Analytics Make a Difference

The essence of analytics in vocational rehabilitation (VR) revolves around two main components: the data itself and its visualization. While vocational rehabilitation professionals typically come from backgrounds focused on service rather than statistics, they face the challenge of meeting performance expectations and managing finances based on data. Government bodies and funding sources demand evidence of effective use of resources, making data visualization crucial. Rather than sifting through pages of raw numbers, visual tools like charts and graphs can make the data more comprehensible and actionable.

I first began using analytics in the late 1990s. As a state VR administrator, I needed to have information to make better decisions about how we were spending our money on services, measure the areas where we had the highest performance as an organization, consider individual counselor performance and performance in different regions of the state. We also had to evaluate specific services that had the highest or lowest expenditures and success, manage money at the end of the year to assure each area had enough money to provide services without delays, and make decisions about order of selection (priority of service). We had been in order of selection for several years and it was inhibiting services to consumers. We needed to make reasonable predictions to increase our overall level of performance. We did not have the advantage of the numerous types of software that exist today to quickly analyze data. We relied on early versions of Excel and SPSS Statistics. It was a very manual and time-consuming process. The same was true for our community rehabilitation partners. Staff and partners were frustrated that we were more interested in “numbers than in people.” However, what was difficult for our team to understand was that numbers represent people and capacity. Better understanding of the numbers potentially meant better (and potentially more) overall services.

Over time, the Rehabilitation Services Administration (RSA) has required more data as part of evaluating agencies and their expectation that agencies evaluate community rehabilitation programs. Annual reports, and more recently, quarterly RSA-911 reporting have pushed agencies to continually be aware of performance analytics. Since the passage of the Workforce Innovation and Opportunities Act (WIOA), analytics have driven evaluation of all WIOA programs, in particular Vocational Rehabilitation, and Department of Labor programs. The most recent initiative of RSA has been the use of quarterly dashboards to evaluate specific performance areas. These visualizations are used to help agencies meet federally established expectations.

Vocational Rehabilitation Agencies

VR agencies often rely on their electronic case management software as the source of the raw data used to produce analytic reports. They can be as simple as demographic data regarding consumers served or as complicated as detailed analytics regarding expenditures and performance details. They can be sufficiently detailed to review the individual performance of a vocational rehabilitation counselor, a region of the state, or the entire state agency. Analytics can also provide understanding about the specific performance of contracted vendors. Ideally the case management system has core workbooks that provide information on focused topics for the agency. Agencies can also customize analytic visualizations to answer specific agency questions using these core workbooks. These visualizations allow the agency to review data, analyze data, organize data to develop response to the Rehabilitation Services Administration, WIOA partners, and state legislative leaders. Effective use of the analytics also creates an avenue for the VR agency to better maintain its case management system. It means that the agency can improve how the case management software is working. By using effective visualizations, the raw data is converted to more understandable representations of the agencies overall and unique performance. It is essential that State VR agencies are successful in using analytics to make performance decisions, financial decisions, staffing assignments, and represent their performance to monitoring sources.

Community Rehabilitation Programs and Supported Employment Providers

Community Rehabilitation Programs (CRPs) and Supported Employment Providers tend to use web-based electronic health records (EHRs) and web-based case management software that is simpler than the state vocational rehabilitation agencies because they are not required to respond to the almost 400 elements of data that state agencies must track. However, this does not diminish their opportunity to provide meaningful analytics and visualizations that help the program understand its own performance and effectively report this performance to state agency partners and funding sources. Effective case management software and EHRs have built in core data sets that support the program’s ability to provide effective visualizations about their performance. Typically, these include raw data charts, bar charts, pie charts, and line graphs. Additionally, the EHS software and case management software also provide extracts of data that can be used in other analytic software. This means the program can create its own visualizations based on what is uniquely important to the CRP or Supported Employment Provider. They can then measure their own key performance indicators (KPIs) for internal or external review. The better the program can describe its performance, the better decisions they can make, and the greater support they have from their funding sources and state agency partners.

What is Needed for Success?

Ideally the State VR agency or Community Rehabilitation Program is using web-based case management software that has sufficient core workbooks to meet their basic needs. The software should be able to replicate RSA dashboard, RSA-911 data, and required WIOA partner reports. For Community Rehabilitation Programs, these core workbooks should easily replicate required reports of their funding partners and internal KPIs. Next, the EHR or case management software should be able to easily download extracts into analytics software that can create unique visualizations representing the specific needs of the State VR agency or Community Rehabilitation Program. Several current analytics programs are being used in the rehabilitation community. Each include unique advantages and disadvantages depending upon the needs of the program. The most frequent analytic/visualization software used in the rehabilitation community are Power BI, Tableau, Microsoft Excel, and Google Data Studio. Power BI and Excel have an advantage of being part of the Office 365 package at no additional cost. Google Data studio is integrated with other Google software. Tableau has a greater ability to provide more sophisticated analysis. All these software options provide substantial visualizations to support the needs of VR agencies and Community Rehabilitation Programs. Finally, training regarding how to use any of these tools is essential. Fortunately, significant free training exists on YouTube and other online sources to meet the needs of most VR agencies and CRPs. Additional training can be purchased from any of the software companies if a program has greater needs.

Conclusion

VR agencies and CRPs can no longer rely on anecdotal stories about performance. There is increased demand across the board for greater details about performance and finances. There is an increased need to tell the story about VR success by detailing the numbers in effective visualizations. It is not an arena that will allow programs to move into the future without building better and more detailed analytic visualizations. VR agencies and CRPs must expect their case management software or EHR to help them easily manage analytics. However, they must also consider using analytic software that will help them create visualizations representing the Agency’s or CRP’s unique story. It is essential for all programs in the VR community to be successful in their use of analytics.