Rats deserting a sinking ship are unfairly likened to a captain who does the same thing before the passengers and crew get to abandon ship.
It’s an especially unfair comparison and aspersion cast on rats when the captain appears to be scuttling the ship himself—since abandonment of a ship that is willfully being sunk by the captain to whom you are expected to be loyal is Darwinian “natural ejection”, not desertion.
Likewise, if the captain is making the crew walk the plank and take a dive in large numbers just to keep the ship buoyant, stable and afloat.
If rats had paid jobs, that’s the fear that extreme organizational downsizing would trigger—”drownsizing”, i.e., making the organization lighter for the sake of bottom-line ballast by jettisoning staff en masse only to ultimately sink both the ship and the crew.
That happens as those that remain succumb to the panic, abandon their posts, siphon off the remaining energies of the remaining crew, spread confusion and more fear, and thereby accelerate the chaos, the spiral into administrative darkness and the sinking into market oblivion.
The Two Forms of “Drownsizing”
“Drownsizing” is quite an apt term, because it captures two interwoven dimensions of downsizing that although conceptually independent are dynamically highly interactive.
Specifically, an organization undertaking radical downsizing may have only one objective—to save itself and its shareholders (if it has any), but may inadvertently create two awful results antagonistic to that goal:
Lose an unacceptable number of remaining staff who fear they will be next to walk the plank through additional cuts or are about to drown with the company as it goes under, dragging them with it. In the best-case scenario, this injects huge inefficiencies, costs and risks into operations.
Be forced to close shop or lose market share because of operational disruptions caused by staff shortages or by the hiring of less-experienced, less-qualified, belated or costly (e.g., in terms of training and orientation) replacements.
Drownsizing, American Style
A bright young Austrian environmental scientist named George, whom I recently met while in Kobe, Japan, while he was in Japan for a conference, recently expressed concern about what he called an “American-style management” approach to downsizing in European operations, namely, draconian cuts that are too broad and deep, thereby triggering large-scale preemptive departures of remaining staff.
For the purpose of this discussion, what matters is not how “American” this kind of drownsizing is, how justified his concerns are or how widespread this phenomenon is or isn’t, but how to make sure it doesn’t happen to your organization, be it a for-profit company or any other enterprise.
The list that follows is not gleaned from experts or consultants (who have been unsympathetically defined by a wag with a wicked sense of humor as “someone who borrows your watch in order to tell you the time”). It is merely a set of what seem to be very logical recommendations to follow to stave off a workforce meltdown and/or operational shutdown as a consequence of substantial and scary downsizing—the key being of course, to make those cuts less scary for those who, for the moment, remain, even when painful for those who don’t.
—Avoid mathematical fairness: When forced to cut staff within a given category, e.g., secretarial or IT support staff, above all, avoid the appearance of being as fair as possible, viz., by deciding who gets axed by lottery or by other random means.
It is worth recalling that there was (more than once) a draft lottery in U.S. military recruitment. That was intended to be fair and unavoidably became terrifying for those who feared their literal number would come up. The same applies in other organizations: Even though the jobs may not be as perilous as combat, a lottery, coin toss or other random mechanism for deciding will make everyone’s job seem imperiled, especially when the downsizing is looming, ongoing or recurrent.
However, avoiding maximal fairness does not mean avoiding fairness altogether. On the contrary, the next suggestion is framed within a different paradigm of fairness, which, although not maximally fair in the mathematical sense of probability theory, may be “epistemologically” fair, i.e., be knowledge-based fairness, in terms of drawing upon what is known about each employee in determining which get to stay and which don’t.
—Make “evidence-based cuts”: Although coin tosses have their place in mathematical definitions of and attempts at “fairness”, they are as out of place in downsizing decision-making as they are in criminal trials.
Both of the latter should and do employ “evidence-based” criteria of fairness—i.e., they follow a rule that says decisions should be based on evidence supporting them in conformity to general principles themselves tested and demonstrated by historical, argumentative and other evidence.
An example of an evidence-based cut would be dismissals based on relative lack of seniority or of some crucial skill, a comparatively thinner history of distinguished periodic performance reviews, or some other distinguishing factor that simultaneously clearly delineates and legitimizes every decision about which employees are or are not retained.
The decision rule employed can be binary or comparative: Yes, X has the preferred certification; no, Y does not. Applying the rule that says “terminate anyone who lacks that certification”, management makes it absolutely (and not relatively, in any sense of that concept) clear why Y goes. Even though X is comparatively better off, it is not because of his relative standing on some rank-ordinal scale vis-a-vis Y; it is because Y lacks the certification, period.
On the other hand, a percentage-based rule, e.g., “Those among the top 45% in terms of sales figures stay” does entail the the evidence will be comparative and based on relative rankings, not simple yes-no binary criteria.
In either case, the remaining employees will take whatever comfort is possible from knowing that they stand on the right side of the “us vs. them divide” that splits the workforce category into two camps: those that have to pack up and camp someplace else and those whose tents will remain pitched where they are.
Yes, this does create a risk of antagonism or distancing between individuals in the two camps or the camps as a whole when not all of those falling into the wrong one have yet to be given notice. That can be bad for morale, collegiality, communications and a host of other important operational elements. Such antagonisms and anxieties among those in the vulnerable camp can swell into a drownsizing, but need not, if handled adroitly.
One way to do that is to review why those who remain do so, despite meeting the criteria for downsizing dismissal. If the reason is the simplest of all—the quota or required number of dismissals has been met, they will then have evidence-based reassurance that they are fine (for at least the moment), as comfort no coin toss, lottery or other utterly “impartial” or random decision method can provide.
However, if they reflect on this reassurance, it is quite likely that they will take the questioning one step further: What decided who survived the quota-based cut?
Even if that was decidedly randomly, the mathematical “fairness” of it all should not spook the remaining staff, since the filled quota, as evidence, replaces the randomness-based rule with one that provides reassurances that further cuts are not imminent.
Reassuring remaining staff that collapse of the organization is not looming is a more daunting challenge, the success of meeting which will depend on the specific organizational details—e.g., stock valuations, unsold inventory, level and prospects of funded R&D, debt, administrative stability and how any damaging scandal is handled.
But if such damage control and reassurance succeed when staff retention is not only necessary, but also sufficient to keep the organization afloat (when all the other essentials for survival are in place), the captain and his team will have been able to accomplish the seemingly miraculous.
Plug the hole in the hull with rats.