In the world of change management, Go Lives are often seen as significant milestones. For many project teams, these events represent the culmination of months or even years of hard work, signaling that a new system, process, or initiative is officially being launched. It’s common for stakeholders to view Go Lives as a key indicator of the success of a change initiative. However, while Go Lives are undeniably important, relying on them as the primary measure of change impact can be misleading and potentially harmful to the overall change effort.
Go Lives are just one piece of the puzzle. Focusing too heavily on these milestones can lead to an incomplete understanding of the change process, neglecting crucial activities that occur both before and after Go Live. Let’s outline the risks associated with using Go Lives to report on change management impacts and offers best practices for a more holistic approach.
Go Lives: A Double-Edged Sword
Go Lives are naturally a focal point for project teams. They represent a clear, tangible goal, and the success of a Go Live can boost morale, validate the efforts of the team, and provide a sense of accomplishment. From a project delivery perspective, Go Lives are critical. They signal that the project has reached a level of maturity where it is ready to be released to the broader organization. In terms of resourcing and business readiness, Go Lives ensure that everything is in place for the new system or process to function as intended.
However, the very attributes that make Go Lives attractive can also make them problematic as indicators of change impact. The simplicity and clarity of a Go Live event can lead stakeholders to overestimate its significance, from a impacted business perspective. The focus on Go Lives can overshadow the complex and often subtle changes that occur before and after the event. While a successful Go Live is necessary for change, it is not sufficient to guarantee that the change will be successful in the long term.
The Pre-Go Live Journey: Laying the Foundation for Change
A significant portion of the change management journey occurs long before the Go Live date. During this pre-Go Live phase, various engagement and readiness activities take place that are critical to shaping the overall impact of the change. These activities include town hall meetings, where leaders communicate the vision and rationale behind the change, and briefing sessions that provide detailed information about what the change will entail.
Training and learning sessions are also a crucial component of the pre-Go Live phase. These sessions help employees acquire the necessary skills and knowledge to adapt to the new system or process. Discussions, feedback loops, and iterative improvements based on stakeholder input further refine the change initiative, ensuring it is better aligned with the needs of the organization.
These pre-Go Live activities are where much of the groundwork for successful change is laid. They build awareness, generate buy-in, and prepare employees for what is to come. Without these efforts, the Go Live event would likely be met with confusion, resistance, or outright failure. Therefore, it is essential to recognize that the impact of change is already being felt during this phase, even if it is not yet fully visible.
Post-Go Live Reality: The Real Work Begins
While the Go Live event marks a significant milestone, it is by no means the end of the change journey. In fact, for many employees, Go Live is just the beginning. It is in the post-Go Live phase that the true impact of the change becomes apparent. This is when employees start using the new system or process in their daily work, and the real test of the change’s effectiveness begins.
During this phase, the focus shifts from preparation to adoption. Employees must not only apply what they have learned but also adapt to any unforeseen challenges that arise. This period can be fraught with difficulties, as initial enthusiasm can give way to frustration if the change does not meet expectations or if adequate support is not provided.
Moreover, the post-Go Live phase is when the long-term sustainability of the change is determined. Continuous reinforcement, feedback, and support are needed to ensure that the change sticks and becomes embedded in the organization’s culture. Without these ongoing efforts, the change initiative may falter, even if the Go Live event was deemed a success.
The Risk of Misleading Stakeholders
One of the most significant dangers of focusing too heavily on Go Lives is the risk of misleading stakeholders. When stakeholders are led to believe that the Go Live event is the primary indicator of change impact, they may not fully appreciate the importance of the activities that occur before and after this milestone. This narrow focus can lead to a number of issues.
Firstly, stakeholders may prioritize the Go Live date to the exclusion of other critical activities. This can result in insufficient attention being paid to pre-Go Live engagement and readiness efforts or to post-Go Live adoption and support. As a consequence, the overall change initiative may suffer, as the necessary foundations for successful change have not been properly established.
Secondly, stakeholders may develop unrealistic expectations about the impact of the change. If they believe that the Go Live event will immediately deliver all the promised benefits, they may be disappointed when these benefits take longer to materialize. This can erode confidence in the change initiative and reduce support for future changes.
Finally, a narrow focus on Go Lives can create a false sense of security. If the Go Live event is successful, stakeholders may assume that the change is fully implemented and no further action is required. This can lead to complacency and a lack of ongoing support, which are essential for ensuring the long-term success of the change.
Best Practices for Reporting Change Management Impact
To avoid the pitfalls associated with relying on Go Lives as indicators of change impact, change management practitioners should adopt a more holistic approach to reporting. This involves considering the full scope of the change journey, from the earliest engagement activities to the ongoing support provided after Go Live. Here are some best practices for reporting on change management impact:
Integrate Pre-Go Live Metrics:
Track and report on engagement activities, such as attendance at town hall meetings, participation in training sessions, and feedback from employees.
Monitor changes in employee sentiment and readiness levels throughout the pre-Go Live phase.
Report on aggregate pan-initiative change initiative impost on business units, pre-Go Live
Emphasize Post-Go Live Support:
Develop metrics to measure the effectiveness of post-Go Live support, such as the number of help desk inquiries, employee satisfaction with the new system, and the rate of adoption.
Highlight the importance of continuous feedback loops to identify and address any issues that arise after Go Live.
Communicate the need for ongoing reinforcement and support to stakeholders, emphasizing that change is an ongoing process
Report on post-Go Live adoption time impost expected across initiatives
Provide a Balanced View of Change Impact:
Ensure that stakeholders understand that Go Live is just one part of the change journey and that significant impacts occur both before and after this event.
Use a combination of quantitative and qualitative data to provide a comprehensive view of change impact.
Regularly update stakeholders on progress throughout the entire change journey, not just at the time of Go Live.
Manage Expectations:
Clearly communicate to stakeholders that the full impact of the change may not be immediately visible at the time of Go Live.
Set realistic expectations about the timeline for realizing the benefits of the change.
Prepare stakeholders for potential challenges in the post-Go Live phase and emphasize the importance of ongoing support.
While Go Lives are important milestones in the change management process, they should not be used as the sole indicator of change impact. The journey to successful change is complex, involving critical activities before, during, and after the Go Live event. By adopting a more holistic approach to reporting on change management impact, practitioners can provide stakeholders with a more accurate understanding of the change journey, manage expectations more effectively, and ensure the long-term success of the change initiative.
The key takeaway is that change management is not just about delivering a project; it’s about guiding an organization through a journey of transformation. Go Lives are just one step in this journey, and it is the responsibility of leaders to ensure that every step is given the attention it deserves.
A lot of change practitioners are extremely comfortable with saying that change management is about attitudes, behaviours, and feelings and therefore we cannot measure them. After all, a big chunk of change folks are more interested in people than numbers. This metaphor that change management is ‘soft’ extends into areas such as leadership and employee engagement whereby it may not be easy to measure and track things. However, is it really that because something is harder to measure and less black and white that there is less merit in measuring these?
“If you can’t measure it you can’t improve it” Peter Drucker”
The ‘why’ behind a lot of industry changes in our day and age come from the fact that data is now dominating our world. Data is a central part of everything that is changing in our world. Since we are now more reliant on the internet for information, the data that can be collected through our digital interactions around our lives are now driving change.
Home assistants like Alexa or Google Assistant can recognize our voices and tell us what we want to know. We can be identified through street cameras. Our Google usage leads to better-targeted advertisements and product promotions. Our Facebook usage leads to a deep understanding of our preferences and lifestyles, and therefore we become targetted by advertisements for what we may find value in (according to Facebook data and algorithms).
