A Wiggly Path To Transformation
According to Sunday Times journalist, Carly Chynoweth, “Managers must learn how to adapt so they can solve problems they haven’t faced before.”
And:
“The fundamental impression they give is that the future can be organised and managed to achieve what you set out to achieve, and as long as you do it right it will come out as planned. But the reality is much more complex. Organisations are wiggly. They don’t operate in the neat, straight-line way conventional management thinking assumes”.
“It is not possible to predict outcomes — they emerge from people’s actions. You might have plans about what you are doing, but so does everyone else.”
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The culture and traditions of 100 year old Utility business make behavioual change hard. Power-plant Engineer’s detailed and precise planning techniques don’t work for this sort of long-term change. In our case, over 70% of the business processes will change. The main hurdle for us was the lack of certainty and predictability over 5, 10 and 20 years. It was impossible to answer the basic questions; when, how and how much? There was discomfort over sanctioning any plans without the ‘details’. This resulted in a period of ‘decision-making-block’.
This is when we introduced ‘Transition State’ planning. This borrows ideas from Complexity Theory: Specifically, the characteristics of Complex Adaptive Systems. We started with the premise that we cannot predict the long range future. We also accepted that outcomes will emerge at various points along the way.
Much like ’Scenario Planning’, we first developed a few hypothetical ideas. These were refined in workshops with subject experts until we reached a reasonable consensus of:
- the principles we will apply to different aspects of the transformation ahead of us,
- an initial guess of when certain outcomes are needed,
- a list of the main influencing events/decisions assessed as ‘Known’, ‘Unknown’ or ‘Unknowable’ now – along with an assessment of risk.
Armed with this, we plotted-out a series of ‘Way-points’ over time. We call these ‘Transition States’. Each has a few goals (expected outcomes) that we estimate to complete. At this stage, Transition States are not pinned to a hard date. Rather they describe the sequence of outcomes, and roughly when we think they’ll happen. Transition States are re-planning points; a time to reassess and re-estimate the next phase of work. The Transition State is an opportunity to amplify value-adding and extinguish value-detracting aspects.
After a few iterations, a more precise view emerged of the early Transition States and a traditional approach to planning and deliverables could be applied.
At first, we were quite concerned that this approach would be rejected by the culture; a plan must be very detailed and accurate before work can start. This, however, wasn’t the case, decision-makers could see the merits of a more agile and iterative approach to complex change. They liked the way ‘doable’ increments became clearer after a few iterations. They also liked the explicit opportunities for re-think and course-correction.
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Is a Complex Adaptive approach the only way to manage large-scale, long-running, change? I’d like to hear how others approach designing and managing business transformations and whether they see the merits of Complexity Theory that we’ve seen,
Implementing an effective enterprise architecture program is about more than just selecting a tool to aggregate and visualize data. As an EA solutions provider, we talk to a lot of organizations in the early stages of implementation, which gives us a unique, clean-slate perspective on the selection process. Frankly, the most obvious misstep that we see is an emphasis on the functionality of the tool versus what it can ultimately accomplish toward real business success.
