SAPPOV: Broken Windows And Broken Lives – How Data Make A Difference
by Art Dorfman Vice President US Public Sector
Data analysis can often seem like an abstract process – something done to data by computers. But the effects data analytics can have are very real – and they could be the difference between life and death.
You have probably heard of the broken windows theory: the idea that a building with a few broken windows is a danger sign. If they are not repaired, a few more will be broken. Eventually, the building becomes uninhabitable, or is occupied illegally, or burns down – damaging the homes or businesses around it.
Opinions differ about whether this theory is accurate – but that doesn’t stop the sight of a broken window being cause for concern in a neighborhood. When I see a house with danger signs like broken windows, it makes me worry about my own home and neighborhood. It used to make me wonder why the city did not take action. When I started working in the public sector, I found out.
Identifying a problem property involves collating many different reports from different agencies and disparate systems: noise citations, code violations, repair reports, police calls, permits, and inspections. Without a unified view of the information, it is hard to target limited resources for maximum effectiveness – and homes and neighborhoods slip into disrepair.
Connecting the data dots
These are data problems – and data are part of the answer. In my home of New England, SAP has worked with the Mayor of Boston’s office to build a Problem Properties Dashboard. The innovative application of SAP HANA’s in-memory processing technology in Boston has reduced the time and effort required to do analysis. It used to take several days for each “problem property”. Now analysis of the whole city can be completed in seconds.
Inputs from multiple agencies are now brought together for analysis by an SAP HANA-based data analytic system. Members of the Problem Properties Task Force receive regular reports and alerts about properties marked as problematic or on a watch list. Issues can be dealt with collaboratively and quickly – reducing the time from the first danger signs to an effective response from weeks to days.
Going beyond traditional analytics, the City of Boston has been innovating further by taking advantage of HANA’s native geospatial analysis capabilities and joint partner ESRI’s geodatabase management capability. Now that the tools are geospatially enabled, display ofdata is even more meaningful. District police captains also utilize this important information resource.
Using the Problem Properties Dashboard, the City of Boston can instantaneously identify and respond to quality of life issues before they escalate in severity. But the transformation of masses of data into actionable information has the power to effect even more dramatic change.
For example, the State of Indiana is aggregating and analysing multiple data sets from child welfare record systems, probation services, the Department of Health and the National Centre for Health Statistics. These analyses help to identify at-risk children and direct interventions to target those most in danger of abuse and neglect. Human supervision would not be able to see the patterns in the reports, but automated data analytics can predict danger, prescribe solutions and prevent avoidable tragedies.
These are cases where data analytics are being used not to interrogate data after the fact, but to detect where the right action can avert a crisis – and potentially save lives.