Financial analysis helps the business answer three important questions: What happened? So, what does it mean? Now, what do we do? Answering these questions helps the business optimize the use of capital and resources.

How can you improve your financial analysis skills? In a companion webinar to the AFP FP&A Guide to What Is Financial Analysis, three finance professionals shared their advice.

Explain the “So What” and “Now What” of the Data

Don't just present the numbers; explain their impact on the business. Focus on the so what and the now what. What do you want your audience to get out of your analysis?

For example, rather than simply saying that cash flow decreased by 20%, explain that the decrease in cash flow could limit the company’s ability to invest in new projects or cover unexpected expenses (the “so what”), and that the company could tighten collections from suppliers or be ready to tap the line of credit (the “now what”).

“This is more impactful because people now understand that this problem has impacts on their business. Now they’re ready to engage in the discussion and offer solutions,” said Hesham Mokhiemer, FPAC, Head of Finance for a diversified group.

Tailor the Delivery to Your Audience

Know your audience for the financial analysis and tailor the language to their level of expertise. “Are you speaking to a business partner who is interested in ground-level details, or are you talking to your CFO who needs a 50-foot view?” said Jermaine Stanislaus, FPAC, Senior Financial Analyst – Media at Bloomberg.

Additionally, anticipate questions your audience may ask you and prepare for them. “If I can’t answer the question, maybe my model wasn’t right, maybe I didn’t have a complete analysis in my spreadsheet, or maybe I needed to go back and do something different,” said Amy Johnson, FPAC, a finance leader.

Consider your delivery style, too. Are you presenting to a large boardroom or a small team meeting? Adapt accordingly. “For a large audience, keep it concise and focused, and for a small group, allow for more discussions and exploration,” said Mokhiemer.

If you create a pre-read for a meeting, be sure to do it in a way that matches the culture of the audience. For example, the team you’re presenting to may prefer a one-page synopsis or a 10-page white paper with five pages of appendix.

“You may even allow for time during the meeting for anyone who hasn’t had time to read beforehand to review what we’re going to talk about,” said Johnson. “It gets everybody on that same page and makes it much more productive.”

After the meeting, write up the things discussed, decisions made, and outcomes or changes that need to be made to ensure everyone is aligned.

Understand the Strengths and Limitations of AI

Every day, we discover new uses for AI in finance, especially in financial analysis. AI can handle jobs like data gathering, report generation and basic financial modeling, freeing up time for analysts to engage in higher-level analysis and strategic thinking.

AI can also enhance data analysis. It can process massive data sets much faster than humans, uncovering hidden patterns and trends that might otherwise be missed. This allows analysts to produce deeper insights and make data-driven recommendations.

When it comes to forecasting, an AI-powered algorithm can analyze historical data and market trends to generate a more accurate financial forecast. This information is crucial for making informed decisions about investments, budgeting and risk management.

In regard to risk management, AI can be used to identify and assess potential risks, such as fraud or loan default. This helps analysts develop strategies to mitigate these risks and protect the company's financial health.

Though AI can do many things well, it’s important to understand what it can’t. AI is good at looking inside the data but not outside it. It could find a needle in a haystack, but it can't find the storm that's going to blow the haystack over.

Understanding where your data comes from and how it’s derived is also important. When AI or machine learning gives you an answer, you always need to ask yourself, does the outcome make sense with my expectations?

The human mind may know something that AI was unable to take into account. Johnson explained, for example, that when she used to do labor planning, there were times when machine learning did not align with the boots-on-the-ground reality.

“As great as machine learning was at the time, it couldn't plan on a concert that everyone in the area would want to go to,” said Johnson. “And sometimes, it would apply the impact of a holiday incorrectly because, in the past, the holiday was on a Thursday, but that year, the holiday was on a Tuesday.”

Practice, Practice, Practice

As with anything, it takes practice to be good at something. Go beyond theoretical knowledge and analyze real companies. “Start with public companies because their financials are easily accessible,” said Mokhiemer. “Make your own conclusions about their financial health and compare them with analyst reports.”

Analyzing other companies’ performance can also give you a benchmark against which to measure your company’s performance.

At work, go beyond your usual tasks and ask for special projects and feedback. In this way, you can expose yourself to other parts of the business and other aspects of finance. “If you want to set yourself apart, you have to be proactive,” said Stanislaus. “Reach out to people and have conversations.”

The world of finance is always evolving, so continuous learning is crucial to your success. Ways to continue growing in FP&A include conversations with peers, professional conferences and webinars, and certifications.

“I believe the best certification to continue learning is the FPAC,” said Mokhiemer. “It gives you up-to-date knowledge and practical application for you to do analysis using the tools and techniques you learn in the certification.”

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