Why using change management ROI calculations severely limits its value

Why using change management ROI calculations severely limits its value

by | Change Measurement, Portfolio management

Change management professionals often struggle with proving the worth of their services and why they are needed.  There are certainly plenty of reasons why change management professionals are required and most experienced project managers and senior leaders would acknowledge this.  However, for the less mature organisations that may not have had effective change management experts leading initiatives, the rationale on the additional value of change management may be less clear.

When we look across different project members and project teams, it is easy to argue that without developers, the technical project cannot progress.  Without business analysts, we cannot understand and flesh out the core business steps required in the initiative.  And of course, we definitely need a project manager for a project.  But, what’s the justification for a change manager?  Many projects have other project or business representatives do the change work instead.

As an attempt to justify in a very direct way, the value of change management, many resort to ROI calculations and aim toward higher ROI.  This ROI of change management may seem like a great way to convey and show in a very direct and financial way, the value of change management towards project success.  After all, we use ROI for calculating projects, why not use the same for change management as well to value the people side of change?

There are plenty of articles on how to best calculate change management ROI.  Here are a couple:

1. PROSCI 

Prosci has a good, clear way of calculating change management ROI within a project (though it doesn’t take into account speed of adoption).  You simply evaluate to what extent employee adoption is important to the project.  Then you take the overall expected project benefits and deduct the part of the expected benefits if there was no adoption.  This is termed “people side benefit contribution”. 

People Side Benefit Contribution = Expected Project Benefits – Expected Project Benefits (if adoption and usage = 0)

People Side Benefit Coefficient = People Side Benefit Contribution / Expected Project Benefits

2. Rightpoint

Rightpoint has a variation to this calculation. They have added ELV (Employee Lifetime Value) to the calculation.

(From Rightpoint.com)

“ELV helps account for important (but often overlooked) benefits of change management such as increases in employee productivity, employee retention, and faster ramp-up of new hires. Including the Investment in Change figure ensures that your calculations account for all the hard costs associated with change.”  https://www.rightpoint.com/thought/article/measuring-change-management-success-defining-and-ensuring-a-solid-roi

Using ROI may be useful when the cost of the initiative is the critical focus for the organisation for its strategic investment.  However, it is not the only way to convey the overall value of successful change management.  In addition, the ROI method limits the value of change management to focus on the cost invested versus the value created.  Also, this type of calculation limits the value of change to a project by project perspective.  

So, how else do we show the direct financial value of change management?  Let’s look to research.  It turns out there are plenty of research examples.  Here are some:

  1. McKinsey & Company. (2016). The people power of transformations. This study found that transformation initiatives are 5.8 times more successful if CEOs communicate a compelling change story, and 6.3 times more successful when leaders share messages about change efforts with the rest of the organization. Link here.
  2. Korn Ferry. (2018). Engaging hearts and minds: Preparing for a changing world. This study found that calls out change as a key trend found that companies with high levels of employee engagement had 4.5 times higher revenue growth compared to companies with low levels of engagement, noting that all companies are undergoing change. Link here.
  3. IBM. (2016). Making change work … while the world keeps changing. This study found that 76% of successful projects include change management activities at the beginning of their overall project plans, which is 33% more than less successful projects. Link here.
  4. IBM. (2015) Why a business case for change management.  The article references a survey carried out in 2010 where companies that apply a value (benefit) realization approach (of which change management is a core component) complete projects at least twice as quickly and under budget by a factor of at least 1.9 times, Compared to those that don’t. Link here.
  5. Towers Watson. (2013). Change and communication ROI.  Organizations with highly effective communication and change management practices are more than twice as likely to significantly outperform their peers in total shareholder returns, versus organizations that are not highly effective in either of these areas. Link here.
  6. Prosci. (2020). Best Practices in Change Management 11th Edition. The paper referred to a Prosci study that found that projects with excellent change management practices 6 times more likelihood of meeting project objectives than those that are poor. Link here.

So the value the importance of change management, let’s take a comparison to see the difference in using a ROI calculation of the value of change management versus using findings from the above research findings to demonstrate the derived value.

