Open Data and Data Science are currently very popular topics but like any technologies they need a clearly defined purpose for their implementation to deliver business value.
For government this purpose can be articulated through the role they can play in achieving high performance goals, such as greatly improving social care while also reducing costs.
Harvard offers an excellent catalogue of use case studies that identify two core dynamics that make this high performance possible:
- From Reaction to Prevention
- Collaborative Case Management
From Reaction to Prevention
The case study for Boulder County is a keen example of both of these principles. Their adoption of an integrated service delivery system has been guided by a simple but powerful objective at the heart of their transformation:
focus on front-end and early intervention measures to prevent more costly services in the future.
It sounds an obvious goal but the reality for most stretched case workers is they are always in a reactive mode, dealing with the consequences of social challenges. These consequences have multiple levels of cascading impacts and costs for government, and the use of data science yields insights which instead enables them to proactively tackle those issues before the impacts occur.
Crime is a key scenario for illustrating this effect. In Predictive Tools for Public Safety the author describes a number of case studies of the police using data analytics to proactively deter crime, rather than always be responding to crimes after they happen. This can eliminate multiple costs such as the damages caused, prison and court system expenses.
Santa Cruz turned to an applied mathematician to develop PredPol, for Predictive Policing, which analyzes previous property crimes to predict where future ones will occur, and plots these hot spots on maps, which are provided to officers at shift briefings for them to utilize for purposes of targeted patrol to prevent the crimes.
In 2006 violent re-offenders established Philadelphia as one of the murder capitals of the USA, and to tackle the issue they employed machine learning algorithms for probationer backgrounds to estimate the likelihood of violent re-offense, prioritizing resources accordingly to reduce the likelihood of future crimes.
Data-driven Strategies for Reducing Homelessness describes how New York City used analytics to proactively identify which families most likely to face homelessness, and intervene to prevent this occurring. HomeBase reduced the number of shelter applications by nearly 50% and reduced the number of days in shelter by 70%, resulting in $1.37 in savings for every dollar spent on the program.
Collaborative Case Management
The second transformative foundation is a Case Management system that enables multi-discipline team collaboration across many different agencies and organizations.
Government suffers from being severely ‘stovepiped’ – They are rigidly organized departmentally and citizens have to interact with each individually in isolation. Boulder County defined and addressed this:
In the past, these services were managed by multiple agencies. But in 2008 the County began a system-wide shift to co-create solutions for complex family and community challenges by fully integrating health, housing, and human services. The idea was to generate a more self-sufficient, sustainable, and resilient community by focusing on reducing the social determinants of poor health, removing barriers to services, and moving the system upstream towards an early intervention and prevention model.
Identifying the needs overlap across agencies, such as housing clients also being recipients of food assistance, they recognized that multiple departments where servicing the same core social challenge, and sought to better collaborate to maximize their collective impact, what they call “wrap around case management”.
Boulder County established an integrated case management (ICM) team and case management software that pulled data from across all the agencies so that they could work as a virtual team which enabled key process capabilities:
- Track clients case histories across programs
- Refer clients to additional program areas
- Collaborate with other departments case workers
- Assemble a portfolio of services
This improved the uptake of individual programs; for example using integrated case management has helped support Boulder County officials as they begin implementing the Affordable Care Act.
Analyzing information shared across the agency, staff are able to identify clients in one program area who may be eligible for subsidized insurance or Medicaid coverage, and can then send out notifications to encourage enrollment.
Integrating Third Sector Services
A very important facet of this approach is the incorporation of the Third Sector organizations into the case management system. A multitude of social organizations such as homeless shelters play a part in the overall journey, and can be part of the client solution.
To further broaden the reach of the integrated case management system, county attorneys drafted memoranda of understanding to incorporate community partners such as nonprofits and community health centers.
Maturity Model – Open Data for Social Impact
These new approaches highlight the key role that Open Data can play. For example MyLA311 describes how LA utilized Open Data publishing to tackle the issue of integrating data from multiple legacy systems, for purposes of auditing call centre performance dynamics.
The City of Austin publishes the metric ‘Percent of Homeless Clients Residing in Shelters that Receive Case Management Services‘ to their Open Data portal. This identifies that a very low number of the chronically homeless are provided case management services, yielding the insights required to better target case work support to those needs.
These highlight the critical success factors for Open Data. In the Reuters white paper Does Open Data Need Journalism, they explore early Open Data projects and how many failed to deliver business or social value because they lacked a clear project objective and poor data quality methods. In short many were a result of governments simply seeking to ‘tick the Open Data box’ and defined success only as publishing the data, with no regard for its quality or its role in solving a particular need.
The field has now matured considerably and a number of best practice resources are available to better guide implementation strategies for Open Data.
The Open Data Institute offers this maturity model for developing these practices, and this blog from Joshua Tauberer describes how it can assist in defining and planning the the technological maturity journey:
The first foundation this establishes for transformation planning is that they define a continuum of technology maturity that integrates multiple other domains rather than treating it like yet another silo, such as Global Identifiers and APIs for example. This encourages and enables governments not to treat Open Data as a standalone project but as one component part of an overall enabling Open Platform Architecture in general.
Other resources offer guidance for how to link its use to meaningful social outcomes.
The Open Data Institute provides Assessment Tools for Open Data Initiatives, and the Sunlight Foundation published a four-step guide to help data professionals maximize the “social impact” and efficacy of those efforts. The 31-page document — called A Guide to Tactical Data Engagement — was written to help city leaders and residents collaborate on open data projects that improve government accountability and transparency, saying:
“Tactical Data Engagement is designed to help cities go beyond open data policy and even open data portals, to facilitate opportunities for the community use of open data to improve residents’ lives”.
Platformation of the Public Sector: Cloud Computing Tools at the Service of Social Change
In conclusion we can think of this overall trend as the ‘Platformation’ of the public sector. The integration of the Third Sector into government case management services is a key dynamic, and the potential for arming them with this mass scale of data-enabled insight is explored in this Canadian paper – Platformation – Cloud Computing Tools at the Service of Social Change.
Platformation prototypes new platforms for information sharing (platform + information = Platformation), which means it tests technological approaches that will enable nonprofits to operate like the open web.
They ask and imagine the huge potential for massive scale positive social transformation that would be made possible, simply through furnishing them with smarter data, and Open Data Science platforms will make this effect possible across government whole.