At work, we are surrounded by work functions and departments that rely on data to run and manage the business. HR, Finance, Operations, Manufacturing, Risk, Procurement, etc. The list goes on. In each of these departments data is an essential part of the day to day running of the function, without which the function cannot be run effectively.
Now with AI, companies are focused on data at an even greater level more than ever. Without data, AI cannot work nor add value to organisations.
So if our world is surrounded by data, why are we not measuring it in managing change? To answer this question let’s look at what we are or are not measuring.
Starting at a project level, these are some of the common ways in which change is often measured:
1. Change readiness surveys
Change readiness surveys are usually online surveys sent by a project owner to understand how stakeholder groups are feeling about the change at different points in time throughout the project. It can be in the form of a Likert scale or free text. Most results are summarized into a quantitative scale of the degree in which the group is ready for change. A simple SurveyMonkey or Microsoft Form could be set up to measure stakeholder readiness for change.
It used to be that change readiness surveys were quite long and wordy. Nowadays, a lot of change practitioners prefer to have shorter ‘pulse’ surveys as a way to regularly check on the stakeholder sentiments for readiness. However, shorter surveys could mean a lack of depth in the feedback you are receiving and limited data to use to pivot as necessary to address any concerns. So, you may find out if your stakeholders are ready for change, but not why. Ensure you balance ease and speed with insight and outcome.
2. Training evaluation surveys
These evaluations are normally based on participant satisfaction across various categories such as content, instructor effectiveness, usefulness, etc. In a face-to-face training format, these surveys are normally paper-based so as to increase the completion rate. For online or virtual training, ratings may be completed by the user at the conclusion or after the session.
Considering most organisations use virtual training formats, it is good practice to incorporate training evaluation at the conclusion of the session before the participants leave (after which it is almost impossible to get the satisfactory level of participant responses).
With the range of digital/AI-enabled tools on offer now, you can design training sessions in a way that requires much less and effort and gives you better results (to read more check out this link from Forbes). Some of these features include:
– gamifying training content to make it more engaging, interesting and fun
– easily creating micro-courses with little instructional design expertise
– incorporate a range of media such as videos and pictures with little effort
– using avatars as instructors to host the content
– easily create quizzes and assessments
3. Communications metrics
One way in which communications may be measured is the ‘hit rate’ or the number of users/audience that views the article/material/page. This may be easily tracked using Google Analytics which not only tracks the number of views per page but also viewership by the time of day/week as well as audience demographic information as such gender and geographical locations.
There is also a range of digital tools on offer to track the effectiveness of communication efforts. With Microsoft applications such as Yammer and Teams, there is already rich analytics capabilities on offer. These include user/group activity, device type usage, etc. Speak to your IT counterpart to access Microsoft Viva Engage which help you measure your community’s reach and engagement. You can find out more about the people, conversations, and questions & answers that make up your targeted communities.
There are also ways to A/B Test your communications message, whereby you have 2 different messages and test this with a smaller group fo audience to see which ones resonate or lead to more action. You can also create 2 different versions of the same intranet page and test messaging this way. When you have concluded the test you can then select the ‘winning’ version to the broader set of audience.
4. Employee sentiments/culture surveys
There are some organizations that measure employee sentiments or culture over the year and often there are questions that are linked to change. These surveys tend to be short and based on a Likert scale with fewer open-ended questions for qualitative feedback. Since these surveys are often sent across the entire organization they are a ‘catch-all’ yardstick and may not be specific to particular initiatives.
There is now a range of AI tools to do text and sentiment analysis if your survey contains text items. All the major technology providers such as Microsoft, Amazon and IBM already provide these tools (some are even free). These are some of the ways you can use AI tools right now:
– detect a range of emotions such as anxiety, anger, and disgust and based on response statistics
– cluster topics based on key response themes
– identify any data anomalies that you may want to exclude
– identify and label tone of voice of the responses, and classification such as positive, neutral, negative
– analyse trends over time
Data analysis and reporting can also be easily leveraged with the range of digital tools on offer. Data analysis tools using AI can automated generate charts and dashboards for you with little effort. Change Automator contains rich survey features that do exactly this, including:
– Easily selecting chart type with one click
– Leverage from AI-suggested data insights
– Generate predictive trends based on existing data
– Easily share charts and dashboards using different ways, including a URL link
5. Change heatmaps
Some organizations devise change heatmaps on excel spreadsheets to try and map out the extent to which different business units are impacted by change. This artifact speaks to the amount of change and often leads to discussions concerning the capacity that the business has to ‘handle/digest’ change. The problem with most heatmaps is that they are usually categorised and rated by the creator of the artifact (or a limited number of people making judgments), and therefore subject to bias. Data that is based on 1 person’s opinions also tend not to have as much weight in a decision-making forum.
In fact, we highly recommend that you don’t use change heat maps as the only way to track change volume. Instead, there is a range of other visuals such as bar charts, and timeline charts that are just as easy to interpret and are more insightful from a decision-making perspective.
Heatmaps are also by design categorical and not particularly precise. It may be useful at a high level for understanding hot spots, but not one to use to make specific decisions concerning business capacity levels and corresponding challenges.
The following is an example of a Change heatmap that uses the standard red, amber green traffic light coding scheme. This may play into the psychological bias of your audience interpreting red as bad and only focus on ‘alleviating’ the red.
6. Change initiative benefit tracking
In addition to typical change management measures, there are various initiatives-specific measures that focus on the actual outcome and benefit of the change with the goal of determining to what extent the change has taken place. Some examples of this include:
System usage rates
Cost reduction
Revenue increase
Transaction speed
Process efficiency
Speed of decision-making
Customer satisfaction rate
Employee productivity rate
Incidents of process violation
Non-initiative based change management measures
There are two other measures that are used within an organizational vs. initiative-specific context, change leadership assessment and change maturity assessment. In the next section, we will discuss these two areas.
Change leadership assessment
David Miller from Changefirst wrote about 3 types of change leaders.:
1. The sponsor whose role is to drive the initiative to success from the beginning to the end. This involves possessing competencies in rallying and motivating people, building a strong network of sponsors, and communicating clearly to various stakeholder groups.
2. The influencer whose role is to leverage their network and influence to market and garner the traction required to make the initiative successful. Four types of influencers as identified by Changefirst includes:
a) Advocates who are great at promoting and advocating the benefits of the change
b) Connectors who are able to link and leverage people across a part of the organization to support the change
c) Controllers who have control over access to information and people and these could include administrators and operations staff
d) Experts who are viewed by others in the organization as being technically credible
3. The change agent is someone who is tasked with supporting the overall change in various ways, including any promotional activities, gaging different parts of the organization on the change and be able to influence, up, down and sideways across the organization to drive a successful change outcome. Some call this the ‘change champion’. They can be your key to influencing across the organisation.
Whilst there isn’t one industry standard tool for assessing change leadership competencies and capabilities. There are various change leadership assessment tools offered by Changefirst as well as other various smaller consulting firms. Some of the ways in which you can assess change leadership may include categories such as Goal Attainment, Flexibility, Decision Making, and Relationship Building.
