Moving on, what we recognize is that analytics is not a destination. It's really what we do with predictive analytics solutions which makes a difference. This slide indicates really that we can use analytics to ensure that the insurance company is meeting the strategy intended set out at the beginning, and if that strategy is being missed or diverted to make the right connection, analytics can help us in terms of the creation of new tactics to deliver on a strategic imperative, for example, or for the creation of best practices to modify our behaviors.
The analytics solution can fit in many part of the organization through distribution, through to sales, supply chain, operational management, marketing, and claims. We will be talking specifically about a couple of those areas a little later.
At the end of the day we're not doing this for the fun of it. It's around using analytics to change your behaviors and change our practices for an insurance company to obtain competitive advantage and to create a differentiated service and product, and ultimately to obtain profitable growth.
We are nowadays in what's described as the fourth age of analytics, and it might be helpful for you as individuals just to think about where you sit in this particular hierarchy of analytics. The foundational analytics is very much the description level, the use of BI tools for reporting to identify what has happened and what is currently happening.
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Second Layer of Analytics
The second layer of analytics is in the area of prediction which is our focus today which helps us anticipate what may happen and perhaps raise alerts or forecast. The third age is what we call prescriptive where we align rule based technology into our predictive models to help us automate our decision.
The fourth age is what we called the cognitive age, which certainly some of the leading insurers are already beginning to think about. The cognitive, again the topic in its own right, some might argue that cognitive are not artificial intelligence but very closely aligned. The reality is that there is a subtle difference. We viewed cognitive analytics as being the use of analytics to help inform decision making, whereupon artificial intelligence is the ability to make decisions for the system to make decisions in its own right.
Actually an interesting and challenging conversation might raise a question at the end of the day. Maybe the key thing for you to take into account is what organizations like Gartner are suggesting. They're saying that 50% of all businesses will be making decisions using artificial intelligence and prediction.
The challenge really is if there's a roadmap towards that situation or maybe a little later than that, where are you on your roadmap? Certainly you won't be able to change overnight, but there can be steps you are taking today which help you compete in the world in height of 10 years time.