The Kernel & Signals

“Good strategy is coherent action backed up by an argument, an effective mixture of thought and action with a basic underlying structure I call the kernel.”
- Richard Rumelt Good Strategy Bad Strategy: the difference and why it matters
Rumelt identifies the kernel of good strategy as:
  1. 1.
    A diagnosis that defines or explains the nature of the challenge.
  2. 2.
    A guiding policy for dealing with the challenge.
  3. 3.
    A set of coherent actions that are designed to carry out the guiding policy.
My approach to crafting strategy was to work Rumelt’s articulation of the kernel of good strategy, whilst adopting principles from complexity theory, emergent strategy and systems change practice. In practice, this means using the systems story as a synthesis from which I have designed a kernel (diagnosis, policies, actions), accompanied by a series of hypotheses, strategic insights and ‘signals’ to assess the success of the actions going forward, to help guide adaptation.

Key Insights

1. Diagnosis, Guiding Policies & Coordinated Actions

The process of drawing out the salient aspects from the systems story is what Mintzberg [63] talked about when he identified Strategic Thinking as involving intuition and creativity, and what author and educator, Jon Kolko [64] talks about when he calls design synthesis a messy process using abductive logic which involves “inference or intuition, and is directly aided and assisted by personal experience”.
From the synthesis work of the Story of System, I was able to create a written narrative of key elements of the history of the system, and a diagnosis of the system dynamics. The articulation of the guiding policies and coordinated actions were then rooted in this diagnosis, and the leverage points work in the systems sight process.

2. Hypotheses

My design practice has been increasingly leaning into using what I refer to as ‘atomic design research’, which is a process of clarifying clear learning goals from which I can set up research activities, and then evaluate and reflect on the outcomes. It evolved from a practice I wrote about as experimentation [65] whilst co-leading Lifehack (a social lab in New Zealand focused on youth mental health).
I find development of hypotheses a useful way of bridging from a diagnosis (“what’s happening here?”) and guiding policy (“what principles are we basing action on?”) to identify assumptions which need to be explored, in order to further inform the coordinated actions (“what are we going to do?”) and help them adaptive and change.

3. Signals

When I wrote about ‘working in the fog’ in the appendix section, I mentioned the need to regularly check a map and compass to ensure we’re heading in the right direction. Signals are based on this idea, and represent the act of checking we’re on the right track - they could be qualitative or quantitative, depending on the situation.
In this case, as I have identified clear coordinated actions which invite participation and use of a solution, I chose quantitative metrics which represent continued use, and associated behaviour change.