Leading in Analytics: 12 Lessons for Building and Leading High-Impact Analytics Teams

Sadly, despite the incredible transformational power of artificial intelligence (AI), more than four out of five AI and analytics projects fail to deliver the value their sponsors expect [1]. This isn’t just an individual or organizational challenge – it’s a systemic problem the entire analytics profession can and must address.

Fortunately, there’s a growing body of knowledge about why these projects fail and how to lead them to success. INFORMS has documented much of this in its “Analytics Body of Knowledge,” particularly in Chapter 2, in which Karl Kempf identified these root causes as the Five Manageable Tasks [2] – necessary, although not always sufficient, for success. These are: (1) choosing the right problem, (2) building the right team, (3) having the right data, (4) selecting the right tools and (5) executing effectively.

Inspired by Kempf’s framework, Cazier collected key best practices from accomplished analytics leaders, which are cataloged in his book “Leading in Analytics” [3]. Among these leaders was Hina Arora, who shared field-tested insights from her experience leading analytics teams in industry – insights she expanded on in a presentation at the 2025 INFORMS Analytics+ Conference [4]. The lessons that follow blend these real-world insights with research-backed practices.

Lesson 1: Lead with a Clear Mission
Before analytics teams can solve big problems, they need to know why they exist.

Mission is not just a slogan; it’s the anchor for culture, decision-making and talent retention. Mission guides everything: technical work, recruitment, engagement and leadership.

Research reinforces this: Mission-driven teams enjoy higher engagement, stronger loyalty and better strategic alignment. A compelling mission helps prioritize efforts, resist scope creep and sustain energy through tough projects.

Lesson 2: Anchor Behavior in Shared Values
If mission defines why you exist, values define how you operate.

Successful teams embed values like transparency, collaboration, experimentation and innovation into their daily practices. Field-tested approaches show that values influence not just internal behavior but also external trust.

Organizations that consistently live their values not only attract top talent but also foster environments in which collaboration, creativity and resilience thrive. Values help teams navigate uncertainty, adapt to change and sustain performance under pressure.

Lesson 3: Inspire with a Compelling Vision
With mission and values established, teams also need a vision that guides effort and prioritization.

Although mission defines lasting purpose, vision narrows the focus to where the team is headed right now. A compelling vision doesn’t just organize work – it builds momentum and attracts internal and external champions.

Research confirms that vision must be tied to real outcomes and communicated authentically. Skilled analytics translators help carry that vision across organizational boundaries, ensuring alignment and enthusiasm.

Lesson 4: Build a Strategy That Drives Action
Vision without strategy is just aspiration. Strategy makes it real.

Clear, actionable strategies require difficult choices. As Collis and Rukstad highlight [5], effective strategies demand clear priorities, not long lists of initiatives. High-performing analytics leaders visibly map strategies across intake, delivery and refinement – ensuring coherent focus.

Without disciplined strategy, analytics efforts risk fragmentation and drift. Strategy must be a living guide, not a static plan.

Lesson 5: Operationalize Your Vision with a Business Model
Analytics teams that act like startups – with a clear business model – build stronger trust and greater resilience [6].

Treating analytics as a client service helps align delivery with stakeholder expectations. Analytics teams that clearly define how they create, deliver and capture value avoid priority confusion and show tangible value early.

Research shows that clarifying who you serve and how you succeed protects focus, strengthens credibility and secures ongoing support.

Lesson 6: Choose the Right Team Structure
Structure is not just an org chart – it’s an enabler.

Hybrid structures combine centralized governance with domain-embedded responsiveness. Early centralization builds trust and quality; mature organizations can thoughtfully decentralize to empower distributed innovation.

At the same time, organizations must consider how much analytics capability to build internally. If all analytics are outsourced with no in-house expertise or ownership, analytics is likely to remain a tactical tool. Building internal capability fosters deeper organizational integration, institutional knowledge and long-term impact.

Structure must evolve with team maturity, relationships and cultural fit. Proximity to decision-makers – being near power – enhances strategic influence and resource access.

