We surveyed senior change practitioners on their key challenges
in using change data to generate insights, and here is what we found …
Change practitioners seem to face quite a lot of challenges across the board in measuring change and demonstrating the value of managing change. For many, there appears to be a level of angst and frustration in not being able to break through and demonstrate insight through change data in a clear and simple way.
Why did we survey this topic? In the new economy, our world is increasingly dominated by technology and data. More than ever data is all around us and our ability to access a range of data is becoming more prevalent. At our fingertips, we can access our phone to see how many steps we have taken today, work email and even workplace chat platforms.
In the business world, the same applies even more so. All facets of how business is being will increasingly be dominated by data. The availability of data. The insight that can be generated by data to make decisions. Data is king and a competitive advantage.
However, in change management, our ability to use data has mainly been restricted to ‘soft’ qualitative data. Of course, all types of data are useful both hard and soft data. However, most of our stakeholders who make decisions on project execution, funding, and prioritisation are focused on hard metrics. We really cannot blame them because hard metrics tell a direct compelling picture, whereas soft, qualitative data requires a level of interpretation and maybe less direct in the implication.
We surveyed a sample of senior change practitioners and received 30+ responses. After sorting through the feedback and responses we grouped them into the following 7 themes. We also directly address each of the challenges posed.
1. Getting buy-in from stakeholders on data input
Some mention the importance of stakeholder support and buy-in in collecting change data. This can be quite challenging if your stakeholder does not see the value of the change data that you are collecting. Since the bulk of change data is derived from each of the impacted businesses and those involved in the initiative, it is critical that the impacted stakeholders are supportive to ensure that data may be collected and response is sufficient.
A key element in ensuring that your stakeholder buy-in to your change data plans is to come up with a ‘sales pitch’ for them personally. Each stakeholder is concerned about their own priorities and challenges. If the change data can be positioned to address one of their pain points, then it will be hard to imagine any stakeholder who will not be interested.
2. How to measure cultural & behavioural change
This is probably the biggest challenge called out across
respondents. Most change practitioners
work on embedding some form of behaviour change. As a result, being able to measure the
behaviour change is critical to demonstrate the value of having a change
manager onboard and the value of change tactics.
And since most initiatives are not end-to-end transformations of everything within the organization, there is usually a limited set of behaviours that the initiative aims to change. Working on measuring a small set of behaviours can be challenging because it is not that we are measuring the whole culture of the organisation, which can be measured by culture inventories such as Organization Culture Inventory (OCI).
One way to do this is to start by defining the actual
behaviours you are trying to measure in very specific detail, in a way that is
behavioural and observable. For example,
customer service representatives will be able to resolve customer complaints in
the first contact without escalating to their team leader. This can easily be measured using the data
from the CRM system that the representative uses.
Then we can break this down into more discrete ‘micro-behaviours’ that will contribute to the overall behavioural outcome. For example, in this example, it could be 1) Establish rapport within the first 3-5 minutes of the conversation and 2) ability to identify a customer complaint 3) Apply structured complaint resolution strategies as per training content 4) Regular supervisor coaching and guidance on complaint resolution performance. These behaviours can be recorded using call listening audits, self-ratings, and/or supervisor ratings.
3. Data requires time, resources and effort to collect.
Change practitioners told us that the amount of work involved in collecting, sorting through, and analysing data is very resource-intensive. Because of this many try and avoid this as they do not have sufficient time or resources to collect data.
A lot of the work required is also very manual. Many mentioned automation as something they
are looking forward to. Change data that
can be automated to save time and energy to follow up, collect, followed by
data analysis is one that everyone looks forward to.
The solution is to leverage various digital tools to better automate the capturing, analysis and visualization of data. For example, Change Tracking is a tool now owned by Accenture that measures change readiness and generated reports. For various task management and collaboration features, most use such as Trello or Jira/Confluence. To measure change impact and change capacity, try The Change Compass.
4. Change capacity
The capacity for the impacted business stakeholder to
undergo and embed the change is often the first that comes to mind when it
comes to change data and reporting. Most
respondents mention manually developing a change heatmap to try and depict the
potential change capacity.
