On change management

Change management is used as a collective term for all approaches to prepare, support, and help individuals, teams and organisations to change. I was challenged by a colleague to put forward my thoughts after she had read my previous post on digitalisation as a complex undertaking.

Change implies that something go from one state to another as water during its phase shifts from ice to floating to gas. Change management boils down to the management of the phase shifts, the transitions, the in between’s than the end states. How difficult this can be can be tested at home by boiling milk. Be prepared to clean up or pay attention to what takes place in the kettle.

The history of change management goes back to Kurt Lewin‘s work on group dynamics and change processes in the first half of the 20th century. At the time of his death in 1947, Lewin was seen as on of the foremost psychologist’s of his day. Today is Lewin best known for his three step change-model, also known as the unfreeze-change-refreeze using using an ice block as metaphor (fig. 1).

Fig 1. Lewin’s Unfreeze-Change-Refreeze model

The challenge with this model is that enterprises pay to much attention on the as-is and the to-be, while ignoring that success or failure is down to the nature of the phase shifts themselves. How this take place is best illustrated by the anatomy of a typical enterprise change process:

  • A problem or assumed short coming has been identified and the board of directors establish a project that is tasked to find solutions and propose alternative course(s) of actions.
  • The board of directors decides to implement one of the proposed solutions and kicks off an implementation project tasked to implement the recommended changes.
  • The implementation project create new organisational units, move people around while people do as best they can to make the wheels turn around.

I know I am tabloid here, but the most important takeaway is that such plan driven approaches does not work. The documentation is overwhelming, and still enterprises stick to the practice. What has proved to work are initiatives founded on lean and agile principles, principles that take into account that the challenge is the transition, not the end states.

Timing change

One reason old practices stick for to long can be found in Clayton Christensen work on disruptive innovation and product lifecycles where a product follows overlapping S-curves. Enterprises with profitable products are almost resilient to change. How Apple’s iPhone knocked Nokia out of business is one good example. Same is how the minicomputer industry was eradicated by the micro-processor in 1989-91. What was perceived as a healthy industry was gone in 18 months.

Dave Snowden has taken this understanding to a new level with his flexuous curves and the liminal moment (the yellow zone in figure 2) that marks the opportunity window. It shows that the change window is when your product is dominating. This is also a reason why changing is so hard.

Fig 2: Credit to Dave Snowden and the The Cynefin Company

Many enterprises stick to old practice despite that the evidence for change is overwhelming. This does not stop with products, but is applicable to work practices as well.

Leading change is hard

Disruptive innovation and flexuous curves can help us to better understand why and when change might be favourable, but they offer no help when it come to leading change efforts. Carl von Clausewitz might be one of the first who put words on the hardship of change in context of a complex system in his seminal 1832 book On War where he state:

“Everything is simple in war, but the simplest thing is difficult. These difficulties accumulate and produce a friction, which no man can imagine exactly who has not seen war.”

War, or battle to use a word that is more representative of 19th century reality can be understood as the dynamic state transition from pre-battle to post-battle that consists of timed and coordinated movements and counter movements of competing agents (armies). The competition ends when one or both sides have had enough. Each force being a interlinked hierarchical network of units built from individual agents and equipment.

There are two main takeaways from the war analogy.

  • That business and change processes can be understood as timed and coordinated movements of resources and therefore face “friction”. Today we would not talk so much about friction but that businesses and enterprises are examples of complex systems.
  • That the Prussian general staff under the command of General Helmuth von Moltke developed a new leadership style called mission command that is still used, a leadership style that emphasis subordinates to make decisions based on local circumstance in their strive for fulfilling the superiors intent. Stephen Bungay explains how these principles are relevant and can be repurposed for business in his book The art of Action.

To conclude, leading change processes is hard because they come with friction (things does not work out in practice as planned) and need a different leadership style than bureaucratic top down linear plans to succeed. This also challenge the way leaders are identified and trained.

