Tag Archives: predictive analysis

Preventing Crime Using Predictive Analytics

In the 2002 futuristic movie “Minority Report,” Tom Cruise heads up a police division called PreCrime. This unit uses predictive analysis collected from mutants to arrest the would-be criminal before the crime is committed. The movie is set in 2054 and while I don’t think we have crime fighting mutants among us, we do have computers that make predictive analysis in police work a reality in 2017.

Predictive Analysis

Predictive analysis uses data mining, statistics, computer modeling, and machine learning to predict future events. This can help companies or agencies to better position a product launch or develop a business continuity plan. It can also help them forecast demand for products or services. Retail stores have used this science for years to plan for resources based on a number of factors such as the day of the week, day of the year, weather, and other data points. Dunkin’ Donuts, for example, uses same day sales for the last year as a factor in deciding how many donuts to start on any given day. This helps to reduce waste from too much product and ensures that a customer can always get a French cruller at the end of a busy day.


This same predictive analysis is being applied to crime prevention. Predpol is an advanced analytics application that police agencies in California, Maryland, Florida, Georgia, Washington and elsewhere are using. The software collects three historical data points: past type of crime, place of crime, and time of crime.

Through historical analysis, Predpol developers have discovered that there is a pattern to crime and criminals and by mining for those three data points the application can predict where crime is likely to occur in the future. There is no personally identifiable information collected or used so as to prevent biases or profiling. Once the predictive analysis is complete, police assign extra patrols to discourage crime where it is expected. Police report this application does indeed help reduce crime in their jurisdictions. This is a case of advanced analytics being used for positive results in communities.


To be fair, the output is only as good as the data entered. Information analysts often refer to this as “garbage in, garbage out.” Software such as Predpol and other applications rely on clean, accurate data to predict future hotspots. In a recent blog post from the Council On Foreign Relations, the authors argue that not all crimes are reported so these tools are limited because they start with an incomplete data set, which results in inaccurate or limited information about future crimes. Police go back to the areas where crimes were reported but miss other obvious opportunities because they lack a full data picture. It is important to factor in other data points in order to understand the full picture.


There will most likely be some pushback from people concerned about profiling of a particular neighborhood or audience, but with reasonably clean and unbiased data collection tools such as these can aid law enforcement agencies in fighting crime and creating safer communities.

Do you have other examples of data analytics that is helping to solve real world problems? Let me know your thoughts.

Author Kelly BrownAbout Kelly Brown

Kelly Brown is an IT professional and assistant professor of practice for the UO Applied Information Management Master’s Degree Program. He writes about IT and business topics that keep him up at night.

Workplace Trends: Increasing Employee Engagement

As the US economy continued to grow in 2016, employers added more jobs and competition for jobs increased. By the end of the year, the Bureau of Labor Statistics reported 5.5 million unfilled jobs. Part of that is due to a skills mismatch and part to competition for a finite number of workers. What do employers need to do to fill all of these openings? I did some research on workplace trends that will hopefully attract workers to these jobs.

Generation Y and Z

The median tenure with an employer is currently 4.6 years. Among millennials, the statistic is 2.8 years. Millennials are concerned about respect and about doing great work. They are more confident in their skills and switch employers when they don’t feel respected or feel that their work is not meaningful. Employers will need to combat this with more transparency. Instead of rolling out new policies, companies will also need to explain the rationale behind the decisions. Better yet, employees should be involved in policy making. Generation Y and soon to follow Generation Z, are both tech savvy so it will be harder in the future to not be transparent. If you don’t believe me, look at Glassdoor.com to see what current and past employees are saying about your company.

 Employee Experience

In recent years, we have used data analytics to increase our knowledge about customers, potential customers, and even suppliers. This year, companies are turning the lens inward to observe employee experience and satisfaction. IBM has been developing people analytics tools as a marketable product and for use in their own workforce. Human resource (HR) departments are able to do predictive analysis on employee satisfaction and hopefully reduce dissatisfaction and excessive turnover. It reminds me of the movie “Minority Report” where there was a method of predicting when a crime would occur and the police stopped the crime before it happened. Perhaps HR can swoop in and persuade a key employee not to leave the organization since it costs a lot more to replace than retain one. HR departments are changing to meet organizational needs, and people analytics is one tool they will be using more in the future.

Blended Workforce

The gig or freelance economy has grown over the last few years, but the emphasis this year will be on blending these contractors with a traditional workforce. Freelancers work on discrete, time-based jobs or projects and then move on after the job is complete. Websites such as Taskrabbit facilitate this. If the trend continues, employers will need to figure out how to blend short-term contractors, who generally make more money, and full time employees who get benefits on top of a salary. They serve different purposes toward the same goal and they often work side by side, particularly on technical jobs such as coding. How do you reward and retain loyal employees who work alongside those who have no loyalty and are hired for a specific task?


These are just some of the trends that employers will be working through in 2017. Some can be aided by technology but most are a matter of attracting and retaining a talented and dedicated workforce in a competitive market.

What other workplace trends do you see for 2017? Let me know your thoughts.

Author Kelly BrownAbout Kelly Brown

Kelly Brown is an IT professional and assistant professor of practice for the UO Applied Information Management Master’s Degree Program. He writes about IT and business topics that keep him up at night.