Over the past decade or so, analytics has undergone a rapid transformation. During its initial stages, analytics was used more as a reactionary measure i.e., to observe the business trends of the past. So, there was a significant time lapse between the pain points and the corresponding course correction. But over the years, analytics bridged this time gap and is currently helping businesses take real-time decisions. Not just that, it is opening up avenues to predict future outcomes so that decision making is more proactive. This paved way for analytics being the backbone of “Strategy” and thus we saw the role of Chief Data/Analytics Officer joining the C-suite. Now with business organizations across the globe embracing Analytics like they did never before, the important question to be asked is “Do citizens have the right to expect their governments to be run on par with the best business organizations?”. The answer to this question is a resounding Yes and this was precisely the vision of Mr. Bloomberg, Mayor of New York city(more on this later in the article), who had setup an Analytics division which helped in making New York a model city in terms of governance.
Government agencies have huge volumes of data and more often than not there would be little/no dialogue happening between departments.This essentially makes them work in silos which curbs the possibility of decision making using collective information. The insights that can be derived out of having a common data warehouse and tapping into the collective knowledge of various departments is left to one’s imagination. It would generate outcomes more than sum of its parts. Now let’s look at some of the Why, What and How of a typical city government’s problems and then we will look at how Analytics, with its arsenal of tools, helps tackle the toughest of these problems.
These are just a few ways that Governments, at least in the developed countries, can utilize the potential of analytics and big data to help serve people better. As is the case with business organizations, it would take some time for governments of developing countries to catch up with their developed counterparts. Now let’s look at some of the case studies and real world examples of how Governments addressed some of the issues mentioned above and how they tapped into an ocean of data to discover pearls of insights.
MODA:
Formally instituted by Michael Bloomberg, Mayor of NYC, at the beginning of 2013, the Mayor’s Office of Data Analytics (MODA) had a clear vision of using data analytics for a more effective and transparent government. MODA represents a paradigm shift in how government works – one that is guided primarily by data and the expertise of the people behind it. MODA created a datawarehouse by the name DataBridge, a common platform to facilitate inter-agency data handshake. The following are some of the major achievements of MODA
PredPol:
Using Big Data and Analytics to reduce crime on the streets is also getting traction these days. Predictive Policing is one such endeavor. The PredPol tool was developed over the course of six years by a team of PhD mathematicians and social scientists at UCLA, Santa Clara University, and UC Irvine in close collaboration with crime analysts and line level officers at the Los Angeles and Santa Cruz Police Departments. It comes with a simple mission of having police officers at the right place, at the right time to prevent crime. To accomplish its mission, PredPol processes crime data in order to:
Los Angeles Police Department (LAPD) scored big success by deploying PredPol. Crimes in the Los Angeles foothill division came down by 13% in the 4 months following the rollout of PredPol compared to an increase of 0.4% in the rest of the city where the rollout had not happened. Over this time period Foothill division was a leader in crime rate reduction among LAPD’s divisions. Similar reductions have been seen in other cities that implemented the tool. LAPD said that they enjoyed a “day without crime” on Feb 13 ’14 in the Foothill division, which stretches 50-square miles, home to more than 250,000 people.
Tackling Fraud and Waste:
Appalling as they may seem, these numbers merely point us to the tip of the iceberg.It is high time Governments take appropriate measures to keep a check on fraudsters from siphoning of funds. Governments could learn a great deal from the Banking and Financial industry in their efforts to curb fraud using advanced analytics. Research by Accenture indicates that the most effective solution for annihilating government fraud at all levels is achieved when leaders drive an enterprise approachthroughout their agencies, integrating andapplying analytics insights throughoutend-to-end processes.
Examples of corrective measures:
MODA, PredPol, Washington State Department’s initiatives are steps in the right direction. With companies like IBM and Accenture envisioning smarter cities and governments, it is just a matter of time for policy and decision making in government agencies to be backed up by statistics and driven by data. Leaders have a big role to play in this transition, to be able to see the big picture and deploy holistic analytic solutions for dealing with the gamut of problems their agencies are facing. I would like to know your views/comments/ideas about the topics mentioned in the article. More precisely, do you see how analytics can empower our municipalities and corporations to serve us better? Do you see how the Govt. of India can lap up data driven decision making? With a PM who stresses on Good Governance and efficient bureaucracy, how can analytics showcase the answers for cutting the costs, increasing ROI?
This article was submitted by Mr. Prashanth Pattamatta as part of his application for Analytics Vidhya Apprentice programme. Prashanth completed his PGDM (MBA) from IMT Ghaziabad, a top rated private B-school in India and has more than 4 years of IT / Analytics experience across several IT giants. He is extremely passionate about learning Analytics and hence wants to be part of Analytics Vidhya Apprentice programme.
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