However, what the change heatmap actually depicts is the amount of change impact the various initiatives have added up together. This shows how much change impact there is and not the actual capacity that the impacted stakeholder groups have. It could be that certain parts of the organization are agile, mature and have great leaders. Therefore, they are able to have a much greater capacity to undergo larger volumes of change than another part of the organization. To read more about change heatmaps go to The death of the change heat map.
To resolve this it is important to map out the level of change capacity. How does one do this? By using historical data and comparing the level of change against business feedback such as performance indicators, and employee and leader feedback. To automate this process whereby you’re able to visualize the impacts of change against the plotted change capacity levels of each part of the business leverage The Change Compass.
5. Change prioritisation
Respondents call out the fact that often prioritisation of
initiatives is made based on typical project manager data points such as cost,
timeline, funding and business results.
The gap is that change data should also be taken into account. Data such as the velocity of the change, the
volume of the change, change capacity, risk of impact on business performance, business
readiness, all should be valid data points to consider in making prioritisation
With the ability to access a range of data points, the organisation is better able to make balanced decisions to maximise benefits and minimise risk. The fact is that with the various challenges listed here in not being able to access a range of change data, decision-makers simply make decisions based on whatever they can get their hands on.
6. Data recency and validity
The usefulness of data is only as good as its recency and
validity. Outdated data cannot be used
to make decisions. What respondents call
out is that it is difficult to ensure that data is constantly updated and
valid. Once again, keeping data recent
takes significant time and effort.
However, various digital tools can again be leveraged to support data
recency. At The Change Compass we build
in a feature to remind users to update information and data recency is also
depicted in reports to reinforce the update of data.
Change governance is critical to be able to support and govern
the change data collected and reported.
Change governance does not need to be a separate body created just for
the purpose of governance change data.
It could be a business unit planning meeting or a part of a PMO agenda
for example. The purpose of the
governance body here is to reinforce the importance of data, review any
generated insights, and make decisions on how to apply insights to business
As a change community, our challenge ahead remains how we adopt and embrace the new world of data and insights. The more we are able to leverage data and not shy away from it. The more we are able to move the discipline forward to that which is seen as directly driving business value and has a critical seat at the table in decision making.
The agile way of implementing changes has been popular for quite a number of years among a range of companies, from small startups through to large corporations. Most agile methodologies do not address the role of change management explicitly as a function. However, at the same time, most project practitioners agree that managing change is a critical skillset. In fact, surveys conducted by the Project Management Institute consistently found that change management is rated as one of the top skills for a project manager.
In this article, we will focus on a range of toolkits that support agile to help change managers implement change. Gone at the days when the change manager needs to work on large presentations and slides detailing every aspect of the plan. It was not uncommon to see more than 100 slides for a change plan. In the agile world, documentation is important but more important is the conversation and working with stakeholders.
Toolkit 1: Change Canvas
The change canvas or ‘change-on-a-page’ is a summary of the change plan. It follows a similar simple and summarised format as a Lean Canvas. The change canvas may be used to socialise what the change is about and the approach in implementing the change with a range of stakeholders.
Previous versions of the change canvas are often designed with more of a project plan slant. In the current version, we focus on a core set of questions that the change practitioner needs to answer in creating a change plan. To download the canvas click here.
Toolkit 2: Change experiment card
A core part of agile is about experimenting and iterating through a series of changes, versus planning one change. The idea is that each small change is an experiment with a hypothesis that can be tested and proven to be true or false using data. When the overall change becomes a series of smaller changes, each change iterates on the previous change. The overall risk of failure is reduced and each change is one step closer toward the ultimate successful end state.
Applying this concept in change management – The change experiment card is a template to help you design, plan and test your change experiment. To download the template please click here.
Change experiments can range from:
Project message positioning to stakeholders
Learning design effectiveness
Effectiveness of a communications channel in engaging with stakeholders
Change readiness tactic
Effectiveness of the change vision artefact
Toolkit 3: Behaviour over time graph
Plotting expected or actual stakeholder behaviour over time is an effective way to anticipate or track how they are experiencing change. It can provide significant insight on whether additional change interventions are required to shift the stakeholder towards the change process effectively, if there are any obstacles being faced or if the time taken along the change journey is the speed as anticipated.
