Change management methodologies are designed to facilitate the process of implementing organizational changes effectively. However, a lot of traditional change management approaches tend to be too rigid and waterfall-like, hindering organizations from embracing agility. Despite the fact that most organisations are using agile methodology to implement change, methodologies have not kept up to date.
Waterfall vs. Agile: The Need for Change
The waterfall model, characterized by a sequential and linear approach to project management, has long been the dominant framework for managing change in organizations. It follows a structured path, where each phase is completed before moving on to the next. While this approach has its merits, it often falls short when it comes to change management, which requires flexibility and adaptability.
Agile methodologies, on the other hand, emphasize iterative and incremental development, promoting collaboration, continuous improvement, and rapid response to change. Agile has gained significant popularity in software development, but its principles can be applied to change management as well. By embracing agility, organizations can navigate the complexities of change more effectively, fostering innovation and resilience.
Most change management methodologies, despite the need for agility and adaptability, often retain a waterfall-like structure. Let’s delve into each phase to understand how this traditional approach persists.
Scoping: In the scoping phase, the change management team typically focuses on defining the scope of the change initiative. However, this phase tends to follow a waterfall approach, where the scope is predetermined and set at the beginning of the project. There is limited room for flexibility or adjustments based on evolving requirements or stakeholder feedback.
Stakeholder analysis: In traditional change management methodologies, stakeholder analysis is often conducted early on in the process. However, this analysis is frequently treated as a one-time activity, with limited opportunities for ongoing engagement and collaboration with stakeholders. This lack of continuous involvement hampers the ability to incorporate diverse perspectives and adapt the change strategy accordingly.
Impact analysis: Impact analysis aims to assess the potential consequences of the proposed change on various aspects of the organization. While this phase acknowledges the need to consider impacts, it often relies on linear and predictable assumptions. The waterfall nature of impact analysis fails to account for the dynamic nature of change and the potential for unforeseen effects or emergent patterns.
Change planning: Change planning in traditional methodologies tends to be highly detailed and extensive, often resulting in voluminous documentation. These plans are typically developed early in the process and are expected to remain static throughout the execution phase. This rigidity can be problematic, as change initiatives require adaptability and the ability to respond to emerging challenges and opportunities.
Execution: The execution phase in waterfall-like change management methodologies is often characterized by a linear sequence of tasks and activities. This sequential approach assumes that each step can be completed before moving on to the next. However, in reality, change initiatives can encounter unexpected roadblocks or require course corrections, rendering this rigid execution process inadequate for effectively managing change in dynamic environments.
Overall, these traditional phases demonstrate how most change management methodologies are still designed with a waterfall mindset, focusing on sequential processes, rigid planning, and limited opportunities for flexibility and adaptation. To truly embrace agility in change management, organizations must shift towards iterative and collaborative approaches that prioritize stakeholder engagement, continuous learning, and the ability to adjust course based on evolving needs and circumstances.
Paying lip service to ‘agile-fy’
To pay lip service to make the methodology more ‘agile friendly’ a lot of proponents of change management methodologies have come up with ways to do this.
Matching the phases to agile work phases
Some have matched the change management methodology to agile work phases to try and make it more agile. This includes matching the planning activities done by change managers to those done by the rest of the agile team, and matching the change management approach to agile delivery phases.
Mapping a waterfall style change management methodology to an agile project does not make your approach agile. Your project change activities may be in synch with the rest of the team, but it does not mean that your approach is more agile.
2. Over-focus on agile ‘capability’
Agile project approaches are about the mindset and a way of operating. Yes, ideally we want to be able to educate and improve the agile mindset and capabilities of everyone across the organisation. However, we know that in reality we may be lucky if a pocketful of stakeholders understand agile ways of working.
The same also applies to change management capability. We can invest heavily on change management capability and try and uplift this across several years. However, the most critical parts of learning is learning through ‘doing’. Learning agile ways of implementing initiatives is best through being involved.
Your stakeholders will related to the experience of being in agile initiatives and remember this a lot more than any training sessions that they go on.
3. Doing more
Some have taken the approach that with agile, there are certain activities we need to do more of, and that doing more of these activities will somehow help us to be more agile in our approach.
More communication about agile approaches. More training. More sponsor alignment. More reinforcement of agile outcomes and phases.
