
Ameren
Marcus W. Dickson
Wayne State University
To start, we wanted to mention one study in a recent issue of Journal of Applied Psychology that hit upon a couple of things relevant to the mission of this column. In “Tapping the Grapevine: A Closer Look at Word-of-Mouth as a Recruitment Source,” authors Greet Van Hoye and Filip Lievens (2009) do essentially what the title suggests: They examine how “word of mouth” works to encourage (or discourage) people to apply with different employers. Word of mouth is one of those ubiquitous recruiting strategies that professionals always talk about and that may be becoming more and more important as the “mouths” become virtual and the words are spread across e-mail and online social networking sites like Facebook, LinkedIn, Twitter, and others. Although research has certainly been done on word-of-mouth sources like employee referrals and networking during job searches, we always welcome additional research, especially when it steps back to present coherent models that look at larger concepts and identifies and clarifies the constructs at work.
But although the melding of science and practical issues is one reason the Van Hoye and Lievens piece stood out, there is perhaps a more interesting and potentially more important reason that harkens back to something we’ve written about in this column, which other thinkers have been advocating in other outlets. Instead of recreating the wheel to look at word of mouth in the context of recruiting research to be published in a journal for industrial-organizational psychologists, the authors realized that other researchers outside of that space have already taken cracks at this nut since the 1960s. Specifically, they look at research done in the product-marketing literature to see how word of mouth affects consumers’ attitudes and behaviors towards brands and products. This is the kind of cross-discipline and cross-boundary research we love seeing, even if it is hard to get started and sometimes takes a lot of extra effort.
Both word of mouth advertising and word of mouth recruiting involve many of the same phenomenon and characteristics—both involve interpersonal communication outside of the company’s control about them and their products. Van Hoye and Lievens acknowledge that word of mouth is a transfer of information in a social context; that the source of information is of a particular, consistent type; and that the information is never under direct control of the company despite any efforts at advertising or guerilla marketing. Furthermore, they note that word of mouth is characterized by face-to-face communication or similar communication through technology (though here I think they sell short the Internet in general and social networking sites in particular), that anyone can do it, that it can be affected by both the motivations of the giver and the receiver (think job seeking vs. bad mouthing here), and that unlike traditional recruiting word of mouth can be either positive or negative.
Following what they call the “recipient–source framework” to predict the determinants of word of mouth and the “accessibility–diagnosity” model to understand how easy the information is to retrieve and use mentally, the authors made several hypotheses about how it would affect subjects’ interest in joining the Belgian Defense Force. Although not all their hypotheses were supported, several were and the authors were able to draw several conclusions. First, those high in Extraversion and Conscientiousness spent more time receiving positive word of mouth. They also found that the more expertise the word of mouth’s source seemed to have, the more people paid attention, and that people were more likely to receive word of mouth information from sources with which they already had strong social ties. And it all seems to matter—positive word-of-mouth information early in the recruitment process relates positively to perceived organizational attractiveness and intentions to apply. We look forward to more research in this vein and seeing what else the marketing literature can teach us.
The next work we wanted to examine extends the concept of taking lessons from other disciplines, but instead of marketing it examines how I-O psychologists—both practitioners and academics—should learn to think in terms of business people in general. In their book, Investing in People: Financial Impact of Human Resource Initiatives (2008), authors Wayne Cascio and John Boudreau hit squarely on another theme that we like to harp on in this column: making research understandable and meaningful to a wider audience in the context of business.
After some introductions and defining of terms, the authors propose what they call a “LAMP” framework for approaching the measurement of human resources initiatives. LAMP is an acronym for a paradigm relating to planning and couching these initiatives (and the research projects that go with them) in terms that break past the shortcomings of traditional approaches and make them meaningful to decision makers and stakeholders elsewhere in the organization. You must have a coherent logic for the initiative and how it connects to the larger business, the right analytics to make sense of the data, the right measures to gather the data in the first place, and the right processes to make use of what you discover.
This framework established, the next chunk of the book dealt with very specific questions that I-O psychologists working in the area of human resources are likely to be called upon to answer. How much does employee absenteeism really hurt the company? How worried should we be about our turnover? Is it going to benefit the company to put in a new fitness center for employee use or to pay for a smoking cessation program? Is it worth it to offer onsite daycare for employees to use in emergencies? How concerned should I be about these employee satisfaction survey results?
The authors obviously don’t give you specific answers to these questions as they relate to your company’s situations, but instead they provide logic, analytics, measures, and processes for each issue to educate the reader on how to approach each question as both a scientist and a business person. Good research methods, theory building, and scientific interpretation of results are stressed but so is communicating the outcomes in terms of dollars (or whatever your local currency may be). If you need a formula for calculating the hourly cost of turnover or absenteeism, for example, you’ll find it here.
The next major part of the book dives head first into the complicated (and often controversial) concept of staffing utility. The authors provide information on measuring and using staffing utility, then its use in decision-making processes for things like enhanced selection systems and HR development programs. This section of the book is not for the faint of heart as it contains some pretty complicated (but powerful) algebra and calls to do some pretty challenging measurement, but utility (pun intended) of this kind of effort can’t be understated when you are trying to sell a program to key decision makers or to communicate the impact of a new program.
So in general I liked Investing in People, even if it bogs down from time to time and once or twice the reader is presented with instructions that basically amount to “just make a best guess and plug the number into your model.” But the message of how to communicate and debate with stakeholders in their own language and on their home turf is an invaluable one if human resources in general and I-O psychology in specific are going to move forward and become a real driving force in business.
