Analytics capability: The new differentiator for modern CIOs

It was the question that sparked a journey.

When I first began exploring why some organizations seem to turn data into gold while others drown in it, I wasn’t chasing the next buzzword or new technology. Rather, I was working with senior executives who had invested millions in analytics platforms, only to discover that their people still relied on instinct over insight. It raised a simple but profound question: “What makes one organization capable of turning data into sustained advantage while another, with the same technology, cannot?”

My analytics journey began in the aftermath of the global financial crisis, while working as a corporate IT trainer. Practically overnight, I watched organizations slash training and development budgets. Yet their need for smarter, faster decisions had never been greater. They were being asked to do more with less, which meant making better use of data.

I realized that while technology skills were valuable, the defining challenge was enabling organizations to develop the capabilities to turn data into actionable insight that could optimize resources and improve decision-making. That moment marked my transition from IT training to analytics capability development, a field that was only just beginning to emerge.

Rethinking the traditional lens

Drawing on 13 years of research and consulting engagements across 33 industries in Australia and internationally, I found that most organizations approach analytics through the familiar lens of people, process and technology. While this framing captures the operational foundations of analytics, it also obscures how value is truly created.

A capability perspective reframes the relationship between these elements, connecting them into a single, dynamic ecosystem that transforms data into value, performance and advantage. This shift from viewing analytics as a collection of activities to treating it as an integrated capability reflects a broader evolution in IT and business alignment. In this context, CIOs increasingly recognize that sustainable performance gains come from connecting people, processes and technology into a cohesive strategic capability.

Resources are the starting point. They encompass both people and technology from the traditional lens (e.g., data, platforms, tools, funding and expertise). Together, these represent the raw potential that makes analytics activity possible. Yet resources on their own deliver limited value; they need structure, coordination and purpose.

Processes provide that structure. They translate the potential of resources into business performance (e.g., financial results, operational efficiency, customer satisfaction and innovation) by defining how analytics are governed, executed and communicated. Well-designed processes ensure that insights are generated consistently, shared effectively and embedded in decision-making rather than remaining isolated reports.

Analytics capability is the result. It represents the organization’s ability to integrate people, technology and processes to achieve consistent, meaningful outcomes like faster decision-making, improved forecasting accuracy, stronger strategic alignment and measurable business impact.

This relationship can be summarized as follows:

Together, these three elements form a continuous system known as the analytics capability engine. Resources feed processes, processes transform resources into capability and evolving capability enhances both resource allocation and process efficiency. Over time, this self-reinforcing cycle strengthens the organization’s agility, decision quality and capacity for innovation.

For CIOs, this marks an important shift. Success in analytics is no longer about maintaining equilibrium between people, process and technology; it is about building the organizational capability to use them together, purposefully, repeatedly and at scale.

Resources that make the difference

Analytics capability depends on people and technology, but not all resources contribute equally to success. What matters most is how these elements come together to shape decisions. Executive engagement, widely recognized as one of the most critical success factors, often proves to be the catalyst that turns analytics from a purely technical function into an enterprise-wide strategic imperative.

Executive engagement has a visible and tangible impact. By funding initiatives, allocating resources, celebrating wins and insisting on evidence-based reasoning, leaders set the tone for how analytics is valued. Their actions shape priorities, inspire confidence in decision-making and make clear that analytics are central to business success. When this commitment is visible and consistent, it aligns leadership and analytics teams in pursuit of genuine data-driven maturity.

In contrast to executive sponsors who set direction and secure commitment, boundary spanners are the quiet force that turns intent into impact. Often referred to as translators between business and analytics, they make data meaningful for decision-makers and decisions meaningful for analysts. By connecting these worlds, they ensure that insights lead to action and that business priorities remain at the center of analytical work.

Organizations that recognize and nurture these roles accelerate capability development, bridge cultural divides and achieve far greater return on their analytics investment. In view of this, boundary spanners are among the most valuable resources an organization can develop to translate analytics potential into sustained business performance.

Processes that make the difference

When it comes to communication, nothing can be left to chance. Without effective communication, even the best analytics initiatives struggle to gain traction. Building analytics capability requires structured, purposeful communication and this depends on three key factors.

First, co-location or physical proximity between business and analytics teams accelerates understanding, strengthens trust and promotes the informal exchange of ideas that drives innovation.

Second, access to executive decision-makers is vital. When analytics leaders have both the ear and access of senior decision-makers, insights move faster, gain credibility and influence strategic priorities. This proximity ensures analytics are not just heard but acted upon.

Third, ongoing feedback loops and transparency ensure communication doesn’t end once insights are shared. Embedding feedback mechanisms into regular workflows such as post-project reviews, annotated dashboards and shared collaboration platforms keeps analytics relevant, trusted and continually improving. These practices align with the growing emphasis on effective communication strategies for IT and analytics leaders, turning communication into a driver of engagement and performance.

When communication becomes part of the organization’s operating rhythm, analytics shift from producing reports to driving performance. It transforms analytics from an activity into a capability that continuously improves decision-making, trust and outcomes.

Capability-driven differentiation in analytics

Technology, people and processes have traditionally been seen as the pillars of analytics success, yet none of them alone create lasting competitive advantage.

The commoditization of information technology has made advanced tools and platforms universally accessible and affordable. Data warehouses and machine-learning systems, once reserved for industry leaders, are now commonplace. Similarly, processes can be observed and replicated and top analytical talent can move between organizations, which is why neither offers a lasting foundation for competitive advantage.

What differentiates organizations is not what they have but how they use it. Analytics capability, unlike technology and processes, is forged over time through organizational culture, learning and experience. It cannot be bought or imitated by competitors; it must be cultivated. The degree of cultivation ultimately determines the level of competitive advantage that can be achieved. The more developed the analytics capability, the greater the performance impact.

The biggest misconception about analytics capability

The capability engine described earlier illustrates how analytics capability should ideally evolve in a continuous, reinforcing cycle. The most common misconception I’ve found among CIOs and senior leaders is that analytics capability evolves in a way that is always forward and linear.

In reality, capability development is far more dynamic. It can advance, plateau or even regress. This pattern was reflected in results from 40 organizational case studies conducted over a two-year period, which revealed that one in three organizations experienced a decline in analytics capability at some point during that time.

These reversals often followed major transformation projects, the departure of key individuals such as executive sponsors or the introduction of new technology platforms that disrupted established processes and required time for users to adapt.

The lesson is clear: analytics capability does not simply evolve. Sustaining progress requires constant attention and a deliberate effort to keep the capability engine running amid the volatility that inevitably accompanies transformation and change.

The road ahead

AI and automation will continue to reshape how organizations use analytics, driving a fundamental shift in how data, technology and talent combine to create business value.

CIOs who treat analytics as a living capability that is cultivated and reinforced over time will lead the organizations that thrive. Like culture and brand reputation, analytics capability strengthens when leaders prioritize it and weakens when it is ignored.

Building lasting analytics capability requires more than people, processes and technology. It demands visible leadership, continuous reinforcement and recognition of progress. When leaders champion analytics capability as the foundation of success, they unlock performance gains while building confidence in evidence-based decisions, trust in data and the organization’s ability to adapt to evolving opportunities and challenges.

People, processes and technology may enable analytics, but capability is what makes it truly powerful and enduring.

This article is published as part of the Foundry Expert Contributor Network.
Want to join?