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How data transforms business decisions

city view at night with traffic lights and trail lights denoting the movement of data
January 15, 2019

The emergence of big data offers the potential to transform the way in which businesses operate. We sat down previously with UL Chief Digital Officer Christian Anschuetz to discuss the complexity of collecting, analyzing and interpreting this data that democratizes business decisions around the world.

In part two of our Q&A, Anschuetz provides insights into how the use of data helps companies access markets, drive quality, understand suppliers and, eventually, predict (and thus avert) risk. Read How data democratizes business decisions for part one.

Q. How can big data alter the way companies look to access new markets with their products?

A. The volumes of data readily available have enabled us to consider moving from an approach of simply applying a static mark to fixed products that pass testing to dynamically understanding supply chains and the nature and composition of the products they bring onto the market. Intersecting that with the compliance landscape of a particular market gives us the opportunity to better assist and understand retailers, distributors and manufacturers in a way that goes beyond only addressing regulatory compliance measures. Instead, we can also help ensure the product meets the higher standards required for sale in specific global markets as well as with individual retailers, such as a large e-retailer or a bricks-and-mortar big box store.

That's where the model is headed. When we start leveraging data to dynamically link the regulatory landscape, we’ll be able to compress the timeframe needed to help products gain entry into new markets.

Q. How will companies start leveraging data to inform product design?

A. Imagine a scenario in which we’re able to examine all the regulations in the world in combination with all the definitions we can find regarding a specific product to gain a stronger glimpse into its ecosystem and specific markets for sale before that product even goes into production.

With the data sets available to us, that scenario is plausible and strategic. We can start accumulating enough data to create a sort of “digital twin” of any product, giving us the ability to predictively model compliance as well as predictively model failures. This not only informs design but drives quality, performance and compliance from the onset.

Take, for example, a television manufacturer. Instead of manufacturing an entire line of televisions and then bringing a select sample set forward for testing to determine if it meets safety, performance and regulation guidelines, they start by clearly defining the television they want to build, and for which market. With that upfront context, we can analyze volumes of data with specificity to be able to inform that manufacturer of everything they need to consider in the way of market insight, regulation and compliance needs, and so much more to conform to the market where they want to sell that television. This data-driven approach enables a manufacturer to fundamentally design a product out of the gate that exceeds all safety and performance criteria before the necessary product testing is ever conducted.

Q. What role does data play in helping companies with risk management and brand protection?

A. Since 2010, more than 110,000 cases of products deemed noncompliant by 27 U.S. regulatory agencies have cost companies more than $270 million in fines and penalties. Between the dollar figure and, worse, incidences of human injury or fatality, there exist real operational challenges that we must address. Part of the problem, however, is our inability to address them because they are so complex, fast and technologically challenging.

Data, however, now gives us greater insight and transparency into supply chains and business operations than ever before. Whereas before it was difficult to trace a manufacturer to a component, to a product, to a geographic destination and, finally, to an end user, that level of specificity now exists. For example, if one of the suppliers in a company’s supply chain violated human labor laws or used materials that were not up to code, the company would be able to trace which materials the supplier contributed with the end product. The company can quickly step in to mitigate risk, engage new suppliers and communicate to its customers what action it will take to right the situation. That’s a compelling use of data to instill trust and protect your brand.

Q. The increase in technology and data generates plenty of benefits, but is there a downside?

A. The real issue is that the world has become more challenging for manufacturers and retailers because of this massive rate of change, which is all underpinned by technology. Technology is a big driver of the increased risk and challenges, but the question remains – can it also be the solution?

The answer lies more in the who than the what. If the right organization can examine it all holistically and start connecting the dots, then we can use technology to solve the problems as opposed to create them.

For example, Amazon uses technology and data to predict what a single customer is going to purchase from one day to the next. They understand an individual’s full life-cycle value and purchasing habits. UL has the ability to model a similar approach to affect safety, sustainability and performance outcomes and be a leader in big data and big science.

Q. How is UL helping bring value to this dynamic data puzzle?

A. All the data, to do all this good, to make all this change to benefit businesses and humanity, in general, all exist somewhere in the world. What doesn’t exist in equal supply is trust. Without enough players who trust each other with all the information, the data cannot come together in a way that can be easily understood by organizations and individuals. This is where we are headed as an organization, to a place where we build trust – not just in us as a repository of the data, but in us as an organization that connects the data repository in a way that provides value for all.

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