Some of the key competencies critical in change leadership have been called out by Pagon & Banutal (2008), and include:
Goal attainment
Assessing organizational culture and climate
Change implementation
Motivating and influencing others
Adaptability
Stakeholder management
Collaboration
Build organizational capacity and capability for change
Maneuvering around organizational politics
There is a range of change leadership assessment offerings from various consulting firms. Whichever one you choose, ensure that it is not overly simplistic and not ‘tested’ and therefore not reliable. Assessments will only be useful if they have gone through the rigour of being tested, with the results showing that they are reliable can be trusted. Anyone can ‘invent’ a simple survey with various leadership categories, but this does not mean they are actually valid. Afterall, if you are asking your leaders to spend time to fill in an assessment survey, you want to be confident that the outcome of the assessment will provide sufficient insight.
Change maturity assessment
Organisations are increasingly realising that managing change initiative by initiative is no longer going to cut it as it does not enable organizational learning and growth. Initiatives come and go and those who rely on contractor change managers often find that their ability to manage change as an organization does not mature much across initiatives, especially across time.
Change maturity assessment is focused on building change capability across the organization across different dimensions, whether it be project change management, operational change or change leadership. The goal of conducting a change maturity assessment is to identify areas in which there may be a capability gap and therefore enable structured planning to close this gap. The meaning of ‘capability’ does not just refer to people skills, but also to process and system capabilities.
Change maturity assessment results may prompt focus and action to improve change management capabilities if used in the right channels to influence the leadership and the business.
There are 2 major change maturity assessment models available in the market. The first is by Prosci and the second is by the Change Management Institute (CMI). Read up more about CMI’s Organisational Change Maturity Model here. To read more about change maturity assessment read out article A New Guide for Improving Change Management Maturity, where we outline how to improve change maturity throughout different business units across the organization.
A comprehensive model of Change Management Measures
In this diagram various change management measures are represented along two axes, one being the different phases of the initiative lifecycle, and the other being different organizational levels of project, business and enterprise in which change management measures fall into.
In the broad initiative phases of Plan, Execute and Realise there are various change measurements and assessments that may be applicable. At the Business and Enterprise levels, these measurements and assessments are not so much split according to initiative phases. Instead, they may be conducted periodically, for example change capacity and impost tracking may be done on a monthly basis, with change maturity assessment conducted at an annual basis.
Project level measures
1. ‘Plan’ phase
In this phase of the project, the team is discovering and scoping what the project involves and what the change is. As a result, the details are not known clearly at the commencement of the phase. Later in the phase the scope becomes much clearer and the team starts to plan what activities are required to implement the change.
The change complexity assessment evaluates how complex the project is. It looks at how many people could be impacted, what the size of the impact could be, how many business units are impacted, whether multiple systems and processes are impacted, etc.
Change resourcing costing. At the planning phase of the project cost required for the change management stream of the work is required. This includes such as any contractors, communication campaigns, learning cost, travel, and administration cost, just to name a few.
Change readiness assessment is usually conducted prior to the change and during the change. Usually, the same set of questions is asked of various stakeholder groups to assess their readiness for change.
2. ‘Execute’ phase
The execute phase is one of the most critical parts of the project. Activities are in full flight and the project is busy iterating and re-iterating changes to ensure successful execution to achieve project goals.
Communication and engagement tracking. Effective engagement of stakeholders in the change is absolutely critical. Stakeholder interviews, surveys, communication readership rates are all ways in which engagement may be tracked.
Learning tracking. Measuring learning is critical since it tracks to what extent the new competencies and skills have been acquired through learning interventions. Typical measurements include course tests or quizzes in addition to course evaluations. On the job performance may also be used to track learning outcomes and to what extent learning has been applied in the work setting.
Change readiness assessment continues to be critical to track during the execution phase of the project
3. ‘Realise’ phase
In this phase of the project the change has ‘gone live’ and most project activities have been completed. It is anticipated in this phase that the ‘change’ occurs and that the benefits can then be tracked and measured.
Change benefit tracking measures and tracks the extent to which the targeted benefits and outcomes have been achieved. Some of these measures may be ‘hard’ quantitative measures whilst others may be ‘soft’ measures that are more behavioural.
Business level measures
Business level measures are those that measure to what extent the business has the right ability, capacity, and readiness for the change.
Change heatmaps can help to visualize which part of the business is most impacted by 1 project or multiple projects. The power of the change heatmap is in visualizing which part of the business is the most impacted, and to compare the relative impacts across businesses. As the number of change initiatives increase so would the complexity of the change. When facing this situation organisations need to graduate from relying on excel spreadsheets to using more sophisticated data visualization tools to aid data-based decision making. To read more about change heatmaps and why this is not the only way to understand business change impact, go to The Death of the Change Heatmap.
Sponsor readiness/capability assessment can be a critical tool to help identify any capability gaps in the sponsor so that effort may be taken to support the sponsor. A strong and effective sponsor can make or break a change initiative. Early engagement and support of the sponsor are critical. Both Prosci, as well as Changefirst, have sponsor competency assessment offerings.
Change champion capability assessment. Change champion or change agent are critical ‘nodes’ in which to drive and support change within the organizational network. A lot of change champions are appointed only for one particular initiative. Having a business-focus change champion network means that their capability can be developed over time, and they can support multiple initiatives and not just one. Assessing and supporting change champion capability would also directly translate to better change outcomes.
Change leadership and change maturity assessment – refer to the previous section
Change capacity assessment.
In an environment where there is significant change happening concurrently, careful planning and sequencing of change in balance with existing capacity are critical. There are several aspects of change capacity that should be called out in the measurement process:
Different parts of the business can have different capacity for change. Those parts of the business with better change capability, and perhaps with better change leadership, are often able to receive and digest more changes than other businesses that do not possess the same level of capability.
Some businesses are much more time-sensitive and therefore their change capacity needs to be measured with more granularity. For example, call centre staff capacity is often measured in terms of minutes. Therefore, to effectively plan for their change capacity, the impacts of change needs to be quantified and articulated in a precise, time-bound context so that effective resourcing can be planned in advance.
The change tolerance or change saturation level for business needs careful measurement in combination with operational feedback to determine. For example, it could be that last month a part of the business experienced significant change impact across several initiatives happening at the same time. The operational indicators were that there was some impact on customer satisfaction, productivity, and there were negative sentiments reported by staff that there was too much change to handle. This could mean that the change tolerance level may have been exceeded. With the right measurement of change impact levels for that part of the business, next time this level of change is seen, previous lessons may be utilized to plan for this volume of change. Utilise measurement and data visualization tools such as the Change Compass to track change capacity.
Enterprise level change measures
At an enterprise level, many of the business unit level measures are still applicable. However, the focus is comparing across different business units to sense-make what each part of the business is going through and if the overall picture is aligned with the intentions and the strategic direction of the organization. For example, typical questions include:
Is it surprising that one part of the business is undergoing significant change whilst another is not?
Is there a reason that one business unit is focused on a few very large changes whilst for other business units there is a larger set of changes each with smaller impacts?
Is the overall pace of change optimum according to strategic intent? Does it need to speed up or slow down?
What is the process to govern, report and make decisions on enterprise level change, prioritization, sequencing and benefit realization?
Is there one business unit that is able to manage change more effectively, faster with greater outcomes? How can other business units leverage any internal best practices?
