Originally published in Forbes.

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Imperfect data is the top scapegoat for life insurers putting off meaningful analytics.

"We don't have enough data." "The data we have isn't organized." "The data we have needs to be cleaned." Any of these sound familiar?

If you're working within life and health insurance, the answer is probably "yes." The life insurance market is further along than most in terms of data collection and process sophistication, but not much has changed in recent years in reality.

Data is vitally important, but it must go beyond owning data. The most significant investment an insurer can make today is understanding data to the point where it informs strategic action and decision-making.

What’s holding insurers back from innovating?

Many life insurers have taken necessary steps to build data lakes, invest in low-code or no-code solutions to gain insights and update data infrastructure. These are the basic foundations to successful, data-based innovation. What's holding many back isn't the data — it's the uncertainty of what to do with it.

The solution to this dilemma isn't an obvious one. Many insurers are collecting data at a rapid rate and sitting on decades of useful historical data about their policyholders, which makes deciding what and where to use data difficult. For many, the temptation to stick with the status quo and say "We have the data, therefore it must be impacting our strategy somewhere" is hard to resist, especially when the alternative requires, for many, a significant shift in mindset.

As insurers continue to hesitate, they leave value on the table.

The reality is that the time when hesitating was something insurers could get away with has passed. Time is money, so is data — many life insurers are wasting both. Insurers have invested heavily in expanding their data lakes, restructuring their data and gaining one-off insights from customer, competitor and market data. Now they need to gain the rewards.

Hesitation is understandable; there haven't been any significant first movers when it comes to meaningfully innovating with data-driven analytics. But it's time for insurers to put their data investments to work, helping deliver on company objectives, improving decision-making and meeting modern customer expectations.

The secret is . . .

The secret approach to getting the most from insurance data is there is no secret — insurers need to start, and do so intentionally.

Data is a powerful tool, but only if it's used strategically. While gaining access to data and insights is valuable, there's a limit to how much value they can provide if they're siloed away and not integrated across the business.

Life and health insurers should seek solutions and platforms capable of more than delivering insights; they should seek those that turn insights into action and decisions. In order to begin leveraging data to get real-world benefits, life and health insurers need commitment across their organizations, finding ways to leverage data where it counts: in the decision-making process.

How insurers can get started

The way for life insurers to start using their data is to pick a use case — a decision that needs to be made — and work through the process. It will look a little like this:

1. Isolate the decision. Clearly define the decision that needs to be made and the different factors that influence it.

2. Determine the data you need to factor in. What data do you have in-house and what third-party data do you need in order to fully understand your options?

3. Collect the data and model your options. Use a combination of analytical tools, data platforms or modeling techniques to illustrate scenarios that incorporate your specific constraints and objectives. Validate your intended approaches with subject matter experts, like actuaries, to ensure you are on the right track.

4. Identify the best option. Based on the modeled scenarios, which choice is going to lead to the best, high-impact decision for your business?

5. Implement and monitor the outcome: Once you've made your choice, implement the decision and closely monitor the outcomes as they play out in the market. Are they what you expected? Why or why not?

6. Repeat the process. Now you've gone through the process, the next time you make a similar decision, factor in your new data from the previous experience.

The reason this process works is its cyclical nature. By incorporating data in a thoughtful and purposeful way in the decision-making process, insurers can understand the ways in which data can actively improve and influence their outcomes, as well as how generating new data can continuously improve the process.

This process is called decision science. While applying it to one decision is powerful, applying it to all of an insurer's decisions takes everything to the next level. Insurers can leverage this approach through a number of different ways, including a decision science platform, a combination of in-house tools and technologies or working with a third-party expert to refine their decision-making process.

When leveraged correctly, direct impacts of decision science include:

• Better alignment between business processes and decision making. Optimize processes like pricing, product development, underwriting and claims management with the specific intent of gaining actionable insights from data.

• Plugging knowledge gaps. Base decisions on validated information, ensuring they're aligned with long-term objectives.

• Evaluating broad ranges of potential decisions. Assess a wide range of scenarios and efficiently evaluate different decisions and their trade-offs.

• Monthly or weekly monitoring makes course correcting simple. Swiftly identify and react to challenges and opportunities in real time.

• Better understand customer, advisor and competitor behavior. See how these factors impact competitiveness and market position.

Decision science allows life insurers to treat decision-making like a science. Integrating this approach across business functions might seem out of reach, the bridge between data and the people who make decisions might seem enormous — but it isn't. Many insurers have already started gaining ground, but there's still work to do. Those looking to lead the pack will take as bold a step as possible with regards to leveraging their data in this way.