Key Takeaways
- Today’s CFOs are expected to play a central role in shaping strategy — using data to advise the CEO, guide investment decisions, manage risk, and drive long‑term growth.
- Organizations that successfully embed analytics into finance decision-making experience benefits including improved accuracy, greater efficiency, and deeper insight.
- Data governance ensures information is accurate, consistent, secure, and usable across the organization.
Data is now central to how finance leaders shape strategy. No longer viewed solely as a financial gatekeeper, today’s CFO is expected to be a strategic advisor — translating data into guidance that drives growth, manages risk, and strengthens long-term enterprise value.
According to research from the Financial Executives Research Foundation (FERF), 85% of CFOs say data analytics is crucial for strategic decision-making. Yet many organizations still struggle to translate growing volumes of financial and operational data into insight leaders can confidently act on. In fact, over 20% of leaders in a recent Eide Bailly survey on data and AI said improving data quality, structure, and accessibility would have the greatest impact on AI readiness.
Top CFOs use data to shape strategy by connecting financial and operational information, identifying the metrics tied to enterprise value, forecasting different business scenarios, and applying clear data governance. For middle-market organizations, the priority is not collecting more data. It is creating a trusted view of performance that supports faster decisions about growth, risk, capital, and operations.
Why Data Analytics Has Become a CFO Imperative
As expectations expand, CFOs are being asked to answer more complex questions faster and with greater confidence:
- Where is the business creating — and losing — value?
- How resilient are our margins under different scenarios?
- Which investments will deliver the strongest return?
- What risks could derail our strategy?
Data analytics enables finance leaders to move beyond hindsight reporting and toward forward-looking insight that informs strategy instead of just explaining results. At its core, data analytics is the process of examining raw data to uncover patterns, trends, and insights that inform decision-making. For finance teams, this capability has become foundational to fulfilling the CFO’s strategic role.
Where CFOs Are Applying Data Analytics Today
Within the finance function, data analytics supports a wide range of high-impact use cases that shape decision-making across the business:
- Financial reporting. Automating data collection and consolidation improves accuracy, reduces manual effort, and shortens close and reporting cycles — freeing teams to focus on analysis rather than reconciliation.
- Performance management. Analytics enables CFOs to track key performance indicators (KPIs), identify areas of strength and weakness, and measure progress against strategic objectives in near real time.
- Budgeting and forecasting. Granular, data-driven forecasts help organizations allocate resources more effectively and adapt quickly as conditions change.
- Risk management. By identifying and quantifying financial risks earlier, CFOs can develop mitigation strategies and strengthen ongoing risk monitoring.
- Investment analysis. Data supports more disciplined capital allocation by improving the evaluation of investment opportunities and expected returns.
The common thread: analytics helps CFOs move from reactive reporting to proactive, insight-driven leadership. Learn how to improve visibility with our CFO Tech Planning Toolkit.
The Payoff of Data-Driven Decision-Making
Organizations that successfully embed analytics into finance decision-making gain clearer visibility, stronger control, and better strategic outcomes:
- Improved accuracy. Data-backed insight replaces intuition, leading to better forecasts, fewer errors, and more confident decisions.
- Greater efficiency. Automation reduces manual work and allows finance teams to focus on higher-value, strategic activities.
- Deeper insight. Analytics reveal patterns and trends that are often hidden in disconnected systems, helping leaders better understand performance and identify new opportunities.
Case in point: One manufacturing organization came to us with an abundance of operational data, but limited confidence in what it was telling them.
We helped them build a unified Manufacturing Analytics 360 environment that connected their disparate systems into one centralized data warehouse. Manual reporting that once took hours each week was replaced by automated information flow, allowing leaders to focus on high-value decisions based on real-time insights they could trust.
For CFOs, these benefits translate into stronger influence, greater credibility, and a more central role in strategic decision-making.
How CFOs Can Use Data Analytics More Effectively
While the potential is clear, execution is where many organizations stall. Top-performing CFOs focus on a few critical foundations:
What Metrics Should Mid-Market CFOs Use to Shape Strategy?
Finance leaders are surrounded by data, but only a small portion of it meaningfully supports strategic decisions. Focusing on a defined set of relevant metrics helps avoid information overload and keeps analytics aligned with business goals.
The first step is understanding which data sources and metrics truly support strategic decisions.
