Guide to Building Data-Driven Organizations in the Public Sector

Managerial Experiments

Team 5

Topic Overview

We live in a culture that is driven by data. Over the past few decades the amount of information that has become available to us has skyrocketed. Technological advances have made it easier to provide data right in the palm of our hands. Technology such as software, smartphones, websites, digital maps and apps to manage our schedules. “Data can be transformative” (p.241) if those using the data know how to properly utilize it. It can be a powerful tool, but only if harness correctly.

One thing that hasn’t changed is that “our ability to learn from information hasn’t necessarily kept pace with its proliferation” (p. 243). In other words, we can accurately measure how much calories we consume in a day but how much does your cholesterol scores improve every week, month or year? We can improve our lives by making our days more productive, eating healthier, making education much more effective and our lives less stressful if we learn to harness these powerful tools.

What we currently suffer from is data overload, so much information makes it difficult to make decisions. This inability to make the best of the data we receive as it becomes more and more readily available is often referred to as “Information Blindness.” Each person’s minds will eventually reach a breaking point and when this occurs people start to ignore options, make bad choices or stop interacting with the information altogether.

We as humans can do a great job of absorbing information, if we break down the data into smaller meaningful pieces. When we do this, it is referred to as “Winnowing,” or “Scaffolding.” This process is the ability to break things down like you would a file cabinet and organize everything into folders and subfolders alphabetically, numerically or whichever method makes things easier to process. According to Eric Johnson a cognitive psychologist from Columbia University who studies decision making, “Our brains crave reducing things to two or three options” (p. 245).

Chapter Summaries

Absorbing Data

This chapter investigates how we absorb data and then transform this data into something useful. It discusses the South Avondale school district as being in an Academic Emergency due to dysfunction, crime, and poor academic scores. This is a community that has been in poverty for decades and this school district had to figure out way to changes things for the betterment of its community. One thing that isn’t an issue though is resources, the city spends 3 times as much per student at South Avondale versus other local school districts. Procter & Gamble invested funds in a computer lab, tutoring center and sports programs.

South Avondale put resources into sophisticated software to monitor each student’s performance. They have a website for every student that has a wealth of knowledge, such as test scores, attendance, homework, and classroom participation. However, six years after this was all created teachers started to admit that they didn’t really look at this wealth of data they had or the memos that they received each week and students continued to fail to meet educational standards. It wasn’t until they implemented the Elementary Initiative (EI) when things finally start making a turn for the better.

When the Elementary Initiative was implemented it forced the teachers to work with the data, then and only then did it impact the way they behaved. They learned by hand how to transform spreadsheets, statistics and online dashboards into meaningful plans. Teachers moved from passively absorbing the data to engaging it. Three years later South Avondale test scores went up so much that the White House hailed EI as model of inner-city reform.

How Iceland Saved its Teenagers

This video covers how teenagers in Iceland were out of control through the 1980’s and 1990’s. In 1998 roughly 42% of those teenagers surveyed said they had gotten drunk and became a focal point due to having the worst numbers in Europe when it came to drinking, smoking and drug abuse. Since then this number has dramatically reduced to just 5% and Iceland has become one of the best areas in Europe. They did this by only utilizing 5 methods.

The first method was to create a curfew for teenagers which meant that youth under 16 years of age must be in doors by 10:00 p.m., and in some place’s parents patrolled the neighborhoods. Secondly, the parents signed a pledge which covered rules that they agreed to for their children’s behavior. Some of the rules included, not to allow their children to consume alcohol and creating more family time. Third, parents had to keep their children occupied and in doing so families received a $500 voucher annually for each child to utilize on afterschool activities.

The fourth method implemented is to base things off science, teenagers fill out a survey on an annual basis. Data gathered covers different aspects of their lives such as relationships with peers and family, as well as substance use and how they feel. A report is created for each community and within two months of the survey each school has a finalized report of the findings, which then gives them the opportunity to fix things if needed. Finally, it is important to get the politicians involved, Iceland spends over 100 million a year on youth activities. Everyone is involved, from the teachers, to the parents, the youth and the politicians when it comes to building or creating a new program for the community. This model developed in Iceland has expanded to over 35 cities in Europe.

Using Big Data to Engineer a Better World

A variety of examples of how data is used to engineer a better world are presented in chapter four of Reality Mining. Participatory sensory projects, such as Serendipity, serve to mediate interactions in large companies or conferences. Data is collected identifying where a person is and what his/her interests are. When a match is identified, each participant is asked if they want to be connected. Only after consent, are the individuals connected. From this idea came the dating app MetroSpark which also requires consent. The key to big data adding value to a community comes only with contributions from the population. When the benefits are clear and privacy is maintained, people are more willing to share personal data to better their community.

Knowledge-brokering systems, such as Tacit, are created to facilitate the sharing of knowledge, interests, and relationships to increase workplace efficiencies. Tacit requires user confirmation in order to share identifying information.

Other ways mobile phones can improve the overall health of a community include applications to report blight to City departments, as well as running, cycling, and commuting routes. Behavior of people in neighborhoods correlated to traffic, air pollution or other environmental data could be useful. Health officials and doctors are interested in collecting data to identify systematic stressors in poor neighborhoods. Collecting data such as routes to school and wait time for public transit, from children’s cell phones could help identify ways to alleviate stressors. While many people may not be comfortable with their children being tracked, phone cost subsidies could be offered along with a trusted community member introducing the idea.

Key Take-Aways (for Yellowdig)

In general, people are great at absorbing data and are not skilled at transforming it into something useful. This can be attributed to data overload. Key is to use the data we collect in a meaningful way.

Iceland collected a great deal of data as they studied underage drinking, the most useful data was collected from the subjects themselves (students).

Data can be used to better communities, improve effeciencies, and connect people. Trust in privacy is increasing and individual use consent is imperative.

Discussion Questions

To what degree should analytic audits be done on data collected to identify the integrity and quality of the data? (Is the data accurate and can we trust it?)

How do we ensure the privacy of data collected but also the accessibility of it by people that can use it (for good)?

Are you more comfortable providing personal data to better a community’s health arena versus providing data for social arenas? Or are you equally uncomfortable providing personal data for both scenarios?

References