Here is an example of a behaviour over time graph.
Toolkit 4: Connected circles analysis
The connected circles analysis chart can be used to understand the influencing powers of various stakeholders within the project. Agile projects are very much dependent on effective stakeholder engagement and collaboration. A range of stakeholders are thrown together within the same project from the beginning and there is a high expectation of successful collaboration and teamwork across the board. This analysis helps you to visualise the power dynamism and influence mechanisms amongst different stakeholders.
With the insight gained from this, the change manager can better focus on how to resolve any relationship issues, risks, and leverage the network to achieve better relationship and outcomes within the group.
Toolkit 5: Causal loop diagram
Systems thinking is critical in agile projects. Systems thinking means that you’re able to see the various components and how these components affect each other within the overall environment, or system. This contrasts with a linear view of A causing B or vice versa.
The causal loop diagram helps to flesh out and analysis key factors in the overall system and what causal relationship there are between different factors.
The below example shows employee sentiments toward a system change. This is a very simplified version of what happens since in real scenarios there could be various factors that are reinforcing each other, leading to lots of arrows pointing at different directions. At a more sophisticated level, you may assign points in terms of the strength of the causal relationship. At a basic level even plotting the causal relationship between a few key factors may generate key insight into the ‘why’ of the dynamics of a situation.
For those who work in organisations that are undergoing a significant number of agile changes, there needs to be a way to capture and visualise these changes so that the data can aid decision making for stakeholders. Using data visualisation, stakeholders can gain a better grasp of the various changes across the organisation and be able to understand key capacity challenges, crunch periods, the velocity of changes across time, and pinpoint particular parts of the organisation that may need extra support.
The following are key steps in which an organisation can leverage tools such as The Change Compass to derive one view of change and to better plan the implementation of changes. With embedded operational routines that regularly focus on change data in conjunction with other business and project data, the business is able to build its change capability through constant reviews, valuable stakeholder discussions, iterations on change tactics and adjusting plans to get ready for change.
Change Management is full of concepts and frameworks that are outdated and not based on empirical research. It seems that in the business world we are very comfortable with concepts that sound like they make sense intuitively. If the concept is simple and interesting then we’re in. We don’t require them to have any scientific proof and research is often not required.
Let’s take one example. The Kubler-Ross model is one of the most popular models that outlines the 5 stages of grief by a psychiatrist from the book ‘On Death and Dying’. The 5 stages are denial, anger, bargaining, depression and acceptance. However, there is a lack of empirical research supporting these 5 stages, and in fact research suggests other expressions of grief.
Moreover, we’ve somehow applied this model to change management assuming that it is relevant. Whilst dying is a change process, this context cannot be generalised across all other changes such as implementing a new system, a new product or a new policy. Moreover, there is no research supporting this. In fact, we all know that there are lots of people who do not go through these phases during lots of change processes. And certainly it would be hard to imagine someone going through these phases after buying a new desirable iPhone from a previous older model?
Now, if there are so many popular concepts that are not backed up by research what should we use that is based on proven evidence? Self determination theory (SDT) by Edward Deci and Richard Bryan should be one that the change management community adopt. It is a broad-based theory about human motivation focuses on people’s inherent growth tendencies and our innate psychological needs. There has been significant research supporting this theory since the 1970s and more research is underway.
What is the self determination theory about motivation?
The theory states that there are 3 innate human needs that if met will provide motivation, motivation to undertake tasks, to develop and to undergo change. These 3 elements are:
1) Competence The experience of mastery and being effective at ones activity. When people feel that they have the skills required to be successful they are much more likely to take on tasks that will help them achieve their goals
2) Relatedness The need to feel belonging and connectedness to others.
3) Autonomy The feeling of choice and control over one’s focus.
Each of the three elements contributes to motivation, by having the right level of skills and confidence, by wanting to be connected to others and by feeling in control over one’s focus or task.
Some implications of these 3 elements on how we manage change include:
1) Simply conducting training may not address someone’s level of competence. The outcome is that they need to feel confident. This means that there should be a holistic focus on a range of learning interventions to promote and support confidence, such as managerial acknowledgement, catering to individual learning styles, supportive learning environment/community after training session, etc.