As mentioned in the Change Management Measures diagram, some enterprise level change measures include:
Change capacity assessment – Does one business unit’s change capacity limits mean that we are not able to execute on a critical strategy within the allocated time? How do we create more capacity? Ways in which to create more capacity could include more resources such as staff, or initiative funding, more time is given, or more talent to lead initiatives
Change maturity assessment – At an enterprise level, the concern is with the overall change maturity of the organization. How do we implement enterprise level interventions to build change maturity through programs, networks, and exchanges, such as:
Enterprise change capability programs
Enterprise change analytics and measurement tools
Enterprise change methodology
Enterprise network of change champions
Strategy impact map – Change management need not be focused only on project execution or business unit capability. It can also demonstrate value at an enterprise level by focusing on strategy execution (which by definition is change). The way in which different strategies exert impact on various business units may be visualized to help stakeholder understand which initiatives within which strategic intent impact which business units. To illustrate this please refer to the below diagram which is an example of a strategy impact map. In this diagram, each of the organisation’s strategy is displayed with different initiatives branching out of each strategy. The width of each initiative correlates with the level of impact that the initiative has on the business over a pre-determined period of time. Therefore, the width of each strategy also indicates the overall relative impact on the business.
This data visualization artifact can be valuable for business leaders and strategic planning functions as it depicts visually how the implementation of various strategies is impacting business units. This helps planners to better understand strategy implementation impacts, potential risks and opportunities, and balancing change pace with strategy goals at various points in time.
Predictive indicators on business performance – We started this article talking about how data is all around us and we also need to better manage change using data. With quantitative data on change impact, it is possible to ascertain any correlations with operational business indicators such as customer satisfaction, service availability, etc. For those business indicators where there is a significant correlation, it is possible to hence use predictive reporting to forecast performance indicator trends, given planned change impacts.
In the below graph you can see an example of this whereby using historical data it is possible to establish correlations and therefore forecast future impact on business indicators. This example is focused on the customer contact centre (CCC) and key business indicator of average handling time (AHT) is utilized as an illustration.
This type of predictive performance forecasting is extremely valuable for organisations undergoing significant change and would like to understand how change may impact their business performance. By demonstrating the impact on business indicators, this puts the importance of managing change at the front and centre of the decision-making table. At The Change Compass, we are developing this type of measurement and reporting function. This is the frontier for change management – to be established as a key business-driving function (versus a standard back-office function).
Change can be measured and this article has outlined various operational and strategic ways in which change measurement can demonstrate significant value. Most corporate functions cannot exist without data and analytics. For example, Human Resources relies on people and pay data. Marketing cannot function without measurement of channel and campaign effectiveness. For Information Technology, pretty much everything is measured from system usage, to cost, to efficiency. It is time we start utilizing data to better visualize change to better plan and make business decisions.
Have a chat with us if you are looking for ways to streamline how you capture, visualise data for decisions, and leverage AI to easily generate insights. This includes the ability to easily do forecasting, ask data questions using natural language and get instant answers.
In almost every change initiative there is an element of behaviour change. For some initiatives, the behaviour change required is large and complex whilst for others it can be as small as pressing different buttons and using a different user interface. Effective behaviour change is one of the most critical outcomes that the change practitioner can hope to achieve. With the achievement of desired behaviours come the ultimate benefit associated with an initiative. On the other hand, not achieving the behaviour change targeted means that the change has not succeeded.
Given the importance of behaviour change in every initiative this article aims to cover key aspects of how a change practitioner should approach and design the behaviour change. Yet, successfully designing and implementing behaviour change is one of the most challenging tasks for the change practitioner. It is common place that many change practitioners do not have the experience to know how to achieve successful behaviour change.
The definition of behaviour change
So what is behaviour change?
Behaviour change “refer(s) to any transformation or modification of human behaviour”.
Wikipedia
This seems like a fairly general definition that is all-encompassing and can include anything ranging from behaviour change in a psychological context or in a social or workplace context.
However, a key part of behaviour change is to recognise that behaviour, by definition, must be observable in some Shape or form. A behaviour can be verbal, non-verbal, or physical behaviour. However, a behaviour cannot be ‘perception’ or ‘thinking’ since these cannot be observed nor displayed necessarily.
Another feature of behaviour change is that the behaviour is to be changed from the current state to a future state. The quantum of the change determines the complexity of the change required and the extent to which a series of change interventions is required to achieve the desired future state. This means, if the behaviour change is easy from the impacted person’s perspective, then the change approach can be fairly light and does not need to be complex. However, if the quantum of the change is large, then a heavy design of change interventions is expected to achieve the outcome.
Some examples of behaviour change within a change initiative context includes:
Using a different computer program interface with different layout or keystroke steps in performing tasks
Different process steps required in disclosing financial details in business reporting
Proactive coaching employees through feedback to improve sales effectiveness
Reporting on risk incidents that are not compliant with company standards
Actively establishing rapport with the customer to demonstrate empathy by acknowledging their feelings and demonstrating effective listening
Speak up against bullying behaviours amongst colleagues
The importance of focusing on behaviour change
Inexperienced change practitioners will normally just followed the standard cookie-cutter approach of filling out the various change templates such as stakeholder matrix, change impact assessment, and a change plan. And then proceed to develop a communications plan or a learning plan before executing on implementation.
So what is wrong with this?
As called out previously, in almost every change initiative there is a set of desired behaviours required to achieve the end state of the change initiative. The job of the change practitioner is to figure this out and design a change program around the achievement of these behaviours. Just by filling in templates and carrying out standard change approaches will most likely not achieve the targeted behaviours.
For example, in transitioning users from an old ERP system to a new digital system with a new look and feel, it is critical to identify the core behaviours required in the new state. Is it that in using the new digital system the user has access to a lot more timely data and therefore the behaviour change needs to be around 1) proactively checking for data and derive insights and 2) use these insights and data to make better decisions.
This means that if you were to just focus on communicating the change and train employees on how to use the new digital system, the whole project may not be deemed to be successful. This is because it is simply a project of ‘installation’ of a new system. However, the benefits targeted by the new digital system is about employees gaining more insights through the ability to easily access a range of data previously not available. Employees may know how to use the new system but it does not mean that they will automatically exhibit these desired behaviours.
One of the tricky things about behaviours is the ‘knowing’ vs. ‘doing’ conundrum. Just because someone knows how to do something it does not mean they will necessarily do it. Just because there is a pedestrian path, it does not mean that everyone will always use it. In a similar way, just because someone knows that the company wants him/her to document sales activities, it does not equate that all sales people will document all sales activities. In fact, in practice, we know that spending time on ‘admin’ such as documenting and entering sales activities into a system is often the last thing sales people want to do.
In the next section we will cover how to drive behaviour change.
How to achieve behaviour change
BJ Fogg model
Dr BJ Fogg is a Stanford professor who founded the Behavior Design Lab at Stanford University. BJ Fogg also wrote the New York Times bestseller ‘Tiny Habits’. What I love about this is that the Fogg model is incredibly simple and practical. It is grounded and backed up by significant empirical research and not just an ‘opinion’.
The Fogg model highlights 3 key elements that must converge at the same time for a behaviour to occur.
1. Motivation – Different motivators have different impacts on behaviour
2. Ability – This refers to how easy it is to undertake a behaviour. Some characteristics include time, money, physical effort, brain cycles (or ease of understanding and processing the task at hand), social deviance (the extent to which a behaviour is out of the social norm), and non-routine (behaviour that disrupts an existing routine)
3. Prompt/Trigger – These are reminders of events that prompt a particular behaviour. It could be an alarm, an associated image/event/person/scent, etc that reminds the person of the behaviour.
