Measuring the success of digital transformation

In this article, we explore why measurement matters, how KPIs should evolve across different phases of maturity, and how continuous improvement turns digital transformation from a project into a permanent capability.

Why KPIs matter in digital transformation

KPIs serve three essential functions:

• Clarity: They provide a shared definition of success, ensuring that leaders, employees, and stakeholders align around the same goals.
• Accountability: They create transparency, allowing organizations to see what is working, what isn’t, and where corrective action is needed.
• Momentum: They help build confidence in digital initiatives. When employees and executives see tangible results, support for further investment grows.

Without KPIs, organizations risk “flying blind.” Projects may be implemented, but it remains unclear whether they deliver meaningful impact.

KPIs across the four phases of transformation

As digital maturity evolves, so too should the metrics used to measure success. KPIs must match the phase of the journey.

Phase 1: Foundation

At this stage, the focus is on building visibility and collecting reliable data.

• Example KPIs: Data availability rates, percentage of processes digitalized, number of operators using digital work instructions.
• Goal: Establish a baseline and ensure that the organization can measure performance consistently.

Phase 2: Integration & interoperability

Here, the objective is seamless data flow and system connectivity.

• Example KPIs: Reduction in manual data entry, percentage of systems integrated, accuracy of real-time OEE measurements.
• Goal: Demonstrate that data silos are being broken down and operational efficiency is improving.

Phase 3: Leverage Data

The focus shifts to creating value through analytics and predictive capabilities.

• Example KPIs: Reduction in unplanned downtime, defect rates lowered through AI-driven quality control, improvement in production yield.
• Goal: Move from reactive problem-solving to proactive optimization.

Phase 4: Autonomous operations

At this advanced stage, the emphasis is on autonomy, resilience, and continuous optimization.

• Example KPIs: Percentage of processes fully automated, number of digital twins in operation, reductions in manual interventions.
• Goal: Achieve advanced efficiency, agility, and competitiveness through automation and closed-loop systems

Building a continuous feedback loop

Defining KPIs is only the beginning. To sustain progress, organizations need a continuous feedback loop that ties measurement to action. This involves:

• Regular reassessment of maturity: Periodically evaluating people, processes, and technology to see where progress has been made and where new gaps have emerged.
• Iterative updates to the roadmap: Adapting priorities and milestones as business needs, regulatory pressures, or technological opportunities change.
• Engagement of stakeholders: Ensuring that employees and managers see the value of metrics and are part of discussions on how to improve them.

When feedback is embedded in the organization’s culture, measurement becomes more than reporting, it becomes a driver of change.

Demonstrating business value

Ultimately, KPIs must translate into business outcomes. Boards and executives are less interested in how many dashboards have been deployed and more interested in how digital initiatives improve profitability, compliance, and competitiveness.

This means communicating KPIs in terms of business value:

• Reducing waste directly supports sustainability goals and lowers costs.
• Improving traceability strengthens customer trust and speeds regulatory audits.
• Reducing downtime increases throughput and revenue.

When KPIs are framed in this way, digital transformation is no longer seen as an IT initiative but as a strategic lever for growth.

A case in point

An international pharmaceutical company offers a telling example. Facing fragmented reporting processes, the company developed an Information Hub in Microsoft Power BI. By centralizing data across packaging and delivery departments, they streamlined reporting, saved thousands of hours annually, and dramatically improved data utilization.

The project’s success was not measured in terms of “reports generated” but in terms of business outcomes: time saved, efficiency gained, and quality of decision-making improved. This reframing of KPIs ensured the initiative was recognized as a strategic success, not just a digital tool deployment.

Continuous improvement as a mindset

Perhaps the most important lesson is that digital transformation is never finished. Technologies evolve, customer demands shift, and competitors innovate. What counts as advanced maturity today may be baseline tomorrow.

By embedding continuous improvement into the DNA of the organization, supported by evolving KPIs manufacturers ensure that transformation remains a living, adaptive process. This mindset not only safeguards competitiveness but also builds resilience in the face of uncertainty.

Conclusion: Measuring what matters

Digital transformation is not about chasing the latest tools or achieving one-time milestones. It is about creating lasting value. The only way to ensure that value is realized is to measure it, consistently, thoughtfully, and in alignment with business objectives.

By defining KPIs for each phase, creating a feedback loop, and demonstrating business outcomes, manufacturers can move beyond technology hype to measurable impact. And by embracing continuous improvement, they ensure that transformation becomes a permanent capability, not a temporary project.

Reflection: Which KPIs are you using today to measure digital transformation and do they truly reflect the business value you want to achieve?