Unlocking the Power of Data in SME Finance Processes
- Werner Harahap
- Nov 23
- 13 min read
Finance teams today face a new reality. Across industries, organizations—whether for-profit or nonprofit—now expect faster insights, more precise forecasts, and stronger decision support than ever before.
Yet, as we observe in finance functions of all sizes, many remain stuck in reactive mode. Teams spend their days validating spreadsheets, reconciling numbers, and reporting on what has already happened. Consequently, leaders want to plan proactively, but the systems, processes, and data foundations supporting finance aren’t robust enough to sustain forward-looking planning.
This article walks through how small and medium-sized enterprises (SMEs) can begin closing that gap by unlocking the full power of their financial data. Along the way, we’ll examine why data-driven finance matters now more than ever, the risks organizations face when they fail to unlock their data, and how a structured approach can elevate finance from a back-office reporter to a true strategic engine.
We’ll also break down the practical steps any SME can take to transform raw information into actionable insight.
Guiding this transformation is the Phoenix Rising Consulting Group D.A.T.A. Framework—a four-stage roadmap that helps finance teams move from labour-heavy reporting to proactive, insight-driven decision support.
Let’s dive in.
Why Data-Driven Finance Matters Now More Than Ever for SMEs
For both for-profit and nonprofit SMEs, data-driven finance has shifted from a competitive advantage to a basic requirement for survival. The operating environment has changed dramatically in recent years. Economic uncertainty, shifting customer or donor behaviour, inflationary pressures, and tighter margins all signal a clear reality: slow, reactive planning is no longer an option. Leaders need clarity—and they need it quickly.
This urgency shows up in how leaders think about data. Salesforce’s 2023 report finds that 80% of business leaders now consider data critical to decision-making, yet many still struggle to translate that belief into everyday practice. Put another way, leaders understand the value of data, but their systems and processes are not built to support data-driven decisions.
It’s no surprise, then, that FTI Consulting’s 2025 Global CFO Survey reports that 85% of CFOs now rank forecasting accuracy as a top priority, with 57% planning to improve it in 2025. After all, reliable insight has become mission-critical: it reinforces budgeting, grant planning, capital allocation, and overall organizational resilience. And when that insight is missing, the consequences are immediate:
Forecasts devolve into guesswork.
Decisions become short-term, reactive, and unnecessarily risky.
Even so, many SMEs struggle to use the data they already have—not because it’s unavailable, but because finance teams don’t have the bandwidth to analyse it. Much of their time is swallowed up by manual, repetitive work that leaves little room for strategic thinking. PwC’s 2024 Finance Effectiveness Benchmarking Study highlights this constraint, reporting that 28% of finance time is still spent on tasks that could be automated.
A closer look reveals where that time goes. PwC reports that 54% of that time is spent on management reporting, 45% on customer billing, and 40% on general accounting. These processes are essential, but they keep finance anchored in the past instead of preparing teams for the future. When teams spend most of their days moving data rather than interpreting it, proactive planning never gets off the ground.
Compounding the challenge is the sheer explosion of data itself. Business & Industry Canada’s 2024 Data-Driven Strategies report shows that 90% of global data was created in just the last two years—an increase so rapid it strains even well-resourced teams. This surge in volume also explains why Salesforce reports that 41% of leaders find data too complex or inaccessible and 30% feel overwhelmed by its scale.
For SMEs that typically lack the data engineering or BI capacity that larger organizations rely on, this complexity becomes an even bigger barrier to turning information into actionable insight. Without a structured way to organize, integrate, and interpret data, finance teams can quickly find themselves overwhelmed—drowning in information but starved of insight.
And this is precisely why unlocking data becomes the turning point. When SMEs unlock their data, everything changes:
They strengthen stewardship.
They elevate planning.
They spot risks earlier.
And most importantly, they make decisions grounded in insight, not intuition.
The Risks of Not Unlocking Data for SMEs
Recognizing why data-driven finance matters is only half the picture. To fully understand the stakes, SMEs must also consider what happens when financial and operational data remain locked, fragmented, or underused.
The consequences are far-reaching. When data isn’t accessible or actionable, both for-profit and nonprofit SMEs face risks that undermine performance, weaken resilience, and ultimately hinder mission delivery.