The power of this model is in its simplicity. You can apply this to any change initiative and the model will guide your thinking on how to design effective behaviour change. When something feels easy to do (low ability), then it will not require a lot of motivation to do it. Alternatively, when something is perceived as very hard to do, then it will require very high motivation to understate the behaviour. The key is to aim above the line. So, either focusing on increasing ability or increasing motivation will result in above the curved line, which means the behaviour taking place.
Example of applying the Fogg model
Case: You are implementing a cost cutting exercise due to the impact of Covid on the organisation. As a result of this exercise, the impacted employees will need to pick up parts of the roles of others who have been let go. The behaviour change required is that impacted employees will need to cover a broader set of tasks and at times have a heavier workload as a result.
Application:
Motivation: The impacted employee’s motivation is currently impacted after seeing their fellow colleagues lose their jobs and hence feeling worried that their jobs may be impacted. This is despite reassurances from senior managers that no more jobs will be cut for the time being. The challenge will be to sufficiently motivate these employees by continuously reassuring them of their job safety and working through the transition of having a broader role responsibility. Appealing to the focus on supporting customers and not letting them down may be a theme to reinforce.
Ability: It is critical to assess to what extent impacted employees are able to carry out new tasks assigned from a skill perspective. Training or coaching may be required. The other area to address is workload concerns. The perception that a heavy workload is required will hinder their likelihood of carrying out the additional responsibilities. Workload prioritisation and protocols are key topics to talk through to reassure employees how workload may eventuate during heavy periods.
Trigger: Different triggers may be designed to remind and reinforce the uptake of new accountabilities. These may include manager 1:1s, team reporting, open visual display of performance indicators, email reminders, colleague reinforcement/coaching, etc.
According to the Fogg model if the new accountabilities are significant it would be best to break these down into smaller behaviour increments vs a ‘big bang’ transition. It could be that there is a gradual transition whereby a period of continuous coaching is required after gradually introducing new sets of tasks for the employee to uptake and practice. After the transition period is completed, the employee then formally uptakes on the full accountabilities.
According to research findings, it is much easier to adopt the new behaviours if the discrete behaviours are broken down to small increment behaviours. Fogg has used lots of different examples of this one of which is doing push-ups. He started by doing 10. Then he would add 1 more every day to the push-up exercise, eventually getting to 100 push-ups. Adding a trigger to the new behaviour is also critical. For example, Fogg gave the example of doing sit-ups first thing in the morning as soon as you get up or doing pushups after going to the toilet. The event of getting up or going to the toilet then becomes a trigger for the new behaviour.
Cognitive Behavioural Therapy (CBT) approach to behavioural change
Cognitive Behavioural approaches to behaviour change.
Cognitive behavioural therapy is a widely established clinical approach to changing behaviours in patients suffering from various psychological conditions or disorders. Cognitive approaches are based on the fact that the way one thinks determines one’s reaction and therefore one’s behaviour. For example, self-talk is a mechanism to change one’s opinion or perception. Constantly reinforcing and verbalising positive statements about oneself may improve one’s own perception of oneself. Alternatively, constant negative self-talk leads to negative self-perception.
Behavioural approaches are based on research that started with Pavlov’s research on dogs where he associated bells as a trigger for food. After a period of time, every time the dogs heard the bell they would start salivating, with salivating being the behaviour. This process of associating a trigger with a behavioural reaction is also called ‘conditioning’. The process of conditioning is to ‘re-program’ the subject so that a new behaviour is introduced in reaction to a trigger.
There are many ways in which cognitive behavioural approaches may be applied to changing a person’s behaviour. For example, lets use the previous example of implementing a new system.
Creating or changing impression of the new system
A communications campaign may be devised to create or change the existing impression of the new system. This would be similar to any marketing campaign that associated particular imagery or messages with a feeling or impression. Over a period of repetition, the employees will start to associate positive impressions and key messages with the new system. Any tag-lines that are reinforced by manager briefings or town hall sessions would also act the reinforce the same messages.
As a part of the training of the new system, it could be that other than learning the ins and outs of the operating the new system, the employee needs to be more proactive in looking at customer information to provide more value-add suggestions to the customer. Practices during the session, with subsequent reinforcements by the team leader or manager would act to build the behaviour change.
The trigger for new behaviours could be any acronyms, diagrams, tag lines, or pictures created as a part of the campaign or training content. It is however important that there is a period of reinforcement or else the behaviour may not occur. The reinforcement may take form in terms of manager support, communication messages, prizes, competitions, and reporting on behaviour progress.
This is why post-release embedment is so important as the embedment process focuses on constantly reinforcing the behaviour so that it becomes second nature. Without this, the newly acquired behaviour will not be sustained. This is like exercise. Exercising a few times and your body starting to get the drift of what to do is just the start of the change. Without a period of constant exercising, it will not become a habit.
The other important cognitive behavioural approach to embedding new behaviour is ensuring adequate and effective social support. Some employees may be quite self-sufficient and are able to resolve any system issues themselves. Others may require a lot more hand-holding. This is why there must be change champions in place who can coach and support employees to support the right behaviours and resolve any obstacles in adopting the new system fully.
How to measure behaviours
Measuring behaviours is absolutely critical because without effective measurement it is difficult to ascertain to what extent the desired behaviours have been obtained and sustained. It is the old adage “What gets measured matters”.
So what are some of the ways in which to measure behaviours? These are some common examples.
Manager rating based on observation
Video recording
Phone/call listening
Attendance (e.g. training)
Test
System/digital reporting that tracks behaviour in a system
Employee-wide surveys specifically designed to focus on targeted behaviours
What categories in which to measure behaviours?
There are many considerations or dimensions in measuring behaviours. The following are some of these:
Time: How long would you want to measure the behaviours to ensure that they have fully embedded and incorporated into business-as-usual. Typical practice is several months after the ‘release’. Tracking reinforces behaviours. This means the longer the tracking mechanism continues – the more likelihood the behaviours will last longer
Level of behaviour change: Is the behaviour being measured black and white in its determination? I.e. is it easy to categories if the behaviour has occurred or not? Or are there different levels of behaviour achievement? E.g. If you are measuring if call centre staff has exhibited behaviour is reviewing customer data and offer suggestions, are there different levels of ‘value add’ behaviours based on customer data, in which case there could be a scale to rate this. Alternatively, it could also be a yes/no type of classification
Frequency: How frequent is the behaviour being displayed? Is it that the goal is to promote the frequency of the desired behaviour? Or are there certain limits expected? For example, if we would like call centre staff to offer value add calls with the customer, are there particular ‘ceilings’ or limited after which it may no longer be valuable for the customer?
Situational considerations: Ranking and classifying behaviours should also always consider situational factors. For example, it could be that the customer was not in the right emotional state to receive value-add suggestions and therefore the behaviour would not be appropriate for that situation. It could also be that the call centre consultant has been suffering from sickness or has been struggling with family difficulties and therefore for a period of time was not performing effectively. As a result, previously acquired behaviours could have dropped temporarily
How do we drive full embedment of behaviours?
These are some key call-outs in ensuring that the behaviours you have set out to transition to not only are achieved but are sustained. Pretty much all aspects of change could determine the extent to which behaviours become adopted or not.
1. Executive sponsorship and drive. You will hear a lot of this in literature and articles that with executive sponsorship and drive it is much easier for behaviours to be sustained.
2. Employee community support and reinforcement. This point acts almost as the balancing point of the previous one. With sufficient employee community support and reinforcement, it is possible to drive continual behavioural reinforcement even without strong executive sponsorship.
