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The rise of the knowledge economy and knowledge worker over the last decade has brought about a new philosophy related to corporate productivity.
That philosophy sounds a little bit like this…
“Hire the best and the brightest, give them the resources and support they need, and get out of their way.”
Sound familiar? It should. It would be difficult to overplay the significance and ubiquity of this belief. The infamous “War for Talent” is real, and I witness everyday the determination of HR and business executives to hire, retain, and develop the most talented employees. Many billions of dollars globally are dedicated to this end. And now, apparently, more and more CEOs are determining that extracting as much as possible from your best employees and laying off everyone else is a great way to reduce costs and bolster profits. (ht: @larsleafblad) They have fully bought into the idea that throwing smart people at problems is the road to success.
I’m starting to believe, however, that this model of organizational productivity is fundamentally flawed.
Ultimately, this model is an expert- or talent-based model of productivity that is neither secure/reliable nor scalable.
Reliability/Security
Talent within organizations always varies. Whether you are Google or General Motors, the “talent” of employees is not uniform; rather, it ranges across some continuum. This inevitably leads organizations, often implicitly rather than explicitly, to operate based on a hub-and-spoke model in which the experts – the hardest-working, most knowledgeable, and/or most resourceful people – are the hubs.
Think of the Program and/or Product Managers, Sales Consultants, and SMEs of various sorts in your company. These are people who many across the company rely on to complete critical tasks, despite the frequent lack of any reporting relationship.
There are a few things inherently wrong with this model. One is that a hub-and-spoke model necessarily reduces throughput. If every plane flying from the west to the east coast has to go through St. Louis, and St. Louis can only clear X number of planes a day, then those constraints in St. Louis necessarily determine the peak productivity of the overall system. St. Louis is the bottleneck. Demand quickly outpaces supply in such a system and, when it does, the inevitable result is WAITING!
In a knowledge-based organization, it is people who do the waiting. And making people wait around for bottleneck experts leads to:
The other problem with hub-and-spoke “expert” models is that they lend themselves to single points of failure. If inclement weather shuts down the St. Louis airport, the whole operation is screwed. Likewise, if one of your critical experts goes on vacation or leaves the organization, the process(es) that relied on that individual can grind to a screeching halt.
Scalability
Clearly, keeping a hub-and-spoke system up and running is difficult enough. Scaling such a model is next to impossible. Experts are hard to find and expensive to retain. Often, they struggle to pass on their knowledge and expertise to others, both because they don’t always realize what makes them “talented” and because the time and incentives don’t exist for them to do this kind of cross-training.
In other words, if your experts are busy (which, in a hub-and-spoke system, they almost certainly are) and value the prestige and job security that comes with being the go-to resource, don’t expect them to help you grow.
So What?
Good question. Clearly, the expert- or talent-based productivity model has some serious flaws. What’s the alternative, then? How about a more process-based approach to human productivity.
A good way to think about this is in terms of Roger Martin’s “Knowledge Funnel.”

The funnel starts with “Mysteries.” These are all of those things that talented people are great at figuring out. They use their brains, background, and/or tenacity to tacitly make sense of the otherwise confounding. In doing so, they become the go-to for solving the mystery every time it surfaces.
That’s all fine and good, but that is generally where the process stops and where the hub-and-spoke development begins. Becoming more and more overwhelmed with the organizational demand for their ability and increasingly attached to the social prestige it offers, these experts seldom help advance knowledge to the next step of “Heuristic.” And without a heuristic there can never be an algorithm. Yet it is at stages 2 and 3 three that real process and its related scalability, reliability, and security begin to take shape.
So, rather than fighting to hire and retain only the best and the brightest, it may be time to start extinguishing experts (figuratively, not literally). Where there is an expert, there is knowledge waiting to be uncaged in a way that can release organizational productivity and growth.
interesting post, mike. i'm currently a hub and it's something i've been thinking about. especially since i've noticed that i go through phases where i'm a bottleneck. but the current structure is marketed as my role/department being a center of excellence (COE) for south-east asia. any thoughts on how i can wean my people of this model (and increase throughput) while maintaining the COE mandate?
Thanks, Kiran. Part of the challenge with COEs is that they can become an end unto themselves, as opposed to a means for enabling the rest of the organization to work more effectively and make better decisions. If you view your role as providing tools and frameworks (i.e. heuristics) for the rest of the business to apply (think of financial models like ROI), you'll probably generate some great ideas for becoming less of a bottleneck. Ideas are the easy part. Giving up control and allowing people to make some mistakes is the generally the harder part of getting started.