Super charge big data: IT as a profit center

January 06, 2020

When it comes to IT and innovation it is time to leverage IT as a profit center rather than a cost center, especially when it comes to big data, which is often a company’s most valuable asset. Companies that innovate using big data grow faster. New capabilities in big data require upending how we view traditional IT and how an organization can exploit this valuable resource. We need IT to take more intelligent risks, think big with innovation, and act as better partners with the business. Let’s take the harness off IT and let it run as a profit center. This article will explore this paradigm shift and some of its benefits.

Take more intelligent risks

Most startup organizations try not to have any cost center subunits of their business. They do this intentionally to ensure every dollar spent is focused on a return on investment and profit. Organizations who have done this, like Facebook, Amazon and Google have quickly revolutionized entire industries and in many ways have reshaped our worlds. Thinking big requires the ability to take intelligent risks. Traditional IT methodologies in data have been slow to respond to change, because they are super risk adverse. This can be a detriment to an organization’s growth, especially when it comes to leveraging big data. Since big data solutions can provide huge differentiation for an organization it’s time to change how we not only see IT, but more importantly to transform its traditional IT role into that of a profit stakeholder.

Thinking big - Innovation focus

The key to big data innovation is to think big. To that end, IT development organizations should be profit centers. They should go directly to the business and offer up new ideas, concepts, features and enhancements. They must engage their business customers as partners and share in revenue streams created by the solutions they build and support. And when IT hit its deadlines revenue can be seized quickly. An example of innovation in data, comes from a major animal nutrition producer that worked with its farmers to develop a big data solution to reduce mortality rates of their shrimp yields. In this case IT provided real time solutions including yield performance, pH levels, and predictive analytics to the farmers. They made the farmer part of their team and as a reward reaped the benefits in less than five months.

Better partners with the business

IT profit centers have less friction with the business, because they take intelligent risks while maximizing business and IT innovation. That means IT and the business teams are working together toward a common set of goals. The benefits in banking are significant. When banks use big data for business, they can implement better risk management processes, personalize offers, and incorporate better retention strategies. According to the 2015 Big Data Use Cases report, published by BARC, the average increase in revenue is 8% coupled with a 10% reduction in overall costs of operations. We must think outside the box and leverage best of breed technology like machine learning and deep learning, all while focused on how business can put this great resource to work.

Conclusion – Not a fad

Innovation, taking intelligent risks, and being better partners is a way of life going forward and not a fad. IT organizations that are profit centers have negotiation power, increasing budgets and can afford to hire best of breed talent. Start thinking about ways to leverage governance and synthetic data as a profit center. Cost center IT is not going away. If you don’t think Innovation is critical to an organization, you might be left behind. Need proof? Look at the Fortune 500 list from 1988 to 2018; only 25% of the top 30 companies remain on the list. Four notable new entrants on the list that leverage IT as profit centers are Apple, Microsoft, Verizon, and Alphabet. Being profit focused for IT is critical, because it’s the future of business growth for all financial institutions.

About the Author
John Thuma, Data Solutions Group FIS
John ThumaData Solutions Group FIS

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