3. Measurement and reporting. With the right measurement and reporting, employees receive feedback on what their performance has been, and this constant feedback acts as a strong reinforcement. This is especially the case if everyone can see others’ behavioural performance. It could be by business unit or individual, but ‘naming and shaming’ can work if that is consistent with the organisational cultural values.
4. Early and continuous engagement. This is a change management 101 point. With early and continuous engagement impacted stakeholders will feel much more engaged with the change. As a result, they will want to exhibit the desired behaviours to make it a success because they feel that they are the ones driving the changes. Alternatively, if the change is perceived as designed and implemented by another party without consultation with the impacted group, there could be resistance or lack of embedment.
5. Culture of continuous improvement. A culture of continuous improvement can also support continual and full embedment of behaviours. If there is a strong culture of analysing the current performance, working on root cause analysis, and team work on actions to improve performance, then behaviours will be adopted. In this situation, any situational or personal factors or not exhibiting behaviours may be called out and addressed to achieve the targeted outcome.
Complexity of embedding multiple behaviours across multiple initiatives
Most organisations are implementing multiple initiatives at the same time. This is the norm as organisations stay competitive, stay relevant, and in business. When multiple projects are going on all driving seemingly different behaviours.
How do we embed multiple behaviours?
1. Understand the different behaviours across initiatives. Rather than focusing on every single behaviour driven by every initiative, the key is to capture and record the top few behaviours targeted by each initiative. For large organisations with lots of initiatives, this may seem like an impossible feat. It could be organising 1-2 workshops to capture these behaviours. Do note that different initiatives may be at different stages of the product life cycle and therefore it may not be possible to capture all behaviours at a particular point in time. Having a regular change portfolio meeting where this could be discussed and captured iteratively would be ideal.
The Change Compass has just released a feature to aid the collection of core behaviours across initiatives so that these may be analysed, understood, and linked to aid better implementation alignment. You can tag key target behaviours to each initiative or project. For example, customer-centricity or efficiency. Then you can look through those initiatives impacting one part of the business and the core behaviours being driven across multiple initiatives.
2. Analyse and group the captured behaviours. After compiling the behaviours across initiatives the next step is to group and understand them.
Are there behaviours that are part of the same theme? For example, what are initiatives that are promoting a closer focus on the customer by promoting better listening and empathy skills?
Are there any behaviours that are ‘contradictory’ to other behaviours? Here is a real example. For a bank, one initiative was tasked to retire and close off a particular credit card due to a lack of profitability. However, at the same time, the same team was asked to try and sell more of their business unit head to meet their sales target.
3. Examine behaviours that are grouped into the same theme and think of ways to better align and join the dots to improve execution and behaviour embedment. This step is the most crucial step and involves running workshops across initiatives to better align approaches and plan for synergistic implementation of change across initiatives. Key discussion points or opportunities may include:
Aligning key messages and positioning for common behavioural themes. For example, if 2 initiatives are focused on improving customer-centric, how might these better align their communication activities, look and feel of communications collateral, wording, and positioning of behaviours.
Align, cross-leverage and cross-reference learning content. If multiple initiatives are all driving common behaviours, can content be cross-reinforced across multiple initiatives to drive a consistent and aligned user experience? This also ensures that there is no duplication of efforts in covering the same content
Align the sequencing and implementation of change activities. If 2 initiatives are both driving similar behaviours, can the various change activities be better sequenced and aligned to drive a better outcome than 2 separate siloed approaches? For example, can the executive sponsor speak to both initiatives in their town hall address, and can change champions be cross-leveraged to talk about both initiatives to help impacted teams join the dots around the common behaviours?
Successful and fully embedded behavioural change is the epitome of successful change and transformation initiatives. Achieving this is not always easy but having the right focus and adopting a structured approach to design behaviour change will ensure initiative success. Don’t be afraid of experimenting to test different ways in which to drive behaviour change. Keep iterating with different approaches to drive the full adoption of behaviours, which in turn will then ensure the full achievement of initiative benefits.
The role of change managers has been left out of the various agile methodologies. This is even though most fully acknowledge the importance of change management in the success of initiatives. Does this mean that the agile teams should and can take on the role of change managers? While most of you reading this article may have change practitioners in the organisations, there are plenty of organisations that run agile teams without change managers in the team.
Is it that in agile environments, change management responsibilities are distributed across team members rather than centralised in a single role? After all the agile team is self-organising and has shared accountability?
For organisations that do not have change managers in agile teams, they are still able to deliver valuable and continuous changes. The difference is in how effective the agile team is in delivering a solution where:
A range of stakeholders are continuously engaged effectively and therefore have high levels of readiness
Stakeholders’ readiness for the pace and design of agile is taken into account and various education/engagement sessions are designed as required
They’re able to identify the various behavioural changes required in fully adopting the change
Stakeholders continuously track and reinforce adoption
The team is aware of the change landscape of impacted stakeholders and can work with them respectively to design and deliver in a way that maximises adoption in a targeted way
It is quite difficult for a small agile team to have all these skillsets. You can equally place the same argument for Business Analysts. Even if the team does not have this role, they could equally undertake a lot of the tasks that a Business Analyst would typically undertake in an agile project, however, maybe not at the same level of professionalism and rigor.
In a small agile team of cross-functional specialists, by design each member is a specialist in his/her functional domain, whether it is testing, software development, operations, etc. It would be rare for a domain specialist to have such a breadth of skillsets to include a range of change management skills. Of course, this is not impossible, but difficult for a team to possess.
An agile team is by design focused on delivering. By design, the agile team is laser-focused on its iteration work and delivering to the schedule at the right quality. It does not have a lot of capacity to devote itself to working with a wide range of stakeholders as a result. The change manager, on the other hand, is by design focused on the world of the stakeholders as well as what the agile team is delivering and designing a series of steps for the changes to take place or a people and organisational perspective.
Moreover, beyond project change management skills, organisations that have a myriad of self-organising agile teams require greater air-traffic control at a portfolio and enterprise level. Whilst this may be fulfilled from a portfolio management perspective, attention should also be paid to change portfolio management. Within a fast-paced change environment, the capacity stakeholders across the organisation have for the changes, and the overall prioritisation and sequencing for these changes are paramount.
Without this, changes may fall off the radar, superseded by other competing changes delivered by other agile teams. Alternatively, change saturation fatigue may be a result. In fact, there is increasing evidence that this is prevalent across organisations. Stakeholders’ capacity for change is limited and must be managed effectively to ensure the right changes are adopted.
If change management so critical to agile changes let’s delve into the essential role that change managers play within agile teams, breaking down their contributions across the four typical phases of an agile initiative: Define, Build, Test, and Deploy.
Define Phase
During the Define phase, agile teams lay the groundwork for the project by identifying objectives, scope, and initial requirements. For change managers, this phase is critical for assessing the scope and complexity of the change and determining the necessary resources and support structures.
Key Activities for Change Managers in the Define Phase:
1. Assessing Change Size and Complexity: Change managers evaluate the magnitude of the change and its potential impact on various parts of the organization. This assessment helps in tailoring change management strategies to address specific needs.
2. Resource Planning: Identifying the required business and change support resources is essential. This includes assembling a team of change champions, communication specialists, and trainers who will help facilitate the change.
3. Strategic Planning: Developing a comprehensive plan that outlines key activities and tactics to engage stakeholders and drive successful change. This plan acts as a roadmap for the entire change management process.
