What is Digital Maturity?
Original Publication June 25th, 2025. Updated January 26th, 2026
For many companies, digital transformation has become synonymous with technology adoption. Executives proudly list off their alphabet soup of tools (e.g., AI, MES, IoT, Cloud, Digital Twin, etc.) as though the number of systems implemented is a proxy for progress. Why? Because it is easy!
True digital maturity isn’t about how many tools you’ve deployed; it’s about how seamlessly your business operates. And the best way to measure that is to look at your handoffs. The fewer handoffs you need to execute work, the closer you are to an operational flow. And in the digital era, flow beats fragmentation every time.
What Is Digital Maturity, Really?
At its core, digital maturity refers to an organization’s ability to leverage digital technologies in a scalable, sustainable, and value-driven way. But that definition is deceptively simple. Many organizations confuse digital maturity with digital presence. Just because a company uses cloud storage, an MES system, and a dashboarding tool doesn’t mean it’s mature. In fact, an overload of tools can often signal the opposite: a fragmented architecture with excessive handoffs and inconsistent data.
One way to think about digital maturity is through the lens of digital literacy vs. digital fluency:
Digital literacy means knowing what technologies exist and perhaps using them in isolated ways.
Digital fluency means integrating these technologies into how decisions are made, work is executed, and value is delivered.
Digital maturity is about the application of digital capabilities, not their accumulation.
Why Fewer Handoffs Signal Greater Maturity
Every handoff in a business process introduces friction. These friction points slow things down, create opportunities for error, and require human intervention that undercuts automation. Consider a typical order-to-cash process. In a digitally immature environment, the process may require multiple manual data entries, system lookups, email threads, and spreadsheet updates. Each one a handoff. In a mature environment, much of this is streamlined or automated, with data flowing seamlessly from order entry through production and invoicing. Digital maturity is how quickly and effectively your organization can turn data into action. It’s the distance between insight and execution, and how much noise, latency, and interpretation get in the way. So how do you measure that? With KPIs designed specifically to evaluate maturity, not just activity or output.
Unlike traditional KPIs that focus on performance (How fast? How much? How cheap?), digital maturity KPIs ask a different question: To what extent have we developed the capabilities (technological, organizational, and cultural) to continuously adapt, integrate, and create value in a digital environment?
That means your KPIs must evaluate things like:
Integration and seamlessness of workflows
Accessibility and usage of data for decisions
Cross-functional alignment and collaboration
Automation of low-value tasks and handoffs
Workforce enablement and digital fluency
How to Choose the Right Maturity KPIs
Before you start tracking anything, it is worth slowing down and being explicit about what you are actually trying to measure. Maturity KPIs should map directly to the capabilities you are trying to build, not just the outcomes you happen to see in one corner of the business. If you skip this step, you will end up measuring activity, adoption, or local performance and mistaking it for progress.
Well-chosen maturity KPIs tend to share a few common traits. They reflect systemic capability rather than isolated wins or one-off improvements. They make progress visible over time and across departments, not just within a single team or function. They are objective enough to be credible, but still grounded in real operational context so they mean something to the people doing the work. And importantly, they allow you to clearly compare where you are today with where you are trying to go, making gaps explicit rather than aspirational.
The test is simple: if a KPI can improve without the organization becoming meaningfully easier to run, it is probably not a maturity metric. A good rule of thumb is to pick KPIs from across at least four to five maturity areas, and ensure they evaluate how work gets done, not just what gets done. Below are five categories of KPIs tailored to evaluate digital maturity, each with specific examples and guidance on what they reveal.
1. Seamlessness of Processes
Processes tell the truth faster than strategy decks ever will. When work flows cleanly, people barely notice the systems supporting it. When it doesn’t, the organization compensates with workarounds, side conversations, and informal fixes. This category exists to surface how much effort is required just to keep things moving.
What to Measure:
Number of handoffs in a core business process (e.g., quote-to-cash, design-to-release)
% of end-to-end processes executed without manual intervention
% of enterprise systems with real-time data exchange
Number of systems required to complete a standard task (e.g., issuing a production order)
% reduction in duplicate or shadow systems (e.g., spreadsheets used outside core tools)
What It Reveals:
Whether you’ve matured beyond point solutions to true integration. Fewer handoffs = greater digital flow and maturity.
2. Data Availability and Decision Use
Data has no inherent value on its own. Its value shows up only when it changes behavior, direction, or timing. Many organizations are rich in data and poor in decisiveness, not because the information is missing, but because it is disconnected from how work actually happens. This category focuses on whether information is positioned to influence action, not just explain outcomes after the fact.
What to Measure:
% of frontline and managerial decisions based on shared, real-time data
% of data automatically captured (vs. manually entered)
% of operations with a single source of truth across departments
Data latency (time from generation to availability)
What It Reveals:
The maturity of your data architecture, the trust in your systems, and the degree to which data is embedded in operational decision-making.
3. Automation and Responsiveness
As operations scale and complexity increases, speed alone is no longer enough. What matters is consistency under pressure. This category looks at whether the organization can absorb variation without stopping, escalating, or improvising every time something unexpected occurs. It is a signal of how resilient and adaptive the operating model really is.
What to Measure:
% of alerts with defined, automated responses (e.g., production rerouting, maintenance scheduling)
Number of process triggers automated based on business logic
% of human interventions required in daily standard workflows
Mean time from event detection to corrective action
% of machine or line downtime addressed proactively using predictive tools
What It Reveals:
How far you’ve moved from reactive to predictive and adaptive behavior. Mature systems enable fast, automated responses, not delayed, human-dependent fixes.
4. Workforce Enablement and Digital Fluency
Technology adoption is easy to mandate and hard to internalize. People will always find the fastest path to get their work done, even if that path bypasses official systems. When digital tools align with how people think and work, they become invisible. When they do not, they become obstacles. This category reflects whether the workforce has moved beyond compliance into confidence, and whether digital ways of working feel natural rather than forced.
What to Measure:
% of employees trained not just in tool usage, but in digital thinking (e.g., process improvement, data-driven decisions)
% of frontline workers interacting with digital systems daily
# of digital suggestions or continuous improvement ideas submitted and implemented
% of tasks completed using standard digital procedures or instructions
What It Reveals:
Whether your people are digitally enabled and evolving alongside your technology—and whether digital is woven into the culture, not just the tech stack.
5. Cross-Functional and Strategic Alignment
Alignment is rarely absent at the intent level. Most teams believe they are working toward the same goals. The problem shows up later, in execution, when priorities compete, timelines drift, and decisions made in one area create unintended consequences in another. This category exists to expose whether the organization operates as a single system or as a set of well-meaning but loosely connected functions, each optimizing its own view of success.
What to Measure:
% of digital initiatives co-owned by business and IT
% of enterprise KPIs tied to digital or data-driven performance
# of transformation efforts that span multiple departments
What It Reveals:
Whether your digital maturity is systemic, or still stuck in silos. Mature companies act cohesively, not departmentally. Digital maturity KPIs aren’t trophies, they’re thermometers. Their purpose is to reveal gaps, expose friction, and surface disconnects. The goal is not to get a perfect score, but to know where you stand, and which areas need investment.
From Busy to Mature: Rethinking the Digital Mindset
A final point worth emphasizing: Digital maturity is as much about mindset as it is about systems. The immature digital organization views transformation as a series of disconnected projects. One initiative for AI, another for IoT, another for cloud. They stack tools on top of each other, each optimized for a local purpose. The mature organization sees digital transformation as a system-wide capability. One that enables flow across people, systems, and decisions. And more importantly, one that evolves continuously. The difference isn’t just strategic. It’s cultural.