2) Change activities should not be implemented for individuals in isolation to others. For example, if elearning is utilised, the change approach should design to provide visibility on how others are undergoing the change process, where they are share their experiences. This is why change champions are so important since effective champions promote and build a supportive community
3) Especially for more significant changes, it is important to design into the change process a sense of autonomy for those impacted. This may seem contradictory to how most company implement change, i.e. one that is characterised by one common set of activities for all employees. What this important to emphasise according to SDT is to build in employee involvement so that they feel that they are shaping and developing the change versus being negatively impacted by it with no choice whatsoever.
There are 2 types of motivations:
1) Controlled Motivation
• “The carrot and the stick” approach to motivating someone • Seduced into the behaviour • Coerced into the behaviour, often with the threat of punishment • Experience of tension and anxiety
Employees that work in a controlled motivation environment usually have negative emotions and their confidence and well-being also suffer. Also, in this environment employees usually take the shortest path to reach the desired outcome. This may or may not have the best consequences for the company. If the company is trying to stipulate a set of behaviours, these may be avoided or blind-sighted to get to the ultimate ‘measure’.
2) Autonomous motivation:
• Experience of volition and choice about the work that one is doing • If the person enjoys the work and finds it interesting, then the autonomous motivation level increases • If the values of the work is consistent with the values of the individual this also increases motivation • If the person endorses the work, then he or she will also be more motivated to undertake the work
Organisations want more autonomous individuals that are aligned their work. Why?
Because research has found that autonomous workers are: • More creative • Better problem solvers and be able to think outside of the box • Better performance • More positive emotions • Better psychological and physical wellbeing
So how do we promote a change environment that develops autonomous workers?
• Take the perspectives of the workers and their mindset, and be clear around what moves them, what bugs them, what they get excited or bored about, their core values and interests, etc. • Providing them with choice and the ability to participate in the change and the decision-making process where possible. This will encourage their buy-in and engagement • Support them with exploring different ideas and trying new ways of approaching the work in a different way. This approach is also very consistent with agile ways of working, encouraging innovation and ‘safe to fail’ environment • Encouraging them to be self-starters and self-initiated • Provide them with a strong and meaningful rationale of the ‘why’ of the purpose of the change so that they understand the reasons behind the change
Edward Deci goes on further to state “Don’t ask how you can motivate others, ask how you can create the conditions for them to motivate themselves”.
From activity driven to design-driven
One of the biggest implication from SDT is that next time you design your change intervention you should focus away from key standard change management activities such as communications and training. Instead, focus on creating and designing the environment from which people can motivate themselves.
This is a fundamental shift for a lot of change practitioners and requires a depth of understanding about how the organisation functions and what will move its dial. It is not about implementing 1 or 2 core activities, it is about implementing a range of interventions to shape the environment to support change.
Some practical ways in which you can design an environment to promote change motivation:
1) Workshops for participants to brainstorm and discuss ways in which they can undergo the change journey 2) Share stories of how other employees have experienced through change personally Use different mediums in which to communicate the change, to appeal to different people preferences (e.g. video, online, face to face, posters, etc.) 3) Leverage key influencers to influence the community Provide sandbox or other platforms (such as online platform, showcase room, etc.) from which employees may experience and play with the new environment 4) Break up the change journey into small steps and milestones and acknowledge each progression 5) Encourage community discussions about the change
The challenge in building change environments
When we start to design a holistic environment for change, most often than not we are designing this for a set of changes and not just one initiative. In this complex, continuous changing environment, we need to be able to keep tab on what the change environment looks like and how it is evolving amongst the various change initiatives.
As different change environment interventions ramp up, we need to be able to visualise how these interventions and activities are impacting the employees and their environment. This includes being able to visualise the pace, scale, nature, and multiplicity of the changes across various parts of the organisation. Using data visualisation tools such as The Change Compass is valuable for organisations within agile environments.
