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How data democratizes business decisions

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January 1, 2019

The emergence of big data offers the potential to transform how businesses operate. No matter their size or industry, many companies are seeking opportunities to uncover insights from data to meet their business objectives – whether it’s to analyze consumer purchasing behaviors to improve product marketing, collect real-time equipment readings in industrial fields to build more sustainable operations, or any other number of possibilities.

According to analyst firm IDC, the data in the digital universe has doubled every two years since 2013 and will reach 44 zettabytes of data by 2020. But as the universe of data grows exponentially, so too does the complexity of collecting, analyzing and interpreting that data. With so much data readily available, how can businesses realistically and practically pore through this influx of information to find actionable insights?

We sat down for a Q&A with UL Chief Digital Officer Christian Anschuetz, who believes that the “democracy of data” will lead to better decision-making, new business models and a vastly different business landscape that we all need to prepare for now.

Q: With the amount of data doubling every two years, how much of it can we consider useful?

A: No matter if you consider it from the perspective of an individual, a company or an entire society, the opportunity – and challenge – is the same: we are awash in data all day, every day. It’s easy, then, to conclude that a certain percentage of that unending information might be useless unless we know how to aggregate it thoughtfully and deliberately. Thankfully, the rapid growth in machine learning technologies and trained data scientists means we can turn the flood of internal and external data into better, more trustworthy insights for decision making. Seemingly random bits of data become useful when those bits are connected, and insights are teased out of the noise.

Q: How will the “democracy of data” impact the business landscape?

A: There used to be a time when companies relied upon singular, all-knowing authorities, either a powerful governmental or international body or a world-renowned expert in a field, to drive their decision making. But now that billions of perspectives on any given facet of critical importance to a business can be found in data, that past approach is fading fast. A quantity of perspectives has a quality of its own, and companies are realizing this as they seek to solve ever more complex global problems. Whether businesses need perspectives related to quality, trust, safety, security, sustainability, and more, the best answers can be found in the democracy of data.

Q: With so many perspectives available in this vast digital universe, is harmonization of these views to get to a decision that will work for a diverse, global population even possible?

A: Think about it like this. Manufacturers don’t design a product against a single global standard. They design it so that it complies with all the guidelines and regulations recommended or required for the intended markets where it will be sold. In much the same way, you don’t harmonize perspective. Instead, you take into consideration all the different inputs to yield the greatest insights on how best to navigate markets.

Q: With surveys showing that trust among customers is at an all-time low, how can data help to close the trust gap for businesses?

A: Trust is a necessary ingredient in the exchange of value from producer to consumer. Without trust, regulators, retailers, consumers, buyers and other stakeholders may reject a company’s offerings in favor of those perceived as less risky or meriting greater confidence. In today’s world of big data, businesses garner trust when they consider a holistic and comprehensive set of perspectives on how to manage risk on the journey to the marketplace.

Take artificial intelligence, for example. There exist concerns that the misapplication of artificial intelligence will compromise the security of nations, families and businesses. But artificial intelligence is just another new technology where we need to evaluate better and understand its opportunities as well as its threats. In the past, a singular organization could provide that perspective, but that doesn't exist anymore and may not effectively build trust in today’s environment. Instead, what’s needed is an organization to sit in the center of experts from every possible facet related to artificial intelligence who can aggregate the very best insights to conclude how to securely bring artificial intelligence into the world. And when you can do that, then you succeed in engendering trust.

Q: What is UL doing to adapt to this new landscape?

A: Organizations like ours must change as fast as the world around us. As we evolve the role we can serve for our clients and the global market at-large, we are investing in our ability to aggregate perspective and insight across ecosystems. We’re building and purchasing the leading-edge technology that will allow us to double the set mass of data and acquiring the right talent with the unique skill sets to help us reach this next level. We’re also partnering with organizations that help enable us to develop the capabilities to sift through that morass of unstructured data to glean insights.

Our ability to pull together that best combination of human talent and intelligent machinery to provide signals out of this mass of data will help our clients make better decisions ranging from how to design safety into products, which markets to explore for growth, how to achieve more sustainable operations, and so much more. Because in reality, for any company in any industry to be successful in this digital era and avoid becoming obsolete, they must consider new business models that leverage the right blend of machine learning and human talent to transform their business fundamentally.

Ultimately, we intend to stand at the nexus of the conversations, perspectives and expert views afforded by big data to help our clients achieve each of their unique opportunities.

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