This blog was written by Dr. Charles Handler and originally appeared in SIOP’s Publication “The Industrial/Organizational Psychologist- July 2014″
The pace of technological change that is happening right now is very rapid. Individuals are improving their quality of life via the adoption of new technologies very quickly and this is forcing organizations to play catch up. Many of these technologies have a direct relation to how organizations engage and work with people. Despite this, it is clear to me that I-O Psychologists are at risk of being left out of the equation. I don’t think this is due to a lack of interest on our part. Quite the contrary, I believe I-O has a core foundation in the social mission to make work better for both individuals and organizations. This transcends any specific technologies. The scary part is that we have to understand that we are not in control of how technology is forcing change, and that to remain relevant we must adapt both our mindset and our toolset.
The rapid changes we are experiencing are making data (big or otherwise) the star of the show. Electronic communication and commerce are generating fertile ground for insight. The cruel irony is that data has been the star of our show for decades, and now once it is finally valued in the mainstream, we are at risk of losing our ability to work with it.
We are feeling this increasingly strong pressure because the nature of data is changing. My background and early training is in Psychometrics and statistics. While it is not my main focus at this point in my career, I know more than enough to be dangerous. But as I have watched what is happening, I have become increasingly convinced that I am not equipped to handle what is coming. I understand the tools and techniques required to handle relational databases and the “V”s that are the earmark of big data (High Volume, High Velocity, High Variety, High Veracity), in concept. However, I am completely lost when it comes to any related tools and techniques. This has been a source of increasing discomfort for me and so it was a chilling epiphany of sorts to hear many other I-O Psychologists who are light years beyond my quant abilities report the same feeling. It seems to be a point of agreement that I-O grad school is not focused (or equipped) to teach us the skills needed to work with the type of data that organizations are starting to adopt as a core business process. In fact command of this stuff is a whole different discipline.
So what are we going to do about this disconnect?
I think the solution begins with revisiting our roots. Now more than ever, we have to understand who we are as a field and what our main differentiator is. This will be essential to our ability to articulate our value proposition and to effectively lobby for our seat at the table.
I believe our main value proposition as I-O Psychologists lies in our ability to understand people via reliable and accurate measurement of the core traits that make them who they are. Hot shot data scientists may be able to manage massive data sets and connect dots to provide organizations with valuable insight, but what they are not trained to do is to properly measure things about people.
Despite some really cool advances in robotics, organizations are still composed of, and run by, people and they rely on people as their customers. Without the ability to measure and understand people, the real insights in clouds of data will remain hidden and the ability to implement positive changes for people and work will remain limited.
Our seat at the table will be offered and honored if we position ourselves correctly. We are scientists who know how to use data to gain insight about people. How can one have “people analytics” without the ability to properly measure things about people?
But to make our mark, we will have to go beyond our core foundation in understanding people and work. Our full value will remain untapped if we are not able to be open to a much deeper level of collaboration than we are used to. The big picture around this is that in order to survive and thrive, I-O Psychology needs to embrace a multidisciplinary approach that will require us to be but one element of a larger team of researchers and scientists working together to gain insight and take action based on what we have learned.
What is going on right now is going to force us to change our mindset about how we work in organizations. At present, most of us are used to working on projects where we are driving the data collection process. Job analysis, validation studies, engagement surveys, performance management, learning- these are all tools that we have closely guarded as our domain. These processes are what generate the data we value to help drive impact in organizations. The reality is that the sources of data that contribute to and define these processes are broadening. Like it or not, we are going to find ourselves slowly losing our ability to drive the data collection and interpretation process.
For example, I didn’t hear crowdsourcing mentioned once in any of the sessions I attended, but I believe crowd sourced data will be a major force that shapes the future of our field. Crowd sourced or not, there is no denying that data will be coming in hard and fast from a multitude of sources and we will not be able to do anything with it on our own. We are going to have to adapt or we will be left in the dust.
My intention in this article is not to be Draconian. In fact I believe our field is entering into the best of times and that we are positioned to take our field to new heights. I am not alone in this opinion. Most of us are proudly aware that the Bureau of Labor Statistics has identified I-O Psychology as the fasted growing profession.
However, in order to fully realize our potential and make sure we don’t go the way of the 8 track tape, we are going to have to embrace some new competencies. These will not replace our existing technical knowledge, but speak to the mindset needed for our success moving forward. The basic sketch that comes to mind includes the following:
Collaborative spirit- Valuing and welcoming the chance to work with others
Multidisciplinary mindset- Working effectively and inexorably with other disciplines
Wide open thinking- Remaining open to any and all ideas as potential sources of valuable insight
Acquiesce- Understanding that our agenda and mindset may not always come first
Sense of urgency- Championing the ability to drive research that can keep up with the pace of change
Embracing technology- Prospecting for and incorporating the latest technologies from outside our field
Humanism- Valuing people and the human experience above all else and seeking to understand how to better the lives of all humans
Collectivism- Understanding the interdependence of every human being and valuing the information that can be gained via the interactions of humans with one another
I view this model as a simple sketch that is open source. It is a starting point for the generation of discussion and ideas amongst all who care to comment. As with all competency models, regardless of the labels we use, there is a common underlying truth. In this case the truth is that while we cannot discard our roots, we had better start growing some new branches.