How to close the analytics leadership gap

In a world obsessed with AI and algorithms, it’s easy to assume that the biggest challenge in analytics is technical. It’s not. It’s human.

How can enterprises nurture a culture that truly uses data-driven decision making? What role do leaders at every level play? And how does targeted education help transform good intentions into business impact?

To unpack this, we sat down with Jack Phillips, CEO of the International Institute for Analytics (IIA), whose thought leadership has guided analytics strategies for over a decade. As an observer, advisor and collaborator on global data initiatives – including the SAS Analytics Leadership Program – Jack offers a unique vantage point on the evolving role of analytics leadership.

From data supply to business demand

Looking back on trends in analytics, Phillips identifies two major shifts over the past decade. The first is technical – think machine learning, big data, and now generative AI. But what truly excites him is the second shift: the organizational transformation.

“We’ve seen enterprises move from a supply-side mindset – focused on data, quality, software – to the demand side,” Phillips explains. “It’s about how to work with stakeholders to change the business using data-driven thinking.”

This pivot means that analytics leadership isn’t just about building technology capabilities. It’s about embedding a data-driven culture that resonates from the boardroom to every function, whether marketing, HR, or supply chain.

Big L and small L: A new definition of leadership

One of Phillips’ favorite frameworks is deceptively simple: Big L vs. small L leadership. In fact, Phillips challenges the very notion of who qualifies as an analytics leader.

“We talk about capital L leaders and small L leaders,” he says. “You don’t have to be a CAO or CDO. Often, it’s the managers and domain experts – the small l leaders – who champion analytics on the ground.”

This democratization is essential. Programs like the SAS Analytics Leadership Program aim to raise the collective data literacy across organizations. Phillips likens it to raising the water level: even a few inches of increased understanding can ripple across an enterprise, unlocking new ways to compete.

Customization is key to making training stick

Even the best training can struggle to translate into real-world outcomes without customization. Phillips sees this repeatedly across industries.

“Learners want relevance. If you’re in healthcare, you expect healthcare use cases. In financial services, it’s about customers and risk. So customizing frameworks to the unique culture and industry vocabulary is critical.”

It’s why the IIA DELTA Plus model – one of several core frameworks used in the SAS program – focuses not just on technical elements, but also on organizational readiness and change management.

The reality check on AI

Of course, today’s hype cycle is dominated by AI. Phillips is cautious, warning against losing sight of foundational analytics work.

“AI is powerful, but it’s a subset of decades of data and analytics efforts. Many enterprises are jumping to hire Chief AI Officers without fixing basic data quality issues,” he says. “This will settle over time. Ultimately, AI will be just another tool in the analytics toolkit.”

The leadership mantra: Bring your data

For Phillips, effective analytics leadership – at any level – rests on a simple principle: back your intuition with evidence.

“I love that old Google saying: ‘Don’t come to the meeting without data.’ Decisions today should be some high percentage data, plus interpretation and intuition. That’s my personal mantra.”

Building a sustainable analytics culture

In partnering with SAS on the Analytics Leadership Program, Phillips sees a shared mission: to cultivate not just skills, but a durable, enterprise-wide mindset.

“It’s about inspiring learners to become ambassadors – ombudsmen for analytics,” he says. “They drive a positive, viral effect throughout the organization. That’s how you embed analytics into the fabric of the modern enterprise.”

Closing thought

As organizations grapple with AI's promises and pitfalls, one truth remains: data and analytics leadership, whether Big L or small L, is more critical than ever. Cultivating that leadership through thoughtful training, tailored frameworks, and a culture of evidence-based decision-making may well be the best investment companies can make in their future.

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