Data Analysts, Do You Know What You Need?

Juan Gorricho, SVP, Data and Analytics, TSYS
Juan Gorricho, SVP, Data and Analytics, TSYS

Juan Gorricho, SVP, Data and Analytics, TSYS

Machine Learning. Artificial Intelligence. Big Data. Business Process Automation.

These buzzwords have often been used by technology vendors to promote their solutions as the silver bullets that would solve all organizational problems. However, implementing such solutions without a long-term view or understanding of an organization’s ongoing workflow and business goals can often disrupt effective streamlining of business processes. Alongside, the lack of equilibrium between people, processes, and technology is also equally significant for a company’s technology initiative to become successful. The job is to tactically implement new technologies and make the company data-driven at a holistic level with an end goal in mind. To derive long-term and sustainable value from data and analytics, we need to look at it from a business initiative rather than restricting it only as a technical initiative. And for such a shift to happen, top-level executives in the organization must always lead the way.

At TSYS, we set up a data and analytics organization to lead the development and implementation of our strategy to deliver a Data & Analytics platform to our customers. We emphasize creating high-quality, data-driven products and services to change the way we manage our business processes. As the senior vice president of data and analytics within TSYS’s Issuer Solutions division, along with my experience gathered from previous roles, I have acquired a broad view of the data analytics spectrum, which I consistently utilize for managing business process.

Challenges in Data Analytics

Business process management has been a hotbed for digitalization, optimization, and improvement of customer lifecycle and experience. More and more, organizations are working to leverage technologies, such as AI and big data, to gather and analyze data more purposefully. Nevertheless, the main challenge that can make or break a company is having a proper business strategy to implement newer technologies effectively. It is one thing to talk about new technologies, and another to invest in the right resources to put together solutions that drive more value to the business. The technologies, if implemented without a holistic view of business processes, will only have a small chance of success.

  To derive long-term and sustainable value from data and analytics, we need to look at it from a business initiative rather than restricting it only as a technical initiative  

Additionally, in order to ensure success, business teams need to own and embrace data and analytics at every stage of their operations. According to a recent study by Ernst & Young, when companies initiate their data analytics journey, company dynamics all the way up to the C-suite level need to adjust and change to ensure a smooth, cultural transition. It’s essential for these senior leaders to take charge of the change to clearly articulate the value of being a data-driven company as a core competency.

My Experience with Data Analytics

At TSYS, we have been undergoing a massive technology transformation over the past few years led by TSYS CIO, Patty Watson, which includes laying the groundwork to create an open technology environment that powers the next generation of digital innovation. Today we sit on a goldmine of data from processing billions of transaction for all segments of our business, but up until a few years ago, we lacked the fundamental data management capabilities necessary to drive business value out of the data. Because of this, when we defined our data and analytics strategy and revamped our in-house data analytics teams, our focus then shifted to the implementation of the necessary technology (namely a data lake), which is a centralized location to store all of the data that we house and utilize this information to create better products and services for our customers. At the start of this journey, we realized that a mere technological investment was not enough to help shape our vision into reality, because as a company we needed a business strategy to connect the technology with our ultimate vision of being a data-driven company.

We started formulating our organizational plan for data and analytics with the end goal in mind. A fundamental guiding principle we follow is that data is useless unless it influences business outcomes. From the desired business outcomes we prioritized, we backtracked to the core workflows to identify the essential data that we require, and the technology that can help us analyze those pieces of information and influence the business outcome. This approach helped us in aligning our data with our business process and strategy, and identifying the areas where we can use the data to create value, not only in terms of technology but in terms of people and processes as well.

Our Data Analytics Journey

Our main vehicle to deliver data and analytics solutions is the TSYS Data and Analytics platform. We built it using modern technology, as well as a combination of various strategic partners at different levels of engagement. We work with partners who have open technology, cloud-based environments in order to be able to integrate with these partners more seamlessly. Our partners have to have a basic set of principles from a technology standpoint, but understand the business value and strategy of what we set out to accomplish, which was to use our ’clients’ data to serve their customers better.

We also consulted with top companies to devise different business strategies and develop specific plans related to our data analytics division.

Determining the Partnership Principles

In our search for a perfect technology partner, we realized certain aspects of the partnership principles remain the same across different verticals. Irrespective of the functional domain of an organization, the general decision-making process of selecting a partner depends on a few fixed attributes. It is imperative for legacy organizations to look at those foundational layers to make their choice for potential technology partners.

When searching for a suitable partner, companies first need to see if their future roadmap is compatible with the capabilities of the technology providers. This understanding will set the right tone to measure how closely the offerings of a vendor align with the strategy of a company. A higher preference should be given to vendors that leverage open source technology and heavily rely on APIs for integration.

Also, one needs to consider a variety of other factors like, whether to choose a partner that is building solutions from the ground up or offering off-the-shelf products, or if a partner is licensing versus offering a solution on a contractual basis. Simultaneously, organizations need to focus on the unique differentiators of their potential partners. From the strategic side of the partnerships, organizations need to focus more on partners that control their technology roadmaps.

Critical to all this, is the decision companies like TSYS need to keep in mind all the time—build versus buy. In data and analytics, our primary guiding principle has been speed to market, which has driven us to choose partners with mature technology (buy) that would accelerate the implementation of core foundational capabilities we needed. With that foundation in place, we can then start building new solutions on top of it, aiming at making the agile development of new solutions a core strategic capability. Said differently, we strategically chose to buy to reach maturity faster and are now focused on building as a way to ensure we excel at it.

The Colossal Role of an Executive Leader

The number and size of opportunities in data and analytics will only continue to grow, particularly as digitalization increases the speed and volume at which data is created. However, executive sponsorship is often taken for granted, because of all the hype around data and analytics, even though it makes a significant difference in enabling successful data and analytics initiatives. In light of that, data leaders should make a conscious effort to educate their peers and groom them about the true essence of a data-driven company. Success in data and analytics heavily depends on the executive leadership and the company’s culture, a responsibility that cannot be delegated by the leaders. The massive cultural change will only happen if executive leaders are ready to become the key stakeholders of a data-driven journey.

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