Let’s take a typical project example.  Company A has …. 

  1. Annual revenue of $1 billion with 5% profitability
  2. The revenue growth is 1%  
  3. Project A costs $1Million and is targeted for $3 million in benefits.  

If the expected project benefits without adoption would be $1Million, then, the people-side contribution is …

 $2Million / $3Million = $667K.

Let’s contrast this to other calculations using research.  

Research findings | Calculation

Korn Ferry study where companies with high levels of employee engagement had 4.5 times higher revenue growth compared to companies with low levels of engagement. Taking a very conservative approach of portioning on 1/3 of employee engagement linked to change, this means 1.5 times higher revenue growth. | Taking a very conservative approach of portioning 1/3 of employee engagement as linked to change, this means 1.5 times higher revenue growth. This means if the revenue growth is 1%, then the additional revenue is $15 Million per year.

You can see that $15 million in value is much higher than the $667K in initiative ROI.  From these examples, you can see that the financial value dwarfs that from the ROI calculation.  On top of this, these are from research findings, which may have a stronger perceived validity and be easier to be trusted by stakeholders than the ROI calculation.

To point out, it is not an apple-to-apple comparison between the change management ROI from one initiative to the organisational value of change management across initiatives.  However, the call out is that:

  1. The financial value of change management does not need to be limited to individual initiatives
  2. The sum may be greater than its parts.  Rather than measuring at initiative levels, research findings are looking at organisational-level value
  3. The value of change management may be more than cost, but also other value drivers such as revenue

As change management practitioners we should not shy away from calling out and citing the value of change management.  Cost may be one value, but the true benefit of change management is both the top line as well as the bottom line.  Directly referring to the research-backed findings also helps to highlight its value size and importance.  

To do this, we should also work to deliver organisational value in managing change and not limit ourselves to one initiative.  Focus on uplifting change management capability in the forms of leadership styles, change governance, change analytics, and change champion network capability, just to name a few.

To read more about calculating the financial value of managing a change portfolio click here.

Have a problem in delivering change using data? Chat with us to find out how Change Compass might be able to help.

What are some of the benefits of using data science in change?

What are some of the benefits of using data science in change?

by | Change Measurement

Change management is often seen as a ‘soft’ discipline that is more an ‘art’ than science.  However, successful change management, like managing a business, relies on having the right data to understand if the journey is going in the right direction toward change adoption.  The data can inform whether the objectives will be achieved or not.

Data science has emerged to be one of the most sought-after skills in the marketplace at the moment.  This is not a surprise because data is what powers and drives our digital economy.  Data has the power to make or break companies.  Companies that leverages data can significant improve customer experiences, improve efficiency, improve revenue, etc. In fact all facets of how a company is run can benefit from data science.  In this article, we explore practical data science techniques that organizations can use to improve change outcomes and achieve their goals more effectively.

  1. Improved decision making

One of the significant benefits of using data science in change management is the ability to make informed decisions. Data science techniques, such as predictive analytics and statistical analysis, allow organizations to extract insights from data that would be almost impossible to detect or analyse manually. This enables organizations to make data-driven decisions that are supported by empirical evidence rather than intuition or guesswork.

  1. Increased Efficiency

Data science can help streamline the change management process and make it more efficient. By automating repetitive tasks, such as data collection, cleaning, and analysis, organizations can free up resources and focus on more critical aspects of change management. Moreover, data science can provide real-time updates and feedback, making it easier for organizations to track progress, identify bottlenecks, and adjust the change management plan accordingly.

  1. Improved Accuracy

Data science techniques can improve the accuracy of change management efforts by removing bias and subjectivity from decision-making processes. By relying on empirical evidence, data science enables organizations to make decisions based on objective facts rather than personal opinions or biases. This can help reduce the risk of errors and ensure that change management efforts are based on the most accurate and reliable data available.

