After moving beyond spreadsheets to centralize data and streamlining workflows by automating processes, the next stage in the transition to a data-driven approach to risk management is ensuring that data from across the firm is used to drive risk, compliance, and claims management-related efforts. As the AWS Cloud Enterprise Strategy blog How to create a data-driven culture puts it, “Data should be for a purpose—not the purpose.” In other words, data must be actionable and available to those who need it. What may initially seem like an ambiguous, even daunting task, can be simplified by asking questions that help define areas of focus, establishing credibility with stakeholders, and careful consideration of the tools used to make the right information available to the right people at the right time. 

Actionable Data: Finding Your Starting Points 

In Turning Data into Actionable Insights, Alaa Khamis — AI and Smart Mobility Technical Leader at General Motors and a lecturer at the University of Toronto — provides a helpful list of questions that can be used when thinking through (and planning for) how to mine your data for “critical actionable insights.” Although the article focuses specifically on the use of data in design and manufacturing processes, the description of data types and the questions he puts forth are broadly applicable across industries by risk professionals and others working toward a more intentional use of their data.   

“Descriptive data analytics provides insight into the past and the present while predictive analytics forecasts the future,” writes Khamis. “Diagnostic analytics provides root-cause analysis and prescriptive analytics advises on possible outcomes and their anticipated impacts.” Khamis provides lists of questions for each type that can be used as starting points, or prompts, to initiate conversations with stakeholders and home in on areas of focus to deliver more insightful analysis and, ultimately, inform actions. 

Descriptive 

• What has happened? 

• What happens now? 

• What are the trends of certain variables? 

• What is the relationship between variables? 

• How is an item performing with respect to other items or a benchmark item? 

Predictive 

• What would happen? 

• When would it happen? 

• Where would it happen?  

Diagnostic 

• Why did it happen?  

• Why would it happen?  

Prescriptive 

• How would the predictions obtained from predictive models impact everything else? 

• What are the proactive decision/actions to be made? 

• How we benefit from predictions/recommendations? 

• What are the best actions to make? 

• What is the best time to take this action? 

• What would be the impact of this action? 

Actionable Data: Establishing Credibility with Stakeholders 

“While most companies are amassing data at an unprecedented rate, many are struggling to a true ‘data-driven culture’ that sticks,” writes Brian LaFaille of Looker, a business intelligence software and big data analytics platform. Building a data-driven culture is, of course, not accomplished overnight. Stakeholders’ buy-in is essential for establishing and sustaining a data-driven culture.   

It’s not uncommon for stakeholders to initially have a “What’s in it for me?” perspective when looking at any presentation of data. “Quick wins” can help to build program credibility and begin to demonstrate value to stakeholders, one approach is to let the problem(s) you are trying to solve guide how data will be used.  

Tom O’Toole, executive director of the Program for Data Analytics at Northwestern University’s Kellogg School of Management, suggests starting with the identification of smaller problems that can be resolved quickly. “Identify a small number of ‘high-leverage’ business problems that are tightly defined, promptly addressable, and will produce evident business value, and then focus on those to show business results,” he writes in What’s the Best Approach to Data Analytics? “The specific business problem drives the team to identify the data needed and analytics to be used.” 

Actionable Data & Quick Wins: A Real-World Example  

The Origami Risk webinar Leveraging RMIS Technology: Doing More with Less, details how a US city put its risk, claims, and data to work — and underscores the importance of delivering personalized “quick wins” with data — at the outset of the COVID-19 pandemic by producing a Mayor’s Report that both informed and led to action.  

Initially sent on a weekly basis, the report provided various departments with a rolling, 30-day dataset that included general liability and workers’ compensation claims information, safety incident details, and weekly and quarterly trends. With increased frequency of COVID-19 incidents, department heads wanted to see more frequent updates of the numbers provided in the report and requested access to the system used to collect, consolidate, and store the data. 

The city’s risk manager, knowing that much of the other data in the system was not appropriate for widespread distribution, followed O’Toole’s quick-win strategy and let the problem drive the data. She built a dashboard that automatically pushed out each department’s COVID-19 incident data twice per day.

Run twice per day, the report was timely. Leveraging the incident collection portal each department was already using to directly report other incident types boosted both accuracy and credibility. And the ability to personalize the report so that each department saw its own data made it easier for department heads to use the data to gauge, in real-time, the effectiveness of various tactics and take action, as necessary. 

Bringing It All Together: The Benefits of an Integrated, Single-Platform Solution 

As the AWS blog referenced above states, a data-driven culture is one that “embraces the use of data in decision making. It treats data as a strategic asset of the company by making data widely available and accessible.” Given the limitations of spreadsheets and the lack of time often available to teams, having the right technology in place is a key component in moving forward as a data-driven organization. However, relying on technology alone, without first considering exactly the questions you wish to answer, the stakeholders who need to be involved, and the results your firm is looking to achieve is likely to lead to increased scrutiny and unmet expectations.  

A highly configurable, integrated, single-platform solution like Origami Risk counters the issues associated with the use of spreadsheets and can contribute to stakeholder buy-in in many ways, including: 

Improved data quality — whether through the direct entry of data into a system or via integrated feeds of data from other systems used throughout the firm, eliminates the error-prone process of transferring data between spreadsheets. Analyses and reports are based on data that is more accurate. In addition to the ability to set up system checks based on defined business rules and the ability to protect designated fields from being updated, the system also stores an audit trail of changes. 

Improved collaboration — Beyond allowing multiple users being able to update or report on data simultaneously, an integrated risk management platform can help to break down silos of data and enhance collaboration across departments. Improved collaboration can potentially have additional benefits. For example, exposure data and/or can be shared with brokers to help ensure that policies are renewed on time and, in many cases, provide information about risk mitigation efforts and the effectiveness of controls that can contribute to renewals at favorable rates. 

Access to real-time data — Origami Risk’s single-platform integrated RMIS, GRC, and EHS solutions include flexible tools that allow for integrations with virtually any third-party software platform, including HR, document management, payroll, and other systems in use across the firm. Automating these feeds not only reduces the amount of time spent manually entering data, but it also means that reporting and analysis is performed using current data. 

Contact us to learn more about how Origami Risk can play a role in your firm’s transition to becoming a data-driven organization.