An individuals leadership practice is an emerging property that is shaped by the context, and therefore can’t be copied. This breaks with the idea that a good leader can lead anything. This mean that its most likely different personalities that succeeds in operational contexts versus say a product development context. As individuals climb the corporate leadership stair this become crucial. To put an individual who have excelled in one context believing that he/she will succeed in a completely different context is dangerous.

How to succeed with change

The literature is crystal clear on how to succeed with change processes. Initiatives that empower individuals to drive change as activists, initiatives where individuals are invited to contribute, and initiatives that move from managed to organic has the best probability to succeed.

To move from managed to organic is most likely the most important of the three. Kurt Lewin’s three step change model still guides how leaders think about change, the problem being that there is no room to be frozen any more. According to McKinsey we need permanent slush that enables constant experimentation with new operating models, business models and management models, adopting the practices required when dealing with complex systems.

A complex system has no linear relationships between causes and effects and can’t be managed by linear measures. This leaves us with three principles as pointed out here:

  1. Initiating and monitoring micro-nudges, lots of small projects rather than one big project so that success and failure are both (non-ironically) opportunities
  2. Understanding where we are, and starting journeys with a sense of direction rather than abstract goals
  3. Understanding, and working with propensities and dispositions, managing both so that the things you desire have a lower energy cost than the things you don’t

Be also aware that its the alternatives with lowest energy cost that will win in the long run. Thats the reason point #3 is so important. We need to make what we will like to see more off cheaper than what we will like to see less off. These things must be anchored in the stories or narratives told by those who experience the existing reality and who in the end owns and lives with the changes.

Summing up, literature is crystal clear on what is the best way to approach change process. It boils down to knowing where you are, move in small steps and maintain a direction. Given the facts, why do enterprises stick to their old failed practices. To answer that question we must address some of the counter forces in play.

Counter forces

Counter forces come in many facets.

  • Old habits are hard to change, as everybody knows who have tried to change a undesired behaviour. Enterprises are structures with internal friction and change resistance that take many forms. Not invented here might be one. Short term energy expenditure might be another.
  • Lewin’s original model is linear, easy to grasp and leave senior leadership with the illusion that change is a final game that can be managed top down. I personally think it feels better from an ego’s point of view as well. Last but not least, its an easier sell for management consultancies providing case studies and best practice.
  • Procurement processes. Many change processes related to introducing new digital capabilities involves procurement of new technology. Procurement processes require that you know what you need. One thing is to buy 100 car’s or 5000 meter with drill pipes. Digitalising a business process something completely different.
  • Perceived senior management risk. Executives seek ways to reduce the perceived risk. One such way is to have contract. In the 1980ties nobody was fired for having signed on with IBM. My theory is that this boils down to psychology. Late sports psychology professor Willy Railo stated back in the 1980ties that “you don’t dare to win if you don’t dare to loose”. In other words its the fear of failure that trigger the behaviour that leads to failure.
  • Approaching business as a finite game. Business and change processes are infinite games, but due to various factors leaders behave as their finite. A finite game is a game with fixed rules and time (football). An infinite game is a game that never ends and enterprises that acknowledge that their in it for the long run will benefit. To learn more check out this link. The main problem might be that funding might be finite as in the case of public sector initiatives that are run by budget allocation.

As we can read, there are many factors and counter forces in play. Some of these are most likely unconscious such as fear, others boils down to ignorance and laziness.

Synthesis

Change management has been with us for a while and literature is clear on what it take to succeed with change. Experiments, involvement, empowerment, small steps, continuous adjustments based on feedback and so om.

Despite this many enterprises stick to plan based approaches with failure in the end. There are many forces that leads to this, one being the finite nature of budgets, and particularly budgets that are managed by political processes.

To me this is at the stage where we know what to do, so its just go do it in ways we know work. Adapt agile practice and begin navigate the maze.