  1. Better Risk Management

Data science can help organizations identify potential risks and develop contingency plans to mitigate those risks. Predictive analytics can be used to forecast the impact of change management efforts and identify potential risks that may arise during the transition.  For example, change impacts across multiple initiatives against seasonal operations workload peaks and troughs. 

  1. Enhanced Communication

Data science can help facilitate better communication and collaboration between stakeholders involved in the change management process. By presenting data in a visual format, such as graphs, charts, and maps, data science can make complex information more accessible and understandable to all stakeholders. This can help ensure that everyone involved in the change management process has a clear understanding of the goals, objectives, and progress of the transition.

Key data science approaches in change management

Conduct a Data Audit

Before embarking on any change management initiative, it’s essential to conduct a data audit to ensure that the data being used is accurate, complete, and consistent.  For example, data related to the current status or the baseline, before change takes place.  A data audit involves identifying data sources, reviewing data quality, and creating a data inventory. This can help organizations identify gaps in data and ensure that data is available to support the change management process.  This includes any impacted stakeholder status or operational data.

During a data audit, change managers should ask themselves the following questions:

  1. What data sources from change leaders and key stakeholders do we need to support the change management process?
  2. Is the data we are using accurate and reliable?
  3. Are there any gaps in our data inventory?
  4. What data do we need to collect to support our change management initiatives, including measurable impact data?

Using Predictive Analytics

Predictive analytics is a valuable data science technique that can be used to forecast the impact of change management initiatives. Predictive analytics involves using historical data to build models that can predict the future impact of change management initiatives. This can help organizations identify potential risks and develop proactive strategies to mitigate those risks.

Change managers can use predictive analytics to answer the following questions:

  1. What is the expected impact of our change management initiatives?
  2. What are the potential risks associated with our change management initiatives?
  3. What proactive strategies can we implement to mitigate those risks?
  4. How can we use predictive analytics to optimize the change management process?

Leveraging Business Intelligence

Business intelligence is a data science technique that involves using tools and techniques to transform raw data into actionable insights. Business intelligence tools can help organizations identify trends, patterns, and insights that can inform the change management process. This can help organizations make informed decisions, improve communication, and increase the efficiency of change management initiatives.

Change managers can use business intelligence to answer the following questions:

  1. What insights can we gain from our data?
  2. What trends and patterns are emerging from our data?
  3. How can we use business intelligence to improve communication and collaboration among stakeholders?
  4. How can we use business intelligence to increase the efficiency of change management initiatives?

Using Data Visualization

Data visualization is a valuable data science technique that involves presenting data in a visual format such as graphs, charts, and maps. Data visualization can help organizations communicate complex information more effectively and make it easier for stakeholders to understand the goals, objectives, and progress of change management initiatives. This can improve communication and increase stakeholder engagement in the change management process.

Change managers can use data visualization to answer the following questions:

  1. How can we present our data in a way that is easy to understand?
  2. How can we use data visualization to communicate progress and results to stakeholders?
  3. How can we use data visualization to identify trends and patterns in our data?
  4. How can we use data visualization to increase stakeholder engagement in the change management process?

Monitoring and Evaluating Progress

Monitoring and evaluating progress is a critical part of the change management process. Data science techniques, such as statistical analysis and data mining, can be used to monitor progress and evaluate the effectiveness of change management initiatives. This can help organizations identify areas for improvement, adjust the change management plan, and ensure that change management initiatives are achieving the desired outcomes.

Change managers can use monitoring and evaluation techniques to answer the following questions:

  1. How can we measure the effectiveness of our change management initiatives? (e.g. employee engagement, customer satisfaction, business outcomes, etc.) And what method do we use to collect the data? E.g. surveys or focus groups?
  2. What data do we need to collect to evaluate the change initiative progress?
  3. How can we use statistical analysis and data mining to identify areas for improvement?
  4. How can we use monitoring of ongoing support or continuous improvement?

The outlined approaches are some of the key ways in which we can use data science to manage the change process.  Change practitioners should invest in their data science capability and adopt data science techniques to drive effective change management success.  Stakeholders will take more notice of change management status and they may also better understand the value of managing change.  Most importantly, data helps to achieve change objectives.

