While evaluating changes in attrition may be hard, it is often easier to determine and evaluate the
minimum improvement required and judge whether this is reasonable than it is to estimate a specific
level of improvement. To determine the minimum improvement required in this case, you first need to
estimate how much it costs when each person leaves your organization. This includes the lost
productivity while the position is vacant, the cost of interviewing and selecting a replacement and
the cost of training the new employee. There are other harder-to-quantify costs like the morale
drain when the remaining employees witness colleagues leaving for supposedly greener pastures. Or
the negative effect attrition has on clients when their favorite employee leaves (potentially for a
competitor). It is important to think these costs through.
But, for our example, letís say the total cost is estimated to be $25,000 for each employee who
leaves. Letís further assume the company has 1000 employees and they average 6 percent annual
attrition. In other words, 60 employees leave per year and need to be replaced. At $25,000 per
person, the total cost of attrition is $1.5 million. In order for the $1 million investment to pay off, we
would need to believe we can reduce attrition by two-thirds ($1 million / $1.5 million).
We may not be able to accurately predict how much attrition will decline. But we may feel
comfortable assessing whether or not attrition will drop by two-thirds, from 60 per year to 20 per
year. When put this way, the decision becomes easier. Since most companies are unlikely to reduce
attrition this much by simply changing benefits, most will reject this investment.
Using fact-based analysis even when the facts are hard to come by can keep companies from
spending money wastefully on initiatives that simply do not make sense financially.
Avoiding Cognitive Biases
Another important reason for embracing fact-based decision making is to mitigate our inherent
cognitive biases. The burgeoning field of behavioral finance examines the ways in which we humans
tend to behave less rationally than what was assumed in our economics classes. While cognitive
biases can stand in the way of rational decision making, fact-based analysis can help restore rigor
and direction in order to avoid suboptimal decisions.
For example, executives often make more investments when the economy and stock market are
strong, despite paying more than they would at the midpoint or bottom of a cycle. Acquisitions, for
example, are often justified by comparing current valuations to comparable companies even though a
whole industry might be trading at double the value it traded at a few years earlier (and maybe a few
Extensive analysis can be completed, of course, but itís not always fact-based. Many acquisitions
that happen at the top of the cycle are made without considering the impact of the next down-cycle
on the value of the acquisition target. Similarly, we tend to avoid acquisitions at the bottom of the
cycle without adequate consideration for the upside when the economy improves. We tend to act as
if good and bad times will last forever.
This is particularly relevant right now. It seems many pundits are predicting a rise in M&A activity
this year. But, since we are hovering at pretty high stock-market valuations, many of the acquirers
will regret their purchases in a few years, when the inevitable down-cycle occurs. To avoid such
situations, use fact-based analysis and evaluate down cycle scenarios in any major investments you
consider, and donít be afraid to work in reverse to determine minimum required benefits when facts
are less certain.