“In the sciences, the authority of thousands of opinions is not worth as much as one tiny spark of reason in an individual man” How does this quote from Galileo Galilei apply to transformation programs? Staffing a transformation program requires a very specific type of strategy. First, there is a need for contributors who are external to the system to transform. Secondly, these contributors can be of two radically different types. The consultants and a champion are these two types that maximize your chance of success. The former corresponds to a statistical thin tail (close to the mean, small impact, the latter to a fat tail (far from the mean, high impact).
The difference between thin and fat tails matters in staffing a transformation.
With fat tailed distributions, extreme events (e.g. a champion joining the transformation program team) away from the center of the distribution (i.e. the organization’s population) create a strong impact on the final performance.
Not so in thin tail distributions (e.g. a group of consultants in the midst of the organization’s population) where you need a number of events (i.e. a number of different consulting teams) to achieve a visible level of impact.
An example of application in an organization is the decision to resource complex transformation programs with two separate (competing?) teams: a traditional consulting team and a single proven champion of the domain.
Why consultants and a champion? Simply because the transformation of a system needs an exchange of energy or information from within and with its outside world to transform itself.
For example, transforming wheat and sugar into a muffin needs heat. And a caterpillar first stuffs itself with leaves, then digests itself and morphs into a butterfly.
This is what consultants and / or champions hired from outside do.
Here is a story explaining the consequences of such a choice.
An aerospace manufacturer had to dramatically and rapidly increase its competitiveness.
The board of directors launched a competitiveness transformation program.
Then, the directors formed a transformation program team with two separate arms.
One was a team made of management consultants (with a capability of, say, X, relatively above the existing organization’s capabilities).
The other one was a just-retired senior executive of the manufacturer’s top competitor (with a capability of, say, 2 X).
The consulting team
On one hand, the consulting team had twelve more or less junior individuals and a senior manager. They were all brilliant MBAs de facto structured around the consulting firm famous toolbox. Adding (or subtracting) a new consultant would not drastically change the consulting team contribution. Nor would this single consulting team impact drastically change the organization’s performance (say f(X)).
This arm of the program is the statistical domain of the thin tail.
The probability of hiring consultants higher than X twice in a row is greater than hiring them once with a capability higher than 2 X.
No single change in the consulting team resources could really modify their impact on the company’s performance. To strongly modify the resulting performance, you need a number of such consulting teams (associated with their high corresponding cost).
On the other hand, the former senior executive was a champion with a proven success in the domain. He had a level (2 X) of experience and knowledge well above the consulting team level. Plus, his seniority gave him a strong influence on the aerospace manufacturer leadership team. As a consequence, he offered an exceptional opportunity to increase significantly the level of performance (f(2 X)) of the company.
This arm of the program is the statistical domain of the fat tail.
With fat tailed distributions, extreme events (2 X) away from the center of the distribution play a very large role. The events in a fat tail may not be more frequent, but their consequences are much bigger.
In my story, while the consultants got bogged down in number crunching and powerpoint presentations, the champion identified a weakness in the development of satellite antennas.
He simply proposed to focus on the antenna design as a primary driver of competitiveness. This single action was going to optimize the need of power necessary to cover a specific surface on the earth. Decreasing the need of power strongly reduces the global weight of the satellite. And a lighter satellite reduces the cost of its launch and its placement in orbit.
As a result, the champion identified a well-known mathematician, the best in this domain. And he recommended that we hire him.
Here, the probability of sampling higher than 2X once (with the antenna expert) is greater than the probability of sampling higher than X twice in a row. As a result, the champion can play a disproportionately large role in determining the new level of performance with a single high-impact event.
Of course, there is a counterpart to this resourcing strategy. The story ended very well. Yet it could have been deceptive.
For example, our famous champion used to fly (First Class) every weekend back home. One of those trips ended badly. Our champion had to spend a week in the hospital. He fortunately recovered quickly and went back to work.
Under fat tails, wrong choices (e.g. too frequent intercontinental travel) or mistakes (the wrong champion) can be terminal. Under thin tails, they can generate great learning experiences (e.g. visiting France during the weekends or hiring different consultants). The consultants and a champion are very complementary.
Key takeaway: a dual-mode transformation program resourcing strategy
There is a key takeaway though. This takeaway is that complex program leaders may have interest to use a dual-mode strategy in resourcing their program.
One mode relies on thin tail distributions with a number of traditional rather average-level people, the other one on fat tails with a recognized champion of the domain.
Again, the consultants and a champion are an excellent source of success in complex transformations.
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