One of a risk manager's primary goals is to control and, if possible, reduce the costs associated with various potential and realized liabilities for his employer. In addressing this challenge, a number of questions arise: Is my program performing well already, or is it doing poorly compared with similar programs? How should I spend limited resources for the greatest return? How do I publish the health of my program to my superiors? How do I persuade business partners within my organization to see the value of data and then pursue risk management initiatives? When used effectively, data analytics can help in answering these often complicated questions.

Working with Data Analytics

Understanding the appropriate use, limitations, and potential skewing effects of metrics in an analysis is critical. For example, when trying to answer the question of whether a given company's program is performing well compared to its peers, it makes sense to attempt to have the peer companies match the industry of the company being measured. Even so, there may be other drivers impacting costs, such as geography, staff morale, and the presence of labor unions. These challenges sometimes lead risk managers to give up on finding answers regarding the overall health of their programs based on a peer comparison.