To begin with, the competitive cost is substantial. Oracle’s Money and Machines: 2021 Global Study reports that 44% of organizations risk falling behind their competitors when they cannot access, interpret, or leverage their data. For SMEs—which operate with tighter margins and shorter decision cycles—this lack of agility can quickly turn into missed opportunities, slower growth, or declining relevance.
The impact extends beyond competitiveness; it affects people just as deeply. Oracle’s findings show that 36% of employees experience heightened stress when finance processes depend on manual work, fragmented systems, or unclear information flows. That strain rarely stays isolated. It spreads across departments, lowering morale, increasing turnover risk, and pulling teams away from the high-value work that drives outcomes.
Data gaps also erode accuracy and efficiency. According to the same study, 26% of organizations experience inaccurate financial reporting—a risk that can create compliance issues, weaken investor or donor confidence, and disrupt day-to-day operations. The study also notes that 35% of organizations see reduced productivity due to rework, bottlenecks, and slow decisions caused by incomplete or inaccessible data. Over time, these issues compound, creating a cycle of delays and frustration that becomes increasingly difficult to break.
Taken together, these risks show that failing to unlock data doesn’t merely limit insight—it erodes competitiveness, strains teams, and weakens both financial and operational stability. Ultimately, SMEs that can’t harness their data fall behind, while those that do gain the clarity and agility needed to navigate uncertainty with confidence.
The Phoenix Rising Consulting Group D.A.T.A. Framework
As the demand for faster insights and sharper forecasting grows—and as the cost of leaving data untapped increases—the path forward for SMEs becomes unmistakable. They need a structured, practical way to modernize outdated processes and elevate data into a bona fide strategic asset.
This is why we developed the D.A.T.A. Framework. It guides SMEs through four interconnected stages designed to transform how finance operates and delivers insight:
D — Diagnose data issues, process bottlenecks, and decision-making blind spots that limit finance’s strategic potential.
A — Automate the data lifecycle to eliminate friction, improve data integrity, and free finance teams from repetitive, low-value work.
T — Transform how organizations forecast, plan, and manage risk by introducing predictive analytics and forward-looking intelligence.
A — Amplify insights across departments so decision-makers at every level can operate with clarity, alignment, and real-time visibility.
Together, these stages create a clear, repeatable roadmap for shifting finance from information gathering to true strategic decision support. Now, let’s look at how each stage works in practice—and how it unlocks the full value of financial data.
Stage 1 — Diagnose Finance Processes
Diagnosing finance processes is the first—and arguably the most critical—step in unlocking the power of data for both for-profit and nonprofit SMEs. Before automation, analytics, or forecasting improvements can make a meaningful impact, leaders must understand why their finance function struggles to produce timely, accurate, and forward-looking insights. This stage brings those root causes into focus across three core dimensions:
Data gaps
Manual bottlenecks
Decision-making blind spots
To begin with, data gaps are often the most pervasive issue SMEs face. Incomplete or siloed information erodes trust and makes reliable analysis nearly impossible. The 2025 Association for Financial Professionals’ (AFP) FP&A Benchmarking Survey confirms this, noting that unreliable or inaccessible data limit more than 60% of FP&A teams. PwC’s 2015 Making Strategic Decisions study reinforces the point: 96% of executives have dismissed data they didn’t understand—proof that when data quality falters, trust collapses, and decision-making suffers.
Once data issues come into focus, a second challenge becomes clear: manual bottlenecks that drain time, attention, and strategic capacity. Despite advances in modern finance tools, AFP data shows that 96% of teams still rely on spreadsheets for planning and 93% use them for weekly reporting. This dependence introduces version-control issues, slows consolidation cycles, and prevents leaders from accessing the real-time insights required for timely, confident decision-making.
The Diagnose stage also uncovers decision-making blind spots—often the most hidden yet most consequential barrier. PwC’s 2015 research finds that only 38% of executives rely primarily on data analytics for major decisions, meaning many SMEs still default to intuition over evidence. Workday’s 2018 Global Finance Leader Survey adds further context: only 35% of finance teams fully leverage the data they already have.
