In 2004, a group of Coloradans sued the Colorado Department of Health Service (CDHS). Wait times for crucial food assistance programs were exceeding the legal limit, which led to the state’s most vulnerable not getting the vital services they need.
The lawsuit brought urgency to the task of reforming operations within the CDHS. When it was eventually settled in 2008, the resolution came with a caveat — the CDHS had to process applications in a timely manner 95% of the time for 12 consecutive months.
Meeting the target seemed improbable: in October 2007 only 70% of regular applicants and 46% of expedited applications to the scheme met the required timeframe.
But the department turned things around. With “C-Stat”, an extensive data and evidence-based framework aimed at making CDHS work more efficiently, it was hitting the required timeframe near-100% of the time by 2017. Here’s how the organisation did it, what it says about how public servants use data, and the leadership lessons to take from the success.
Inspired by the New York Police Department’s organisational management tool CompStat, C-Stat is a framework that requires all Colorado counties and departments within the CDHS to conduct performance meetings based on data analysis.
The CDHS oversees 25 health and human service programs, including facilities for at-risk youth, community living centres for veterans and the elderly, mental health institutions for mentally ill adults, and centres for developmentally disabled adults.
C-Stat fosters an environment of continuous development. It does this by, first, using a combination of data comparisons and follow-ups to learn how departments are improving, and second, by acknowledging departments that are succeeding.
The first steps of C-Stat require department managers to identify places where their department is underperforming, based on standards set by an oversight body or federal funder. Department managers then set a monthly goal that will be measured over the course of 12 months with progress reported to the Governor’s office monthly.
Although setting goals can be difficult for social services because it often involves measuring behaviours — for instance, it’s difficult to collect data on why people aren’t paying child support — the CDHS departments would set a measurable outcome for things where data may not be present, according to an IBM Center for Government study on C-Stat.
Initially, they would gather data that was already being collected from the state and federal governments to track progress. Over the years, the CDHS developed more measures and developed new technologies for data collection, such as developing a sophisticated data portal.
Although data collection and data analytics are important, unless department leaders are re-prioritising or implementing new strategies based on their “performance scorecard” —a monthly report that shows how close departments are to reaching their goals — the whole process of C-Stat isn’t being adequately carried out, Kamensky said.
C-Stat requires comparisons to inform and educate departments to drive improvements. Executive leadership meets regularly to discuss expectations for each department and discuss performance scorecards. Performance scorecards are used to recognise departments that are meeting targets and provide help for those that are falling behind.
For example, ten counties worked together during C-Stat meetings in 2012 to identify ways to make the benefits process run smoother. They recognised that the benefits processing system was outdated and worked together to secure funding to hire a contractor to modernise the system, which fed into the larger state system easier.
Wait times between 2012 – 2017 for benefits applications were then on target 98.76% for regular applications and 98.23% for expedited applications. The new expectation is that applicants will receive a response to their application in 48 hours.
Re-focusing investments in quality and timely data allowed department leaders to form new strategies for effective change based on quantifiable results.
Data engagement and leadership
Inspired leadership is required to manage the complicated dynamics between the 64 departments, 5,000 employees, hundreds of contractors, and oversee the annual budget of $2.2 billion.
“C-Stat isn’t just an initiative, it was his [CDHS head Reggie Bicha’s] leadership style, and that’s why it works in some places and not so much in others, because the leader has to be comfortable to use data and have regular means to devote his or her time to actually participate in these meetings,” said John Kamensky, senior fellow at the IBM Center for The Business of Government.
For C-Stat, executives commit 240 hours per year on performance meetings to discuss the data findings. Kamensky added that active engagement in meetings from top level executives is important for lower level managers to find it authentic and take the practice seriously.
According to Kamensky, Bicha also fostered an environment of trust. Departments and counties, for example, weren’t penalised when the data revealed they were not reaching targets and were instead given lee-way to fix problems. Bicha similarly guaranteed that there was active communication between the CDHS and external contractors to ensure that solutions were found, not blame.
Individuals and departments were also recognised for exceeding and successfully meeting targets, which helped generate good will towards the implementation of C-Stat.
In 2015, lawmakers signed a no confidence letter to replace Bicha due to his reforms within the child welfare departments, but governor John Hickenlooper refused the demands giving Bicha full reign to “innovate and improve” human services.
The results paid off, and Bicha was not only praised for his work, but instituted a larger framework of data sharing and collaboration between departments, counties, and state systems that delivered real results. – Amelia Axelsen
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