Check out The Ultimate Guide to Measuring Change.

Also check out this article to read more about using change management software to measure change.

If you’re interested in applying data science to managing change by leveraging digital tools have a chat to us.

Change Practitioner Q&A Series: Fiona Johnson

Change Practitioner Q&A Series: Fiona Johnson

by | Change approach

In this Change Practitioner Q&A series we talk to change managers to ask them how they approach their work. This time we are talking to Fiona Johnson.

Change Compass: Hi Fiona, describe yourself in 3 sentences.

Fiona:
I’m a ‘seasoned” change practitioner who has survived many types of workplaces relatively unscathed ! Honestly, I could write a book about it.
I always try and see the positive aspects of any workplace and do my best to enhance and support the cultural norms AND keep a sense of humour.
I like to collaborate with professional and supportive team members and coach and mentor team members.

Change Compass: What has been the most challenging situation for you as a change practitioner? Tell us what happened and how you fared through it.


Fiona: I’ve had a lot of challenges, but I think the key is getting leaders to lead the change and supporting them.

I had an instance where I had to “sell” the benefits of change management to a very resistant Financial Controller. At the start of the project ( basically an operating model change) , he was totally focussed on the numbers and not the people and lacked the insight that change is always about people.

I had a team made up of business representatives and I set up regular fortnightly meetings to get his attention on issues we needed resolving and keep him up to date. I made the meetings short and sharp and each team members gave an update on the work they were doing to give them visibility. He realised the value of change management once the project delivered as that was when the gaps became evident. I think we were able to prepare him for the implementation but once the project wrapped up it was evident there was a lot of embedment activities not planned for and I think this would have caused more pain.

Although change initiatives are clearer now about the roles and responsibilities of the Sponsor and Business Owner, there is a still a reluctance amongst senior leaders to lead from the front in case it’s a failure and reflects negatively on them. I think this is an education piece and leaders need to trust change managers.

Change Compass: What are the most critical and most useful things to focus on when you first start on a project, and why.

Fiona: These tend to be the questions I focus on …
• What are the business drivers? Why? Because this helps form the narrative and links to strategy and then to the frontline – “What’s in it for me?”
• Who is the Sponsor and how actively engaged are they? They need to be involved and advocating throughout the project.
• How much funding is set aside for Change Management ? I’ve implemented change on a shoestring but its better if there is funding for communication and training as this indicates consideration for the recipients.
• What’s the organisations history of managing change – is there a “good” change example and what made it stand out, conversely what was a poor experience and what factors contributed to it ?
• What is the culture like ? Take note of employees’ surveys as they provide markers on morale and pain points.
• Finally identify a network of strong champions and advocates to help the change and provide them with the tools to do this.

Change Compass: As change practitioners we don’t often get to stick around to see the fruits of our labour, but from your experience what are the top factors in driving full change adoption?

Fiona: For me ….
• Understanding the future state and identifying existing organisation metrics that can monitor and measure, or if there are gaps, ensuring these are filled before the change.
• Handover to a committed business owner to manage and maintain momentum and who understands their role and responsibilities.
• Building governance structures to review and report on the changes to the Executives or using existing forums.
• Reporting and tracking are key but also other types of controls such as operating procedures and training.
• Involving other areas such as QA, Compliance, HR and Finance in the discussions relating to embedment

Change Compass: You’re known to be great at explaining complex changes to stakeholders. What’s your secret?

Fiona: I have the grandmother test … would your grandmother understand this?
Also, use basic communication rules such a targeting your audiences – there’s a difference between communicating to white collar and blue collar. Other tips include …
• Use storytelling and personas your audience can relate to
• Use your advocates and sponsors to spread the message.
• Keep it simple and use a variety of mediums

Change Compass: Great insights! Thanks Fiona!

Also check out our Change Practitioner Q&A with Alvaro Pacheco.

