"India Puts The BIG In Big Data"

The pace of innovation from data analytics is far exceeding the predictions of enterprises and developers. The unified access and deployment of insights across an enterprise are a critical element to its competitiveness. In these radically changing paradigms, industries and nations need all the advantages they can from the emergence of Big Data.

Anthony McMahon, ‎Senior Vice President, Platform Business, Database, Technology, Analytics & Mobility at SAP Asia-Pacific, talks with Biztech2.com about the state of data analytics in India, the role of the C-suite and examples of what India can aspire to from a global outlook.

McMahon works to provide enterprises with SAP solutions for both SAP and non-SAP applications through its platform, with nearly 50% of its customers using non-SAP applications. Correcting a common myth about SAP, he said: “many customers see SAP as an ERP application company but we’re equally a platform and technology company.”

How do you place India in comparison to the rest of the region with respect to data analytics as a key feature of business practices?

SAP’s view of Big Data is different since there are lots of definitions that are floating around. We have today enterprises managing their own analytics applications on contained enterprise data. That’s the way things have been going for many years. The new data sources – web, social, call logs, transactional logs, sensor data are a different challenge. For an organisation or government, they can take advantage of new services to take care of customers better, provide new solutions, get better operational efficiencies by blending or integrating insights from the new sources coupled with enterprise goals.

India is as equally placed as any other nation but its needs are proving unique. India puts the BIG in Big Data . The amount of data companies need to deal with is large simply because of the population. China and India in that context have unique challenges. India is helping push SAP to cope with that stream and data volume.

India’s usage of big data is very advanced in power and utility industries, such as the smart meters for distribution networks. Newer banks are also further along than their legacy government backed counterparts. Telecoms are even more advanced, even more than China, due to the competitiveness towards understanding and predicting consumer needs which are higher.

But it is still a developing market. SAP is actively working with utility companies for smart meter roll outs, we’ve rolled out SAP HANA smart meter utility and applications for some companies in Australia but the size and scale in India much larger and very different.

What areas do you help organisations deploy big data?

The areas SAP has unique offerings in are mainly geared to generate a relevant way for enterprises to capitalize on the data. We’re trying to bring industry knowledge to these new data sources and help our customers. Companies need a data platform that can cope with insights from much larger data sets over a period of time or real time, which is what SAP HANA delivers, very different from some legacy architecture that are currently in use. The solution, from data to analysis through to mobile devices, which is also an advantage is are other big area of focus.

How are the solutions for analytics positioned on the platform?

Let me give you an example. We’re dealing with cases of older banks in India which have legacy infrastructure, monolithic data storage warehouses, that isn’t coping with these applications from new data sources. And not just as a technology solution with HANA or HADOOP or from our analytic stack, but also the business problem or opportunity in customer retention like new customer sign ups, as well as fraud and risk management, and not all these solutions are from SAP.

We think the new applications that need to be written to cope with these new opportunities are going to come from start ups rather than the traditional provider. So we’ve worked a lot with start-ups – if you’re going to write do so for next generation – for higher analytics e.g. a bank here, is getting better solutions from an Indian start up for fraud and risk management rather than from a legacy applications provider.

How can enterprises justify the investment in these solutions?

Most decisions are based around what problems they are looking at an opportunity to solve. Figuring out the use case is most important, it’s usually not with the CIO but the CMO. We are working with line of business leaders, retail banking or value added services departments or head of retail markets – more business outcome oriented. We develop use cases that these organisations currently can’t do or haven’t been doing due to limitations in existing architecture or a business process. We tend to priorities the list – from easy to do to those that are transformational. We work through traditional ROIs that a particular entity uses, and once we’ve firmly understood then we talk to them about existing investments, that they can continue to use and review what they would like to supplement with new architecture by HANA or Sybase IQ or HADOOP. And what other analytics that the companies want to overlay. They might already have a business intelligence solution but no visualization or predictive solution, so we can work with them to provide those solutions.

The most important thing is to establish the use case, get ROIs for company approval process and then see how the architecture will be rolled out. Companies are far more cautious that they retain business data and add customer value, so they prefer to figure out a phased system in steps.

How can small and medium enterprises with limited budgets take advantage of these solutions?

Big data doesn’t need to mean big enterprise. They can take on data services, that are available for certain industries and across specific lines of business. An example of this opportunity is of a company in China which has for certain provinces made agreements with the government around information or business registrations related to public services. As the sole aggregator of that data, they go on to sell the information to industries such as telecoms for analysis. These types services will be accessible regardless of what size your company is going to be. They package the data as a service and SMEs use their own sources of data in conjunction with those data sources and blend them for insights.

How can enterprises assure the security and privacy of their data?

The challenge for most CIOs or CISOs goes up as they need to operate in this new environment, they need to protect their employees, consumers and brand. We have consulting services that help in security and risk assessment, but also practical solutions like single sign-on that control access points. We also have analytics around people within the network to prevent risk, we have systems like segregation of duties, and process controls which provide an automated way for CIOs etc to identify risks within the network.

How can enterprises assure stability of data storage off shore vs. on shore?

There are still a lot of concerns for many companies and countries regarding data storage. Dealing with certain companies and institutions specially in banking service industry most countries have laws that enforce the data to remain on shore.

However, some countries and industries are willing to see the data and business process managed off shore if they are advantageous to business outcomes, but through legal means. The off shore storage is better in certain cases due to reliability of power supply, cost of land, power etc., such that in another geography these problems go away. I don’t think there is an answer for it right now and its both in and out.

There is an interesting example of a Telco in Pakistan that chose to locate its data outside to ensure supply and risk management. They had to go through a lot of hurdles to do so but it was a good decision for business continuity.

Are CIOs leading decision making regarding data analytics?

The CEO is actively asking all the C-suite what’s the Big Data strategies they need to use. Soon these decisions are not just going to be the CIO but the CMO or even the CFO in some instances. In terms of actual use, part of the C-suite that is driving the willingness of big data is from the CMO or in some cases the heads of lines of business. They will partner with someone else if the CIO isn’t able to meet their needs.

The budget division we see is that more than three fourths of big data projects have not been from the CIO’s budget but from other lines of business in a company or the CMOs. The CIO will want to see to it that how can the budget that is leaving the organisation be saved. Ultimately the CIO wants to have a big play to leverage the already made investments in legacy data architecture. This brings them some opportunity to have a more strategic seat at the table, to contribute more business value to the company.