Using the insights and core concepts from the self determination theory will serve
significant value for the change management community. Not only are its concepts well- researched and proven by research, there is a range of directly applicable implications for
the change practitioner. No longer do we have to work with frameworks that are fashionable but lack the rigour of empirical research. The challenge now is how we adopt this within our change approach and ‘change the way we approach change’.
There are many facets of driving agile changes. Agile changes are featured by such as developing minimum viable product and not investing too much initially, developing a series of iterations to gradually improve the product, engaging stakeholders early and frequently to ensure the outcomes meet business needs, developing working product/solutions from which feedback may be sought to feed iterative improvements prior to final release.
With so many facets of implementing agile changes, what is
the most important part of driving agile changes? What is the core concept that must be done right
without which the change would not be considered ‘agile’?
One of the most critical parts of agile change is the
concept of developing a hypothesis that can be tested. The outcome must be clear in terms of whether
the solution developed meets the business needs or not.
In waterfall methods of delivering projects, the focus is on
spending significant focus understanding and detailing features and ‘requirements’
from the business. From these, the
solution is then designed and developed.
The problem with this approach is:
Significant resources and investment may be
required to sufficiently develop the solution depending on the complexity
It may also take a long period of time to
involve various stakeholders and investigate solution design options before a final
product can be developed. A series of
design decisions also need to be made, each step taking time to undergo
The business may not know what they want and
they would need to provide ‘requirement’s that may or may not meet their
needs. For example, prior to the launch
of iphones, touch screen phones were not popular and were not seen as the
design of future phones
The risk can be significant if the solution developed
does not meet business needs. Millions
of dollars of project investment could have been wasted if this is the case.
On the other hand, what is the advantage of a hypothesis based approach?
Does not spend a lot of time creating a
sophisticated solution or product.
Instead, a simplified version is developed which captures the core of
business need. This is then tested, and then
the results can then feed into further improvements required. In this way, the process allows organisations
to fail early and cheaply in order to eventually come up with the winning
Instead of focusing on detailed planning which
is based on a series of assumptions which may not have been tested to be valid,
the focus is on deriving a solution that CAN be tested and validated or
invalidated. This is especially important
when the solution is new and has not been implemented previously in the
The hypothesis approach is a scientific approach
where the focus is on proven results based on data. In the same way a laboratory technician would
conduct a series of experiments to test the properties of a chemical solution to
further understand it, in the same way the project team would conduct a series
of ‘experiments’ (or iterations) to gradually test and from testing results,
improve the solution
Tests are always based on ‘real’ data and real
scenarios therefore there is a much greater chance that the final solution will
meet business needs
The importance of a hypothesis-approach for organisational agility
The survival and growth of a company are dependent on its ability to go into different products, different territories or different customer groups to expand its offering. In order to do this, the company needs to ultimately launch various products or services that do not exist currently or that have not been launched in certain new areas/segments.
Therefore, the ability of the organisation to continuously develop, launch and learn from new products and services is critical for its success. Each product launch is a new hypothesis that is to be tested. And with each testing, a set of learning is achieved which will improve its next product launch. In this way, this is how companies become agile and develop the ability to flex and change based on its ability to generate hypotheses.
For digital businesses developing hypothesis is a core way of operating. A hypothesis can be as small as testing the wording of the website using A/B Testing to see which wording is more engaging for website visitors. A/B Testing is where a certain number of visitor traffic is channeled into one version of the website versus another version. And the results of visitor interactions can be used to validate which version is more engaging.
Change management hypothesis testing
To truly adopt a hypothesis-based approach to change management one needs to adopt change hypothesis testing. What is change hypothesis testing I hear you ask? It is basically developing a series of small change experiments to test assumptions. Change experiments are important because they help to inform what change tactics or approaches work or do not work.
Some examples of change experiments include:
Wording of campaign phrases or positioning
Email click-through rate based on details such
as who email is from, time of delivery, etc.
Effectiveness of training exercises
Employee awareness after town hall messages
Impact assessment approach effectiveness
Campaign medium effectiveness such as freebies,
However, it is critical to ensure that hypothesis to be tested is not time nor resource intensive. The experiment must also be tested using feedback data. The hypothesis cannot be proven or disproved unless it is backed by hard data and not just opinions.