Build Phase
In the Build phase, agile teams start developing the solution. Change managers intensify their efforts to understand the potential impacts of the change and begin engaging stakeholders.
Key Activities for Change Managers in the Build Phase:
1. Detailed Stakeholder Assessments: Conducting thorough assessments to identify how different stakeholders will be affected by the change. Understanding these impacts is crucial for tailoring communication and training efforts.
2. Initiating Stakeholder Engagement: Early engagement with stakeholders to communicate the vision, goals, and expected outcomes of the change. This engagement helps in building awareness and buy-in from the outset.
3. Scenario Planning: Since the exact nature of the change may not be fully defined, change managers work with various scenarios to anticipate potential challenges and opportunities. This flexibility allows for adaptive communication and engagement strategies.
Test Phase
The Test phase is where agile teams validate the solution through testing and feedback. For change managers, this phase is pivotal for ensuring stakeholders are prepared for the upcoming changes.
Key Activities for Change Managers in the Test Phase:
1. Collaborating on Testing Processes: Working closely with agile teams to determine how stakeholders can be involved in testing. This may include business testers, change champions, or end-users who provide valuable feedback.
2. Designing Communication Content and Learning Interventions: Developing and rolling out communication materials and training programs to prepare stakeholders for the change. These interventions are tailored based on feedback from testing.
3. Engaging Stakeholders Through Various Channels: Utilizing demos, team briefings, and other engagement channels to keep stakeholders informed and involved throughout the testing process.
Deploy Phase
The Deploy phase marks the transition of the solution into the live environment. Change managers play a crucial role in ensuring a smooth transition and full adoption of the change.
Key Activities for Change Managers in the Deploy Phase:
1. Ensuring Readiness: Before deployment, change managers gather evidence that stakeholders are ready for the change. This involves assessing training completion, communication effectiveness, and overall preparedness.
2. Executing Engagement Strategies: During deployment, change managers leverage various engagement channels to support the transition. This includes continued communication, support hotlines, and face-to-face interactions to address any concerns.
3. Monitoring and Feedback: Establishing performance metrics to monitor the adoption and effectiveness of the change. Feedback is collected and analyzed to make necessary adjustments and integrate the change into business-as-usual operations.
Key Differences in Change Management for Agile Teams
While the core principles of change management remain consistent, their application within agile teams introduces unique challenges and opportunities. Here are some key differences:
Proactive Integration in Cross-Functional Teams
Change managers actively contribute to the progress of agile teams by embedding themselves within the cross-functional team structure. This close collaboration ensures that change management activities are aligned with the development process, allowing for more effective and timely interventions.
Flexibility and Adaptation
In agile environments, the content and nature of changes may evolve throughout the project lifecycle. Change managers must remain flexible, working with scenarios and adaptable communication strategies to respond to shifting requirements and stakeholder needs.
Continuous Feedback and Engagement
Ongoing stakeholder engagement and continuous feedback are cornerstones of effective change management in agile teams. Regular check-ins, feedback loops, and open communication channels help to identify and address concerns early, ensuring smoother transitions and higher adoption rates.
Iterative Planning and Adjustment
The iterative nature of agile projects necessitates continuous review and adjustment of change management plans. Change managers must be prepared to tweak strategies, update communication materials, and refine training programs based on real-time feedback and evolving project dynamics.
Practical Tips for Change Managers in Agile Teams
1. Embed Yourself in the Team: Become an integral part of the agile team to gain a deeper understanding of the project dynamics and build strong relationships with team members.
2. Embrace Flexibility: Be prepared to pivot and adapt your change management strategies as the project evolves. Flexibility is key to staying relevant and effective. Come up with scenarios such as communication materials and engagement tactics as needed.
3. Drive Proactive Open Communication: Create an environment where stakeholders feel comfortable sharing feedback and concerns. This openness will help you address issues promptly and maintain trust. Note that stakeholders may need learning interventions to truly understand and adjust to agile ways of working.
4. Leverage Data and Metrics: Use data and performance metrics to monitor the effectiveness of your change management efforts. Data does not just apply to the rest of the agile team. Change management data is no less valuable. This will help you make informed decisions and demonstrate the value of your work. To read more about how to measure change check out our practical guide here.
5. Continuous Stakeholder Engagement: Engage with stakeholders early and often. Building strong relationships and maintaining regular communication will increase the likelihood of successful change adoption.
6. Understand the Change Landscape: Since the change manager’s role is to adopt a people lens, it is critical to see from the impacted stakeholder’s perspective the range of changes they are or will be going through. Change that is designed in a vacuum will not be successful.
Change managers play a pivotal role in the success of agile teams, ensuring that changes are effectively adopted and integrated into the organization. By understanding the unique dynamics of agile projects and adopting flexible, proactive, and iterative approaches, change managers can significantly enhance the readiness and adoption of changes. Their efforts not only support the agile team but also drive the overall success of the organization in navigating an increasingly intense landscape of changes.
Change management professionals are increasingly requested to provide measurement, data, and insights to various stakeholder groups. Not only does this include tracking various change outcomes such as business readiness or adoption, but stakeholder concerns also include such as change saturation and visibility of incoming initiative impacts.
To become better at working with data there is much that change managers can learn from data scientists (without becoming one of course). Let’s explore how change management can benefit from the practices and methodologies employed by data scientists, focusing on time allocation, digital tools, system building, hypothesis-led approaches, and the growing need for data and analytical capabilities.
1. Time Allocation: Prioritizing Data Collection and Cleansing
Data scientists spend a substantial portion of their time on data collection and cleansing. According to industry estimates, about 60-80% of a data scientist’s time is dedicated to these tasks. This meticulous process ensures that the data used for analysis is accurate, complete, and reliable.
In the below diagram from researchgate.net you can see that for data scientists the vast majority of the time is spent on collecting, cleansing and organising data.
You might say that change managers are not data scientists because the work nature is different, and therefore should not need to carve out time for these activities? Well, it turns out that the type of activities and proportions of time spent is similar across a range of data professionals, including business analysts.
Below is the survey results published by Business Broadway, showing that even business analysts and data analysts spend significant time in data collection, cleansing, and preparation.
Lessons for Change Management
a. Emphasize Data Collection and Cleansing: For change managers, this translates to prioritizing the collection of reliable data related to change initiatives. This might include stakeholder feedback, performance metrics, impact data and other relevant data points. Clean data is essential for accurate analysis and insightful decision-making. Data projects undertaken by change managers are not going to be as large or as complex as data scientists, however the key takeaway is that this part of the work is critical and sufficient time should be allocated and not skipped.
b. Allocate Time Wisely: Just as data scientists allocate significant time to data preparation, change managers should also dedicate sufficient time to gathering and cleaning data before diving into analysis. This ensures that the insights derived are based on accurate and reliable information.
It also depends on the data topic and your audience. If you are presenting comparative data, for example, change volume across different business units. You may be able to do spot checks on the data and not verify every data line. However, if you are presenting to operations business units like call centres where they are very sensitive to time and capacity challenges, you may need to go quite granular in terms of exactly what the time impost is across initiatives.
c. Training and Awareness: Ensuring that the change management team understands the importance of data quality and is trained in basic data cleansing techniques can go a long way in improving the overall effectiveness of change initiatives. Think of scheduling regular data sessions/workshops to review and present data observations and findings to enhance the team’s ability to capture accurate data as well as the ability to interpret and apply insights. The more capable the team is in understanding data, the more value they can add to their stakeholders leveraging data insights.