Collectively, these findings reveal that the challenge isn’t only about accessing data; it’s also about using it effectively. When decisions aren’t grounded in insight, bias creeps in, warning signs go unnoticed, and avoidable surprises become far more common.
At Phoenix Rising Consulting Group, we surface these gaps, bottlenecks, and blind spots through structured diagnostics, workflow analysis, process mapping, stakeholder interviews, and system audits.
By the end of the Diagnose stage, SMEs gain a clear, evidence-based understanding of where data breaks down and where the most significant opportunities for improvement lie, creating the foundation for every stage that follows.
Stage 2 — Automate Finance Processes
Once data gaps and bottlenecks are identified, the next step is to remove the manual burdens that keep finance stuck in reactive mode. That’s why, in Stage 2, we shift from diagnosis to action—using technology to replace repetitive, error-prone tasks with clean, reliable, and scalable processes. By reducing spreadsheet-heavy routines, automation restores capacity and builds the data integrity required for meaningful analysis.
To appreciate the importance of automation, it helps to look closely at where time is actually being lost. PwC’s 2024 study shows that many of the most routine activities—management reporting, customer billing, general accounting, reconciliations, and the financial close—remain heavily manual. Because these tasks absorb so much finance capacity, automating them accelerates cycle times, standardizes data, enhances auditability, and significantly reduces human error.
Naturally, removing manual bottlenecks requires more than isolated fixes; it demands modernization of the systems finance relies on every day. FTI Consulting’s 2025 survey makes that clear: 86% of CFOs are prioritizing automation and system upgrades, and 79% plan to strengthen FP&A tools to support real-time data access, scenario modelling, and predictive planning. These priorities underscore a simple truth: finance transformation depends on reliable, real-time data. That’s why we help SMEs select, configure, and integrate the right ERP, EPM, and BI solutions to ensure smooth, end-to-end data flow.
As automation takes hold and modern systems replace fragmented workflows, another critical benefit emerges: deeper data integration. With cleaner, more consistent information flowing across connected systems, finance can finally combine financial, operational, and external data in ways that unlock forward-looking insight. Workday’s 2018 research shows that organizations blending these datasets produce far more accurate and responsive forecasts. And in practice, this integration delivers value differently across SME sectors:
For for-profit SMEs, it strengthens visibility into customer demand patterns, sales cycles, and operational performance.
For nonprofit SMEs, it clarifies donor behaviour, program costs, and grant cycles.
In effect, this level of integration elevates automation from a simple efficiency upgrade to a genuine strategic enabler.
Ultimately, Stage 2 moves finance beyond manual reporting and into a world of high-quality, always-on insight, laying the data foundation required for predictive, strategic decision-making.
Stage 3 — Transform Finance Processes
The Transform stage is where finance shifts from explaining the past to anticipating the future. Once automation delivers cleaner, faster, and more reliable data, SMEs can start building the forward-looking capabilities that position finance as a strategic partner rather than a historical reporter. In essence, this stage moves organizations from backward-looking reporting to predictive decision support, enabling leaders to anticipate change rather than react to it.
Predictive analytics sits at the centre of this shift because it fundamentally expands finance’s line of sight. Aro’s 2024 Predictive Analytics in Financial Management research shows that organizations using predictive techniques see forecasting accuracy improve by 30%—a step change that dramatically strengthens their ability to anticipate what’s coming. With this enhanced clarity, SMEs can predict funding cycles, customer demand, donor patterns, and operational pressures well in advance. As a result, leaders shift from reacting to yesterday’s results to planning confidently for tomorrow’s realities.
This predictive capability doesn’t just improve planning—it also reshapes risk management. Aro’s case studies show that predictive models can reduce credit default rates by roughly 20% while surfacing fraud patterns and emerging risks much earlier than traditional reporting. And when applied across different sectors, the benefits become even more pronounced:
For for-profit SMEs, predictive intelligence sharpens demand forecasting, improves disruption detection, and strengthens long-term planning.
For nonprofit SMEs, it enables earlier visibility into donor churn, program needs, and the likelihood of grant renewal.
