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AutoGov/Government Case Study

Company Profile

Through our case studies, AutoGov profiles business situations where our client’s business process strategy has been significantly impacted by our tactical technology solutions. These solutions are carefully crafted to provide dynamic input into the decision-making matrix and designed to create maximum operational efficiency.

The organization profiled in this case study is a Social Services Department in this state’s fourth largest state agency. The agency collaborates with the state’s counties and largest city to:

  1. Provide foster care, adoption and protective services to children
  2. Collect and distribute child support payments
  3. Provide temporary cash, food stamps and medical assistance to families

The department also funds programs for homeless persons, refugees, and migrant workers, victims of crime and women who are displaced, battered or assaulted. In total, the department serves over 700,000 people in need.

Business Situation

Like many of its counterparts across the country, this state’s Social Services Department faces enormous backlogs in determining applicant eligibility for social services. Overwhelming numbers of needy citizens juxtaposed against continuing budget reductions limit the ability to hire additional staff and place ongoing pressure on the business process. Delays in decisions are a significant issue for people who require medical payment assistance for their nursing home stays.

The agency presented an urgent need to AutoGov to devise a solution that would expedite accurate decisions without engaging additional staff. The solution needed to be technology-driven to provide maximum impact and reach across all offices within the department’s jurisdiction.

Technical Challenge

AutoGov found that the department uses an older main frame system to track and manage assistance applications. All applications are paper-based requiring staff workers to input the collected data into the system. Backlogs occur frequently even though workers are required to make accurate decisions within 60 days.

The outdated paper-based system and aging technical tools only exacerbate the problem. Workers must double check information submitted by applicants regarding their income and assets. In addition, without a system to easily merge outside data sources for verification and validation into a single tool, additional time is added into the evaluation process.


After analysis, AutoGov determined that the solution to the department’s challenges was within reach but it would require merging of technology with a business process redesign.

First, AutoGov designed and built an algorithmic model that predicted the Medicaid eligibility risk level of each applicant. This model was developed through sophisticated data mining of the state’s historical case load for each program.

Since ease of use was a primary concern of the state, the algorithm was translated into a numeric score, accompanied by a list of the riskiest items present in each case. This solution enabled state workers to prioritize their work, focusing time and effort on cases that require the most work and ultimately those that present the greatest risk of slipping past the 60 day decision window.

Workers are now able to assess cases with scores on either end of the spectrum (very low risk, very high risk) and make quick disposal decisions. Those cases that score in the middle are prioritized and receive the most attention. The new process substantially reduces ambiguity and allows workers to focus on the pursuit of missing or risky information.


To achieve maximum benefit, the department began its implementation by using the new scoring tool to assess every case in its backlog. Within six weeks, the department had successfully retired the entire backlog with a 95% accuracy rate.

Simultaneously, the department found that it experienced a 30 percent overall increase in productivity. Quickly, the decision was made to deploy the solution into the business process. Today the department uses the AutoGov solution to score every long term care application it receives and is seeking to determine the impact a comparable solution could potentially have on other assistance programs.

Some of the additional benefits to our solution include:

A Final Word

Business process redesign rarely contemplates the level of sophistication AutoGov brought to this client. However, the pressure on this particular process is so intense that anything short of an innovative, highly advanced solution would have resulted in little benefit to the client.

Today, the state is moving toward a revamped understanding of how predictive technology can dramatically impact their day-to-day business processes. It is the sort of “out of the box” thinking that AutoGov brings to the table through our understanding of the power of analytics and the intelligent use of Big Data.

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