New Era of Decision Making
A panel of global leaders in business consulting, IT services and system integration discusses the challenges—and benefits—of becoming an analytics-driven enterprise.
Meet the Panelists
Richard Brown, global program director for big data and analytics at Capgemini
Sunny Chu, digital, data and analytics lead in Asia Pacific for Accenture
Forrest Danson, U.S. analytics practice lead for Deloitte Consulting
Spyro Karakizis, digital, data and analytics lead in Australia and New Zealand for Accenture
Dilip Krishna, director of governance, risk and regulatory strategies for Deloitte and Touche
Mishell Meyer, digital, data and analytics practice lead for financial services in North America for Accenture
Anurag Seth, vice president and global delivery head for Analytics and Information Management Group for Wipro
The concept of data analytics is deeply etched into the psyche of most organizations. But the advent of more powerful systems and new data sources—including mobile devices, geo-location services, sensors, blogs and social media—has created new opportunities for analytics. These issues are top-of-mind for the C-suite, which recognizes that their organizations must evolve into analytics-driven enterprises to stay competitive. Teradata Magazine talked with seven global leaders in business consulting, IT services and system integration about the challenges, opportunities and what it takes to be a data-driven enterprise.
The Time is Now
Have you developed and implemented an analytics strategy for your organization? If the answer is no, you may need to play catch-up. Our panel of experts was unanimous: The time to embrace analytics is now. Here’s what they had to say about leveraging analytics to drive the business:
Anurag Seth: Data is changing dynamically and changing fast. It’s mobile. It’s social data. You need to take actions on that data, and with the older technologies or tools, that is not possible. A simple example is in the airlines, which can drive promotions to particular customers. If you can offer a promotion to a passenger while he’s on a flight, such as a coupon to a local concert, you make him a loyal customer forever. You are also cross-selling.
Richard Brown: You need to be agile with business intelligence (BI) development, and you need to be able to respond to business needs in the short term. If you go back to the business and say, “You’re not going to get this in six months,” then you miss the opportunity. An analytics-driven enterprise is about having information as a core part of your processes and decision making.
Dilip Krishna: Traditional BI is all about producing reports, which by definition, have information that is obsolete the moment it is on the page. The information is also static. I see a number on the page, but my next question can’t be answered except by asking someone for another report. It tends to create a long cycle of information generation. New analytics shortens that cycle of information innovation to what I think of as “the speed of thought.” The rapid turnaround, within seconds or minutes, is an important, almost psychological driver toward new insight that traditional BI just has not been able
Got What It Takes?
Becoming an analytics-driven enterprise requires instilling a culture in which everyone thinks about, leverages and benefits from data. Our experts dug into some fundamental questions: What does that look like in day-to-day practice? What are the key attributes that set analytics-driven enterprises apart from those that are merely data-knowledgeable?
Spyro Karakizis: I’m a big believer that it’s a top-down structure. This is not a grass roots movement. In fact, we encourage organizations to look at their business strategy. What is it you want to achieve as an organization? How do you propose to grow? Is it by developing new products, breaking into new markets or making key acquisitions in areas that complement your existing model? That obviously comes from the C-suite. Then it basically trickles down and is propagated through the various rungs of the organization.
Krishna: C-suite executives are ensuring that decisions are based on and supported by data at all levels, not made from the gut. In a best-in-class implementation, you don’t walk into the boss’s or CEO’s office without data to back up a conclusion or position.
People who do that in data-driven organizations usually don’t last long.
Forrest Danson: To me, an analytics-driven approach implies that it’s embedded into the business processes and value chains. That is what takes it from being “analytics as a bolt-on” to something that’s really an
Sunny Chu: You need the right talent to be able to put together models that let you perform the analytics that drive insights and recommend actions. The data scientist is an essential role to put together all the pieces and say, “This is how we’re going to get the outcome we want.” Data scientists, by nature, fit this need.
Face The Challenges
Thriving in an analytics environment requires changing the company culture, fostering partnerships and ensuring quality data.
Becoming an analytics-driven organization doesn’t happen overnight. It takes time and money of course, but it also takes determination to overcome the challenges that will inevitably arise.
According to our experts, thriving in an analytics environment requires changing the company culture, fostering partnerships and ensuring quality data.
Brown: One of the first steps is to get senior executives to use the data directly out of the BI systems rather than the endlessly massaged numbers they get today. This is a painful process at the beginning. It’s rarely less than a couple of months, and often more, where you sort out the issues. For some, it seems too painful and they can’t address it. But you have to keep moving through the pain. The danger is that some people think an analytics-driven approach is a technology solution only. The organizations that make a difference embrace it as a transformational journey.
Karakizis: Becoming data driven is an evolutionary transition. Organizations move from basic to more advanced reporting. Then they open up the business user population and allow the users to conduct analytics and report on their own in a more self-service manner. Finally, there’s the shift to predictive analytics and using large volumes of diverse data. All of that is predicated on having good, trustworthy, clean, well-connected data that you can draw conclusions from. If you decide to leapfrog over any of this process, you’re probably not going to be successful.
Krishna: Data analytics is a different animal. It’s ever-changing. If you’re building out a data environment, you will never get a full set of requirements that can be implemented in that environment. So the way business and IT work together on analytics is completely different from how they have typically worked in the past. That’s very hard to do, and no one ever gets it right the first time. But over time, they learn how to work together.
Mishell Meyer: Analytics is squarely on the C-suite agenda, but it is being executed at the functional level. The question of “Who owns the data?” is not less important than “How can we get the data?” and enabling data access to those who can use it to drive business outcomes. The opportunity here is for IT to enable solutions that can be leveraged effectively by business and functional users.
Seth: The explosion of data is continuously happening. The struggle that people face is, “How do you separate ‘real data’ from the rest?” and that is where you need a very strong analytics initiative so you can take insights out of data that is relevant to you.
Chu: An analytics-driven enterprise requires businesses to have an understanding of what types of insights they want. And then they start thinking about the data architecture. What type of data do they need to conduct analytics and drive insights? Having centralized services to manage the data and analytics, and the ability to tie issues to outcomes within that framework, is where you get the value.
Colleen Marble is a frequent contributor to Teradata Magazine. Her last article covered the Teradata Unified Data Architecture™. She has been writing about business, marketing and information management since 1996.