Two recommended readings are the EU field guide on crisis management and this article on Safety Interventions in an energy company. Teaser provided from it’s abstract

The paper describes a case study carried out in an electric utility organization to address
safety issues. The organization experiences a less than satisfactory safety performance
record despite nurturing a culture oriented to incident prevention. The theoretical basis of the
intervention lies in naturalistic sense-making and draws primarily on insights from the
cognitive sciences and the science of complex adaptive systems.
Data collection was carried out through stories as told by the field workers. Stories are a
preferred method compared to conventional questionnaires or surveys because they allow a
richer description of complex issues and eliminate the interviewer‟s bias hidden behind
explicit questions.

The analysis identified several issues that were then classified into different domains (Simple,
Complicated, Complex, Chaotic) as defined by a Sense-Making framework approach.
The approach enables Management to rationalize its return on investments in safety. In
particular, the intervention helps to explain why some implemented safety solutions
emanating from a near-miss or an accident investigation can produce a counterproductive
impact.
Lastly, the paper suggests how issues must be resolved differently according to the domain
they belong to.

Next post will be on failed IT projects.

Digitalisation; a complex undertaking

Complexity

Complexity is the result from something with many parts that interact in multiple ways, following local rules that lead to nonlinearity, randomness, collective dynamics, and emergence. Emergence represents the concept of being more than its parts, its unpredictable properties or behaviours created by the many interactions.

Human societies is one example of a complex entity or system. Both the Chinese Covid-19 protests and the 2022 Iranian turmoils are examples of how emergence can materialise from a state that at outset looks calm or stable.

Other examples of complex systems are traffic and traffic control, Earth’s climate and biological eco-systems, warfare, and firefighting. Of these traffic and traffic control are man made where safe and secure behaviour is maintained through simple rules. Earth’s climate is a different beast with its unknown and even unknowable relationships.

Digitalisation

What is less understood is that digitalisation is a complex undertaking. Digitalisation boils down to retrofitting human enterprises with new digital tools, tools made from computer software, tools enabling change of business and operating models.

There are several factors that contribute to the inherent complexity.

  • Firstly, digitalisation impacts the interactions in human organisations that are complex systems before the technology arrived on the scene.
  • Secondly, computer software captures and materialise human ideas and thoughts with the caveat that its impossible to predict the effect of an idea before its tested. The effect being that digital tools are shaped by their creation process and context.
  • Finally, the fallacy that buying a off the shelf solution makes the organisational implementation or retrofitting easy.

All digitalisation initiatives begin with a promise that the new technology / solution and new ways of working will be for the better. In most cases the opposite is true, most often large scale digitalisation efforts goes wrong or at least run into severe problems.

Helseplattformen“, a Norwegian health care digitalisation effort that has ended up in the news lately due to problems. The scope is a new integrated patient record system across multiple hospitals, specialists and GP’s in one of Norway’a health regions. According to the news from January 2023 3.8 billion NOK’s have been spent and its expected that additional 900 million NOK is needed (who belive in that?). One thing is the costs, more important is the impact on the daily health service production for 720.000 inhabitants.

This is just one example out of many. I have personally witnessed several dosens failed digital or IT related initiatives during my career, leaving us with why. Why do these undertakings run into trouble and why are we not able to learn?

The simple answer is that digitalisation is a complex undertaking as enterprises are complex adaptive systems with non-linear and unpredictable cause-effect relationships. To explore what that mean in practice is it time to turn to Dave Snowden and his Cynefin sense making framework.

Cynefin

Cynefin, pronounced kuh-nev-in, is a Welsh word that signifies the multiple, intertwined factors in our environment and our experience that influence us (how we think, interpret and act) in ways we can never fully understand.

Cynefin domains

Cynefin divides the world in two, the ordered world to the right and the disordered world to the left each world divided into two domains separated by a liminal zone. In the clear domain there is a direct response from what is sensed and an appropriate response and the domain is governed by best practice. When best practice fails, we fall off the cliff into chaos. In the complicated domain the relationship between what is sensed and the appropriate response require analysis and expert judgment. There can be more than one solution to a problem and it requires good practice.

In the disordered world we find the complex domain and chaos. In the complex domain there is no linear relationship between what can be sensed and the appropriate response. The only way to deal with the complex domain is to probe, then sense and finally figure out what to do. This is the domain of experimentation and its a domain that require exaptive (repurposing / innovative) practice. We discover that something we have can be used to solve something we never had thought about.

