Digital Transformation is the latest wave of applying digital technologies to improve government services and operations. In this blog, I’ll explore what Digital Transformation in government really is and how it differs from other initiatives of applying digital technology in government.
The use of digital technologies in government started several decades ago with the introduction of the first mainframe computer into government and has been growing ever since. Before we got to the era of “Digital Transformation” what were the main waves of applying technology in government and how is “Digital Transformation” different?
- The first wave was “Government Computerization“: This was the wave of using computers to improve the key internal government operations, such as better accounting, planning and consolidation. This is, for most of the world’s governments, a mature and largely done phase. Improvements, upgrades and enhancements of the systems will continue especially as impacted by the other waves described below.
- The second wave was the era of “E-Government“: E-Governemnt (“E-Gov” for short) was characterized by using the Internet specifically to digitize government processes and in particular government services as used by the public. This wave consisted predominantly of implementing the digital equivalent to legacy government services.
- The third wave was the era of “Smart Government” which built on e-gov by re-imagining government processes to be more citizen-centric rather than the traditional department-centric design of processes. This wave greatly improved the way citizen’s interact with government and presented them with a single-window to government and also afforded government a 360-degree comprehensive view of the citizen. This wave is still unfolding around the world and will continue to develop over the next several years. New technological breakthroughs, such as Blockchain and Machine Learning, are opening up new vistas for improved service and operations.
- The fourth and newest wave is Digital Transformation of Government. What sets Digital Transformation apart from “Smart Government” is that Digital Transformation is defined as the initiative(s) resulting from addressing one or more of the following questions:
- How can we use data, and Big Data in particular, to provide services or do something that could not be provided or done otherwise?
- How can we use IoT (Internet of Things) to provide services or do something that could not be provided or done otherwise?
- How can “Data” become the service?
In this blog, part 1 of a 2-part series, I will briefly examine the first point above, the use of data and big data to offer services that could not be done otherwise. This is known as the “Data Driven Government“.
Government (every government) is one of the most prolific generators of data: every transaction or interaction between government and citizen, or between government and business results in ever more data added to government. The challenge is not in having enough data but rather in turning this data into actionable insight and valuable information. Up until recently, few organizations had the ability to sift through this huge amount of data and glean valuable information out of it. Recent advances however are making it possible for large and small governments to undertake this very effectively. These advances include pervasive- or hyper-connectivity (with all system being connected to the Internet and each other), cost-effective super-computing using industry-standard platforms, cloud computing and improved cyber-security.
“Data Driven Government” is the use of Big Data coupled with advanced and predictive analytics to inform government decisions, provide greater insight and allow government to allocate resources to where they are most effective and impactful.
One shining example is the State of Indiana in the United States and its use of Big Data and Advanced Analytics for reducing infant mortality. Indiana’s infant mortality stood at 7.7 per 1,000 live births in 2011 falling in the bottom 20% of all states for this key health indicator. Furthermore, the Centers for Disease Control (CDC) classified Indiana among the states where no significant improvement had happened in the previous 6 years, whereas the U.S. national average dropped by 12%. This elevated infant mortality to be among the state’s top priorities.
The government commissioned a data-driven analysis that unified data from 15 previously unlinked data sets and departments resulting in 9 billion lines of data. By applying advanced analytics and machine learning techniques, 3 key findings were achieved (source: A summary of findings and quantitative investigation targeted at: Reducing Infant Mortality in Indiana, December 2014):
- Infant mortality risk in the state of Indiana is not randomly distributed, but exhibits statistically significant patterns that could be used for targeted investment of resources to improve outcomes.
- Inadequate prenatal care, Medicaid enrollment, and young maternal age were shown to be the strongest predictors for adverse birth outcomes.
- While the identified high-risk subpopulations account for only 1.6% of all births in Indiana, they account for nearly 50% of infant deaths, suggesting that the identified subpopulations are not only significant, but could be used as the basis for targeted interventions.
With this insight the state of Indiana was able to truly tailor solutions and programs to the people who need help the most, increasing the effectiveness of such interventions and savings lives across the state.