WSIB enters second century with advanced analytics

Better analytical insights for better decision-making and return to work

Ontario’s Workplace Safety and Insurance Board (WSIB) is undergoing a transformation into a modern, responsive and fiscally sustainable system as it enters its second century of service to Ontarians. This effort was triggered by mounting evidence that its business model was fundamentally broken: Expenses had exploded in the decade between 1999 and 2009. Benefit costs had gone up by 60 percent – from $2 billion to $3.2 billion a year. At the same time, injury claims had actually dropped by 40 percent. The math just didn’t add up. Why was this happening? There was no evidence that workplace injuries were becoming more serious. The duration of workers’ claims was getting longer and longer – yet it wasn’t a shortage of jobs to go back to that was to blame, as employment was growing over the period. So why were workers not getting back to work and becoming so dependent on benefits, to the tune of over $1 billion more per year?

We knew we could trust SAS products in developing our advanced predictive analytics to support our decision making.

Eugene Wen
Vice President and Chief Statistician

Advanced analytics, together with actuary, finance, operations and business analytics, were called in to find the answers. Dr. Eugene Wen led the advanced analytics team to find more innovative ways to deliver evidence-based insights for decision makers. Their objective: to ensure that the WSIB began focusing on health outcomes for injured workers, as opposed to simple claims processing without regard to actual results, as had been the approach in the past.

Wen, the WSIB’s Vice President and Chief Statistician, turned to SAS as the main predictive analytics tool to meet this ambitious goal: “SAS is recognized by trusted industry experts as the market leader, and has been a proven partner of the WSIB for several decades,” says Wen. “We knew we could trust SAS products in developing advanced predictive analytics to support our decision making.”

Analytical insights for strategic decision making

Wen and his team, working together with the WSIB’s operations, actuarial and finance business areas, carried out a series of initiatives on data mining, predictive modeling, randomized sampling audits and focus groups. They tracked historical trends, quantified influences of past business management changes and benchmarked claim management efficiencies. The results were delivered to senior leaders to help them determine the best way forward. The analyses were so successful that senior management has decided to make them regular functions, and use them in monitoring and evaluating the progress of business transformation and operational efficiency.

Predictive modeling findings support better claim services

Using predictive analytical tools from SAS, the WSIB was able to identify, verify and quantify key drivers for claims related to benefit duration and cost. This information helped them to better serve injured workers. For example, the model found that injured workers with first languages other than English or French took longer to return to work after being injured. This directed the WSIB to make extra efforts in working with immigrant community groups to address the unique needs of these injured workers. They consulted with local community organizations and established a new Vocation-based English as a Second Language program, as part of Expanded Work Reintegration services, to replace the previously used standard ESL class. It provides oral language instruction in the worker’s identified suitable occupation or job goals, along with paid work placement experience with an employer, of up to 26 weeks. These services are offered by Ontario Government-approved, community-based and primarily not-for-profit organizations.

The WSIB also developed forecasting models for key business indicators, for example, incoming claim volume and their duration of staying on benefits, using time series procedures of SAS. The WSIB can now forecast these key indicators each month for the following 12 months. Convinced by its high precision in back-testing, the operation teams are using these forecasts in business planning and resource allocation.

Established predictive modeling capacity

As part of the business transformation of the WSIB, Wen built a predictive modeling team comprised of experienced statisticians with advanced SAS expertise. The WSIB also established a predictive modeling environment equipped with leading-edge SAS tools and data sources for his team.

In addition to the predictive modeling team, the WSIB also has a team dedicated to data quality, data governance, injury coding and business analytics led by Mark Brion, Vice President of Corporate Business Information and Analytics. Their outstanding support provides a solid foundation for success in predictive analytics and management decisions.

“We are grateful as analytical professionals that the organization realizes the value of predictive analytics to the business and invests to build the capacity,” says Wen. “Without guidance from senior management and support from all levels of the organization, none of this would have happened. And it’s just the beginning: A major modernization of our systems and data is underway, and the predictive analytics will be able to do more data mining and contribute much more in the future.”



More than a decade of increasing costs, despite reduced injury claims from injured workers, required the century-old organization to modernize its operations.



  • Informed strategic decision making.
  • Improved business efficiencies.
  • Increased client service quality.
  • More efficient resource allocation.

About WSIB

Ontario’s WSIB is one of the largest workplace insurance organizations in North America. Managing more than CAD $4 billion in premium revenue each year, and with close to 4,000 staff, the WSIB is entirely funded by employer premiums and investment revenue. It provides employers with no-fault collective liability insurance. For workers who are injured, or contract an occupational disease at work, the WSIB provides return-to-work and recovery services and loss-of-earnings benefits, and covers the costs of required health care.

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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