Common financial KPIs CFOs rely on include:
| Strategic question | Supporting metric | What the CFO is looking for |
|---|---|---|
| Are we growing profitably? | Revenue growth and operating margin | Whether growth is improving or diluting profitability |
| Can we fund the strategy? | Cash flow and days cash on hand | Capacity to invest without creating liquidity risk |
| Is working capital improving? | DSO and cash-conversion indicators | Whether growth is absorbing too much cash |
| Where are costs changing? | Labor, supply, and operating expenses | Margin pressure and operational inefficiency |
| Are investments producing value? | Return and performance measures | Whether capital is supporting strategic priorities |
What Data Problems Create the Most Risk for Growing Companies?
Analytics is only as reliable as the data behind it. Data governance ensures information is accurate, consistent, secure, and trusted, creating a reliable foundation for analytics and future innovation.
An effective data governance framework typically includes:
- Data ownership: Clear accountability for the accuracy and integrity of key data elements.
- Data standards: Consistent definitions, formats, and rules across systems.
- Data quality controls: Processes to monitor, validate, and correct data.
- Data security: Safeguards to protect sensitive financial information.
Technology plays a critical role here — but only when paired with clear ownership and disciplined processes. Data quality tools can identify errors and inconsistencies, while data integration platforms help consolidate information from multiple systems into a unified view — creating a more reliable foundation for analytics.
How Should CFOs Prepare Their Data for AI?
Modern analytics requires tools that align with decision making needs, not just reporting requirements. CFOs are increasingly investing in technologies that make insight more accessible and actionable, including:
- Dashboards and reporting tools that surface real-time performance
- Business intelligence (BI) platforms that enable deeper analysis and visualization
- AI-enabled analytics that support forecasting, scenario modeling, and anomaly detection (when data foundations are ready to support reliable outcomes)
The goal isn’t technology for its own sake — it’s enabling faster, more informed decisions across finance and the broader business.
We’ve assembled resources to help CFOs assess their technology landscape, strengthen data foundations, and plan the next phase of their analytics and AI journey. Get the resources.
Turning Data into Strategic Advantage
In a business environment defined by uncertainty and complexity, the most effective CFOs don’t just report on the business — they shape its future through insight-driven decisions. By focusing on the right data, establishing strong governance, and building scalable analytics capabilities, finance leaders create the foundation needed to adopt advanced tools — including AI — with confidence.
While many CFOs see the potential of AI, success depends on whether the underlying data, governance, and decision processes are ready to support it. Eide Bailly brings finance, operations, data, and technology perspectives together to help middle-market organizations strengthen reporting, improve data governance, and turn analytics into better business decisions.
Improve decision-making through stronger data, reporting, and planning processes. Download the CFO Tech Planning Toolkit.
Frequently Asked Questions
How can mid-market CFOs make data-driven decisions?
Start by connecting the data you already have. Most mid-market organizations don’t lack data — they lack integration. When financial, operational, and technology data sits in separate systems, leaders make decisions with an incomplete view.
To become more data-driven, CFOs should establish clear data ownership, create a single source of truth, and focus analytics on the decisions that matter most — such as growth, risk, cash flow, and capital allocation. Strong governance and phased improvements to reporting, forecasting, and scenario modeling help turn financial data into a strategic advantage.
How is the CFO role changing today?
Today’s CFOs are expected to go beyond financial reporting and compliance. They play a central role in shaping strategy — using data to advise the CEO, guide investment decisions, manage risk, and drive long‑term growth.
Why isn’t traditional financial reporting enough anymore?
Standard reports provide a historical view of performance, but they don’t explain why results happened or what may happen next. Strategic CFOs rely on analytics to uncover performance drivers, identify risks earlier, and support forward‑looking decisions.
What financial metrics matter most for strategic decision‑making?
While metrics vary by organization, CFOs often focus on indicators that connect financial performance to operational outcomes — such as gross revenue, operating margin, and EBITDA— rather than tracking every available data point.
What role does data governance play in analytics success?
Strong data governance ensures analytics are built on accurate, consistent, and secure information. Without clear ownership, standards, and quality controls, even advanced analytics tools can produce unreliable or misleading insights.
Do CFOs need advanced AI to become data‑driven?
Not necessarily. Many organizations begin with dashboards, reporting, and business intelligence tools. AI can enhance forecasting and scenario analysis over time, but success starts with clean data, clear objectives, and analytics aligned to business priorities.
Where should CFOs start if their data feels fragmented or overwhelming?
Start by identifying the decisions that matter most to the business, then focus on the data and metrics that support those decisions. From there, strengthening data quality, governance, and integration creates a foundation that analytics — and AI — can build on.
Get insight at the speed of now with accurate, reliable data that flows seamlessly through your organization.
Who We Are
Eide Bailly is a nationally ranked accounting and advisory firm bringing financial, operational, and technical solutions to middle market and high-growth organizations.
