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 analysed.

Integrated FP&A is an approach that addresses the criticality of data by combining Financial Planning and Analysis (FP&A) into one process that provides a comprehensive view of an organisation'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 FP&A professionals to focus on more strategic tasks.

As an example, if other departments email spreadsheets for the FP&A to rekey into the planning tools, the opportunity to automate here would be to give stakeholders access to the system to input data or otherwise build a new process to consolidate the spreadsheets into an upload template to be input into the FP&A tool.

In short, integrated data management is essential for any FP&A function that wants to operate effectively and efficiently.

Data Management Is Critical to FP&A

When data is organised 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 organisation, the first step should not be to publish a report, but to step back and perform a robust data assessment. From there, findings regarding the data quality can be summarised, validated and better understood, producing a much higher-quality analysis.

Building on the example above, by managing data effectively and freeing up more time during the day, FP&A professionals spend more energy analysing profitability and identifying ways to reduce costs.

Even better, the trust between the FP&A function and management soars as more timely and accurate insights are delivered, allowing organisations to make better, faster decisions without second-guessing themselves. 

Getting Started with Data Management

Often, when analysts step into a new role or organisation, 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 organisation'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 summarise and present true insights to organisational leaders.

Here’s how to get started:

1. Put checks and balances into place that tie to the GL (General Ledger) and trusted sources.

• Do reported labour 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?

2. 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.

3. Perform common sense checks.

• Are full-time employees reporting labour 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?

4. Utilise 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.

5. 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 Artificial Intelligence/Machine Learning (AI/ML), and implement Business Intelligence (BI) solutions.

As we step back, we can see that, eventually, building a world-class finance function requires creating a solid foundation of great data and processes. By improving data quality and accuracy with Integrated FP&A, professionals can enhance their careers and organisations by providing valuable insights to decision-makers.

This article was first published on the SAP Blog.