Many CEOs and their boards are fixated with transforming their organizations. Whether this has to do with their business model, the elusive “Digital Transformation”, or to intervene to improve culture or innovation processes, the truth is that we live in a very dynamic and competitive world, and change is part of our everyday reality.
Everything changes, and as soon as we start to feel comfortable with something, a business need or an external factor makes us go into the change cycle once again.
What is unusual is that very few studies have been dedicated to the analysis of transformation itself. There are many tools and frameworks to approach how to deal with change. Still, not enough research has been committed to measuring resistance to change and understanding the main factors that are important for a successful transformation to occur.
Many tools, methodologies, and change frameworks are based on practical experience and sometimes even subjective assumptions of how change occurs. In EXYGE.COM, one of our core values is to have factual, theoretical, and useful information to guide strategic decision making. This does not exclude the field of change management. Although not abundant, there is research about how transformations occur and Industry 4.0 technology (analytics, IoT, and artificial intelligence) make possible today a level of change management that would have represented a massive undertaking in the past.
The 5 Pre-Requisites of a Transformation
Through research, we now know that five elements are usually present in a successful transformation and they need to be monitored and understood to guide the decisions during the management of the change cycle, regardless of the tool or framework you use for managing that change:
- Understanding of the Actual Situation: The point of departure in behavioral terms needs to be defined in detail. This is where most of the tools focus, but alone they are insufficient.
- Ambition for change: beyond the reason for the change, you need the intent to change. There needs to be a personal reason for it. The WIFM (“What is It For Me”) approach and the good communication practices suggested in traditional change management try to explain and convince the target audience, but it has been tough to monitor the receptivity of these messages until a few years ago because of the massive effort it requires.
- Alignment of the intent: after everyone is convinced and motivated to change, you need adjustment to ensure that the purpose is pointed in the right direction. This is usually done by cascading strategic objectives through different levels of the organization into more specific sub-objectives relevant to each particular team or area.
- The effort required to change needs to be precise. In practical terms, understanding the energy implies to “operationalize” new behaviors into processes and tasks – convert the concept of the effort required into actionable items – “what needs to be done.”
- Finally, the fifth element is capacity – having the possibility in real terms to do what needs to be done without this being a long term or excessively hard action to do. Capability means not only knowing what to do but being able to do it with low to medium effort. Training is usually how this is approached, sometimes piloting a project to acquire proficiency into what needs to be done at scale.
The problem until very recently with these last three elements of transformational change (ALIGNMENT + OPERATIONALIZED BEHAVIORS + CAPACITY) is that they have been challenging to measure at a scale.
As these transformations deal with people, to monitor the transformation, the individual elements need to be monitored at a team or even personal level, and doing this on an ongoing basis has been a massive undertaken that was not practical or economically feasible to do.
This is where automation, artificial intelligence, and Industry 4.0 capabilities have played a role recently in making possible this complete and ongoing measurement needed to drive, adjust and correct the change management and transformation process, improving the chances of success.
Leveraging AI and automation to “Power Up” Transformation Management
The traditional way to implement change in an organization involves making available information to everyone within the company. However, the feedback regarding how information, tools, and training are received, understood, and used to change behavior has been limited in scope. Until recently, we were not able to monitor with granularity on an ongoing basis. You needed to base your input on snapshots and generalizations/assumptions about the findings. Those were the “tools of the trade” for steering the transformation initiative.
The “new way” of doing things, leveraged by automation, AI, and IoT, does keep using the communications tools and the “push” activities. The transformation is in the feedback and, more importantly, in the reaction to that feedback at a granular level.
Through automation, AI, and a collaborative platform on the cloud, the transformation project can drive change monitoring the transformation’s traction at scale – but at a team and individual level.
There might be different ways to leverage automation to communicate, process feedback, and “nudge back” to the organization during a change management process. In EXYGE, we chose to partner with Transparency Lab in The Netherlands to bring this technology to Spain, Portugal, and Latin America, basically because they have everything packed in only one platform. Still, the concepts are applicable and implementable with different tools, although managed separately, which implies the effort of the transformation’s manager and the decision making steering team would have to devote some time connecting the dots. If you get an integrated tool for this – whichever you prefer – your effort will be focalized only on the value-adding activities.
If you would like to know more about the concept of “nudging” for change management traction control, I recommend reading “Nudge” by Richard H. Thaler. It’s a very enlightening read on how to change people’s behavior.