With the economy in the state it’s in right now, organizations are often facing decisions that can lead to survival or organizational demise. One of those decisions can be the extent to which the organizations focus on innovation. Latham and Braun’s recent article (2009) in Journal of Management looks almost prescient in its appropriateness because they looked at unprofitable publicly traded software organizations during the technology downturn of 2000–2001. They also considered whether (a) the extent to which management and ownership overlapped, and (b) the availability of undesignated financial resources affected decisions to invest resources in innovation. Gathering publicly available data about financial performance and investment in research and development (R&D), Latham and Braun found clear evidence that:
[M]anagers with more equity participation (i.e., more “skin in the game”) and more slack resources reduced R&D spending at a greater rate than those with less. This suggests that managers faced with potential loss of their firm-linked personal wealth and/or job security were more inclined to curtail risky investments. (p. 275)
These findings supported theoretical models related to personal agency in decision making, as well as the extent to which threat leads to rigidity. However, the findings don’t suggest that these are inherently bad decisions; in fact, those failing organizations that continued investing resources in uncertain innovations (and presumably, in innovations with uncertain payoff timeframes) were more likely to totally fail than were those organizations that diverted resources away from longer-term innovation-oriented projects and towards shorter-term, more secure resource investments. In short, when your personal wealth is tied to firm performance, and there are slack resources with which to work, you’re less likely to “bet the farm” on R&D investments. Perhaps you don’t do it when it’s your personal wealth presumably because of agency-oriented decisions (i.e., I personally will be affected by this), and you don’t do it when there are slack resources because you don’t have to take the longshot bet as your only hope of surviving. I liked this article because it helps us understand the decisions that current financially challenged organizations have made and are making, and it relies on hard data that were always available. It just took some clever researchers to track down the data and put them to good use.
We usually close the column that follows the SIOP conference with a review of sessions from the conference, but this time around, we’re just going to hit one presentation—the closing keynote address by Steve Kerr. Dr. Kerr is well known in our field, having been on the faculty at Ohio State, USC, and Michigan, then serving as chief learning officer at GE under Jack Welch, and working now at Goldman Sachs. (See Greiner, 2002, for an interesting conversation with Dr. Kerr about these experiences.)
Steve’s basic premise in his talk (or at least, our main take-away point) was that there’s a lot of research that goes on in organizations, and we can and should be helping to make that research better. Much of that research will never meet the standards for publication (insufficient sample sizes, lack of control groups, threats to validity, etc.), but that doesn’t mean that the research isn’t useful. Academics who focus primarily on publication need to remember that “publishable” is not a synonym for useful, nor is “not publishable” indicative of “not useful”. (The correlation might even be negative.)
Dr. Kerr asked the audience to consider a favorite restaurant that suddenly started serving bad food in an unpleasant atmosphere. “How many times would it have to be bad before you would stop going?” Most people answered with three or fewer times. Steve then pointed out that three cases in one condition will never be enough to achieve statistical significance, and yet most people (and certainly most managers) make their decisions in situations analogous to this one—they don’t have much data, but the data appear to be convincing to them. If we as organizational researchers and practitioners can help organizations to get better data, or more data, or to think more carefully about the data to which they attend, we will be doing a tremendous service to those organizations, even though none of that will likely ever be publishable. In short, Dr. Kerr’s message was that science that is useful and used in practice is closer to being good science than is science that is never done because the researcher claimed not to have the resources necessary to do the research perfectly. That doesn’t mean we shouldn’t have respect for published research—we simply shouldn’t dismiss research that we simply shouldn’t dismiss research that is useful for decision making solely because it does not meet standards of generalizability or sample size required for publication.
In closing this issue’s column, we wanted to take a moment to let you know of some changes coming up. I (Marcus) have been asked to take on a new column for TIP that will be focusing on I-O education and classroom issues, and so I’ll be moving out of the role of co-editor of this column. I’ve enjoyed the chance to help spread the word about research that is what we all profess to be most interested in: work that advances our theoretical understandings of people at work, while at the same time providing specific, practical information to organizational practitioners about how to address the problems they wrestle with each day. Although I had known Jamie prior to this column, it’s been a privilege to get to know him better as we’ve worked on this column together for the past 3 years. (Thanks to Laura Koppes for inviting us to do this column and to Wendy Becker for her support in continuing it.)
Good Science–Good Practice will continue (of course, good science and good practice will continue, but so will the column!), with Tomas Giberson taking over as co-editor. Tom has a great background as a former full-time (and still frequent) organizational consultant and now assistant professor at Oakland University (and, I have to mention, graduate of Wayne State’s I-O PhD program). Tom and Jamie will be back next issue in this column (reach Jamie at jmadigan@ameren.com and Tom at Giberson@oakland.edu), and look for a new TIP column on education and classroom issues from me as well (I’m at marcus.dickson@wayne.edu, if you have topic suggestions or questions you’d like me to address).
References
Cascio, W. & Boudreau, J. (2008). Investing in people: Financial impact of human resource initiatives. Upper Saddle River, NJ: FT Press.
Greiner, L. (2002). Steve Kerr and his years with Jack Welch at GE. Journal of Management Inquiry, 11, 343–351.
Latham, S. F., & Braun, M. (2009). Managerial risk, innovation, and organizational decline. Journal of Management, 35, 258–281.
Van Hoye, G, & Lievens, F. (2009). Tapping the grapevine: A closer look at word-of-mouth as a recruitment source. Journal of Applied Psychology, 94, 341–352.