Finance leaders face growing pressure to control labor costs, improve forecast accuracy and measure returns on the company’s largest investment — its people. Yet even the best FP&A models miss a major source of variance: hidden inefficiency inside the workforce.
According to recent workforce benchmarks from ActivTrak, organizations operate at only 87% of expected productivity. That gap translates into $11.2 million in wasted salary per 1,000 employees each year.
For finance teams, this is not an HR challenge. It’s a structural financial blind spot that distorts budgeting, headcount planning and ROI projections. Time spent on low-value tasks, duplicated effort, meeting overload and poor process flow rarely show up in P&L statements or variance reports.
Finance leaders need a clearer line of sight into how work happens across teams and how that work impacts cost, utilization and output. Workforce analytics provides that visibility and strengthens the financial narrative behind every resource decision.
As finance teams take on more responsibility for productivity and performance, many organizations now rely on performance management practices to better connect labor activity with cost efficiency and strategic outcomes.
Turning activity data into financial insights executives trust
Most finance teams plan staffing and capacity using job descriptions, historical budgets and leader input. But actual work rarely matches those assumptions.
A recent Deloitte study found that 71% of employees perform tasks outside their formal role. And only 24% of peers with the same title do the same work. This disconnect leads to misaligned staffing, inflated budgets and recurring productivity issues that finance leaders can’t visualize with traditional systems.
Workforce analytics shifts planning from role-based assumptions to real activity patterns. Instead of modeling around “Finance Manager” or “Analyst,” finance teams see the actual distribution of work across tasks, applications and workflows. This creates a more accurate baseline for labor needs, capacity constraints and process inefficiencies.
Why finance leaders need workforce analytics and intelligence
Forecasting and budgeting improve when finance has clarity on:
- How teams actually spend their time
- Which tasks consume the most hours
- Where bottlenecks limit output
- How much of the workday goes to high-value work activities
This insight gives finance leaders a new layer of financial intelligence. Instead of relying on manager impressions, clear metrics quantify the cost of inefficiency, compare output to time investment and correct mismatches between staffing levels and workload.
Linking productivity trends to finance workforce decisions
Workforce analytics and intelligence highlights productivity trends that directly impact financial performance. For example:
- If analysts spend 30% of their time on manual data cleanup, this measurable cost affects output.
- If controllers lose productive hours to system switching or fragmented tools, the result is reduced capacity for critical work.
- If teams exceed sustainable workloads, overtime and talent turnover increase.
Insights like these help justify process improvements, workload redistribution or a larger investment in technology to increase output. It also creates greater alignment between labor planning and business priorities.
Solving finance department staffing and resource questions
Many finance teams feel stretched even when headcount is high enough on paper. The problem isn’t always staffing levels. It‘s the mismatch between the skills available and work required.
Recent CFO research from Deloitte found that 50% of finance leaders cite engagement issues and 45% cite lack of skilled talent as top challenges. Another 79% expect to use AI within the next two years to help close skill gaps.
Workforce analytics allows you to break work down into its underlying skill components so hiring and development decisions reflect real needs, not assumptions.
Addressing finance department staffing challenges
Instead of budgeting for broad roles like “Senior Accountant,” workforce analytics shows the specific skills and number of hours needed. For example, your data might point to:
- 20 hours per week of financial modeling
- 15 hours of compliance reporting
- 10 hours of data normalization
- 5 hours of variance troubleshooting
These insights help determine whether to hire, redistribute tasks, upskill existing staff or automate specific workflows. This approach reduces overstaffing risk and prevents chronic overload on critical roles.
Using skills gap analysis for finance professionals
Activity patterns expose where skill gaps slow down key financial workflows. For example, if analysts spend a high percentage of time struggling with advanced modeling or system integrations, that signals a training or staffing gap. Use this insight to decide whether training, hiring or technology support will deliver the strongest return.
Forecasting labor costs with confidence and accuracy
Labor forecasts are far more precise when built on activity data rather than assumptions. When finance teams know the exact hours required for core tasks, forecasts are defensible and hiring decisions are more accurate.
