By John Baule, CEO and Co-founder, FutureView Systems
Cash might be king, but data is the key to insights and one of your company's most coveted resources. Thriving companies require well-rehearsed plans driven by analytical insights provided by finance. These insights must be developed on a foundation of solid, structured data. Historically, getting to this structured data has been a challenge for finance teams, requiring them to assemble data stored in multiple formats across many systems manually. Even when the data is captured, getting to the point of "available to analyze" requires careful thought to convert the information into relevant key metrics and reports.
And what happens when disparate data meets exponential increases in data? If the technological revolution of the past forty years since the development of the spreadsheet has taught us anything, it is that providing stakeholders with information and analysis always begets requests for further information and analysis. As we progress into AI, the information your organization will require to compete will undoubtedly expand at an accelerated pace.
Getting From Data to Analysis
Analysis requires solid, structured information built on consistent, captured data. This means you need to figure out what to measure and then work backward to determine the necessary data and the structure you will use to organize it before you can begin any analysis. Your goal is to provide your stakeholders with insights, so an excellent way to start is with the end in mind. Have conversations with your company’s decision-makers to understand what analysis they need. Then, apply reverse engineering to determine what you need to gather in terms of data to meet their requirements.
One of the most effective ways to develop an analytical framework that fits your company’s needs is a recurring “guess and test” method. Forecast a particular metric and then compare it to the actual outcome. Analyze the variances and make any necessary adjustments. If you do this a few times, you will begin to have a framework of metrics that are relevant to understanding the historical performance of your business, create a dataset to enhance your analysis, and enable a driver-based forecasting as you look to the future.
Be prepared to make changes. Often, the analysis that decision-makers think they need changes when they receive the information. Flexible tools will mitigate this and allow you to fine-tune analysis to fit their requirements precisely.
Relevancy is a critical component of the analytical framework you develop. The metrics you develop will usually go many levels beyond what is reported in the basic financial statements. However, it is critical that these metrics are integrated with the financial statements as they represent the final scoreboard. For example, if I am measuring the hourly utilization of a consultant in a services business, I need to be able to connect this measurement to the way that the firm measures the cost of goods sold or gross profit.
Providing Actionable Insights
Once you have a well-understood and clearly defined analytic framework built on accurately measured data that is structured and organized, you will be able to effectively analyze your business. Then the real fun begins — doing something with the analysis. The reason you do all of this work is to drive decisions. Presenting your analysis clearly to stakeholders forces them to do the hard work of making choices.
Let’s face it, making decisions in the absence of perfect knowledge is really hard and scary. Business leaders will use every excuse imaginable to keep from making a definitive choice for which they will be held accountable. That is where the finance professional is essential for driving the conversation by doing three things: making it clear that a choice is required, providing actionable insights as the basis for action, and minimizing potential excuses by ensuring the data is as complete as possible. This means data must be accurate, it must be provided timely, and it must be carefully analyzed for holes. If a decision-maker finds a formula error in a spreadsheet, they might use it as a tactic to avoid the decision. Given this inherent conflict between the finance professional who is attempting to drive tough decisions and the accountable decision-maker trying to dodge the decision, using tools that produce data quickly, automatically and with built-in quality control is essential.
How to Deliver Actionable Insights?
To achieve high-quality analysis, you need the right tools to make you more efficient and effective in your business partnering efforts. Integrated planning and forecasting is necessary to align your stakeholders around the proposed actions necessary to hit the targets established in the annual budget. Once you develop a framework based on conversations with your budget owners, executives and other key stakeholders, you can leverage technology and automation to expedite your data to insight transformation.
In our FP&A session at AFP 2023 in San Diego, “Delivering Actionable Insights: Converting Analysis to Action,” we will discuss the role of finance in identifying the underlying drivers of your business and providing insights necessary to make rapid adjustments.
So, grab your favorite caffeinated beverage and join us on Monday, October 23, 2023, at 8:30 AM to learn how to deliver actionable insights for your business partners.
Speakers:
John Baule
CEO and Co-founder, FutureView Systems
Keith Haas
CFO, FutureView Systems
Madison Bates
Chief Accounting Officer, Wunderkind
Check out the full lineup of AFP 2023 sessions on the Session Explorer.