At the bottom we find the chaotic domain where the only way forward is to act, then sense and respond. When in chaos practice is made as we go.

The liminal zone is split in two; A – aporetic and C – confused. Being confused in context of Cynefin implies not knowing what domain we are in and therefore we end up using the wrong approach to the problem at hand. Addressing a clear problem as it was a complex problem by running experiments is not effective. The opposite is worse, addressing a problem in the complex domain as it was clear or complicate leads easily into chaos.

Being in the aporetic zone we know we deal with unknowns and even unknowables and choose to use that insight to our advantage by running parallel experiments. This is what agile software methods like Scrum do and it goes even further. Hackathons are structured visits to chaos where we do stuff and figures out what we learnt when finished.

By accepting that digitalisation is a complex undertaking that requires enabling constraints, exaptive (repurposing) practice and a probe-sense-respond approach is the key to success. We must stop approaching digitalisation as it is in the ordered world using linear processes and thinking.

Enterprise practice

Enterprises, they be in private and public sector trives in the ordered world. The beliefs in “ordung must sein” can be overwhelming. There are routines and processes for everything. That said, there are thousands of things that need to be done within an enterprise that fall into the clear and complicated domains.

Problems pile up when topics belonging to complex domain is approached and managed as it is complicated or clear. Digitalisation and software development are two such things. Some enterprises uses task forces when something serious have gone wrong. This is a wise thing to do when you have felt over the cliff into chaos and need to find a way back to order, but its reactive in nature and it will never prevent them from falling over the cliff next time.

The catch is that when a complex problem fails, the path toward chaos is linear. What and why it went wrong can be explained, but it can’t be prevented without deep change to the culture and governance model.

Enterprises must train their leaders and employees to work experimentally with digitalisation and improvement. Admiral Nimitz understood this 80 years ago, it should be within reach for todays enterprise leaders as well.

Enjoy the story and embrace complexity. Its a wonderful world of opportunities.

Nimitz

When the US Navy entered WWII in 1941 it was equipped with two new technologies, radar, and VHF radio. Technologies that were expected to enable better understanding of the battlefield and clarity in the decision making. It was the opposite that happened. The new technology contributed to confusion and disaster.  

Admiral Nimitz and his staff understood that something had to be done and decided that each ship should have a new function, a Combat Information Center (CIC). Since once size does not fits all, he decided that each ship should experiment with how to implement the function allowing them to nurture what worked. For more details read the book [link]. 

The output from the CIC was a plot representing the ships understanding of the battlefield, own and enemy resources from interpretation of radar and radio traffic.  There are many things that can be learned from this 80-year-old story. Firstly, that what Nimitz and his staff did was to use exaptive practice, they repurposed plotting that the Navy had used for decades. Secondly, he probed by running parallel experiment governed by enabling constraints e.g., that every ship should have a CIC, while its design was adapted to ship type. 

During 1943 as the experimentation continued the CIC evolved from being an information system to becoming a system of distributed cognition. This evolution came from practical combat experience leading to the CIC being tasked to use weapons in given situations. All in all, the CIC both clarified and simplified the work of ship command. 

Ultimately the CIC became a system of distributed cognition fully integrated with the ships command functions. The work of making sense of available information was shared across different roles that distributed the cognitive load, and allowed for rapid assessment, analysis, synthesis of incoming information using visual plots as a symbolic information system.   

Conclusion

The US Navy’s CIC is an example of how to address a complex challenge using Cynefin’s recommended approaches. Nimitz use of safe-to-fail experiments, exaptive practice and enabling constraints unlocking his subordinate’s creativity enabled new unanticipated solutions to mange shipboard information. Nimitz deliberately avoided imposing solutions and instead created the conditions for a solution to emerge. He provided direction and used regular feedback loops to amplify useful approaches and dampen the less useful ones. 

For those in doubt, this is the practice that digitalisation initiatives require.