Availability Heuristic
If people are asked the question, what is higher; the number of murders versus suicides in the United States, they answer unequivocally that there are more murders than suicides (unless they are experts in this field). This is because we hear or read about murders on the news frequently – our System 1 retrieves this information quickly and assumes that because we hear about homicides a lot, they must be more frequent, however, this is untrue. Leaders can effectively utilize this human tendency to create “rules of thumb” by, for example, communicating about positive change experiences frequently. Large scale projects often produce bursts of communications when specific phases are underway, rather than on a regular and frequent basis. Frequent and ongoing communications and discussion about projects creates two important heuristics – firstly that change can be positive, and secondly, change is something that is ongoing versus occasional and scary.
The Status Quo bias
I, like most people, stick with default settings when I, for example, download a new software program – I most often simply accept the recommended defaults. Software vendors who include a “Recommended” setting are leveraging the “Status Quo bias” that almost all of us have. Most of us are largely unaware of our actions when downloading new software. [[\]Leaders can also leverage this human tendency for inertia by providing recommendations when people are faced with changes, or when they need to make change related choices. For example, most change leaders know all too well that employees tend to resist change when it is forced on them. A technique to both overcome this resistance is to provide several options AND to include a recommended selection. For example, a few years ago I was working with a procurement team developing new global processes. Instead of deploying new required process, we held workshops that allowed employees to bring their own thinking and experience into the process. We provided a few examples of what other regions had successfully implemented and made a recommendation on what we thought was best. Almost universally, the recommended default was accepted without resistance.
Fear of loss versus incentive of gain
Humans tend to hate losses much more than they are excited about gaining the same thing. For example, if people are asked to play a game where a coin is flipped – if heads these people win $X dollars and if tails they lose $100. Kahneman describes research that shows that $X will generally have to be about $200 for people to be willing to play this game. In other words, the fear of losing is about twice as great as the possibility of winning. For example, I was working on a project some years ago where incentives where provided to keep consultants on the project until the end (consultants tend to begin looking for their next project many months in advance of the end of an existing project, and will tend to leave the existing project for a new one. This project offered bonuses for consultants to remain to the end. These bonuses had little effect, and many consultants left early. A more effective method would have included retaining a portion of the consultants agreed pay until the end to leverage their fear of loss.
