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Big Data Analytics will bring a whole new level of business growth

Big Data Analytics will bring a whole new level of business growth 

IT in Canada recently spoke with Ray Bariso, vice president of Ericsson’s Business and Operations Solutions business in North America. Ray also heads Ericsson’s OSS/BSS Global Engagement Practice Community.

In this interview, Ray tells IT in Canada that the future of Big Data Analytics is going to be about achieving new levels of business growth across all industries to be able to leverage analytical insights to grow revenue more proactively and on demand. He also shared the two biggest challenges that are faced in the Big Data Analytics field today.

IT in Canada: Can you tell us a little about your history with Big Data and Big Data Analytics?

Ray Bariso: I’m responsible for Ericsson’s business and operations solutions business for North America. I took over this role in 2012, and in 2012 when we were looking at the market to see where the communications service provider and other enterprise industry trends were going, customer experience management and Big Data Analytics were two of the areas that were getting significant attention in the forward looking, five plus years in terms of growth trends. So as a result of that, we took a look at our organization and built a new Big Data and Analytics & Customer Experience Management practice. We established, re-allocated and hired into this practice a group of people, including data scientists, network experts, social media experts, business intelligence experts, Big Data architects, etc. that worked closely with our software business unit, which had begun productizing our Big Data platform, Ericsson Expert Analytics from five years of R&D. The history goes back to understanding the market or the market trends at work, what our customers were spending money on, and putting together and investing in a team that was going to address that growth opportunity. 

ITIC: What do you consider to be the two biggest challenges in the Big Data Analytics field?

RB: The first big challenge is an enterprise organizational challenge, I would say. That challenge stems from the fact that every organization has data throughout their enterprise – there’s marketing data, customer data, product data, network data, services and customer service information. Every enterprise has to become what we call a ‘data-driven enterprise.’ To be able to take all the data across the different organizational silos and horizontalize that and make it available across the company from an end-to-end enterprise perspective. [That] is a big challenge for every company.

I’ll give you an example…from a communications service provider perspective; you have the marketing guys who understand the offerings, the rates, what resonates with the market and what doesn’t. From a customer care and billing perspective, you know your customers plans, devices, usage, how much they’re spending month-to-month, what they’re upgrading to, how long they’re keeping their phones before upgrading, etc. From understanding your customers’ point of view in a Service Operations Centre, you know who your customers are by various segments, the demographics of them, what devices they’re using where, what time of day they’re using them, when they’re using certain applications, when they’re not using applications, how video traffic is affecting usage from geographic location and time of day perspective. Then you have the network guys that understand where all the network endpoints are and how a voice call flow or an internet or video session is working end-to-end across the network. Taking all that information from all those different organizations, stringing them together horizontally to create and end-to-end view for an end customer is challenging, based on the organizational structure. This is a very important business challenge where Ericsson is focused on providing customer solutions for.

The second big problem is finding the right combination of people and expertise that know how to decide which data to keep, track, store and utilize, and have the ability to use static data and data in motion together to make real time decisions. Whether there [are] operational decisions to reduce costs or optimize a process, or to formulate the next best offer for a customer to monetize services better for your customer that they will appreciate. Being able to understand what those algorithms are, and finding people who know how to do that is a big problem, as there is a shortage in the market of skilled talent that have this cross-functional expertise.

It’s an organizational and cultural problem inside companies, number one, and number two is the access to and putting together the right resource base for putting algorithms and all the right information together.

ITIC: Is there a quick fix or something that can be done to resolve or mitigate these problems?

RB: Yes, I mean from an IT industry perspective, it would be the CIO [who should] take a look at this across all the lines of business, the business owners, customer care, marketing, network supply chain, etc., and start that industry shift. You need tools, a Big Data architecture, and you need to leverage the information you have now. You need to put a plan together that leverages the information you have, that’s not only data at rest in traditional data warehouses and reporting databases, but you also need to take advantage of new cloud technologies and Big Data streaming architectures, to be able to evolve for the future. You have to realize that it’s not like a revolution; you have to evolve to it over time. There are still a lot of changes in the market, but you also don’t want to wait for everything in the market to settle and become solid, because then you’ll be behind your competitors. So there’s no quick fix, but there is a sense of clarity that has now come in the past few years that has moved us from the hype to reality phase, and there are some significant architectures being put together and invested in, and there are real use cases that you can learn from other industries like Amazon, Target, and other companies leading the way.  It’s important for some of the traditional industries to look at this because the new digital, webscale companies have already made progress in this regard.

ITIC: Where do you think all this is going to be the next five years, in terms of Big Data Analytics?

RB: Ericsson’s vision is what we call the networked society. We believe every person and every industry is going to be empowered to reach their full potential. This networked society isn’t a vision for the future, it’s happening right now and we’re the major enabler of this. If you think about the communications industry, it took 100 years to connect to a million places. It took 25 years to connect five billion people. By 2020, we forecast 26 billion connected devices, which confirms we are well on the way to reaching the vision of 50 billion connected devices. As a result of connecting all of these things you hear from the Internet of Things or IOT and machine to machine or M2M, there’s going to be this exponential growth in the amount of data being generated by people, places and devices. These have to be managed and can be leveraged to enhance customer experiences, increased business efficiency and innovate new revenue streams enterprises. When we talk about this data-driven enterprise, the future is going to be about enhancing the customer experience using this data and achieving new levels of business growth in different and existing industries to be able to leverage these insights to grow revenue more proactively and on demand – kind of like the, Apple, and other digital web-scale enterprises.

ITIC: What are your thoughts on Moore’s law as it may pertain to Big Data?

RB: I think Moore’s law will continue to reveal itself with respect to network, storage and computing power for cloud technologies that are being leveraged for Big Data architectures. So processing speed, networking, memory doubles every 18 months. I’ve read whitepapers that say it’s even accelerating because technology is moving so fast. If you apply the technology in Moore’s law to a business perspective, we also have the potential to leverage multiplicity and scale for operational efficiency, revenue generation and eventually the increase business metrics such as net promoter score, or NPS. So technology advancements are going to continue to accelerate and will be leveraged by business to enhance overall business performance faster and at scale in the future.  Moore’s law will affect Big Data by having the ability to handle, processing and analyzing petabytes of data today, but exabytes, zettabytes and yottabytes in the future at a fraction of the time.

ITIC: So the future is still bright.

RB: Oh, for sure. If you think about this notion of the networked society, every single enterprise and business is going to change as a result of mobility, broadband and cloud. And it’s all data that’s going to help transform the future and change how processes we know today are going to be significantly different in the future for every industry and business process. Think about the connected car, remote patient healthcare monitoring, wearables, the smart grid, transportation, supply chains, and smart cities – for every single one of these industries you can come up with a hundred use cases on how things can be better, faster, cheaper, and how data is the driver behind that.   

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