As these capabilities mature, their effect on decision-making becomes impossible to ignore. PwC’s 2015 research finds that organizations relying on data analytics for major decisions are three times more likely to achieve significant performance improvements. And because those improvements compound year after year, the lesson is clear: predictive intelligence doesn’t just inform decisions—it accelerates organizational agility at every level.
In short, Stage 3 is where we help SMEs embed predictive thinking into budgeting, planning, and performance management, turning finance into a reliable source of foresight.
Stage 4 — Amplify Financial Insights
Once finance can anticipate what’s ahead, the next challenge is ensuring those insights reach the people responsible for acting on them. Predictive intelligence creates little value if it remains locked inside the finance function, so Stage 4 focuses on making insights accessible—clearly, consistently, and in real time.
This is where many SMEs get stuck. Workday’s 2018 survey shows that only 25% of organizations offer self-service access to financial insights, even though real-time dashboards dramatically reduce bottlenecks and speed up decision-making. Without this accessibility, teams end up waiting for reports instead of acting on insight, creating delays that weaken execution and alignment across the organization.
To close this gap, we help SMEs build intuitive, role-specific dashboards that give teams in development, programs, operations, and sales direct access to the metrics that matter most to their work. The value of this kind of access becomes clear quickly. Salesforce’s 2023 research shows that leaders who can easily access and understand their data feel more confident in their decisions and report less uncertainty—a direct result of having insight available when it’s needed.
As uncertainty decreases and confidence grows, teams perform with greater discipline and focus. That improved operational discipline directly supports the cost savings highlighted in Business & Industry Canada’s 2024 report, which shows that data-driven operating models reduce costs by 15–20%—a meaningful advantage for SMEs navigating tight margins.
But amplifying insight is not just a technology challenge; it’s a people challenge. Salesforce reports 73% of companies plan to increase investment in data skills. Yet AFP’s 2025 survey shows the skills gap remains wide: 56% of employees still lack the technology and data capabilities needed to use insights effectively. This gap makes data literacy a critical requirement—not a nice-to-have—as SMEs work to build a truly insight-driven culture.
Simply put, by closing access gaps, strengthening data fluency, and equipping teams with role-specific dashboards, Stage 4 turns insight into coordinated action.
Phoenix Rising Consulting Group helps SMEs build the systems and skills needed to make real-time intelligence usable, ensuring that finance insights flow across every team and fuel faster, smarter execution.
Want to strengthen the data literacy and digital capabilities your workforce needs to unlock financial insights? Check out our article: Organizational Competencies—Leveling Up Your Workforce for the Next Decade.
Put together, these four stages form a practical roadmap for shifting finance from a reactive reporting function to a true strategic partner. By adopting the D.A.T.A. Framework, SMEs gain the structure, clarity, and momentum needed to turn raw information into meaningful insight—and unlock the full value of their financial data.
How SMEs Can Get Started With Unlocking Data
Now that you’ve seen how the D.A.T.A. Framework unlocks the power of data in finance processes, the next question is simple: where should SMEs begin? Fortunately, getting started doesn’t require a sweeping overhaul on day one. What it does require is a structured starting point that builds momentum over time.
Here are five practical steps to help you move in the right direction:
Step 1 — Diagnose Your Data and Processes
Start by assessing the quality, accessibility, and consistency of your financial and operational data. Identify where unreliable, incomplete, or siloed information is slowing down reporting or creating blind spots for leadership.
Once data issues are visible, shift attention to the underlying processes. Map out the manual tasks that consume time and drain capacity.
From there, examine how decisions are made today. Look for situations where teams default to intuition instead of insight, as these patterns often reveal deeper process or data weaknesses.
Taken together, these diagnostics provide a clear baseline. They help you prioritize high-impact improvements and build a focused roadmap for unlocking your data.
Step 2 — Automate What Slows You Down
With problem areas mapped, the next step is to target the high-volume, low-value tasks absorbing finance’s time.
Introducing automation streamlines these workflows, reduces errors, and frees teams from constant data movement, enabling them to shift from repetitive execution to higher-value analysis.
Modernizing your finance systems in these areas creates the operational backbone needed for real-time insight and more strategic, data-driven decision-making.
