Data analytics and budget formulation
Chief Financial Officers (CFO) should view data analytics as a critical first step in performing their budget formulation while facing reduced staffing, increased workload, and growing pressure to improve decision quality.
- Data analytics and automation
- Streamline the budget formulation process
- Identify savings and efficiencies
- Models can forecast costs
- Integration of operational and financial data
Data analytics and automation
Federal CFOs face increasing pressure to do more with fewer resources. Caught in the crosswinds of chronic budget constrictions and increased accountability, CFOs and their budget teams are often constrained by stagnant staffing levels, inflexible decision-making processes, antiquated data systems, and modernized systems that magnify data quality issues. Data analytics and automation can help relieve these pressures by streamlining the budgeting process with greater efficiency. The application of analytics with financial and operational data can also provide CFOs with insights to influence the operational planning decisions which define the line items of budget.
Streamline the budget formulation process
Data analytics can have a transformative impact on the ability of federal budget staffs to plan budgets by reducing manual work through basic automation and improved analysis. Few federal CFOs and budget teams operate with a fully mature enterprise financial system capable of accommodating every aspect of the budgeting process. Simple investments in analytics technology and incremental adoption can yield efficiencies and create opportunities for advanced reports and analysis. CFOs can expand their influence beyond the books by developing data driven solutions to project costs, analyze budget performance, and prioritize the allocation of funds to maximize the operational impact of the budget. Data from multiple sources can be integrated, and through visualization analytical capabilities, a more complete picture of the organization budget from initial build to execution emerges. This information brings the CFO and budget teams enhanced decision-making power and clarity in the direction those decisions should take.
Identify savings and efficiencies
In a perfect world, CFOs would have sufficient understanding of requirements to plan exactly for each line item. But there are a lot of variables, often outside of CFOs’ control, that limit the effectiveness of resource allocation and the ability of the stakeholders to operate with maximum efficiency. As a result, significant amounts of expired funds are often returned to the Treasury because unliquidated obligations were never identified or there was insufficient time to repurpose the money. Data analytics offers CFOs solutions to mitigate this problem in the year of execution and take corrective measures for planning. Analytics can drive dashboards and produce customized reports to identify and prioritize where funds are available.
Models can forecast costs
Identifying and predicting the costs of critical operations is not always a straightforward process due to a number of external variables. In these circumstances, CFOs can leverage data analytics to run cost models. CFOs may use Monte Carlo simulation or other cost modeling and analytical tools to approach operations under constrained budgets. Such tools can enhance the information available to the CFO and provide confidence in decisions that will require the direction of limited funds to those areas that sustain critical capabilities and maintain a level of operational readiness. Because these cost modeling and analytical approaches can cut across budget lines—fuel, maintenance, parts, and manpower—they provide greater granularity, traceability, and scenario analysis to CFOs as they consider making budget decisions that affect operational requirements. Additionally, such analytical techniques offer flexibility and capability to address a wide spectrum of unique organizational operating models where CFOs may rely on external variables for their budget forecasts.
Integration of operational and financial data
Armed with data analytics, CFOs can provide more than just financial transactions and balances by also driving and informing operational decisions. Collaboration and communication between the CFO and the operational managers can be mutually beneficial as they weigh performance and costs to determine the most efficient allocation of resources and return on investments. The integration of cost analysis and operational performance data may reveal insights into the most effective and transparent resource allocation and requirements prioritization. While not all CFOs will have access to operational data, recognizing the existence and potential of the vast amounts of unused data is a starting point for collaboration, yielding results in the short term and incrementally building support over time.