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Change Management in the World of Digital Transformation


Change management refers to the structured approach to transition individuals, teams, and entire organizations from a current state to a desired future state. It is a crucial discipline for companies undergoing digital transformation – leveraging new technologies to fundamentally evolve and improve business operations, models, offerings, and culture. This white paper has four key objectives related to change management in digital transformation. First, it will explain why adopting a strategic change management model is essential for the success of any digital transformation initiative. Second, it will analyze and recommend an established change management framework optimally suited for managing transformations driven by new technologies. Third, the paper explores how change management strategies may need to differ when dealing with disruptive versus sustaining technologies. Disruptive innovations like artificial intelligence and cloud computing can create more uncertainty and require more flexibility. Finally, the paper will synthesize critical learnings into a set of best practices – the vital success factors organizations must embrace in change management to realize the full benefits of digital transformation. With sound change management principles, companies can smooth the transition, accelerate the adoption of new tech-enabled working methods, and unlock value. Without it, even the most promising transformation efforts face significant hurdles that often lead to failure.

Change Management and Digital Transformation

Change management provides the critical framework and discipline to drive successful digital transformation. Digital transformation refers to integrating digital technologies into all business areas, fundamentally changing how companies operate and deliver value (Bellantuono et al., 2021). It encompasses three interrelated transformation areas: adopting new technologies and tech-enabled processes, evolving business models and strategies, and facilitating the cultural and organizational changes necessary to support new working methods. When executed well, digital transformation can yield dramatic improvements, including increased efficiency, superior customer experiences, faster innovation cycles, additional revenue streams, and greater business agility (Bongomin et al., 2020). However, the same technologies that underpin these breakthroughs also disrupt existing tools, policies, skillsets, and organizational structures, inevitably creates resistance and implementation hurdles that can undermine initiatives if not adequately addressed. Surveys show that up to 70% of digital transformations fall short of expected benefits partly due to change management failures (Brinkerink et al., 2022). Change management bridges this critical gap by taking a structured approach to transitioning an organization without disruption to fully leverage new technologies. Key strategies include conducting rigorous stakeholder analyses to identify needs and concerns, formulating targeted communication plans that clearly articulate the vision and business case, ensuring executive solid sponsorship and cross-functional coalition-building, rolling out skills training and development programs, designing reinforcement mechanisms like incentives and metrics aligned to desired changes, and instituting strong program governance models. This upfront work and continuous support of impacted groups is proven to dramatically accelerate adoption, address cultural barriers, and prevent productivity losses, employee disengagement, and implementation failures that often plague digital transformation efforts. The risks of digitally transforming without change management are substantiated by sobering statistics – as many as 70% of transformations fall short of goals, and 30% are outright failures. Beyond wasted resources and missed opportunities, failed initiatives can also carry reputational damage and significant opportunity costs from disruption (Bloomberg, 2021). For example, GE and Ford each invested billions in pursuing ambitious Internet of Things (IoT) transformations. Still, they achieved only a tiny fraction of the operational and financial benefits initially targeted due to lukewarm end-user adoption stemming from inadequate upfront planning and engagement (Coccia, 2018). The key lessons underscore why change management is the linchpin for smoothly realizing intended digital transformation business outcomes.

The risks of failed digital transformation highlight why change management provides such vital scaffolding. Whether due to employee disengagement, loss of productivity, implementation failures, or reputational impacts, organizations experience massive opportunity costs when ambitious technology-driven initiatives flounder. A seminal example came when GE invested billions in an Internet of Things (IoT) transformation centered on sensors and analytics to optimize maintenance and output across power turbines, jet engines, and healthcare machines. The technology capabilities were successfully built, but adoption languished amidst cultural inertia. By one estimate, nearly $500 million was spent without yielding even half the projected $15 billion value over five years. The reasons echo broader change management pitfalls (Kang et al., 2020). Leadership needed to adequately explain the business case or ready the workforce for such a drastic shift from break-fix to predictive protocols. The organizational gravity also outweighed any urgency or incentives to embrace unfamiliar tools or data-based deviations from lifelong experience, manifested in lackluster training completion metrics. The small wins and behavioral changes vital to sustainable change were neither achieved nor reinforced. It serves as sobering evidence that even sophisticated technical integrations will waste away without the human process and cultural recalibration change management is designed to catalyze.

Change Management Models for Digital Transformation

Of the various established change management frameworks, Kotter’s 8-Step Change Model is the optimal approach for organizations undergoing large-scale digital transformation. Digital transformation refers to integrating digital technologies like cloud, mobile, AI, IoT, and analytics to fundamentally evolve business operations, models, products, and services (Kang et al., 2020). It requires simultaneous technological and organizational change on a sweeping scale. Kotter’s model is uniquely suited for driving urgent, enterprise-wide transformations – precisely the approach needed to reinvent businesses in the digital age. It provides a straightforward yet flexible structure centered on setting a vision for change, forming a guiding coalition, and systematically removing barriers (Kang et al., 2020).

