In today's business world, making informed decisions based on accurate and up-to-date information is critical for success. In this process, data is more important than ever before. FP&A professionals must play a crucial role in data management, ensuring that financial data is appropriately collected, stored, accessed, and analyzed.
Integrated FP&A is an approach that addresses the criticality of data by combining financial planning and analysis into one process that provides a comprehensive view of an organization's financial performance. Data management ensures that all members of the FP&A team are working with the same information, which can help to avoid misunderstandings or errors.
Furthermore, by automating data-intensive tasks, data management can help free up time for
Data Management is Critical to FP&A
When data is organized and accessible, analysts and decision-makers can quickly identify trends and patterns critical to strategic planning, product development, and resource allocation.
Thus, when analysts seek to derive insights from an organization, the first step should not be to publish a report, but tostep back and perform a robust data assessment. From there, findings regarding the data quality can be summarized, validated, and better understood, producing a much higher-quality analysis
Building on the example above, by managing data effectively and freeuing up more time available in the day, FP&A professionals spend more energy on analyzing profitability and identifying was to reduce costs.
Getting Started with Data Management
Often, when analysts step into a new role or organization, one of the first things they look forward to doing is plugging into the available analytical tools. While there are many great tools available for performing analysis, it is smart to think about analysis from the start-to-finish process instead of over-focusing on the outputs of the business processes and data; a word of caution is advised.
When an organization's process integrity is not fully understood, is inconsistent, or has fundamental flaws in how it is captured, measured, and calculated for input into an ERP (Enterprise Resource Planning) or analytical tool, then all outputs and analyses cannot be trusted.
For these reasons and more, data management is critical to businesses, serving as the steady bedrock upon which an advanced FP&A function can be built. FP&A must be a trusted partner in verifying input and then outputs to produce trustworthy recommendations to their business partners.
5 Data Management Best Practices in FP&A
Every FP&A practitioner can follow a few pieces of advice for performing a data quality assessment.
By understanding the importance of high-quality data management and the processes behind them, FP&A professionals set themselves up for success. Once data is trusted, analysts can move forward without questioning whether the actuals are actuals, and confidently summarize and present true insights to organizational leaders.
Here’s how to get started:
Put checks and balances into place that tie to the and trusted sources
Do reported labor hours tie out to hours reported by staffing agencies and internal clocking?
Do all reports produce the same measure for any given metric, such as production volumes?
Are items reported in inventory easily identifiable and located accurately?
Observe the process and speak with the operations
Ask to see how materials are consumed, transferred, and produced in the systems.
Watch how different people perform identical processes.
Look for where estimates instead of actuals are recorded.
Perform common sense checks
Are full-time employees reporting labor hours worked that are unrealistic and vary drastically?
Do related products have vastly various levels of profitability?
Does the operations lead or plant manager have confidence in the outputs based on their expertise and experiences?
Utilize internal business experts to validate whether the messages from data are accurate.
If the data does not tie to how the business works, look for what is still missing.
Establish clear goals and objectives for data collection and analysis, and systems to support those goals.
Designing processes and systems to support those goals, acquiring high-quality data from reliable sources, and storing and maintaining data in a secure and accessible manner are vital.
Advancing Data to the Next Level
Getting started with excellent data management best practices is critical to advancing to what is next.
Once the basics of data are mastered, FP&A professionals can begin to investigate and advocate for more advanced data storage and analysis tools. For example, FP&A professionals can identify multiple data sources and work to aggregate them into a data lake, incorporate AI (Artificial Intelligence) & ML (Machine Learning), and implement business intelligence solutions.
As we step back, we can see that eventually build a world-class financne functions requires building on a solid foundation of great data and processes. By improving data quality and accuracy with integrated FP&A, professionals can enhance their careers and organizations by providing valuable insights to decision-makers.