There is no singular change curve

There is no singular change curve

by | Agile, Portfolio management

There is no change curve.  A single change curve doesn’t exist in most organisations.  The concept of a single change curve means you’re always looking at it from the myopic lens of a single project or a single change.  If we adopt a humanistic and human-centred view, what we see is that at any one time there are likely multiple change curves happening, to the same person, the same team, the same organisation.

At any one time, an impacted stakeholder maybe undergoing the 3rd iteraction of changes in one project, whilst partially adopting the new behaviours of another project, whilst just learning about the details of yet another project.  And it may not even be projects or programs. It could be smaller team-led continuous improvement initiatives.

The concept of Agile methodology has revolutionized the way organizations approach software development and project management. It emphasizes flexibility, adaptability, and continuous improvement. However, the frequent introduction of multiple Agile changes within an organization can lead to multiple ‘S’ curves, which can result in several challenges related to adoption and business performance and capacity.

Multiple S curves refer to the continuous introduction of new Agile changes, each of which leads to a new adoption process and a corresponding performance improvement. This results in a series of S-shaped curves, each representing a different stage of the Agile adoption process.

The S curve is assuming that all of the changes are well implemented with good people experiences.  The initial curve shows the slowness of the change adoption in the beginning, followed by a faster change adoption process, and finally capering off.  

However, when the change is not well implemented due to various reasons the experience can be more like a V curve, where the experience and performance dips down into the ‘valley of despair’, followed by a ramp-up of improving experiences and change adoption.

The introduction of multiple Agile changes within an organization can lead to several challenges related to adoption and business performance and capacity. Firstly, continuous change can lead to confusion and uncertainty among employees. It can be difficult for employees to keep up with the latest changes and understand how they should adjust their work processes accordingly. This can result in decreased productivity and morale among employees.

Moreover, frequent changes can also result in increased cognitive strain and workload for employees. They may need to continuously learn new processes and techniques, leading to burnout and decreased job satisfaction. 

Another challenge of having multiple Agile changes is that it can lead to decreased consistency in processes and outcomes. Each change may result in different outcomes and different ways of working, making it difficult to standardize and measure performance. This can result in a lack of accountability and a decrease in the organization’s overall efficiency.

In addition to the challenges related to adoption and performance, multiple Agile changes can also result in a decreased business capacity. The frequent changes can disrupt established workflows, making it difficult for teams to complete projects in a timely manner. This can lead to decreased project velocity and increased project risk, making it challenging for the organization to meet its goals and objectives.

So, while Agile methodology is a powerful tool for organizations, the frequent introduction of multiple Agile changes can result in several challenges related to adoption, performance, and capacity. To mitigate these challenges, organizations should take a strategic approach to Agile adoption, ensuring that changes are well-planned, communicated effectively, and implemented in a controlled manner. By doing so, organizations can ensure that the benefits of Agile methodology are realized while minimizing the risks associated with multiple changes.

To truly manage the multiple change curves, data is key.  Without understanding which change curves are happening at what time it is not possible to manage change holistically.  With data, you can easily drill into what is happening when, to whom, to what extent, and in what way.  It is only with data that we can effectively orchestrate change across the board.

If you are going on a journey to capture change impacts across the organisation, be aware of how you are capturing the data so that you are truly addressing business issues critical to the organisation.  For example:

  • Ensure that the data captured can be easily formatted and visualised to support a range of business decision-making contexts without too much manual work.  The more manual the set up of the data is, the more time and effort it requires to answer the various data cuts that stakeholders may be needing
  • Balancing critical data points required versus having too many data fields and therefore too Cumberland and difficult to capture the data.  The more data you are required to collect, the more complex the process is for those whom you are collecting the data from
  • Thanks to the nature of agile projects, the data will change constantly.  The tracking of constantly changing change data is critical.  However, it should also be easy and quick to update the data
  • Organisations under changes will invariably have changes in organisational structures, teams or roles.  Ensure that your data-capturing process makes it easy to update the structure as they change.

Have a chat with us to understand more about how to leverage digital solutions to multiple change impacts across the organisation, and how to leverage AI and automation to make your lives easier in leveraging a data platform to make critical business decisions using change impact data.

