Editorial
In today’s data-driven economy, turning raw information into business value is not just a competitive advantage — it’s a necessity. But achieving this transformation requires more than just the latest tools; it demands a deep organizational commitment to data literacy, clear business alignment and a culture that values informed decision-making at every level.
As organizations grapple with increasing data complexity and volume, the question becomes: how do they effectively harness data to drive business results?
Sean Cook, Aegon CDO, said, “Everybody has this idea there is value in data, and they want to tap into it — but there is a lack of understanding of where to begin and how to get past the hype.” The answer according to Cook, lies in equipping teams with the skills to understand, question and apply data insights — unlocking smarter strategies, faster innovation and stronger performance across today’s enterprise.
Most 'Data-Driven' Organizations Aren’t Really Data-Driven
Despite enthusiasm for being data-driven, many organizations overestimate the extent to which their decisions are guided by data.
A common misconception among business and data leaders is that the implementation of business intelligence (BI) tools automatically results in increased data-informed decision making. Our research at Dresner Advisory Services reveals a disconnect: while 86% of organizations claim they make data-driven decisions all or most of the time, other evidence — both quantitative and anecdotal — shows these claims often overstate the truth. The percentage of organizations stating they make data-driven decisions all the time is 43%, raising important questions about what is getting in the way.
The gap between BI deployment and true data-driven decision-making stems from several persistent challenges.
Metrics may be available, but their interpretation is often undermined by poor data literacy, weak analytical skills or organizational politics. Even where powerful analytics are at hand, decision-makers often override or disregard data in favor of gut instinct, status quo thinking or internal agendas. This aligns with Russell Ackoff’s classic typology in "Creating the Corporate Future," which describes two distinct approaches:
- Reactive decision-makers who resist change and selectively suppress data
- Inactivists who become paralyzed by over-analysis
Both approaches stand in stark contrast to preactivists and interactivists, who actively use data to shape future outcomes and navigate uncertainty with intent.
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How to Build a Culture of Data-Driven Decisions
To close the gap, data leaders must go beyond deploying tools; they must also cultivate a culture where data is trusted, understood and acted upon. This means identifying champions within the business who are willing to rely on data, and creating structured, targeted plans to expand their influence.
Other steps that can help move organizations from claiming to be data-driven to truly being data-driven include implementing:
- Training programs
- Literacy campaigns
- Improved storytelling with data
- Changes to performance incentives
When more people within an organization consistently use data to make decisions, tangible business benefits follow. Decision-making becomes faster, more aligned with strategic goals and more likely to achieve the desired outcomes of BI investments. Our data shows a reinforcing loop at play: organizations that describe their BI initiatives as completely successful also report high levels of data-driven decision making — 66% say they make such decisions all the time, and 26% most of the time.
As data-driven decision-making increases, it drives greater BI success, which in turn supports even broader adoption. This virtuous cycle is what data leaders should aim to create and sustain. According to Barb Wixom, Cynthia Beath and Leslie Owens in "Data is Everybody’s Business," they must do two more things:
- Do something than they otherwise wouldn’t
- Convert value created into money or get money directly from data by selling it
Translating BI Insights Into Strategic Wins
To increase the impact of BI and realize the full promise of data-driven decision making, data leaders must go beyond system deployment and dashboards. They must identify and close the gaps that prevent people from acting on data, even when it is readily available. This requires analyzing how decisions are currently made, determining where data is being ignored or underutilized and creating targeted plans to shift behaviors.
The goal is to reorient decision-making processes to be more fully grounded in data, ultimately leading to better business outcomes.
A productive starting point is to get below the surface of BI initiatives and analyze whether critical decisions are truly data driven. Leaders should ask:
- Are specific metrics in place and clearly tied to the decision?
- Are those metrics influencing decision makers?
- Are business outcomes improving as a result?
These questions help identify where gaps exist — in literacy, training, data recency, organizational culture or even politics — and clarify what is standing in the way of better, more data-informed choices.
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How to Identify and Close Data Literacy and Usage Gaps
Once deficits are identified, data leaders should prioritize the most critical issues, categorizing and ranking them based on their impact on decision quality and data effectiveness. From there, they can build targeted improvement plans. These should include a blend of actions: improving data literacy through education, increasing the visibility and timeliness of data, refining metrics and ensuring executive support to push changes through. In short, leaders must match the right interventions to each decision-making environment.
Importantly, this process must be grounded in fact, not perception. Many organizations assume they are data driven without measuring how often data shapes decisions. By evaluating outcomes and tracing them back to the role of data in the decision process, organizations can replace assumptions with evidence. This not only drives continuous improvement but also builds a strong business case for further investment.
Finally, successful change depends on buy-in — from executives who must support the vision, and from decision makers who must understand how these changes improve their results. Data leaders should engage cross-functional teams within each BI initiative and develop clear, actionable implementation plans. When done well, these plans transform decision processes, drive more consistent data use and create a foundation for greater BI success across the enterprise.
