3 innovative change management frameworks for digital transformation

The tried and tested change management playbook, while crucial, is often insufficient for the digital realm. Digital programs are not solely technological overhauls but sweeping revolutions in working, decision-making and creation of value.

When businesses embrace artificial intelligence (AI), internet of things (IoT), robotic process automation (RPA) and other digital technologies, they need a new change management model – one that addresses the unique challenges of the digital age and employs innovative frameworks to create authentic digital fluency in operational teams.

Synthesizing PROSCI ADKAR with digital transformation

Before venturing into newer models, it is worth considering how the well-proven PROSCI ADKAR model can be tailored to digital transformation projects specifically. Having used this model on numerous large transformations, I have found that it is a good starting point when tailored for digital-specific issues.

The ADKAR model – awareness, desire, knowledge, ability and reinforcement – is a structured approach to individual change that effectively scales to organizational scale. Here’s how I’ve adapted it for digital transformation:

• Awareness: Beyond merely reporting “what's changing,” digital transformation requires building awareness of competitive threats and risk of industry disruption. In consulting with a pharma client on the rollout of predictive maintenance systems, we took operators from one of the competitor’s factories (who’d already been through the transformation) and sent them to swap stories – both the pitfalls and the benefits. Building awareness this way (person to person) was exponentially more powerful than executive presentations.
• Desire: Digital change tends to resist because gains can be perceived as abstract or distant. I have discovered that building “digital experience rooms” where groups can experiment with new technology in a relaxed environment stimulates genuine desire. In one electronics producer, we created a “digital twin sandbox” where production groups could simulate process changes and observe the consequences immediately – building emotional commitment that PowerPoint presentations could never replicate.
• Knowledge: Digital knowledge transfer requires breaking away from past training. In recent instances, we’ve set up “digital apprenticeship” initiatives that pair digitally literate millennials with experienced operators. This reverse-mentoring approach is far superior to classroom training because it places digital abilities in the context of operational acumen.
• Ability: The knowledge-ability gap is particularly dramatic in digital transformation. We bridged this gap by applying “digital confidence sprints” – structured two-week blocks where teams apply new tools to solve a specific business issue with deep coaching support. At a medical device firm, such sprints compressed the knowledge-to-proficiency gap from six months to over six weeks.
• Reinforcement: Automated tools realize the strength of reinforcement by the capability of data analytics. We now make “adoption dashboards” that plot trends in system adoption, highlighting not only individual success but also collaboration success. Dashboard measurements allow leadership to provide commendation at the time and specific mentoring.

ADKAR is great to begin with, but digital change usually requires extra frameworks to shed light on how to approach special elements of the digital challenge. The following frameworks complement ADKAR by treating special digital subtleties specifically.

Join us at All Access: Change Management 2025 to explore overcoming resistance to change and measuring the success of change initiatives

1. The digital change velocity model

I stumbled upon this method by accident while wrestling with a troubled MES implementation at a contract manufacturer. We were attempting to roll out all digital capabilities simultaneously across the entire organization, and the result was a disaster – extreme pushback, plummeting productivity and a near-mutiny by middle management.

After a painful project hiatus and restart, we developed what I now call the digital change velocity model. This model, which I have subsequently applied successfully in three different manufacturing companies, recognizes an undeniable fact: digital transformation requires varying implementation rates within different organizational domains.

Three zones of velocity

1. Foundation zone (slow, deliberate change)

• Core systems and infrastructure
• Systems of regulatory compliance
• Data governance frameworks   

2. Integration zone (moderate, systematic change)

• Cross-functional processes
• Management systems
• Performance metrics and incentives

3. Innovation zone (rapid, agile change)

• Customer-facing applications
• Internal productivity tools
• Analytics and insight generation

The key here is that organizations must operate at multiple speeds simultaneously, rather than dictating one velocity of change throughout the business. This is an acknowledgment that certain parts must be changed slowly and carefully, while others are assisted by rapid iteration.

Implementation approach:

• Map organizational pieces to respective zones of velocity.
• Describe in a clear way which pieces belong in each zone.
• Apply appropriate change methodologies in each zone (e.g. classical waterfall for foundation elements, agile for innovation elements).
• Introduce integration mechanisms to enable synchronization among zones.

The transformation experience framework

I learned this tactic the hard way when a technically impeccable IoT rollout was being deliberately frustrated by frontline supervisors. Weeks of trying to make sense of the resistance finally netted me a curt reply from one manager: “you’ve spent millions optimizing the machines’ day, but you’ve made our day-to-day worse.”

That mindset compelled us to develop this people-first methodology centered around employee experience amid digital transformation. It treats employees as “customers” of the change initiative and not an obstacle to be overcome. The methodology addresses the emotional journey of transformation, not merely the rational justification for change.

Key elements:

1. Experience mapping: Encoding the current and future desired employee experience in key digital touchpoints.
2. Friction identification: Identifying specific pain spots in the adoption process.
3. Intervention design: Designing specifically articulated support structures for different persona types: digital pioneers (early majority), pragmatic adopters (practical majority), cautious integrators (late majority) and digital skeptics (reluctant majority).
4. Feedback loops: Ongoing assessment of adoption experiences for refining strategies.

This strategy places human experience at the center of the change process, rather than treating it as an afterthought to technology uptake.

The digital influence network

Rather than relying on formal organizational structures, this approach finds and mobilizes informal influence networks to spur digital uptake.

 Steps to implementation:

1. Network mapping: Using organizational network analysis to identify influential people regardless of their position in the hierarchy.
2. Digital ambassador program: Engaging high-impact employees across functions and levels to be change agents.
3. Capability building: Both technically upskilling employees as well as providing change facilitation capabilities.
4. Peer learning communities: Creating formal and informal learning platforms for knowledge exchange and solving problems.
5. Success spotlighting: Creating a process to harvest and amplify early wins and learnings.

In a recent implementation of electronics manufacturing, we discovered 22 influencers across three factories. With their advanced training and dedicated time for peer mentoring, we had 87 percent of new digital workflows adopted within four months – well ahead of the past standards.

All Access: AI in PEX is 2025

All Access: AI in PEX 2025 is designed to address these challenges and empower organizations to successfully integrate AI into their process improvement initiatives. The content series will bring together industry experts, thought leaders, and practitioners to share insights, best practices, and real-world case studies.

Register Now