Applying Real Time and Predictive Analysis to Visitor Identity and Access Management

Through the use of real-time and predictive analytics, that data can become a powerful resource. The use of Real-time and predictive analytics enables organizations to turn their data stores into knowledge and insight with swiftness and exactness as required time on time, and I think this cannot be achieved by any human. This insight could enable a different action to be taken – potentially improving an outcome, saving money or even saving lives, yes really I mean it.

Let us imagine a situation in a hospital with the Identity and access Management Application installed, of the last 100 visitors to the hospital with this age group, department, affiliated clinics, 31% visited the Neurology Department, 45% visited Intensive care unit and 30% visited Cardiology department and 5% other diagnosis. The one month visit rate was 30% between the age group 20-30 years and 35% between the age group 40 -50 years and the peak visit timings was 7.00 AM to 8:00AM  and 3:00 PM to 4:00 PM. Now the Security Administrator of the hospital can explore data across the departments, time and age or any other parameters. Now decision can be made for an individual department using population based content.

Emerging real-time analytics have the potential to provide this kind of significant value. The idea is to enable depth of insight across a broad distributed set of data — at a minimum, across a hospital and its many departments and affiliated clinics, but even better across its multiple hospitals, where traditionally an observable pattern can be hidden by the number of visitors, repeated visitors.

Predictive analytics work in a similar way, but with a focus on analyzing data and providing probabilities of various outcomes in the future. In the scenario above, imagine Predictive analytics system provides the additional information, like the predictive return of the visitors due to the patient admitted for a longer term.  A same visitor with the 48 hour return rate on initial visit. Based on this type ok knowledge, the security officers can predict the Visitor flow to each department and relatively plan the workforce in each department.

So both real-time and predictive analytics take the power of data beyond mere storage, categorization and traditional periodic reporting. Key insights like the proverb needle in a haystack; just increasing the amount of data storage is as good as adding more and more hay, but real-time and predictive analytics serve as a powerful magnet to accelerate the search for the needle