Four key factors make Kotter’s eight steps well-matched to managing change in digital transformations:

Gonçalves (2023) highlights four defining features that make Kotter’s 8-Step model well-aligned to managing organizational change in digital transformations. First, the model emphasizes establishing a sense of urgency and rallying stakeholders around an ambitious transformational vision that drives meaningful action versus incremental gains. Digital transformation efforts require pushing boundaries to differentiate truly. Second, Kotter stresses securing strong cross-functional sponsorship and alignment to overcome the cultural and structural obstacles intrinsic when making profound, enterprise-wide changes that cut across hierarchies and silos. Succeeding with expansive initiatives requires coordinated, aligned leadership backing new integrated working methods. Third, the model explicitly ties any proposed changes and investments to tangible customer and financial outcomes over technology for its own sake to force accountability and drive competitiveness. Finally, and foundationally, Kotter balances the process and people sides, recognizing transformations flounder without disciplined change infrastructure and motivating hearts and minds. The phases focused on small wins and consciously embedding changes into culture cement new tools, mindsets, and capabilities so organizations do not backslide. Together, these interdependent strengths make Kotter the premier framework for leading companies through turbulent, tech-driven business model reinvention centered on more connected, insightful, and responsive modes of value creation.

Real-world examples abound of firms leveraging Kotter’s approach to frame successful tech-led business transformations, including Mastercard, Sony, Oracle, IBM, and Chevron (Smol et al., 2020). The model’s track record confirms its advantage versus others like McKinsey 7S (best for incremental change), Bridges (focuses only on transition), or ADKAR (helpful but not comprehensive). Gonçalves (2023) echoes why Kotter’s model is well-suited for digital transformation, emphasizing establishing urgency, aligning leadership, communicating vision, and systematically removing barriers. He observes how Kotter’s later phases focused on reinforcing change maps to strengthen new digital capabilities and working methods. Smol et al. (2020) similarly highlight Kotter’s vision, alignment, and celebrating wins as key strengths while underscoring risks if organizations fail to anchor changes, a common pitfall after digital implementations. Firms may backslide into old ways without consciously cementing new tools, metrics, and cultural traits. In an environment of constant digital disruption, Kotter’s blend of urgency, vision, alignment, and reinforcement offers the proper framework to keep organizations in a productive state of perpetual transformation rather than risky one-off initiatives. The model checks all the factors when selecting a change management approach for far-reaching technical transformations,includes scale, speed, change readiness, flexibility, and applicability across business, cultural, and technological focal areas.

McKinsey’s 7S model offers functional analysis but proves more suited to incremental adjustments versus ambitious efforts to reshape entire industries. Bridges Transition Model brings needed empathy but does not provide comprehensive process support across a transformation’s entire life cycle. ADKAR offers simple prioritization of the human element but lacks more considerable picture governance and infrastructure for significant initiatives (Smol et al., 2020). Finally, agile change management platforms that apply Kotter’s principles to more fluid, iterative environments characterized by constant flux rather than definitive end states have emerged, helps bridge structure with flexibility but still benefits from Kotter’s overarching phases. Kotter’s 8-Step Change Model applied to digital transformation change management stands the test of time by balancing boldness and discipline, outcomes and adoption, process and people needed to turn technical potential into competitive resurgence.

Change Management for Disruptive Technologies

Managing change for disruptive technologies differs fundamentally from incremental or sustaining innovations in digital transformation. Disruptive technologies displace established systems and ways of working to catapult entirely new paradigms and sources of value (Kang et al., 2020). Examples include artificial intelligence (AI), cloud computing, Internet of Things (IoT) and blockchain. These break existing tradeoffs to uniquely deliver simplicity, accessibility, flexibility, or intelligence that redefines ecosystems. The profound uncertainties they introduce around competitive dynamics, required capabilities, optimal operating models, and the feasibility of beneficial adoption require a tailored change management approach.

Four dynamics characterize disruptive technologies that diverge from change management for non-disruptive transformation:

  1. Precipitous Uncertainty: Disruptive innovations inherently lack defined applications, clear value propositions, intact ecosystems, proven use cases, and defined maturity curves early on (Kang et al., 2020). Unknowable complexity on multiple fronts requires iterative sensemaking and co-creation well past traditional planning stages.
  2. Rapid Iteration: The speed of software-based advances greatly accelerates experimentation, evolution, and proliferation, demanding accelerated cycles to keep pace. Change intervals compress from years to months.
  3. Far-Reaching Impacts: Disintermediation spans products, channels, data flows, roles, and operating models requiring more sweeping change and executive commitment versus isolated initiatives.
  4. Strategic Ambiguity: Disruption theory tells us new technologies underperform along traditional metrics until crossing to unlock wholly unforeseen use cases. This strategic opacity stresses culture, patience, and options-based perspectives.