Doing more of these activities may be somewhat beneficial depending on your organisation, again it does not make your change approach more agile. This approach is focused on providing ‘support’ for the organisation. It is also you acting as a side-party from the rest of the agile project team, helping the organisation to accept agile. In some situations this may be needed, but again it detracts from what makes your methodology and approach more agile.
How to change your change methodology to be more agile
The “Get One Piece Done” principle from the book ‘Shape Up’ by Ryan Singer is an excellent concept that describes one of the core practices of agile. If there is one core agile principle in which to remember to get the biggest impact, this is it. It offers several advantages over traditional waterfall-like approaches:
Focus on outcomes: Instead of getting stuck in lengthy planning and documentation phases, this principle encourages organizations to focus on delivering tangible results. By setting a clear goal for each bet, teams can align their efforts toward achieving specific outcomes.
Embrace flexibility: Change is unpredictable, and rigid plans can quickly become outdated. By working in short cycles, organizations can adapt to evolving circumstances more effectively. If circumstances change, teams can adjust their course and priorities accordingly during the subsequent bets.
Foster collaboration and autonomy: The “Get One Piece Done” principle promotes collaboration and empowers teams to take ownership of their work. Teams have the autonomy to decide how to approach and complete their bets, fostering creativity and engagement.
Learn and iterate: Agile approaches emphasize learning and continuous improvement. After completing a bet, teams reflect on their experience and incorporate feedback into subsequent bets. This iterative process allows for rapid adaptation and refinement of change initiatives.
The following diagram (adapted from the book) illustrates how to use the ‘Get one piece done’ principle in ‘shipping’ change work. In agile software development, the term ‘ship’ means to deliver an output to the customer. This does not include any work internal to the project team such as planning, testing, and technical development. It is only when a piece of software is ready to be shown with working functions, that it is said to be ‘shipped’.
Change practitioners should also adopt the same agile approach in their work. Rather than relying on a series of project work phases and only ‘ship’ at the end of the project, is much more ‘waterfall’ in approach than agile. Agile teams ‘ship’ solutions throughout the project. Likewise, change practitioners can also ‘ship’ a range of change outcomes throughout the project.
Don’t wait until we have more clarity. The solution is evolving so the ‘clarity’ will also continue to evolve.
Continue to pulse and experiment as the solution continues to evolve. Just like how the agile team is showcasing features continuously as the solution is being developed, change managers should also showcase the change approach and findings through experiments.
For change management, this means testing different pieces of the change approach throughout the project.
Testing engagement channels/medium
Testing messages
Testing training content
Testing town hall design
Testing team briefing design
Testing impact assessment
Testing implementation loading/capacity
Testing speed of adoption
Testing level of engagement
Testing continuation of adoption
What key features should each test incorporate?
Each test should be small enough to be released quickly without too much work, buy-in and time.
Ideally each test should also be ‘new’ and not have been tested before. Note that even if it had been tested by another project, the context could be different.
The number one focus for each experiment is to learn something that will help you form the overall change approach.
So unlike most methodologies where the tracking, measurement and adaptation of the change approach happens at the end after the release, in an agile approach it should happen as early as possible. The eventual change management approach should be an aggregation of a series of tests and small ‘change releases’ that result in the eventual change approach.
Measurement
Measurement plays a crucial role in agile change management experiments, enabling organizations to assess the effectiveness and impact of their initiatives. Here are a few key reasons why measurement is essential in the context of agile change management:
Assessing Progress: Measurement allows organizations to track the progress and outcomes of their change management experiments. By establishing clear metrics and key performance indicators (KPIs), teams can objectively assess how well they are progressing towards their goals. This provides visibility into the effectiveness of different strategies and helps identify areas that require adjustments or improvements.
Data-Driven Decision Making: Agile change management emphasizes making decisions based on empirical evidence rather than assumptions or guesswork. Measurement provides valuable data and insights that inform decision-making processes. By collecting and analyzing relevant data, organizations can make informed choices about adjusting their approaches, reallocating resources, or prioritizing specific actions.
Learning and Continuous Improvement: Measurement is instrumental in facilitating learning and continuous improvement. Through regular measurement and evaluation, organizations gain insights into what works and what doesn’t. By analyzing the data, teams can identify patterns, uncover root causes of challenges, and discover opportunities for optimization. This iterative process enables organizations to adapt their strategies, refine their approaches, and enhance the effectiveness of future change management experiments.
