Cities buy software but are cities really getting the problem solving value from that software? Understanding the value of the huge amounts of data now available and designing the software and databases to yield solutions to difficult problems through predictive analysis of the data leads into the next generation in city software.
For hundreds of years paper has guided city operations. Memos, work orders, purchases, permits, ordinances defined the interdepartmental, interagency and public communications involving city government. Moving into the digital age, cities are thrilled by software’s promise to automate these traditional operations. But automating these operations with software barely scratches the surface of the gold mine of information that good software can offer to cities. But as cities rush to invest in the time and paper saving offered by software, I contend that cities are still in stage 1.0, moving from paper to automated data collection, in their use of software. Software offers much greater value to city operations and service than time saving and paper saving efficiencies.
Cities, and other public agencies like schools and non-profits, that want to enter software stage 2.0, moving from automated data collection to predictive analysis of data, and benefit from the gold mine of values that software can offer, must consider the following three issues:
- What problems do you want to solve?
Imagine a magic wand that would enable city managers to solve some of the thorniest problems in their jurisdictions? It is hard to even define the problems because city leaders assume solutions would require money they don’t have. In the early 1980’s when many large cities were enmeshed in crime fighting, George L. Kelling and James Q. Wilson offered the now famous “Broken Window” approach to managing the problem of crime. Police focus changed to look for signs of disorder and these signs could be tracked by reported physical evidence such as broken windows. The broader label for the “broken windows” approach is “predictive analysis”.
Whether the organization wants to know where to spend limited money to satisfy the most library book readers or to get troubled youth through high school graduation or to reduce the homeless population, be clear about the problems to solve. With city halls using more software, the likelihood that the data needed to solve complex social problems is within reach.
2. What are the data characteristics associated with the problem to be solved?
The beauty of software is that it allows for the accumulation of a huge amount of data, “Big Data”. This data offers the potential to be the new “magic wand” for the 21st century public official and brings cities into the 2.0 stage of software value, IF it is used effectively. Data offers visual patterns that highlight problems, predicts where problems may occur and suggests ways to solve problems. The description of the problem and the use of the data requires an iterative process that considers the community’s problems, the data describing these problems and the data available or potentially available through software. The software offers new opportunities for cities. But the reflection and deliberation necessary to define problems and to understand the significance of potentially available data using the lens of software technology, will be a new experience for many public sector officials. Step through this analysis and problem definition phase carefully. It will yield a list of attributes to add to the software database.
- Is the taxonomy for defining the data robust enough to solve the problems?
Back in the day of paper based work flow processing, organizations could only dream about finding the time to review thousands or hundreds of thousands of pieces of paper to figure out if there were patterns in permit requests, school attendance reports, ambulance calls, etc. When these processes were converted to machine readable data in stage 1.0 of cities’ software use, the relief at the reduction in paper usage was palpable. With new talk about “Predictive Analysis” and “Big Data”, local government service providers begin to sense new possibilities for solving social problems and building civic engagement in the community. But to make the most of these rich possibilities, software has to be selected with real problems in mind and a taxonomy developed for defining data elements before any data is entered.
What is a taxonomy? A taxonomy is the end result of assigning all the data collected according to all the data characteristics and categories that will allow it to be compared to other data. A taxonomy for software includes the concept of a unique identifier, for example, an address. It includes additional location information like neighborhood, precinct or zip code. It includes chronological information like the date of entry into the database, the date of acquisition, etc. It can include a wide range of additional information such as the reporting source: police, schools, etc., Time and thought spent developing a taxonomy is directly related to the ultimate value of the data for predicting and solving problems. Each data item must have a unique identifier. Each unique identifier should be related to as many other classifications and categories as feasible in order to make this process valuable.
This thoroughness in creating a taxonomy and developing a clean and useful database brings powerful rewards but comes with important responsibilities for protecting the privacy of citizens in the community. Clean data and privacy assurances will emerge as a key part of the discussion in city software 2.0 conversations.
by Barbara Thornton, AssetStewardship.com