The Next Revolution in Big Data - Cognitive Analytics

Illumeo Blog's Profile

We wake up every day to news of something new and interesting that is being developed by a startup or even some venerable old technology behemoth. This decade is probably the one which caused the greatest disruption for many established industries and redefined the way business is done.

Despite having negative connotations, disruption is not a bad thing for established players. It’s just a shakeup which gets rid of the excess flab and forces the industry to think of new things. This is how researchers at some of the existing Business Intelligence firms came up with the concept of Cognitive Analytics.

Cognitive Analytics is the next step in the evolution of data processing and presentation. For example, many professionals still struggle with Excel (which is now 32 years old by the way) for their business planning, budgeting and reporting needs, many others have migrated to purpose built platforms and SaaS offerings which make your life much easier. These platforms can take data directly from the source (accounting software) and in a matter of seconds throw up nice looking graphs and charts with arrows pointing to the upper right corner of the screen (the kind your boss likes to see).

With Cognitive Analytics, however, even this is passé. Cognitive BI wants to turn the world of business marketing, finance, sales, etc. into a natural, two way conversation. The front end would be something similar to Siri or Cortana – you raise a query via speech or text and the system converts your natural speech into meaningful computer commands. The real work, however, happens at the back end.

Let’s have a look at how it might really work with the help of an example. Suppose you ask the Cognitive BI system, “How do I double my profits?”. The system will decipher the question as a goal seeking problem with the objective being to increase the “Net Profit” variable by 100%. The system has access to all your financials, procurement systems, customer management systems, vendor management system, invoices and purchase orders data, shipping manifests, banking limits and balances and so on. It will create a model which combines all of this information and plugs in the various variable and fixed costs. Once this is done, it is a far simpler matter to test scenarios and hypotheses. The system will use a goal seeking, iterative algorithm to come up with various steps which could lead to the doubling of profits.

Now, some variables are obviously not clearly defined or predictable. For example, the revenue might fluctuate, the currency rates will fluctuate, there might be transportation delays and so on. The system would assign a probability then, to each of its answers. Option 1 might be something like an 8 step process with a 95% chance of success which involves switching your vendor overseas and choosing a different shipping method. Option 2 might be an easier 3 step process but with only an 80% chance of success. The thing is, much of the non-value-add prep work is taken out, allowing the user to focus on the actual business issues.

Cognitive analytics is not restricted to the finance function. There is great potential in any field which relies on big data – like marketing for example. Cognitive analytics allows for smart automation which greatly speeds up the process of identifying consumer behaviors and patterns. In fact, the relationship between cause and effect or stimuli and response in consumer behavior is sometimes so subtle that marketers can’t even imagine unraveling all of it. However, cognitive systems would be able create a map of these responses to stimuli and eventually maybe even replicate consumer behavior itself!

The best thing with Cognitive BI is that you can test hypotheses all day long and come up with solutions that you didn’t even know existed. Will such a system herald in a new era of business growth and opportunity by revealing hidden insights and leading us to new ways of thinking? We think yes, but maybe we should ask Siri!