Would you expect a doctor to diagnose a patient just by looking at them? Of course not. The doctor would first collect hard data: a medical history, vital signs, and run a battery of tests. Data is critical in deciding what’s wrong and how to cure it.

If doctors look at data before they take action, why should insurers be any different?

All too often, we rely on our gut instincts or simple profit-and-loss statistics to make major business decisions. But our instincts can be faulty and emotional, and the bottom line can be a lagging indicator. Like doctors, we need a tool that lets us be proactive, not reactive.

That tool is financial analysis, an efficient method for tracking the progress of your business. Here’s advice on how this applies to the insurance industry.

Choosing Which Metrics to Monitor

In a complex business like insurance, you have many different pieces of data to choose from. What’s important is limiting your key metrics to those that are the most meaningful and can be influenced by business decisions. Too much data can be overwhelming; the wrong data can lead you astray or not result in taking action.

Matt Weeks, Director of Financial Planning and Analysis at Aspida, recommends narrowing your benchmarks to less than a dozen indicators to focus on regularly. He recommends the following:

1. Core financial measures.

These are the most obvious numbers to watch and where companies spend the majority of their financial analysis resources. What’s important varies by industry but the core metrics are similar—sales, expenses, assets, etc.

Weeks notes that looking at these line items individually may not be very useful but understanding how they move in relation to each other is generally the key.

“Are your operational expenses growing and becoming an issue? If they are growing slower than revenue growth, then maybe this is okay. Are you rapidly adding to your asset base? Don’t get too excited until you check that equity is growing at a similar rate.”

To make this analysis easiest, ratios will often give better insight, he adds. “Think expense ratios, return on equity, investment yields, etc.”

2. Operational data.

Don’t make the mistake of only watching the accounting numbers. Operational data is often your best source for identifying trends early. In insurance, it is important to monitor the number of policies issued and the average face amount per policy, says Weeks. Additionally, keeping a close watch on claims payments versus expectations is essential to catching problems early.

3. Industry data.

Internal benchmarking is certainly important, but you should also look to compare your data with averages from across the industry for context.

“If premium is shrinking during a time industry premium is increasing, then it would raise a red flag that you’re losing market share,” notes Weeks. “I would be more accepting of decline in a particular product line if the entire industry was going that way.”

The same goes for measures like investment yield or expense ratio—the only way to know if you’re part of a trend or an outlier is by comparison with the rest of the industry.

4. External/macro-economic data.

Be aware of external factors such as tax reform, regulatory changes, and macroeconomic factors that could influence your business model, advises Weeks. Knowing what’s going on in the broader environment can help you prioritize how to analyze your own business.

Snap-on Success

Identifying a few specific indicators to track your performance helps you identify problems before they fly out of control, and find potential opportunities for new growth.

By analyzing recent performance against historical trends from your own business or from the insurance industry as a whole, you can get a sense of performance issues even before they show up in your bottom line. Looking at this long-term data helps you to get beyond the noise to identify clear patterns in your business.

Building models utilizing historic data is a powerful tool that lets you try new things, tracking the effects of a single change.

By observing how your data reacts to (for example) a one point increase in your investment returns, you can decide whether it’s a strategy worth pursuing. You become a data scientist, experimenting with new ways to grow your profitability in order to prioritize business initiatives that have the opportunity for the largest impact on your financial results.

Create an Analytical Tool

Trends will only become apparent once you’ve gathered enough statistical data to draw meaningful conclusions. That’s why it’s so important to collect your chosen data in one place.

You may already have monthly financial reporting tools that draw from your general ledger and other source systems, but you can create a new spreadsheet or use a reporting tool that easily generates charts and graphs to make the trends apparent quickly.

Wherever you assemble the data, you can help yourself mightily by making the process as automated as possible.

“If you’re spending a ton of time just aggregating data,” says Weeks, “then you’re spending too many resources there and don’t have as many resources focused on actually making the decisions based on what the data tells you. We’re always trying to integrate systems and streamline reporting processes so time is spent on analytics, not spreadsheet creation.”

Where to Find External Data

In some businesses, reliable external benchmarks can be hard to find and difficult to accumulate. Fortunately, insurance’s strict financial reporting requirements mean that a great deal of comparable industry data is available at your fingertips.

When to Do Analysis

Rather than setting up a rigid schedule for assessing data, determine what works best for your business. Ongoing assessment is optimal.

Do your analysis as frequently as you can, advises Weeks, depending on the availability of data, how often you would expect trends to change, and the resources it takes to compile that data.

Allow your process to be fluid, based on what you sense is changing in the market, he adds, “so that you dive in at the right place and at the right time without arbitrarily just updating spreadsheets at month-end” and generating a chart that shows results.

Evaluate the tradeoff of a workload that’s not helping you make a business decision versus being able to develop actionable analytics.

What If You Fall Short?

A good analytical tool will alert you if any of your key metrics suddenly dips below your normal level or that of the rest of the industry. Fortunately, because you’re looking at underlying data rather than simple profit and loss, you should be able to quickly diagnose the cause of the problem and potentially remedy it before a significant impact to the bottom line.

“You have to get to the underlying business driver, and figure out the business decision that should be made based on that,” says Weeks. “For example, if you’re not making the same investment yield as other companies in the industry, then you look into the reasons why—is it because your asset mix is different than the industry?”

Summing Up

Instead of relying on guesswork, use financial analysis to recognize trends and fix problems before they impact your bottom line. Carefully select a limited number of internal and external categories to monitor, and then watch them consistently to spot changes or shortfalls.