I have spent the past week in Paris working for a client to support their digital transformation initiatives which are many and various. The client is a luxury brand and is well on its way in transforming what it does and how it does it. Our most recent project together has been exploring how data from across the organisation supports both transformation and innovation.
The notion that digital and data transformation needs to work at a systems level should be familiar to many. It is not possible to identify change at a project level alone; ignoring the relationships between projects or departments. Changes in the way we work may affect how we deliver a consumer or customer experience and changes in our business model will certainly have an affect on both results and culture.
On the Eurostar to London yesterday I explored how others have linked transformation and systems thinking and found a useful article in Systems Thinker in which Daniel Kim asked What is your organisations core theory of success? He creates a model of a possible core theory in which he links the quality of thinking in a company to the quality of their results.
He uses causal loop notation to show the relationships and to show a reinforcing feedback loop: improving relationships improves thinking which improves action which improves results which strengthens relationships.
This feels like a good starting point for thinking about digital transformation and today I spent a couple of hours extending this model to consider some of the core areas on which organisations often focus their efforts on change. These are what we do for the consumer, how we make money, how we perform work, the culture of our organisation and the data and technology that are driving change.
Here is my (very draft) core theory of success in transformation:
My diagram maintains Kim’s core elements but shows some of the underlying components that drive these factors. Notice a couple of strong reinforcing feedback loops that are common in digital transformation: how data is being generated and harnessed to drive richer consumer experiences and how company culture enables new ways of working and ultimately results (which has a positive influence on culture).
I’m happy that Kim’s model remains intact. In his article he goes on to explore some of the balancing feedback loops that exist in organisations and I will need to do the same. These will perhaps explore how technology and automation can damage culture or increase friction between organisations and their customers.
Systems modelling is a great way to think about how things interact and as a modelling tool really helpful in demanding that we make things explicit.
Please let me know if your have seen or worked on similar models or have comments on the above.
4 Comments
Daniel · 11/04/2022 at 08:04
Maybe should include individuals in the model above. How would someone reacts to those changes. Transformation would require company and individuals mindset to make it work
jonathanbriggs · 11/04/2022 at 15:38
Thanks Daniel – I fully agree and I think individuals and their potential resistance to change are part of the next stage of this diagram. I need to think about the balancing feedback loops.
Karl Fredrik · 11/04/2022 at 17:32
I see similarities with Douglas Engelbart’s work on “boosting the collective IQ” that inspired many early human-computer-interaction researchers, most notably the xerox parc branch that slowly became apple (indirectly). This draft captures some of his models nicely, the human+tool symbiosis (if all you have is a hammer, every problem looks like a nail) and the ABC layers of organizational improvement (business as usual, tooling, improving how we improve)
jonathanbriggs · 13/04/2022 at 15:59
Really appreciate your input @Karl