Key Findings Report from our Close to Reporting Faster Webinar.

Despite modern finance systems and analytics tools, many mid-market organizations still struggle to move quickly from month-end close to investor-ready reporting.

Insights from EBM’s Close to Reporting Faster webinar and the 2026 Finance Agility Benchmark Survey highlight a consistent pattern: while teams may trust their numbers, fragmented data and manual consolidation continue to slow the path from close to insight.

This article distills the key lessons shared by EBM and Blue Ops experts — revealing what’s really holding finance teams back, and how leading organizations are cutting reporting timelines by up to 80% through connected data and modern analytics.

Watch the on-demand webinar: From Close to Reporting, Faster.

1. The Structural Inefficiencies in Close Processes

Data from more than 230 surveyed finance leaders highlights a persistent structural issue across mid-market finance teams.

Over 50% of respondents report that their month-end close takes 6–15 business days, before reporting even begins. A further segment exceeds 16 days, signaling foundational gaps in process design, system integration, and data availability.

The challenge compounds after close. Nearly 90% of organizations require more than three additional days to produce finalized reporting packages for leadership and stakeholders. As discussed during the webinar, this level of latency is increasingly untenable given today’s automation and integration capabilities.

Root Technical Drivers

• Siloed ERP environments, especially within PE-backed platforms acquiring multiple add-ons
• Fragmented chart-of-accounts structures and inconsistent master data
• Manual reconciliation workflows that cannot scale
• Undefined or outdated data governance models

These structural issues result in extended cycle times, heavy reliance on analyst intervention, and inconsistent reporting outputs.

2. Why Excel-Centric Reporting Breaks at Scale

The survey and webinar both highlighted Excel as one of the most widely used reporting tools, yet also one of the biggest bottlenecks. Manual Excel models rely on point-in-time exports, offline manipulation, and individual tribal knowledge to function.

Bennett Celichowski, Finance Director at Compass, emphasized that while Excel provides control, it also anchors teams to manual processes and delays the reporting cycle.

Adam Beck, VP at Blue Ops, expanded in this by framing Excel-based reporting as a data trust issue. Sponsors, investors, and boards increasingly expect automated, repeatable, and traceable reporting pipelines. Excel-based workflows lacks:

• Embedded data validation and business rules
• Version control
• Auditability
• Cross-system harmonization
• Scalable refresh cycles

Manual assembly increases variance and error — and in capital-constrained or investor-led environments, tolerance for avoidable risk is low.

3. The Strategic Cost of Manual Reporting

The most overlooked consequence of slow close-to-reporting cycles is the erosion of strategic finance capacity.

When finance teams spend 10–20 days each month closing, reconciling, cleaning data, and assembling backward-looking reports, they lose the bandwidth to:

• Perform forward-looking scenario modeling
• Support pricing, margin, and working-capital optimization
• Partner with operators in real-time
• Drive proactive insights instead of reactive explanations

Finance can become trapped in “reporting the weather” instead of influencing the forecast.

4. Connected Data Is the Primary Enabler of Faster Reporting

Across more than hundreds of companies supported by EBM Software, a common pattern emerges: the teams that reduce close-to-report cycle times the fastest have a centralized, governed finance data foundation paired with automated BI delivery.

Key architectural components include:

1. Unified data model
Standardized chart of accounts, entity structures, customer hierarchies, SKU attributes, and time dimensions allow harmonized reporting across ERPs and acquisitions.

2. Automated data pipelines
ELT workflows continuously ingest, validate, normalize, and transform ERP, CRM, POS, e-commerce, and operational data.

3. Finance semantic layer
Rules-based definitions for revenue, margin, adjustments, allocations, and KPIs ensure consistency across departments and reporting consumers.

4. Power BI as the Visualization Engine
Power BI serves as the governed reporting layer, enabling:

• SLA-driven refresh cycles
• Dynamic drill-downs
• Traceability from dashboard to transaction
• Role-based security for management and investor audiences

This architecture shifts reporting from “manually assembled spreadsheets” to production-grade analytics infrastructure.

5. Modern BI Reduces Reporting from Days to Hours

When BI is powered by validated, governed, and harmonized data, teams can move from close to reporting within hours rather than days.

This acceleration is driven by:

• Automated refresh schedules
• Pre-built reporting templates
• Consistent financial definitions
• Rule-based validation checks
• Drillable dashboards replacing static decks

Transformation is not theoretical. Organizations adopting this approach routinely achieve 50–80% reductions in reporting cycle times by eliminating manual assembly and rework.

6. Investor Expectations Continue to Rise

Approximately 60% of survey respondents represent PE- or VC-backed organizations, where expectations for reporting rigor and speed are significantly higher.

These environments demand:

• Faster lender reporting
• Consistent analytics across platforms
• Clear visibility into revenue and margin drivers
• Post-acquisition integration speed
• Clean data to support valuation, QofE, and growth strategy

In this context, automated BI is no longer a differentiator; it is the minimum standard for investor readiness.

Conclusion: The Path to Finance Agility Requires Systemic Change

The data is clear: slow reporting cycles are not merely a workflow problem; they are a data architecture and process-maturity problem.

To operate strategically, finance organizations must move beyond incremental fixes and transition from manual, Excel-driven reporting to a connected, governed, and automated finance intelligence ecosystem.

Teams that adopt this model unlock:

• Faster reporting (up to 80% reduction)
• Higher data confidence
• Better decision agility
• Improved investor and board communication
• More time for forward-looking analysis

Finance leaders no longer have to choose between speed and accuracy.
With connected data infrastructure, both become possible.

Watch the on-demand webinar: From Close to Reporting, Faster.