In the private sector, applying analytics and using big data is a major trend that’s gaining momentum — 73 percent of private-sector enterprises said they are now using analytics or plan to start in the next two years, according to a leading research firm’s latest report. Likewise, applying analytics to big data is “one of the hottest trends in the public sector,” according to Tod Newcombe, a senior editor with Government Technology.
In the private sector, the two top areas of focus for big data projects are improving business process efficiency and customer experience. On the public-sector side, the range of challenges being addressed is more diverse — amazingly so, in fact.
- Suffolk County, N.Y., has built data models to predict the location of mosquito population outbreaks and risk for West Nile virus infections.
- Chicago’s Rodent Control Agency has applied analytics to better target the highest risk areas for rat problems, and reduced 311 calls about rodent problems by 15 percent in one year as a result.
- The Indiana Department of Revenue spotted more than 74,000 returns filed with stolen or manufactured identities in 2014 with a new identity-matching effort that compares tax returns to a database of fraudulent or stolen identities. This was a 4,900 percent increase over the prior year, when just 1,500 cases of identity theft were detected.
A number of U.S. law enforcement agencies are applying analytics to: investigate the smuggling and use of contraband cellphones and other illegal activities in a major state prison system; identify the top perpetrators of illegal gun sales in an East Coast state; and apply social network analysis to identify the most connected leaders in networks of violent gangs in a major city.
These applications aren’t about predicting future criminal activity, but are focused on helping investigators quickly determine who, what, where and how crime has happened, and helping them identify and apprehend the right suspects quickly and efficiently. Clues are often hidden in vast quantities of data; and effective analytics is essential in helping join the dots and uncover the truth.
Why isn’t the adoption of big data analytics moving faster?
There are at least four consistent obstacles:
Money — The Wynyard Group has surveyed hundreds of law enforcement leaders on their use and attitudes toward analytics over the last two years. In 2015, 88 percent of surveyed law enforcement leaders said they believed that intelligence-led policing and data analytics has the potential to improve law enforcement effectiveness, but only 34 percent said they were currently using analytics. The main obstacle? A lack of money, according to 66 percent of respondents.
IT resources — Most state and city police agencies are resource-constrained in this area. Often, police agencies rely on IT teams that must serve many or all of a city’s, county’s or state’s agencies, so they don’t always get the required level of IT leadership and resources applied to projects.
Data quality and access — The concept of getting value from big data appears simple, but the reality is usually very challenging. Challenges include getting data access in the first place, data hygiene issues, building the necessary level of IT infrastructure to process and store the data, and getting approvals to work in a cloud environment.
Risk taking — Government leaders can be wary about pursuing projects with perceived risk or uncertainty, and innovative data analytics projects are often a step into the unknown.
Even in the face of those obstacles, it’s encouraging to see the growing momentum in law enforcement to pursue the promise of analytics and “intelligence-led policing.” While traditional hot-spot policing has been around for two decades, the capabilities are growing in sophistication.
“Since the advent of CompStat in New York in 1994, police departments have used statistical analysis to predict criminal patterns,” wrote Harvard Professor Stephen Goldsmith in a 2014 paper titled Digital Transformations: Wiring the Responsive City. “Today public safety agencies are using sophisticated data mining to produce insights and focus on underlying causes. The breakthroughs for these agencies will again set a pattern for government, as predictive analytics power the advance of ever-more effective government.”
We are at a tipping point for seeing an increasing level of interest in applying analytics in federal, state and local government. This is driven in part by necessity as data volumes continue to exponentially increase and the answers get harder to find without the use of analytics. It’s also driven by leaders in government becoming more comfortable with technology and being willing to learn the lessons of past technology project failures rather than be constrained by them. We see more and more public agencies evaluating how they can apply analytics to their specific missions and the growing acceptance of cloud computing offers a way to overcome the challenge of the under-resourced IT departments outlined above.
The recently published Federal Big Data Research and Development Strategic Plan promotes the value locked within big data and underscores the tremendous promise ahead for applying analytics to address a diverse range of public-sector challenges.
“We envision a big data innovation ecosystem in which the ability to analyze, extract information from, and make decisions and discoveries based upon large, diverse and real-time data sets enables new capabilities for federal agencies and the nation at large; accelerates the process of scientific discovery and innovation; leads to new fields of research and new areas of inquiry that would otherwise be impossible; educates the next generation of 21st-century scientists and engineers; and promotes new economic growth,” according to the plan.
Derek Brown is vice president of the Americas for the Wynyard Group, a market leader in crime fighting software.
