How is HPA relevant in today’s world?
The key thing is which business process or use case within a certain industry it is relevant for. E.g. in retail there is a tremendous amount of POS data, inventory data and pricing. In order to manage promotions you need to do a high degree of calculation. Campaign management and marketing cuts across industry segments and organizations are always trying to get an uplift in marketing performance in order to do better segmentation. Moreover, there is a tremendous amount of data coming from social media. It is relevant to customer service, customer information, product-related information etc. It is vital for the Indian market as it has the three dimensions of volume, variety and velocity. There is the social segment where one can mine the data, segment it and interact with it in real-time. The Indian government is one of the foremost sectors using analytics because of the amount of data that it has to deal with.
In what way can organizations build a culture around analytics and derive value from the same?
There are companies that are more forward thinking that will leverage analytics rapidly. E.g. a third tier South African bank was competing against the big banks there. It was able to focus on what the competition was not doing well. It monitored the themes and, as soon as it figured out that something was not working, it began to hand out incentives and offers. In this manner, it was able to capture market share.
What is happening on the customer intelligence front?
Organizations have to use internal data along with external data for them to gain an overall view of their customers. This information needs to be integrated and cleansed and managed properly. Integrated marketing management is not about just making an offer but, rather, it’s about how you follow the customer lifecycle in terms of what they do, their interactions etc and mine that data to create a better campaign. Decision management is about how you get results from analytics in a way that business users can do something about it.
How does decision analytics differ from real time analytics?
Decision analytics is a higher level of analytics. Real time analytics is only an attribute in terms of the speed with which you can arrive at a decision. You may have different streams of real time data coming in where there is combination of events that need to be clustered before you can make a decision.
What are latest trends that you are witnessing in the field of Big Data?
Big Data is just getting started. Presently, organizations are struggling with information. They do not know what’s relevant, if they should store it and how they can extract value from it. According to a McKinsey report, organizations do not have enough skilled people to handle Big Data. India with its technology background, the kind of service-oriented mindset that it has is in the best position to take advantage of business analytics. Right now, there is a dearth of required skill-sets but once people begin to see financial gains, they will realize the need to modify their skill-sets. E.g North Carolina University started a program in Statistics and students who graduated from there ended up earning more than MBAs. The beauty of big data analytics is that you do not know if the model is right, but you can do a fast fail. Earlier, it took an organization a couple of months to test the effectiveness of a campaign. That time can be shrunk considerably.
When do you think analytics will be part of core infrastructure?
Over the last three to five years, analytics has become a part of the mainstream. Within the next two-three years it is going to become even more prevalent. Organizations invest a lot of money into storing data. If they are storing so much data, they might as well get value out of it.