I enjoy watching TV crime series like Law and Order, Crime Series Investigation (CSI), CriminalMinds, Numb3rs, Person of Interest, as well as real-life mystery stories on shows like 20/20 and others. Obviously, the popularity of these types of shows means I'm not the only one who enjoys this type of entertainment.
Here at SAS, we often distinguish between two major uses of analytics:
- Reporting on historical data to discover patterns and trends based on past events. Often referred to as business intelligence, this type of analysis can identify root causes of events.
- Advanced analytics that can be used to make predictions or optimize complex processes based on multiple data sources. This type of analysis can help you identify relevant factors that occur prior to an event you are investigating, so you can monitor and detect similar situations in the future. This allows you to take proactive migration actions that can lessen the impact or potentially avoid a future situation all together.
Getting back to our crime shows, Law and Order, CSI, and 20/20 are examples of shows that tend to use historic data or business intelligence, because they are all about root cause analysis based on historic data or events that have occurred in the past.
On the other hand, shows like Criminal Minds, Numb3rs, and Person of Interest are examples of applying more advanced analytics to root cause analysis, because these shows not only detect the root cause analysis but go beyond solving the historical situation to focus on predicting future events before they occur. Using these more advanced methods, they can make decisions and take actions to avoid or lessen the impact of another occurrence from happening.
Industry examples using advanced analytics
How does this apply to industry issues? Well, I'm glad you asked. This analytic process can be applied across industries and departments to help improve processes and ultimately the bottom-line of any organization.
In the oil and gas industry, advanced analytics can help improve safety and reduce non-productive time in both upstream and downstream processes. In the upstream exploration & production area, analytics can be applied to improve overall drilling efficiency and safety. In the downstream area, analytics are used to proactively monitor heater performance.
In the utilities space, this same type of analytic processing can help utilities before, during, and after outages and for improving customer satisfaction by offering the right energy program to the right customers.
Analytic based asset monitoring across the smart grid can similarly benefit from the same type of proactive monitoring as the heaters in oil and gas related plants. Any type of fraud whether its energy theft in utilities, tax evasion, insurance or medicaid fraud, or financial fraud can all benefit from applying this same type of analytical process.
These industries aren't solving murder mysteries on a Hollywood set, but they are applying analytics to solve real world problems with pretty impressive results. For an example that does involve solving crimes, read this recent post about using analytics to improve anti-money laundering (AML).