How analytics improve finance workforce budgeting
Workforce analytics helps finance teams:
- Replace assumptions with empirical workload data
- Build staffing models based on required hours per task
- Predict overtime or burnout risk before it occurs
- Understand the true cost of distractions or low-value work
- Identify process improvements that save labor hours
This results in cleaner budgets, fewer surprises and more credible projections for the CFO.
Modeling workforce planning for financial team impact
With activity-level detail, finance teams model different workforce scenarios:
- The cost of increasing automation
- The savings from improving productive hours
- The impact of shifting work from high-cost to lower-cost roles
- The ROI of adding headcount to reduce cycle times
These models help finance leaders answer C-suite questions with data, not intuition.
Advising the CFO: The metrics that matter for labor ROI
Labor is the largest controllable expense in most organizations. Yet many teams still measure it only in cost terms. High-performing companies treat talent as a capital asset with measurable return. According to McKinsey, organizations with a high “return on talent” generate 300% more revenue per employee than median performers.
Workforce analytics and intelligence give financial teams the metrics needed to quantify labor ROI and guide strategic decisions.
How to use workforce analytics to improve ROI
Key ROI drivers are measurable once you track:
- Productive hours vs. total hours
- Cost per task or workflow
- Output per employee by skill set
- Utilization rates across teams
- The financial impact of distraction or rework
When these drivers improve, so does the financial return on labor investment.
How labor trends impact EBITDA and ROI
Workforce analytics also helps finance leaders quantify how work patterns affect EBITDA. For example:
- Reducing non-productive time increases throughput without new headcount
- Balancing workloads reduces overtime and turnover
- Eliminating redundant work lowers operating expenses
- Improving focus time accelerates revenue-driving activities
These insights help answer the CFO’s fundamental question: “Where should we invest to improve returns?”
Strengthening hiring, upskilling and talent decisions
With skills-based visibility, hiring is a targeted investment rather than a crude headcount adjustment. It allows finance teams to align talent decisions with strategic priorities and evaluate whether the organization should hire, develop or automate to meet demand.
Improving accuracy in talent acquisition for finance roles
Workforce analytics clarifies when it’s time to hire, or if restructuring existing roles is a better option. It highlights the level of experience required and the skills that drive the most financial value. This reduces hiring misfires and increases confidence in recruitment budgets.
Using skills gap analysis to guide talent strategy
Skills gaps become financially visible through:
- Delays in project completion
- High time spent on rework
- Increased reliance on manual processes
- Inconsistent quality of analysis
These patterns guide decisions about targeted training, role redesign or investment in technology.
Building a future-ready finance organization with workforce analytics
Finance organizations are shifting from static, job-based planning to dynamic, skills-based strategies. Workforce analytics supports this transformation by giving leaders real-time visibility into capacity, performance and output.
Evaluating workforce technology for finance departments
Finance leaders need tools that translate activity patterns into cost, utilization and productivity insights. Workforce analytics platforms provide dashboards that make these relationships clear and allow leaders to monitor changes over time.
Integrating workforce planning into daily operations
When activity-level data is part of monthly reporting, forecast reviews and planning cycles, finance teams can:
- Adjust capacity models in real time
- Identify emerging productivity risks
- Support strategy discussions with operational evidence
- Improve alignment between finance, operations and HR
This positions finance as a strategic partner with a deeper understanding of how work and cost interact.
A clearer path to strategic value
Finance leaders manage the budgets, models and forecasts that guide the business. Workforce analytics strengthens this role by providing clarity into the work that drives financial outcomes. With real-time visibility into how work happens and how labor investments perform, it’s easy to answer the C-suite’s most important questions with confidence.
Ready to bring workforce clarity to your finance strategy?
Close the gap between financial planning and real workforce performance with ActivTrak’s real-time workforce intelligence. See how finance leaders reduce waste, optimize staffing and forecast with confidence. Connect with our team today.
