Navigating the world of digital transformation

Caption: 
Panel discussion at NTT Global Forum 2016 held in Singapore

The astonishing speed with which the digital revolution is transforming businesses and even entire industries is making it a challenge for different-sized companies to clearly understand digitalization and fully grasp its implications. Successful navigation of this new digital landscape largely entails a not-one-size-fits-all strategy, but as a recent panel discussion at the NTT Global Forum 2016 in Singapore revealed, there are certain aspects of the organization that need to be emphasized more than others when starting a digital transformation journey, particularly where big data is concerned.

Integrating data analytics into the organization, and deriving the full value out of it, must be a C-Suite initiative that’s cascaded throughout each department.

Chan Kok Long, Executive Director and Co-founder of iPay88 Sdn Bhd, a payment gateway provider, says his company’s digital transformation journey was led by top management and the heads of departments having direct interface with the customers. “For a company of our size, good digital innovation is having a keen understanding of the fundamental needs of our customers. At the end of the day, they’re the ones giving us revenue so when we started off on our big data journey, we prioritized the particular bits that have a direct relationship with customer satisfaction,” he says. 

Increasing customer satisfaction may be a good business case for big data, but Len Padilla, VP for Product Strategy at NTT Europe, asserts that relying solely on one aspect of the organization “runs the risk of missing a trick. When you talk of big data and analytics, what we’re really talking about is answering questions and a lot of the time it’s about looking for the questions we don’t even know exist.”

Padilla adds that it would be dangerous to treat IT like the standard business case practice where you go through the costs and benefits and prove that, at the end of the day, the project will make money. “Big data needs to be multi-lingual. It’s not only about finance or customer service—these are just a few of the languages of the organization. The important thing if you’re looking to push a big data initiative, or even any kind of project, is to find different stakeholders within the organization who stand to benefit from the project. And that can be everything all the way from the customers to the employees, and even the board. Find out what kinds of things are important for them, and make sure your business case speaks to all those different languages,” he advises.

Culture, complexity at large

Successful digital transformation demands a culture activated by top leadership that encourages innovation and risk taking, and empowers all the stakeholders of the company. This is easier said than done—involving various facets of the organization to push for big data can be quite tricky, as these are often new initiatives some members of the C-Suite may not fully grasp just yet.

Binu Azad, Director of Business Analytics and Partner Management for Philips Healthcare, speaks of the risks of “complexity at large.” Says Azad, “You’re bulldozed with external factors of needing to do something versus acquiring the purpose, and you lose the intent with which you’re setting it up. Big data is one of those — you don’t start big data when you don’t even understand where the demand is coming from. You should be digital-ready before tapping on to it. Ask yourself whether your organization is culturally ready to use and consume and benefit from this.”

Andy Cox, the Chief Technology Officer of Dimension Data Asia Pacific, suggests a three-pronged approach to building the business case for digital projects. “You have to challenge the status quo from three lenses: how digital can improve physical operations, how you can use it to be innovative and agile in terms of bringing new products and services, and what channels you can use to market it,” he states.

Data security and privacy

While exploring the potential of new, data-driven business models, companies need to tackle how to manage security and privacy more effectively.

The SVP of NTT Security’s APAC Field Operations, Raymond Teo, asserts that many companies need to rethink their approach to security. With cybercrime a growing threat, security shouldn’t just fall under the responsibility of the IT department or the CIO/CTO. “With big data comes the big risk of aggregating the data — to adversaries, this is a goldmine. The approach we recommend is really founded on the fact that security is part of the entire life cycle. It should be catered to at the start of the digital transformation because as your requirements, priorities and business situations change, so do your security needs change as well,” says Teo. 

With massive amounts of data now being routinely collected and stored to further drive business value, the question of how these companies continue to respect and protect data privacy of their customers needs to be addressed. This is especially relevant to multinationals like Philips, which not only deals with accumulating massive amounts of data but also cross-country movement of data where privacy is driven by the regulations of the countries within which their businesses operate.

“How we manage the privacy of our customers is really multi-nodal, meaning on one hand there’s that level of transactional business data that is general, and there’s the individual data element wherein security of the information is in the hands of the one who owns it. So we may have element A and element B of the data that is general, but when it comes to individual data, the user’s permission is needed to use it. Individual data is highly secure and difficult to get to unless you have permissions,” says Azad.

Padilla observes that in the healthcare and financial services sectors, customers are finding it of benefit to anonymize the data—separate the analytics platform and the system of record where data is actually tied at the individual level. When it comes to managing different levels of data sensitivity, it is critical the corporations think about hybrid cloud platforms.

“Because of security and regulatory compliance, the first reaction is to do everything in-house in private systems, but what we need to do is take the data apart. Figure out which data is critical and can never move, which data are anonymized, and make use of different platforms for these different types,” says Padilla, reiterating once more that one of the key things with big data initiatives is that, often, companies don’t even know what the questions are. “Treating data involves a lot of trial and error, a lot of laboratory analysis, and that involves a lot of compute time. If we do it on our own private systems, we’ll run out of budget. Whereas if we use cloud systems, we can take advantage of the cost benefits. So it’s really about understanding which data is critical, and treating the less critical data in a public cloud while treating the very private data closer to home.” 

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