So next time you talk about THE change curve, just be aware that you’re likely not adopting a people-centric view of change. You may want to look more holistically at what your impacted stakeholders are undergoing or about to undergo.  Adopt a holistic mindset of what impacted stakeholders are going through as you plan out your change approach.

If you’re interested in exploring more about managing agile changes check out the following:

How to deliver constant changes as a part of agile change management

As a change manager how do I improve my company’s agility

Agile change playbook series

Designing a Change Adoption Dashboard: A Guide for Change Managers

Designing a Change Adoption Dashboard: A Guide for Change Managers

by | Change Measurement

good change adoption dashboard can make or break the full benefit realization of a change initiative.  It captures the essence of what stakeholders need to focus on to drive full change adoption.  This visual representation of the status and progress of a change initiative provides real-time data and insights into how well-impacted employees are adopting the change and what steps can be taken to improve adoption rates. In this article, we will outline the steps for designing an effective change adoption dashboard.

Change adoption is often only measured toward the end of a change initiative.  This is a mistake since the adoption journey can start as early as the project commencement, or when stakeholders start hearing about the initiative.  At a minimum, change adoption should be defined and agreed upon before significant change impact happens.  If you are implementing a system this will be well before the system go-live.

These are the key steps in building a great change project adoption dashboard.

 

Step 1: Define the Objectives of the Change Initiative

The first step in designing a change adoption dashboard is to clearly define the objectives of the change initiative. This includes understanding what the change is, what it aims to achieve, and what the desired outcomes are. Understanding the objectives of the change initiative is critical to defining the metrics that will be used to measure adoption and success.

If your initiative has a long list of objectives, be careful not to be tempted to start incorporating all of these into your dashboard.  Your task is to pin down the most critical change management objectives that must be met in order for the initiative to be successful.  If you are really struggling with how many objectives you should focus on, aim for the top three.

 

Step 2: Identify Key Metrics

Once the objectives of the change initiative have been defined, the next step is to identify the key metrics that will be used to measure adoption and success. These metrics should be directly tied to the objectives of the change initiative and should provide actionable insights into the progress and success of the change.

Some examples of metrics that can be used to measure change adoption include:

1. Stakeholder engagement levels (depending on your stakeholder impacts these could be customer, employee or partners)

2. Stakeholder engagement levels (depending on your stakeholder impacts these could be customer, employee or partners)

3. User adoption rates

4. Process improvement metrics

5. Time to adoption

6. Feedback from employees

The key is to locate the few metrics that will form the core of what full change adoption means.  As a general rule, this often means a behaviour change of some kind.  Here are some examples.

1. If the goal is changing a business process from A to B.  Then you are looking for employees to start following the new process B.  Then, identify the core behaviours that mean following process B.

2. If the goal is to start using a new system, then you would focus on system usage.  Also focus on tracking any workarounds that employees may resort to in order not to use the system.

3. If the goal is to improve customer conversations, then you would focus on the quality of those conversations using key indicators.  This may involve call listening or customer satisfaction ratings.

Again, ensure you are not over-extending yourself by picking too many metrics.  The more there is, the more work there is.  Having too many metrics also lead to attention dilution, and you start to loose stakeholder focus on the more critical metrics compared to less critical ones.

In the group of metrics you’ve chosen, if there is no behaviour measure then it is likely you may have missed the most critical element of change adoption.  In most cases, behaviour change metric is essential for any change adoption dashboard.

If your change process involves too many behaviour steps, then focus on ones that are easier to track and report on.  In a system implementation project, they could be system usage reports or login frequency.  

