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Data Analysis Steps for Risk Managers

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Data analysis can help predict the outcome of a situation or allow you to protect your organization against risk. As discussed in a previous blog post, analysis has many benefits including mitigating repetitive losses, lowering insurance premiums, and more. We recognize that data analysis can be difficult, particularly for organizations with a lot of data and complex processes. In fact, an estimated 75% of organizations lack the technology or strategy to effectively use their data. That’s why we came up with this simple guide on the steps for data analysis.

1. Gather data.

This may seem obvious, but data collection can actually be the most difficult and time-consuming part of data analysis. It’s important to make sure the data you collect is valuable: it must be accurate, reliable, and complete. You should regularly clean up data to make sure that it is up-to-date and correct. If you don’t have good data going into analysis, the results will be inaccurate and unhelpful. This process is very challenging to do manually: it can result in all kinds of errors and an inability to see the whole picture. We suggest some kind of centralized database; one that will store all data in a way that is comprehensive, organizable, and searchable. This way, you can instantly access any type of information you need.

2. Determine what kind of trends you’re looking for.

It’s likely that your organization has a lot of data about many different things. This can lead to data overload, where management receives too much information to process and is unable to use it effectively for decision-making. You must decide what you want your data to tell you. Are you looking for areas where costs are too high? Trying to identify new risks? You can analyze data to produce any solution once you know what the question is.

3. Choose a time frame.

Once you know what you’re trying to learn, you must set a time frame for data analysis. Will you be studying information from last week or the past five years? Depending on the type of results you want, different terms will be appropriate. For example, to determine where costs have risen, you may look at data from the last two years. To identify new risks, you could focus on patterns in incidents over the last quarter.

4. Run data analysis.

This step has the potential to be most difficult. Inputting and formatting data into a visual form is difficult and time-consuming, even after all data is collected. By the time a report is built, data may no longer be timely or relevant. However, with an effective system, this step can be as simple as clicking a button to produce any chosen report on your data. ClearRisk’s report functioning allows users to create any kind of report on any internal data in seconds, allowing risk managers to focus on the next crucial step.

5. Study results and take action.

When looking at your results, determine whether trends are related and if they stay the same over time. Consistent patterns identify areas where you may need to make changes. Most importantly, use your analysis to communicate and make recommendations. Results aren’t very valuable if they don’t produce actionable information. Inform management and employees of red flags, consider your findings while making business decisions, and implement mitigation measures to tackle any areas of concern.

6. Monitor and repeat.

Analysis doesn’t end with one report. Regularly running the same tests validates data and allows you to determine which strategies are working and which aren’t. Expand your analysis to include more information to make even better decisions. As you work, investigate new trends and target high-risk areas while seeing the impact on the organization. Our software allows you to schedule the automatic creation of reports on a regular basis so you never miss a detail.

 

Analysis can be complex, but the benefits it promotes are widespread. Follow these steps to achieve excellent data analysis and start making better decisions today.

ClearRisk’s Risk Management Information System takes all the guesswork out of data analytics. Our centralized database allows online data submission, and our report and dashboard functions facilitate the creation of any type of report with just one click, ensuring that your analytics constantly provide relevant and complete information.

Topics: risk management data analysis data analysis risk management data analysis steps