Cognitive 101: Cognitive Data, Where do I go from here?
I agree with Forrester: “all companies are in the data business now.” The thing is that companies are not really good at using their data — let alone being good at using their data to make better decisions in real time. Why? Because enterprises today only access, at most, 20% of their (structured and easy to read by technology) data — 80% remains dark because it’s unstructured data (AKA data that is hard for technology to read and assess).
Enter cognitive technology.
In order for enterprises to more fully tap into their data, they will have to use cognitive technology to analyze it. Cognitive technology will sift through all of an enterprise’s (structured and unstructured) data, understand it, learn from it, and draw conclusions to augment a knowledge worker’s (i.e. C-Suite, line-of-business, etc) ability to do their job.
Enter cognitive data.
The IDC predicts that by 2020, 50% of all business analytics software will include prescriptive analytics built on cognitive computing functionality and services embedded in new apps. So cognitive data will simply be the outcome of leveraging your enterprise’s data to the max and abstracting real time information to help you, among many other things, make better decisions for the business.
Is cognitive data real?
Well, according to Computer Weekly, over 89 percent of telecom executives believe cognition will have a critical impact on their future business. In insurance, 96 percent of insurers plan on investing in cognition capabilities. You hear similar sentiments from a myriad of industries.
Who is heading down the cognitive data path?
In his post, “Beyond Big Data: From Analytics to Cognition,” International Institute for Analytics Director of Research, Thomas Davenport, notes three companies that are down the path of cognitive data: Bosch, GE and Toyota are 100% in on advancing data analytics:
The Bosch Group is using intelligent fleet management, intelligent vehicle-charging infrastructures, intelligent energy management, intelligent security video analysis, and much more. GE is using sensors streaming data from turbines, locomotives, jet engines, and medical-imaging devices. Toyota is using telematics.
Other companies on the same page are American Express, Capital One, and JP Morgan Chase.
How does this work?
In brief, here’s how cognitive data technology works:
- First, there is an automatic classification and extraction of information (including text, photos and handwriting) from complex and variable docs / data in real time
- Second, there is an analysis of content (to understand information in context) and then the technology chooses an appropriate response
- Next, the technology runs application rules to make sure docs / data only go to the right people (who can take action)
- Fourth, the technology learns through training; users can give it example docs / data to learn from
- Next, the technology will create a knowledge base over time, and in the long-run, shorten response times, boost classification of docs / data accuracy.
It is at the end of this process that the technology provides a knowledge worker with insight to use to augment her abilities — allowing for faster and more precise decision making and business process execution.
It sounds too good to be true. Are there any downsides to cognitive data?
Yes. Two big ones that come to mind include: having a risk of running into security breaches (but as you may have already guessed there are cognitive security solutions for that!) and, most importantly, getting your enterprise to a point where you can (and it makes sense) to deploy cognitive technology.
Know how ready you are for cognitive solutions. If you don’t know, I suggest you speak with your tech team and tech partners.
Where do I go from here? I’m interested in cognitive data.
A great answer came from IBM InterConnect 2016. Watch the video here or keep reading.
You can go in many directions, of course. But to make it easy here are three paths to consider on your cognitive journey:
- Dip your toes into cognitive computing. Start with cognitive apps.
- Leverage a cognitive computing SaaS solution.
- Go all in and decide to transform your company into a cognitive business (be aware that this option will take a lot of capital and many years to do).
And there you go.
Cognitive data is a powerful technology that will inevitably transform the way we work (live, learn, and play) one step at a time.
But remember that you need to start with data. If there is no data there is no cognitive computing and no cognitive data.
Good thing we have mounds of it, right?!
Where are you with your cognitive journey? Is there another aspect of the cognitive / AI world that you would like to learn more about? Happy to get some answers for you.
“Cognitive 101” is an introductory series on the world of Cognitive Computing and Artificial Intelligence (AI). Written by Lolita Taub and written for C-suite and Line-of-Business seeking to address business challenges and goals using the smartest tech.
Originally published at www.huffingtonpost.com on September 20, 2016.