Demonstrating Value: Measurement helps organizations demonstrate the value and impact of their change management initiatives. By quantifying the outcomes and benefits achieved through the experiments, organizations can communicate the success and value of their efforts to stakeholders, leadership, and other teams. This not only fosters transparency but also builds credibility and support for future change initiatives.
Alignment with Strategic Objectives: Measurement allows organizations to align their change management experiments with strategic objectives and desired outcomes. By establishing relevant metrics and aligning them with organizational goals, teams can ensure that their efforts are contributing to the overall strategic direction. Measurement provides a means to assess whether the experiments are moving the organization closer to its desired state and achieving the intended benefits.
Accountability and Transparency: Measurement promotes accountability and transparency within change management initiatives. By setting measurable targets and regularly reporting on progress, teams can ensure that they are accountable for the outcomes of their experiments. This transparency also enables stakeholders and leadership to understand the impact of the change initiatives and make informed decisions based on the results.
In conclusion, while many change management methodologies still adhere to a rigid waterfall approach, there is a growing recognition of the need for agility in navigating change. By embracing the power of change management experiments, organizations can transform their change approach into a more agile and adaptive one.
Change management experiments provide a structured and iterative framework for testing and refining different strategies, interventions, and processes. They enable organizations to learn from real-world experiences, gather empirical data, and make evidence-based decisions.
By treating change as an ongoing series of experiments, organizations can continuously adapt and improve their approach, leveraging the power of agility to navigate the complexities and uncertainties of the ever-evolving business landscape. With a mindset rooted in experimentation and a commitment to measurement and learning, organizations can truly transform their change management practices and achieve more successful and sustainable outcomes.
To read up more about agile change management, visit our Agile Knowledge section for a range of articles on managing agile changes.
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 may be less clear.
When we look across different project members, 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. This may seem like a great way to convey and show in a very direct and financial way, the value of change management. After all, we use ROI for calculating projects, why not use the same for change management as well?
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. You simply evaluate to what extent people 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.
Using ROI may be useful when the cost of the initiative is the critical focus for the organisation. However, it is not the only way to convey the overall value of 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:
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.
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.
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.
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.
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.
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 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 ….
Annual revenue of $1 billion with 5% profitability
The revenue growth is 1%
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:
The financial value of change management does not need to be limited to individual initiatives
The sum may be greater than its parts. Rather than measuring at initiative levels, research findings are looking at organisational-level value
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.
Change management is often seen as a ‘soft’ discipline that is more an ‘art’ than science. However, managing change, like managing a business, relies on having the right data to understand if the journey is going in the right direction. 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.
What are some of the benefits of using data science in change?
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.
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.
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.
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.
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:
What data sources do we need to support the change management process?
Is the data we are using accurate and reliable?
Are there any gaps in our data inventory?
What data do we need to collect to support our change management initiatives?
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:
What is the expected impact of our change management initiatives?
What are the potential risks associated with our change management initiatives?
What proactive strategies can we implement to mitigate those risks?
How can we use predictive analytics to optimize the change management process?
Example of predictive analytics from The Change Compass
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:
What insights can we gain from our data?
What trends and patterns are emerging from our data?
How can we use business intelligence to improve communication and collaboration among stakeholders?
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:
How can we present our data in a way that is easy to understand?
How can we use data visualization to communicate progress and results to stakeholders?
How can we use data visualization to identify trends and patterns in our data?
How can we use data visualization to increase stakeholder engagement in the change management process?
Example of a project dashboard from Change Automator
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:
How can we measure the effectiveness of our change management initiatives?
What data do we need to collect to evaluate progress?
How can we use statistical analysis and data mining to identify areas for improvement?
How can we use monitoring
The outlined approaches are some of the key ways in which we can use data science to manage change. Change practitioners should invest in their data science capability and adopt data science techniques to drive change 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.
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
One of the most feared aspect of change by organisations is its impact on performance. There is a wide variety of change which can determine the potential for performance dips during the change process. However, there is a significant body of research on the phenomenon of performance dip during system implementation. This refers to a temporary decrease in performance or productivity that often occurs when a new system is introduced or a significant change is made to an existing system. In this article we review key research studies on performance dips during change.