These dynamics carry several critical implications for managing change:

First is emphasizing organizational agility, innovation culture, and iterative development cycles reflecting faster external clock speeds (Coccia, 2018). Linear, monolithic approaches fail in the absence of defined requirements or definitive end states. Next is the earlier involvement of change agents to spot inflection dynamics and transformative potential ahead of settled practices or financial validation. This earlier integration and proximity to technical teams also increases adaptability to non-linear advances. Third, greater executive commitment is required to fund uncertainty and endure years without traditional returns common in emergent paradigms. Leadership must expand attention spans and performance metrics. Additionally, organizations benefit from decoupling innovative teams from legacy divisions to escape conditioned, outdated assumptions around customer needs or technical possibilities (Brinkerink et al., 2022). Managing change means reinforcing the cultural hallmarks of exploratory innovation like neurodiversity, datified decision rights, horizontal authority, and incentivizing evidence-based failure given the number of dead ends confronting true unknowns. Realized exponential transformation hinges on whether organizations adapt their mental models around change itself – the timescales, mindsets, and structures needed to harness uncertainty and extremes rather than reinforcing historical norms. This expanding capacity to change then enables the operational dexterity to smoothly adopt each wave of disruption.

While disruptive and sustaining digital innovations vary across many technology dimensions, perhaps the deepest distinction lies in the respective mindsets and mental models behind change management strategies (Brinkerink et al., 2022). Sustaining technologies that optimize rather than transform can leverage traditional change management frameworks like Kotter’s that provide useful yet linear steps. They benefit from defined roadmaps, requirements and end states. Point A to Point B trajectories centered on driving adoption suffice when the means and ends are reasonably understood.

In contrast, guiding organizations through disruptive, exponentially advancing technologies necessitates very different change management principles better tuned to chaos, ambiguity, nonlinear shifts and unknown unknowns. The mental model moves from planning sequences to fostering initial conditions that allow for sense-making, emergence and constructive capitalization from exponential currents rather than predefined rigid implementations. This equates to setting direction more than defining destination, infrastructure more than intentionality, releasing rather than restricting or changing the way we change. Correspondingly, disruptive change management relies more on vision, values and platform thinking to build transformational capacity (Bongomin et al., 2020).

Beyond shaping mental models, several organizational capabilities prove vital to managing change amidst disruptive technologies yet remain secondary for sustaining innovations:

  1. Leadership Storytelling – to provide coherence, meaning-making and enroll organization in co-authorship rather than top down messaging
  2. Ecosystem Curating – to drive shared infrastructure, leverage network effects and accelerate capability building through common pools
  3. Architecting Options – to mitigate uncertainty by creating plausible alternative futures not plans, roadmaps or point forecasts
  4. Data Sensemaking – to support evidence-based interventions and navigational awareness amidst complexity
  5. Incentive Redesign – to spur ecosystem engagement, value co-creation and counter loafing from uncertainty

These differentiating capabilities must become organizational meta-skills to fluidly adapt strategy, structure, processes and culture in step with accelerating technology revolution cycles (Bellantuono et al., 2021). Sustaining and disruptive change management ultimately diverges between optimization and transformation mindsets, improving the present or creating the future.


In an age of digital disruption, strategic change management frameworks offer vital scaffolding to smooth ongoing technology-driven transformations. Kotter’s 8 Step model has proven its value for guiding sweeping, enterprise-wide realignment required to leverage disruptive advances and reimagine outdated business models. It balances the urgency, coalition-building, communication, and cultural adaptations vital to dismantling aging hierarchies on accelerated timeframes. When the competitive paradigm itself is shifting, the model compels organizations to remain in a constant state of productive transformation. At the same time, disruptive technologies pose uncertainties that necessitate more flexible change management approaches. Buttressed by strong guardrails and principles for aligning leadership, reinforcing desired changes, and supporting affected stakeholders, organizations require additional dexterity to iterate through ambiguity. Amidst exponential progressions, the capacity to change itself must evolve from traditional linear steps to setting initial conditions and mental models to harness ongoing exponential progressions. By fusing change management foundations with resilience to ambiguity and accelerated clocks speeds, leaders can smooth turbulent waters ahead into engines of innovation and growth.


Bellantuono, N., Nuzzi, A., Pontrandolfo, P., & Scozzi, B. (2021). Digital Transformation Models for the I4.0 Transition: Lessons from the Change Management Literature. Sustainability13(23), 12941.

Bongomin, O., Ocen, G. G., Nganyi, E. O., Musinguzi, A., & Omara, T. (2020). Exponential disruptive technologies and the required skills of industry 4.0. Journal of Engineering2020, 1–17.

Brinkerink, M., Zakeri, B., Huppmann, D., Glynn, J., Gallachóir, B. Ó., & Deane, P. (2022). Assessing global climate change mitigation scenarios from a power system perspective using a novel multi-model framework. Environmental Modelling and Software150, 105336.

Coccia, M. (2018, January 11). Disruptive firms and industrial change.

Kang, S. “., Chen, Y., Svihla, V., Gallup, A., Ferris, K., & Datye, A. K. (2020). Guiding change in higher education: an emergent, iterative application of Kotter’s change model. Studies in Higher Education47(2), 270–289.

Smol, M., Adam, C., & Preisner, M. (2020). Circular economy model framework in the European water and wastewater sector. Journal of Material Cycles and Waste Management22(3), 682–697.

Gonçalves, L. (2023, October 3). Change management framework for organisational Insights. ADAPT METHODOLOGY®.


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