Lesson 7: Hire and Cultivate the Right Team Composition
Skills matter. Mindset matters more.

Beyond technical ability, top hires bring mission commitment, value alignment, learning agility, collaborative spirit and the ability to navigate complex stakeholder environments.

Effective hiring focuses on building ecosystems in which talented people thrive. Incentives, culture and leadership development are just as important as recruiting. Field-tested practices also emphasize the importance of aligning incentives and recognition systems with team values and mission – ensuring that collaboration, innovation and resilience are rewarded alongside technical achievement. Teams that hire carefully and cultivate supportive ecosystems tend to outlast and outperform those that focus narrowly on technical skills alone.

Lesson 8: Set the Team Up for Success from Day 1
Great teams don’t emerge by accident – they’re designed intentionally.

Clear expectations – roles, responsibilities, deliverables – accelerate trust and momentum. Early wins matter, even small ones. They build credibility, reduce skepticism and establish a track record of impact.

Research and field experience both show that psychological safety and early results set the foundation for sustained success.

Lesson 9: Maximize Organizational Synergy
Analytics must be a force multiplier, not a silo.

Successful teams integrate analytics projects visibly into enterprise priorities. When analytics becomes part of decision-making rhythms, it shifts from being a reporting function to a strategic enabler.

Leaders who visibly align analytics with mission-critical initiatives secure stronger sponsorship, better resource support and longer-term relevance.

Lesson 10: Empower Effective Engagement
Analytics leadership is as much about enabling others as delivering insights.

Cross-functional co-education helps partners frame better questions, recognize better opportunities and support analytics success.

Raising analytics literacy builds internal advocates who champion, protect and expand analytics functions – making literacy a form of political capital as well as technical skill.

Lesson 11: Lead Change as a Core Leadership Skill
Analytics transforms workflows, relationships and expectations, which makes change leadership a core competency.

Effective change leaders don’t just manage resistance – they proactively engineer early wins, visible pilots and small victories that build momentum. Kotter’s 8-Step Change Model [7] and field experience alike show that early validation creates momentum and helps cement lasting transformation.

Lesson 12: Build a Culture of Joy and Fun
Analytics is serious work – but serious work done well should be joyful.

Camaraderie, creativity and joy fuel resilience and innovation. Data storytelling days, hackathons and shared celebrations help transform analytics teams into collaborative, purpose-driven communities.

Teams that intentionally create joyful, trusting environments are better equipped to navigate uncertainty, solve complex problems and retain their best people.

Final Reflection

The lessons shared here aren’t theoretical. They are field-tested, research-supported and refined through real-world leadership. As analytics leaders, we are called not just to manage and analyze data but to build cultures in which people thrive, contribute meaningfully and deliver lasting value.

References

1. Ransbotham, S., Khodabandeh, S., Kiron, D., Candelon, F., Chu, M. & LaFountain, B., 2020, “Expanding AI’s impact with organizational learning,” MIT Sloan Management Review, Vol. 62, No. 1, pp. 1-11.
2. Kempf, K. G., 2018, “The five manageable tasks,” INFORMS Analytics Body of Knowledge, Chapter 2, pp. 32-48, Hoboken, NJ: Wiley.
3. Cazier, J. A., 2023, “Leading in Analytics: The Seven Critical Tasks for Executives to Master in the Age of Big Data,” New York: Wiley Press.
4. Arora, H., 2025, “Building, Mentoring and Leading Analytics Teams: 12 Lessons from the Trenches,” Presentation, 2025 INFORMS Analytics+ Conference, Indianapolis.
5. Collis, D. J. & Rukstad, M. G., 2008, “Can you say what your strategy is?,” Harvard Business Review, Vol. 86, No. 4, pp. 82-90.
6. Osterwalder, A. & Pigneur, Y., 2010, “Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers,” Hoboken, NJ: John Wiley & Sons.
7. Kotter, J. P., 1995, “Leading change: Why transformation efforts fail,” Harvard Business Review, Vol. 73, No. 2, pp. 59-67.