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Digital Transformation of Organization Change Management

Chris Wilhelm

VP, Transformation & Change Consulting, EPAM

Danielle Gorder

Consultant, Business Consulting, EPAM

Dennis Leskowski

Senior Manager, Life Sciences Consulting, EPAM

Big budget dollars were just spent on an advanced software implementation.  It’s a major rollout that leverages the latest in business intelligence, cloud, security, IoT and automation. But are business users actually adopting the end product? Are they utilizing its capabilities to the fullest?

Data analytics and, more specifically, a holistic data and reporting strategy should be viewed as an instrumental component to every organizational change management (OCM) approach. While change is inherently about driving new behaviors, one of the gaps we’ve observed is that the traditional OCM approach can be reactive in its implementation and fails to incorporate digital engagement tools. As a result, there is often a lack of data-driven measurement and insight, which could assist in both monitoring the change journey (before, during and after development) and ensuring the end solution is adaptable and adoptable for business stakeholders.

Digital engagement tools can assist with establishing an informed set of KPIs, baseline measurements and business stakeholder targets. Change managers can then relay these insights to stakeholders to keep them informed, motivated and engaged, as well as developers to improve end-user experience, course-correct progress and achieve optimal business outcomes. 

Let’s explore how digital engagement tools can help organizations throughout the entire organizational change journey:


Traditionally, to determine the appropriate change model for the business, change managers needed to conduct surveys and interviews manually to gain insight into the user population and evaluate stakeholder behavior. That summary was then passed on to a product owner who was often more concerned with capturing the old business process than creating a new business user experience.

Today, change managers can collect and predict user adoption from data sets available through digital engagement tools. For example, EPAM added simple click-tracking software to a large biotech company’s legacy system to gain insight around how and when scientists were accessing and managing files. Having a baseline of user adoption before implementing any change management approach, combined with the irreplaceable face-to-face interactions between employees, provides a foundation for how the new system will truly advance the user experience.


The largest gains in OCM have been the application of agility to the change process itself.  Typically, OCM has been seen as a “tack-on” to a project – a mere insurance policy to say that we tried to consider user adoption.

It’s crucial to embrace the change manager as a vital part of the development process. Through the change manager’s arsenal of traditional interpersonal engagement tools, as well as leveraging the latest advancements in data science, we are able to better drive user adoption during the user design and user experience process.

For example, our consultants work with companies to optimize each sprint, not only by using feedback from subject matter experts (SMEs) that are normally engaged during the product development process, but also from a host of everyday beta testers who provide real-time feedback. We gather usage statistics while also asking about positive and negative sentiment and utilizing advanced linguistics text analysis to provide insight into human emotions that can be ambiguous. In a recent human resource (HR) hiring software implementation, our change management consultant gathered a group of non-employees to test the new hiring portal and retool the HR workflows to be more end user-friendly – resulting in better engagement and measurably higher recruitment rates.


With the dawn of digital engagement, most businesses can easily track clicks and traffic. Even small, in-house applications are now equipped with business intelligence software to find end-user statistics on usage. For example, EPAM currently tracks post-training engagement to see where users are finding unplanned workarounds and how often bugs are encountered.  With this information, software updates can happen faster – during the hypercare period (immediately after deployment) as opposed to months down the road.

Digital engagement after development benefits users, business sponsors and even finance teams in the following ways:

  • Allows for the measurement of production value in real dollars (a bonus for today’s dwindling department budgets that want to prove big gains)
  • Provides course-correction opportunities to ensure that each minimum viable product (MVP) evolves the experience and utility of the toolset
  • Enables input into the future roadmap for features and engagement experiences

When coupled with “before development” baselining, new, big budget implementations can now be showcased as major wins, where actual production value is measured in real dollars.  


Overall, leveraging data and measurement for OCM is foundational to our approach.  Nothing will replace the change manager’s need to dive into the stories behind the data through personal interaction. However, we’ve seen how data patterns help us ask better questions, adapt our approach and find paths to effective solutions that were previously unknown.

The goal of an implementation’s change management program will always be the same – user adoption. By embracing data analytics in OCM, we can surpass that goal to confidently decrease change failure rates and increase measurable success.

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