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Data constantly in transit, difficult to understand its path

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Sunil Rajguru
New Update
transformation

Micro Focus’ Genefa Murphy, Chief Marketing Officer, and Saurabh Saxena, Country Director–India, talk about the importance of digital transformation and the changes taking place in the IT industry today.

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Implementing digital transformation

Genefa: Digital transformation is not new. It's been around for a long time. Now, it's just got that extra focus. When it comes to digital transformation, you need to look at both above the line and below the line mandates. Above the line is how you can use digital in order to create new revenue streams, new ways to interact or approach with your customers and engage with them. Below the line is how to essentially run the business to be as effective and efficient as possible.

But it's ongoing. Digital transformation is not a one and done thing. You have run your business while transforming. You're always going to have to do both. I think the biggest challenge that enterprises have face is when it comes to digital transformation is: Knowing where to start, knowing where to do it and how to take a practical approach. There are many forms of it: You can transform your engagement with the customer. You can transform your IT services. You can digitise your processes. There’s the scalability issue too. We see varying levels of maturity when it comes to digital transformation. I think you've seen Europe having a more efficiency and effectiveness on the processes. In Asia Pacific, you've got smart cities initiatives like Digital India.

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Then there’s the larger enterprise versus SMB. Sometimes that's where the enterprise struggles and SMBs potentially have an easier approach because they don't have as much heritage complexity, or the scale of complexity. That’s where we differentiate ourselves. If you want a provider who is only going to be cloud first, SaaS first, cloud only SaaS only, that's not us. We specialise in the complex. We deal in the hybrid: Hybrid applications, hybrid infrastructure, hybrid data sources.

The Digital India story

Saurabh: In India, the gross merchandise in e-commerce has grown almost 2X in the last 3-4 years. That’s ordering food, apparels and everything. Even in public transportation, Ola and Uber have grown from 140 million rides to about half-a billion rides a year in a similar time frame. You are engaging with the customers in a more digital rather than physical nature. In the government e-market place and eNAM (National Agriculture Market), the revenues that have increased in the recent year have been tremendous. It's predicted that in the next 4-5 years in India 55% of transactions are going to be cashless. Manufacturing organisations are leveraging digital. They're using insights for production planning and for supply chain optimization.

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Analysts will come back and predict that every organisation across board is going to be digital in the next four or five years. Enterprises in the past have invested in a plethora of technologies, probably in silos. They do a CRM project in one way. They do an ERP project in one way. They do an HRMS in another way. They may have an ecosystem, which is across an Oracle, a Microsoft, on a private or public cloud, on virtualized VMware or even open source. It's all over the place. How do you get some sense in this whole ad hoc way? That’s why digital transformation is critical. How can you run the way it was running and transform so that you have much more efficiencies, much more optimization and at the same time innovate at lower costs?

This young generation is also an impatient one. They will move from bank to bank, telecom provider to telecom provider, Zomato to Swiggy, Flipkart to Amazon overnight, if they don't get the services, if they don't like the user interface, if they don't like the way that they are being treated. Hence organisations need to keep pace with what the requirement is. This is the current digital ecosystem and digital transformation requirement.

Data explosion-IoT revolution—Are we ready?

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Genefa: I don't think we are ready. With all of that IoT, there are a lot of unknowns. The context is changing. We talk about security, risk and governance. We talk about securing what matters most: The identities, the apps and the data. But what is an identity? Is an identity a person? Is an identity a thing? Should those identities be treated equally? The data that they are giving off: Should that be treated equally? Or should it have a different policy. So I may need to treat a person and the data that they create differently to how I treat a thing in an IoT world and the data that it creates.

IoT and other aspects like that bring across a whole other set of use cases that we have not anticipated for how data will be used. In a modern world where data is constantly in transit, across multiple facets, people are moving from their mobile device to their laptop, they're accessing a SaaS based application, a cloud-based application, an on premise application. It's becoming very hard for enterprises to truly understand the path of that data.

The dangers of AI bias

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Genefa: How are we making sure that the algorithms that we're actually building are not subject to the bias of the individual that is building them? You use ML to then evolve that algorithm and take it to the next level. But if the foundation is not stable enough, then we're not going to be actually creating something that can really truly be successful. I think that's one of the challenges. The algorithm is still built by a human. If you start with a bias, all you're going to do is reinforce the bias. AI is only as good as the data that is available.

One of the big challenges is in the testing space. It’s being able to look at building an application that has to run on different platforms: Windows, Mac, Android, iPhone etc. One of the big challenges has always been testing the multiple scripts that you have to create. We've embedded AI into our testing solutions to provide intelligence so that the tool can actually learn more. What does a login button look like consistently across all of these different platforms? So now we can just build one script instead of 5-10 in the past.

Saurabh: We are embedding AI-ML in each one of our solutions across board, whether it is in the area of application lifecycle management in the area of hybrid IT management or in security. We are doing user behaviour and end user analysis using AI-ML. We are automating as much as we can via Robotic Process Automation. I think the whole purpose of AI-ML is automation is: To automate as much as possible and get the humans to do much more innovative work.

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Looking to the future…

Genefa: As we go forward in 2020, security will continue to be a prominent feature in the technology landscape, especially as you have the world of IoT evolving, people trying to understand what does truly a world of zero trust actually mean? How do I develop next generation security policies and data governance too? We’ve seen the start of things like GDPR in Europe and now California has the California Privacy Act. The United States is looking at putting forward their global view of data privacy. We'll start to see much more about predictive analytics and insights and how they can be used to business advantage. There will be a continuing evolution of things like DevOps and how that evolves to be much more about DevSecOps.

Saurabh: The most significant trend that you've seen obviously, is the investment in security. Indian organisations are investing more and more into security testing and application testing at the beginning of the life cycle itself. In the area of infrastructure, I think most of the organisations realise it's a complex, multi-cloud hybrid ecosystem. They're looking at simplifying the way they can look at what's available in their ecosystem. They are looking to consolidate everything that's happening across silos. It won't be a homogeneous ecosystem. We don't foresee that in the country. I think it's going to be a heterogeneous hybrid ecosystem because the decision making is spread across the enterprise; it’s just not left to the CIO. The businesses are making decisions as well.

data
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