What are some of the research studies on performance dips during system implementation? Here are a few research studies that provide some insight into the degree of performance dips during system implementation:
A study published in the Journal of Computer Information Systems in 2019 found that performance dips during ERP implementation projects can range from 10% to 25% on average, with some organizations experiencing dips as high as 40%.
A study published in the Journal of Information Technology Management in 2011 found that performance dips during enterprise system implementation can range from 5% to 50% on average, depending on the organization and the type of system being implemented.
A study published in the International Journal of Information Management in 2016 found that performance dips during electronic health record (EHR) system implementation can range from 5% to 60% on average, depending on the organization and the level of customization required for the EHR system.
What about for transformation programs? What are some of the findings on how much performance could dip during the transformational change process?
Here are some examples of the percentage of performance dips observed in various transformation programs:
A study by McKinsey & Company found that organizations undergoing digital transformations typically experience a 10% to 15% dip in productivity during the implementation phase.
A research report by the Hackett Group found that companies implementing large-scale enterprise resource planning (ERP) systems experience an average performance dip of 5% to 15% during the implementation phase.
A case study of a large Australian bank’s transformation program found that the organization experienced a 10% to 20% dip in productivity during the implementation phase.
A study of 10 organizations that had implemented new supply chain management systems found that they experienced an average productivity dip of 12% during the implementation phase.
The percentage of performance dips
The percentage of performance dip with transformation programs can vary widely depending on a variety of factors, such as the size and complexity of the transformation, the industry, the specific processes and systems being impacted, and the level of planning and support provided during the implementation.
It’s important to note that these percentages are only rough estimates, and the actual performance dip can vary widely depending on the specific context of the transformation program. Organizations can minimize the impact of performance dip by carefully planning and managing the implementation process, providing appropriate training and support to employees, and monitoring performance closely during and after the implementation.
Why causes the performance dip?
One key factor that contributes to performance dip is the learning curve associated with the new system. Users need time to become familiar with the new software or hardware and may initially struggle to complete tasks at the same speed or with the same level of accuracy as they did with the previous system.
Another factor is the disruption to established workflows and processes that can occur during system implementation. When a new system is introduced, it often requires changes to the way work is done, which can lead to confusion and delays until everyone adjusts to the new way of doing things.
Research has found that performance dip tends to be most pronounced in the initial stages of system implementation and can last anywhere from a few days to several months, depending on the complexity of the system and the level of support provided to users during the transition.
Overall, it is largely change management factors that can cause performance dips. For example:
Resistance to change. When employees are asked to change the way they work, they may resist the change, leading to a decline in performance. Resistance can be due to various reasons, including fear of the unknown, lack of understanding of the reasons for the change, and concerns about job security.
Implementation issues: When new processes or technologies are not implemented correctly, they may not work as intended, leading to a decline in performance. Implementation issues can be due to various reasons, including inadequate planning, insufficient resources, and unrealistic timelines.
Communication breakdowns: When communication between stakeholders breaks down, it can lead to confusion and misunderstandings, leading to a decline in performance. Communication breakdowns can be due to various reasons, including inadequate planning, insufficient resources, and unrealistic expectations.
Organizational culture: Organizational culture can also contribute to performance dips during transformation programs. When the organizational culture does not support change, employees may be resistant to it, leading to a decline in performance. Organizational culture can be due to various reasons, including leadership style, history, and values.
What about performance dips when there are multiple changes going on?
Research has shown that implementing multiple changes simultaneously can lead to a higher risk of performance dips. Here are some examples of research studies that have explored this issue:
“The Effects of Multiple Change Initiatives on Perceptions of Organizational Change: Implications for Employee Outcomes” by Michael Tushman and Philip Anderson (2004): This study found that implementing multiple change initiatives at the same time can lead to increased uncertainty and confusion among employees, which can lead to a decline in performance.
“The Effect of Multiple Change Programs on Employee Well-being and Work Outcomes: A Longitudinal Study” by Michal Biron and Yair Bamberger (2012): This study found that implementing multiple change programs simultaneously can lead to increased stress and burnout among employees, which can negatively impact their performance.