 

 

 

 

 

Examples of target behaviours as a part of behaviour change

Step 3: Choose the Right Visualization Techniques

The next step in designing a change adoption dashboard is to choose the right visualization techniques. The visualizations should be chosen based on the data that needs to be displayed and the insights that need to be gained. Some examples of visualization techniques that can be used include:

 

    • Bar graphs: to display changes in metrics over time
    • Pie charts: to display the distribution of data
    • Line charts: to display changes in metrics over time
    • Heat maps: to display the distribution of data on a map

Selection of charts can be technical, and your goal is always to choose the right type of chart to make it easier for the audience to understand and interpret.  Minimise on having too many colors since this can be distracting and overwhelming.  Use colours carefully and only to show a particular point or to highlight a finding.  Choosing the wrong chart can mean more questions than answers for your stakeholders, so choose carefully.

Visit our article ‘Making Impact with Change Management Charts’ to learn more about data visualisation techniques.

Beyond just having a collection of charts, modern dashboards have a mixture of different types of visuals to aid easy stakeholder understanding.  For example, you could have different data ‘tiles’ that show key figures or trends.  You may also want to incorporate key text descriptions of findings or trends in your dashboard. Having a mixture of different types of information can help your stakeholders greatly and avoid data saturation.

 

 

 

 

Example of chart styles from The Change Compass

Step 4: Design the Dashboard

Once the objectives, metrics, and visualization techniques have been defined, the next step is to design the dashboard. The design should be intuitive and user-friendly, with the ability to drill down into the data to gain deeper insights. The dashboard should also be accessible to all stakeholders, including employees, managers, and executives.

Data visualisation is a discipline in itself.  For a general overview and key tips on chart design and selection visit our article to learn more about data visualisation techniques.

To reduce manual work in constantly updating and producing the dashboard for your stakeholders think about leveraging technical solutions to do this for you.  A common approach is to use excel spreadsheet and PowerBI.  This may be feasible for some, but it often involves using a PowerBI expert (which may come at a cost), and any time you want to change the dashboard you need to loop back the expert to do it for you.

The Change Compass has incorporated powerful and intuitive dashboarding and charting features so that you do not need to be an expert to create a dashboard.  Reference our templates as examples and create your own dashboard with a few clicks.  

 

 

 

An Example of a Change Adoption Dashboard from The Change Compass

Step 5: Test and Refine the Dashboard

The final step in designing a change adoption dashboard is to test and refine it. This includes testing the dashboard with a small group of stakeholders and getting their feedback. Based on their feedback, the dashboard can be refined and improved until it provides the insights and data that stakeholders need to drive change adoption.

A key part of this step is testing any automation process in dashboard generation.  Is the data accurate?  Is it recent and updated?  What operating rhythms do you need to have in place to ensure that the process flows smoothly, and that you get the dashboard produced every week/month/quarter?

Step 6: Continuously Monitor and Update the Dashboard

It is important to continuously monitor the change adoption dashboard and update it regularly. This will help to ensure that the dashboard remains relevant and provides the most up-to-date information on the progress of the change initiative.

The reality is that stakeholders will very likely get bored with the same dashboard time and time again.  They will likely suggest changes and amendments from time to time.  Anticipate this and proactively improve your dashboard.  Does it drive the right stakeholder focus and conversation?  If not, tweak it.

Good stakeholder conversations mean that your stakeholders are getting to the roots of why the change is or is not taking place.  The data presented prompts the constant focus and avoids diversion in that focus.  This is also a journey for your key stakeholders to find meaning in what it takes to lead the change and reinforce the change to get business results.

Summary

Designing an effective change adoption dashboard is a critical step in ensuring the success of change initiatives. By providing real-time data and insights into how well employees are adopting the change, a change adoption dashboard can help key stakeholders make informed decisions and take action to improve adoption rates.  Ultimately it is about achieving the full initiative benefits targeted. By following the steps outlined in this article, change managers can design a change adoption dashboard that provides the insights they need to drive change adoption.

Building and executing a change adoption dashboard can be a manually intensive and time consuming exercise. Leverage technology tools that incorporates automation and AI. You will find that this can significantly increase the speed in which you are able to execute on not just the change dashboard, but driving the overall change delivery. For example, you can leverage out-of-the-box features such as forecasting and natural language query to save significant time and effort.

Have a chat to us about what options there are to help you do this.

Chat with us about automating dashboards