The 'flywheel effect'
Knowing the quality of candidates is arguably more important than measuring efficiency
Mar 8, 2016
By Ian Hendry
Some of you may be aware of the “flywheel effect.” If not, journey back to 2001 and recall Jim Collins’s book Good to Great in which he railed against the many myths regarding change.
For example, he referenced “The Myth of Fear-Driven Change: The fear of being left behind, the fear of watching others win, the fear of presiding over monumental failure — all are drivers of change, we’re told.”
He proceeded to explain that fear doesn't drive change — but it does perpetuate mediocrity. So within the context of change, Collins introduced the idea of the flywheel effect.
Imagine the change initiative to be a heavy flywheel which represents the organization, and as you introduce different initiatives to the change process, it inches the flywheel forward.
In Collins’ words, “After two or three days of sustained effort, you get the flywheel to complete one entire turn. You keep pushing, and the flywheel begins to move a bit faster. It takes a lot of work, but at last the flywheel makes a second rotation. You keep pushing steadily. It makes three turns, four turns, five, six. With each turn, it moves faster, and then — at some point, you can’t say exactly when — you break through. The momentum of the heavy wheel kicks in your favour. It spins faster and faster, with its own weight propelling it. You aren't pushing any harder, but the flywheel is accelerating, its momentum building, its speed increasing.”
The initiative starts to take root, many start to push in the same direction and, as organization commitment is achieved, momentum elevates to the point where the organization is firing on all cylinders. These repeated successes move an organization from being good to great.
It was therefore interesting to me that HR People & Strategy used a post by Joanne Rencher to link the flywheel effect with people analytics, our topic for discussion at next week’s SCNetwork meeting. Unquestionably, the profession has accepted the fact that we have moved from being a department led by good people instincts, to one that employs science and rigour.
Whether or not we are as sophisticated as to adhere to the six steps of evidence-based management laid out by the Center for Evidence-Based Management, I believe the majority of HR leaders bear witness to the fact that evidence and hard numbers are critical to being more influential in the C-suite.
Rencher makes the point that the more we can tie math and technology with behavioural indicators, the more insights we have to drive the business, which is turn moves the flywheel onward. As credibility builds, the more HR can rightfully take a front seat in the early stages of strategy development.
Long ago, we realized that the statistic of “time to fill,” in isolation, was obsolete. Knowing the quality of candidates is arguably far more important than measuring efficiency. So we began the journey of building our competency in the world of HR analytics.
As a yardstick of your progress, can your organization respond to the following questions that Rencher poses?
How long will our top talent stay and what are the best predictors of those decisions?
What is the profile of top talent that is successfully recruited and on-boarded to our company?
How many of our teams are working for managers with successful track records?
Where are our vulnerabilities, due to a shallow talent bench, which could cause us to miss our forecasts or programmatic goals?
There is no question that the bar will continue to be raised and predictive analytics will be an expected deliverable from HR teams. Join us as RBC shares its journey in building its analytic capability under the helm of Robert Carlyle. Learning how to add rigour to assessment processes via scenario, sensitivity and risk analyses, will be just one of the takeaways.
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