2. Leveraging Digital Tools: Enhancing Efficiency and Accuracy
Data scientists rely on a variety of digital tools to streamline their work. These tools assist in data collection, auditing, visualization, and insight generation. AI and machine learning technologies are increasingly being used to automate and enhance these processes.
Data scientists rely on various programming, machine learning and data visualisation such as SQL, Python, Jupyter, R as well as various charting tools.
Lessons for Change Management
a. Adopt Digital Tools: Change managers should leverage digital tools to support each phase of their data work. There are plenty of digital tools out there for various tasks such as surveys, data analysis and reporting tools.
For example, Change Compass has built-in data analysis, data interpretation, data audit, AI and other tools to help streamline and reduce manual efforts across various data work steps. However, once again even with automation and AI the work of data checking and cleansing does not go away. It becomes even more important.
b. Utilize AI and Machine Learning: AI can play a crucial role in automating repetitive tasks, identifying patterns, data outliers, and generating insights. For example, AI-driven analytics tools can help predict potential change saturation, level of employee adoption or identify areas needing additional support during various phases of change initiatives.
With Change Compass for example, AI may be leverage to summarise data, call out key risks, generate data, and forecast future trends.
c. Continuous Learning: Continuous learning is essential for ensuring that change management teams stay adept at handling data and generating valuable insights. With greater stakeholder expectations and demands, regular training sessions on the latest data management practices and techniques can be helpful. These sessions can cover a wide range of topics, including data collection methodologies, data cleansing techniques, data visualisation techniques and the use of AI and machine learning for predictive analytics. By fostering a culture of continuous learning, organizations can ensure that their change management teams remain proficient in leveraging data for driving effective change.
In addition to formal training, creating opportunities for hands-on experience with real-world data can significantly enhance the learning process. For instance, change teams can work on pilot projects where they apply new data analysis techniques to solve specific challenges within the organization. Regular knowledge-sharing sessions, where team members present case studies and share insights from their experiences, can also promote collective learning and continuous improvement.
Furthermore, fostering collaboration between change managers and data scientists or data analysts can provide invaluable mentorship and cross-functional learning opportunities. By investing in continuous learning and development, organizations can build a change management function that is not only skilled in data management but also adept at generating actionable insights that drive successful change initiatives.
3. Building the Right System: Ensuring Sustainable Insight Generation
It is not just about individuals or teams working on data. A robust system is vital for ongoing insight generation. This involves creating processes for data collection, auditing, cleansing, and establishing governance bodies to manage and report on data.
Governance structures play a vital role in managing and reporting data. Establishing governance bodies ensures that there is accountability and oversight in data management practices. These bodies can develop and enforce data policies, and oversee data quality initiatives. They can also be responsible for supporting the management of a central data repository where all relevant data is stored and managed.
Lessons for Change Management
a. Establish Clear Processes: Develop and document processes for collecting and managing data related to change initiatives. This ensures consistency and reliability in data handling.
b. Implement Governance Structures: Set up governance bodies to oversee data management practices. This includes ensuring compliance with data privacy regulations and maintaining data integrity. The governance can sponsor the investment and usage of the change data platform. This repository should be accessible to stakeholders involved in the change management process, promoting transparency and collaboration. Note that a governance group can simply be a leadership team regular team meeting and does not need to be necessarily creating a special committee.
c. Invest in system Infrastructure: Build the necessary system infrastructure to support data management and analysis that is easy to use and provides the features to support insight generation and application for the change team.
Data scientists often use a hypothesis-led approach, where they test, reject, or confirm hypotheses using data. This method goes beyond simply reporting what the data shows to understanding the underlying causes and implications.
Lessons for Change Management
a. Define Hypotheses: Before analyzing data, clearly define the hypotheses you want to test. For instance, if there is a hypothesis that there is a risk of too much change in Department A, specify the data needed to test this hypothesis.
b. Use Data to Confirm or Reject Hypotheses: Collect and analyze data to confirm or reject your hypotheses. This approach helps in making informed decisions rather than relying on assumptions or certain stakeholder opinions.
c. Focus on Actionable Insights: Hypothesis-led analysis often leads to more actionable insights. It is also easier to use this approach to dispel any myths of false perceptions.
For example: Resolving Lack of Adoption
Hypothesis: The lack of adoption of a new software tool in the organization is due to insufficient coaching and support for employees.
Data Collection:
Gather data on the presence of managerial coaching and perceived quality. Also gather data on post go live user support.
Collect feedback from employees through surveys regarding the adequacy and clarity of coaching and support.
Analyse usage data of the new software to identify adoption rates across different departments.
Analysis:
Compare adoption rates between employees who received sufficient coaching and support versus those who did not.
Correlate feedback scores on training effectiveness with usage data to see if those who found the training useful are more likely to adopt the tool.
Segment data by department to identify if certain teams have lower adoption rates and investigate their specific training experiences.
Actionable Insights:
If data shows a positive correlation between coaching and support, and software adoption, this supports the hypothesis that enhancing coaching and support programs can improve adoption rates.
If certain departments show lower adoption despite completing coaching sessions, investigate further into department-specific issues such as workload or differing processes that may affect adoption.
Implement targeted interventions such as additional training sessions, one-on-one support, or improved training materials for departments with low adoption rates.
5. Building Data and Analytical Capabilities: A Core Need for Change Management
As data and analytical capabilities become increasingly crucial, change management functions must build the necessary people and process capabilities to leverage data-based insights effectively.
Lessons for Change Management
a. Invest in Training: Equip change management teams with the skills needed to manage data and generate insights. This includes training in data analysis, visualization, and interpretation.
b. Foster a Data-Driven Culture: A lot of organisations are already on the bandwagon of Encourage a culture where data is valued and used for decision-making. The change management needs to promote this equally within the change management function. This involves promoting the use of data in everyday tasks and ensuring that all team members understand its importance. Think of incorporating data-led discussions into routine meeting meetings.
c. Develop Analytical Frameworks: Create frameworks and methodologies for analyzing change management data. This includes defining common key metrics, setting benchmarks, and establishing protocols for data collection and analysis for change data. Data and visual templates may be easier to follow for those with lower capabilities in data analytics.
Practical Steps to Implement Data-Driven Change Management
To integrate these lessons effectively, senior change practitioners can follow these practical steps:
Develop a Data Strategy: Create a comprehensive data strategy that outlines the processes, tools, and governance structures needed to manage change management data effectively.
Conduct a Data Audit: Begin by auditing the existing data related to change management. Identify gaps and areas for improvement.
Adopt a Hypothesis-Led Approach: Encourage the use of hypothesis-led approaches to move beyond descriptive analytics and derive more meaningful insights.
Invest in Technology: Invest in the necessary digital tools and technologies to support data collection, cleansing, visualization, and analysis.
Train the Team: Provide training and development opportunities for the change management team to build their data and analytical capabilities.
Collaborate Across Functions: Foster collaboration between change management and data science teams to leverage their expertise and insights.
Implement Governance Structures: Establish governance bodies to oversee data management practices and ensure compliance with regulations and standards.
By learning from the practices and methodologies of data scientists, change management functions can significantly enhance their effectiveness. Prioritizing data collection and cleansing, leveraging digital tools, building robust systems, adopting hypothesis-led approaches, and developing data and analytical capabilities are key strategies that change management teams can implement. By doing so, they can ensure that their change initiatives are data-driven, insightful, and impactful, ultimately leading to better business outcomes.