The Case for Making Data Literacy a Business Priority
Data Literacy is "the ability to read and communicate the meaning of data, while also recognizing the value of information to policy development and decisions making. Strategies that build a more data literate workforce will strengthen a company’s ability to manage and use data effectively."
- Randy Bean in "Fail Fast, Learn Faster"
It is no surprise that data literacy has emerged as a critical differentiator in the success or failure of business intelligence initiatives.
Yet many data leaders are not acting with the urgency required to meet the challenge. Without meaningful progress in data literacy, organizations risk seeing their BI investments questioned, underutilized or abandoned entirely. Worse still, companies with stagnant literacy levels may find themselves outpaced by more capable, data-savvy competitors. The warning signs are clear: slow progress, limited impact and mounting pressure to demonstrate tangible returns on analytics spending.
Recent findings reveal that only about one-third of organizations report high (22%) or extremely high (10%) levels of data literacy. The majority (52%) place themselves in the moderate range — an admission that leaves significant room for improvement.
The connection between data literacy and BI success is well established: organizations with higher literacy levels consistently report greater success with their BI initiatives. These organizations not only use data more effectively, but also embed it more deeply into decision-making processes, performance tracking and strategic planning. Literacy acts as the connective tissue that turns data into decisions, and decisions into results. With this in mind, data leaders must revisit, re-energize and retool their literacy programs — treating them not as optional training modules, but as business-critical infrastructure.
The rise of artificial intelligence — especially generative AI and agentic AI — only heightens the urgency. While AI tools promise to automate and accelerate insight generation, they do not replace the need for human understanding of data. On the contrary, AI expands the playing field, flooding organizations with synthesized insights, some of which may be misleading or incorrect. Without high levels of data literacy, decision makers may accept flawed outputs at face value, unable to question, contextualize or verify the data behind the chatbot. In this way, AI demands more, not less, literacy — raising the bar for what it means to be data fluent in today’s enterprise.
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Now is the time for data leaders to take bold action. A renewed focus on data literacy — grounded in executive support, embedded in everyday workflows and responsive to new AI demands — can protect and amplify BI investments. More importantly, it can empower the organization to make smarter, faster and more effective decisions in a rapidly evolving business landscape.
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How to Scale Data Literacy Across the Enterprise
To unlock the full value of business intelligence and analytics investments, organizations must approach data literacy as a strategic capability — one that needs continuous attention, innovation and alignment with evolving business priorities.
Assess Existing Data Literacy Programs
The first step is to conduct a comprehensive inventory of existing data literacy programs, assessing both their reach across the organization and their effectiveness in equipping people to make better decisions. This audit should not only highlight which departments have benefited from past literacy efforts, but also reveal where awareness, adoption or comprehension remains low.
Identify Key Business Scenarios
Next, organizations should zero in on business scenarios that are high in value, complexity or risk — especially those where poor data interpretation can result in costly missteps. These areas should be prioritized for targeted improvements in data literacy. Instead of treating literacy programs as static or one-size-fits-all, data leaders should shift their mindset from maintenance to acceleration. That means refreshing outdated materials, re-energizing participation and experimenting with new formats such as role-based training, simulations or AI-guided learning tools that connect literacy gains directly to business impact.
Prioritize Executive Buy-In
Executive sponsorship is essential for long-term success. Business leaders must understand that accelerating data literacy isn’t just about individual upskilling (though that's certainly still important) — it’s a necessity for keeping pace with the rising tide of data volume, complexity and change. Their buy-in is critical to embed literacy into performance objectives, resource planning and culture. With executive support secured, a two-pronged strategy can be put in place: one that improves specific data literacy programs tied to critical BI initiatives, and another that uplifts general data literacy across the broader organization.
Pinpoint Data Literacy Effort Gaps
To ensure alignment with business needs, data leaders should identify where existing data literacy efforts lag behind the growing complexity of BI tools, data sources and analytical use cases. These gaps often correlate with struggling BI initiatives. Prioritizing these mismatches enables smarter investment and more immediate impact. Targeted interventions can then be piloted in a few high-value BI projects, demonstrating results and building momentum for broader rollout.
Track Vital Metrics Over Time
Finally, no literacy program can thrive without clear metrics and regular performance reviews. Organizations should define and track specific success measures, such as:
- Improved decision accuracy
- Higher BI adoption
- Fewer rework cycles
Exposing these metrics widely helps link data literacy improvements directly to BI success and business outcomes. Embedding periodic review cycles ensures programs stay relevant, uncovers new opportunities and continues driving business growth at scale.
The Future Belongs to Data-Confident Organizations
Real business value from data isn’t achieved by tools alone — it’s realized when the entire organization commits to using data with confidence, clarity and consistency.
Data leaders must foster a culture that views data not just as an asset, but as a vital decision-making partner. This requires elevating data literacy from a training initiative to a strategic imperative, closely linked to performance, innovation and agility. By closing the gap between BI implementation and real decision impact, and by embedding data fluency into the DNA of the enterprise, organizations can finally turn the promise of data into sustained competitive advantage.
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