Step 3 — Transform How You Plan and Forecast
With automation improving data quality and availability, you can begin applying predictive analytics to strengthen forecasting accuracy, anticipate risks earlier, and extend your planning horizon.
Start with simple, practical tools—cash flow projections, demand trends, donor-cycle forecasts, or scenario-based budgets— that give leaders a clearer view of what’s coming. These models don’t have to be complex to deliver value; their true power lies in moving finance from hindsight to foresight.
Step 4 — Amplify Insights Across the Organization
Once finance can generate forward-looking insights, the next step is to ensure they reach the people who need them. Extend real-time dashboards and self-service data analytics beyond finance so every function operates from the same source of truth.
Shared visibility accelerates decision cycles, strengthens cross-functional alignment, and embeds data into day-to-day execution—not as an afterthought, but as a consistent operating practice.
Step 5 — Invest in Data Literacy Across Teams
To fully unlock the value of shared insight, build data literacy across your workforce. Equip staff to interpret dashboards, question assumptions, and apply insights confidently in their daily decisions.
When teams understand the numbers, they trust them—and that trust is what converts financial insight into coordinated action, smarter execution, and sustained performance.
Collectively, these five steps form a practical and scalable path for both for-profit and nonprofit SMEs to unlock the full value of their data. Start small, build momentum, and let each improvement compound—because once finance becomes truly data-driven, the entire organization moves smarter, faster, and with far greater confidence.
The Bottom Line
Unlocking data is more than a systems upgrade; it’s a strategic shift that strengthens financial resilience, sharpens forecasting, and elevates decision-making for both corporate and nonprofit SMEs.
When teams apply the D.A.T.A. Framework, they:
Diagnose root issues
Automate manual work
Transform reporting into predictive intelligence
Amplify insights across the organization
Together, these capability gains ensure finance stops simply reporting performance and starts actively shaping it.
If your team is still spending more time producing reports than generating insight, now is the time to act. Book a Needs Assessment to pinpoint your data gaps, uncover automation opportunities, strengthen forecasting capabilities, and identify the integration pathways needed to build a truly data-driven finance function.
The outcome? A clear, customized roadmap that accelerates your transition from reactive reporting to strategic, insight-driven decision-making.
To continue the journey, follow Phoenix Rising Consulting Group Inc. on LinkedIn for ongoing insights on finance transformation, data analytics, and operational excellence.
About the Author
Werner Harahap brings over 20 years of experience in finance, accounting, and systems integration to his role as Co-Founder and Director at Phoenix Rising Consulting Group. Passionate about collaboration and continuous improvement, he helps organizations
streamline processes and unlock sustainable value. Born in the Netherlands and now based in Canada, Werner’s multilingual background and cultural fluency allow him to connect easily across teams and communities. Beyond work, he’s an active volunteer and community advocate, known for his commitment to mentorship, inclusion, and building lasting relationships that make a positive impact.
References
PwC (2015). Making Strategic Decisions.
https://www.pwc.com/ee/et/publications/pub/pwc-making-strategic-decisions.pdf
Workday (2018). Global Finance Leader Survey.
https://www.workday.com/en-us/forms/reports/finance-redefined-workday-global-fins-leader-survey.html
Oracle (2021). Money and Machines: 2021 Global Study.
https://www.oracle.com/a/ocom/docs/applications/erp/money-and-machines-report-2021.pdf
Salesforce (2023). 73% of Business Leaders Believe Data Reduces Uncertainty and Drives Better Decisions. https://www.salesforce.com/news/stories/data-skills-research/
Aro (2024). Predictive Analytics in Financial Management. https://www.researchgate.net/publication/385025548_Predictive_Analytics_in_Financial_Management_Enhancing_Decision-Making_and_Risk_Management
PwC (2024). Finance Effectiveness Benchmarking Study.
https://www.pwc.se/sv/cfo/finance-effectiveness-benchmarking-study-2024.pdf
Business & Industry Canada (2024). 7 Data-Driven Strategies That Are Revolutionizing Canadian Businesses Today. https://www.industryandbusiness.ca/7-data-driven-strategies-that-are-revolutionizing-canadian-businesses-today/
AFP (2025). 2025 AFP FP&A Benchmarking Survey Report: Technology & Data.
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