“The Impact of Multiple Change Initiatives on Perceived Organizational Performance” by Matthew Davis and Stephen Taylor (2008): This study found that implementing multiple change initiatives simultaneously can lead to a decline in perceived organizational performance, which can impact employee morale and motivation.
“Managing Multiple Organizational Changes: The Role of Prior Change Implementation and Timing of Change Initiatives” by Sebastian Kunert and Christiane Stenger (2019): This study found that implementing multiple changes simultaneously can lead to a higher risk of performance dips, but that prior experience with change implementation and careful timing of change initiatives can help to mitigate this risk.
Overall, these studies suggest that implementing multiple changes simultaneously can lead to a higher risk of performance dips. However, it is not that organisations should simply avoid implementing simultaneous changes. Morever, implementing simultaneous change is a fact of corporate life and continuous development. No modern organisation can survive by implementing only one singular change at a given time.
How to avoid performance dips across the portfolio of change initiatives
“Managing multiple change initiatives: the role of planning, sequencing, and implementation” by Jelena Spanjol and Susan Ashford (2018): This study found that careful planning and sequencing of change initiatives can help to reduce the negative impact of multiple changes on employee performance. The authors suggest that organizations should prioritize changes based on their strategic importance, and implement changes in a way that minimizes disruption to employees.
In particular, the following 3 points have been highlighted.
Prioritization: Organizations should prioritize changes based on their strategic importance, and implement changes in a way that minimizes disruption to employees. This can involve aligning changes with the organization’s overall strategy, and ensuring that employees understand how the changes will benefit the organization.
Timing and sequence: The timing and sequence of changes can have a significant impact on employee performance. Organizations should consider the timing of changes relative to other initiatives, as well as the sequence of changes. For example, changes that are more disruptive to employees may be better implemented after other, less disruptive changes.
Coordination: Effective coordination of multiple change initiatives is crucial to minimize the negative impact on employee performance. Organizations should ensure that there is clear communication and coordination between different departments and teams involved in the changes, and that there is adequate support and resources available to employees to help them adapt to the changes.
In fact similar findings have been concluded across various McKinsey studies as well. Having clear prioritisation and sequencing is absolutely integral to deliver significant value to the organisation across the initiative portfolio. 40% more value. That is correct. Organizations that are focused on prioritizing and sequencing across the initiative portfolio can gain 40% more value than those that do not.
If you’re keen on achieving 40% more value across your change portfolio have a chat to us about how The Change Compass digital solution can help you do just this.
How to avoid performance dip during system implementation change initiatives
Here are some research findings from different articles on how to reduce performance dips during system implementation projects:
1. “Reducing Performance Dip During Implementation of Large-Scale Information Systems” by David Straub and James King (1996): • Encourage and support employee participation in the implementation process. • Provide adequate training and education on the new system. • Communicate effectively with employees about the changes and their impact. • Provide adequate technical support and resources. • Establish clear and specific goals for the implementation process.
2. “Managing multiple change initiatives: the role of planning, sequencing, and implementation” by Jelena Spanjol and Susan Ashford (2018): • Develop a comprehensive change management plan that includes communication, training, and support. • Prioritize and sequence change initiatives to minimize disruption and avoid overload. • Provide clear and consistent communication about the changes and their impact. • Involve employees in the design and implementation process. • Monitor and address resistance to change.
3. “A multi-level model of employee attitudes toward organizational change” by W. Matthew Bowler et al. (2010): • Foster a positive attitude toward change by providing clear and consistent communication, support, and training. • Encourage employee participation and involvement in the change process. • Provide resources and tools to help employees adapt to the change. • Monitor and address resistance to change. • Recognize and reward employee efforts to adapt to the change.
4. “Reducing the Performance Impact of Software Upgrades” by Albert J. Simard and Lionel P. Robert Jr. (2004): • Develop a comprehensive training program that focuses on the most relevant features of the new system. • Provide ample opportunities for practice and feedback. • Establish a clear and specific timeline for the implementation process. • Communicate effectively with employees about the changes and their impact. • Provide technical support and resources to address any issues that arise.
In conclusion, research suggests that organizations that use a combination of these change strategies are more likely to avoid performance dips during transformation programs at a portfolio level. By carefully managing and monitoring the portfolio of initiatives, providing appropriate training and support to employees, and continuously improving performance, organizations can ensure a successful transformation that delivers the desired benefits.
