Is analytics technology gaining widespread usage in the workforce with the advent of mobility?
The workforce is becoming digital and expectations from a digitized workforce have gone up dramatically. This marks a general shift in what people expect from analytics. People who are getting some kind of analytical content form about 15-20% of the workforce as of now and that is set to change dramatically by 2020. We see tremendous growth in the number of people who are going to demand and have access to information about their business, their clients and their competition at their fingertips. Organizations are bracing up for this as they are realizing the value of analytics.
Decisions often get made at the edges of the organization. That is why companies are working out how to get the information and knowledge to travel to the decision making edges of the organization. Mobility is a huge part of this wave as it is the quickest way of ensuring that information reaches to the periphery. Mobile adoption is higher in emerging economies as compared to the developed ones.
In a country like India, where penetration of mobile devices is high, the proliferation of smartphones is still low. Does this present a challenge when it comes to deploying analytics?
Device compatibility is a challenge for us but it’s a bigger challenge for our customers. They are trapped in the upgrade cycle, which is on the backfoot at present. A typical cycle for device replacement is 3-3.5 years. Companies have to secure data, ensure employee reliability and manage access identities.
The big challenge with mobile analytics is to decide on what data to send and where. There are so many types of data today, ranging from financial to operational data, and an organization has to filter all of this in order to transmit the same to the periphery.
How is the social media analytics space developing in India, especially when businesses are still reluctant to use social media extensively?
Social media analytics is an interesting challenge for organizations. There are two aspects to it. One is that of collecting information from the social sphere and the second is with regard to using that information to do something different with it. The collection of information remains the biggest barrier for social media analytics in India. There is a public set of information, which includes Twitter etc. Then there’s closed and hard to consolidate information that is private. To top it all, there are other sources of information such as the merchandizing system or an Amazon.com and now there’s also a proactive mechanism of social feedback that organizations use. These are enormous quantities of data that need to be cleaned up before they can be used. Another challenge is that a lot of core technology for processing this data is still in English.
Is BI in the Cloud gaining acceptance in India?
We have taken a progressive stand on BI in the Cloud and it is a pretty extensive focus area for us since we have a rather substantial SaaS base across South-East Asia. Cloud analytics are still in the pipeline for India and not so evolved. The Cloud depends a lot on the question of whether or not a standalone SMB can derive analytical value from individually doing BI in the Cloud or is it better to bundle a packaged solution. SMBs are increasingly saying that they want to run their business from a single location; that’s why packaged solutions running in the Cloud are picking up in this sector.
Security in the Cloud depends on how you perceive things. Sometimes, it could be much better than when you host your data within the organization. For instance, if you are hosting your data with Amazon, you are probably getting the services of one of the 300-400 best security experts in the world. Feeling safer by keeping your data in your own organization is a security misconception.
How is the advent of in-memory impacting the BI space?
There is a lot of talk of price rationalization with regard to in-memory technology. We don’t think that it’s going to happen for a while yet because the RoI is extreme. The cost of memory is coming down but the cost of software is highly differential today depending on how much memory you can pack into a single box. In-memory software continues to sell at a premium because the return on investment is incredible. It is not only about getting information faster, though that’s the key selling point. It is about transforming your business by finding a way to do things differently.
Real time is not the game changer for analytics; enabling decision making at the fringes is. As that realization dawns on organizations, the adoption of in-memory analytics will gather pace.