Change Curve: The Dynamic Change Process [Part 4] – Adaptation

I’m coming towards the end of my broad exploration of Change in the Social Age. I started out by looking at the manifestations we see of change: ‘Resistant‘, where it’s squashed, ‘Constrained‘, where it’s lethargic and limited, and ‘Dynamic‘, which is the root of agility. In the last few articles, i’ve focussed on the third of these states, Dynamic change, and introduced a four part model: the Dynamic Change Model. This takes us through the ‘Framing‘ of change, the ‘Co-Creation‘ (and co-ownership of that change). Today i’ll expand on ‘Adaptation‘, before tackling the ‘Narrative‘ in a subsequent piece.

Change Curve - Dynamic Change - Adaptation

Change is not a simple challenge, so a solution will be less about one action, more about a complex pattern of adaptation. I say ‘adaptation‘, because an agile organisation will exhibit stress free behaviours: not behaviours that are ‘coping’ or an effort, but rather behaviours that are adapted and effortless. The agile organisation thrives in the new world, it doesn’t struggle to survive.

Change Curve - Adaptation

The ability to thrive is determined by a combination of factors: mindset, technology, community and permission amongst them. In the agile organisation, there is a facilitating mindset, which allows for curiosity, there is a range of socially collaborative technology, which permits the ‘sense making‘ conversations to take place, there are vibrant and supported communities, to develop creative and innovative ideas, and there is permission to challenge and rehearse.

For these reasons, agility can only come from a broad pattern of adaptation, a restructuring of the organisational entities (HR, IT etc) to be facilitating, to be fit for purpose. A move away from entities being mechanisms of control, towards them being facilitating and supportive.

Change Curve - Dynamic Change

Within the context of the Dynamic Change model, the purpose of adaptation is to enact iterative change in response to synchronous feedback. It’s about watching and listening as we take action, gathering data, analysing it effectively and reinforcing those things that build momentum.

And when i say ‘data‘, i don’t simply mean what we want to hear: we need to gather meaningful data on the effectiveness of change efforts, both where they succeed and where they fail, to provide the foundation of solid decision making. It’s the quality of this decision making that ultimately facilitates amplification and momentum, or constrains the organisation to lethargy.

A definition of the data we capture should not be ‘that which is easy to measure‘, but rather ‘that which is a meaningful measure‘. Whilst specific for each use case, that should include both quantitative and qualitative measures: those things that we count, and those things that we feel, because organisational change is about a little of both.

It’s probably worth dismissing a misnomer here: the difference between quantitative and qualitative data is not simply that one is ‘hard‘ and the other ‘soft‘, but rather it’s to do with our ability to enumerate rather than enunciate the response. Can you count it, or do you just feel it? The semantic difference is not one to get overly caught up in here, but we need both, and our route to capture both is through the co-created narratives we have talked about earlier.

For an organisation to change, it must actually change, but it must also be imbued with a sense of momentum and energy. Just changing the physical or quantifiable features of the organisation will not necessarily change it’s culture or mindset. Those are much more qualitative, created in the moment and harder to measure externally.

To get to the heart of these, we have to be creative. And our efforts at measurement need to be joined up. Constrained organisations often have a lot of activity taking place: they are busy and well intentioned, but with little holistic energy. The isolated efforts are planned, actioned and analysed in isolation, whilst in a Dynamic approach we have to take an overarching perspective.

I’ve talked previously about how change must be co-created and co-owned, but that doesn’t have to mean both the organisation and the communities bringing the same thing to the conversation: we can each bring specialisms, and measurement is one specialism that we may want to hold within the organisation itself. A small unit within any change team dedicated to facilitating a range of measurement approaches: a consulting body that can support the co-created conversations. Not own them. So as groups plan activity, we can support them with offers of how it can be measured, and as they #WorkOutLoud, we can gather data, then when we reflect upon completion of one step, we can learn, together. And learn holistically, aligning the data from one change story with similar data points from others.

Change Curve - the Control Effect - chocks away!

So in a Dynamic approach, we build data gathering into every thread of change, each of the co-created activities, giving us a rich field to mine. But that analysis is, again, not owned by the organisation: in the best traditions of open data, we need to be transparent with our assessment. The analytical process indeed may be carried out within and alongside the communities themselves, facilitated and supported by our data experts. You don’t have to be a statistician to understand rigorous analysis, but it helps if you are supported by someone or something that can help translate data into decision points. It’s this facility that is often lacking in decision making.

Whilst a co-created and co-owned model of change may sound less robust than an organisationally defined and owned one, it is, in fact, more powerful, if we use data correctly and share the responsibility out effectively.

With strong data, we can reach decision points: what have we measured, what worked, what didn’t work, and, through the parallel narrative, what do we feel about that. Then, how can we reinforce the positive and operate around the negative: where do we share our stories of success and how do we learn from our stories of failure?

This is an active storytelling exercise: looping these narratives back into relevant parts of the organisation, back into the tacit, tribal capability within teams. We are not looking to ossify and stratify this learning into some knowledge base, but rather to use it to empower teams and individuals. Knowledge is always abstract unless it’s applied.

Our purpose is to reinforce strands of activity: those conversations that are moving us in the right direction, we can recognise and reward. Those that take us somewhere else, somewhere that neither the co-created group conversation nor the organisation itself want, can be learnt from and archived into our tribal wisdom. We learn from our mistakes, take advantage of our emergent reason and build a shared story of change.

In an ecosystem analogy, as the ecosystem changes, we have to adapt. But our pattern of adaptation must be broad, to cater for the diverse evolutionary pressure exerted upon us in the Social Age. Whilst broad, it doesn’t have to be random: within this section of the Dynamic Change model, we are uncovering the benefit of planned activity and holistic measurement, leading to active decision making and reinforcement of success stories.

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About julianstodd

A learning and development professional specialising in e-learning and learning technology.
This entry was posted in Adaptability, Change, Change Management and tagged , , , , , , , , , , . Bookmark the permalink.

12 Responses to Change Curve: The Dynamic Change Process [Part 4] – Adaptation

  1. Michele Madden says:

    this is my favourite piece! .)

    Sent from my iPad

    >

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