Transcript: Data Not Content Is Now Publishers’ Product

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Interview with Grace Hong, Wolters Kluwer Tax & Accounting Division

For podcast release Monday, March 7, 2016

KENNEALLY: Information is the new petroleum. Just as oil and its byproducts, including gasoline, drove innovation and development in the 20th century, information will spearhead change across the decades of the 21st century.

Welcome to Copyright Center’s podcast series. I’m Christopher Kenneally for Beyond the Book. Industry analyst Doug Laney has defined infonomics as the study of the production and consumption of information. In this view, information is accounted for and managed as a business asset. As publishers remake themselves into information providers for the digital age, they should abandon the notion of content as their product, says Grace Hong. Instead, publishers must move to the marketplace that big data has opened up. Grace Hong, vice president of strategic markets and development and general manager of learning solutions for Wolters Kluwer’s tax and accounting division, joins me now from New York City. Welcome to Beyond the Book, Grace.

HONG: Hi, Chris. Thanks for inviting me on the show.

KENNEALLY: We’re delighted to have you join us today, because big data is much on the mind of publishers and many other industries in 2016, but I’m going to guess that a few of them are really wondering, what’s the big deal all about? You’ve got some interesting thoughts on all this. I think the place to start, though, Grace, would be to give us a definition of what we mean by big data.

HONG: Big data really addresses, I think, more of – is a reflection of what’s been going on with the evolution of information and technology in the past 30 years. From the ’80s to now, we’ve seen information go from analog, from books, vinyl records, looseleafs, and tapes, to in the ’90s, the PC revolution, with digital information being produced by hard drives and CDs, moving into the age of the internet, where we have structured data, databases, traditional BI, and then more recently to the cloud, with datacenters, virtualization, new technologies.

I think we’re at a moment where the data itself and information has to be adapted and personalized to the user with the growth of information. I think big data represents the opportunity presented by the growth of data overall, and particularly the growth of unstructured data. In my space, which is tax and accounting publishing, as well as legal publishing, much of that data is captured not only by servers or by databases or our products themselves, but also through the text that we produce, through the tax code, and other sources of content.

KENNEALLY: It’s all very interesting, and I’m still learning myself. You mentioned a term, and I just want to be sure our listeners understand the difference – there is this notion of structured data and unstructured data. Can you give us a brief definition of the difference?

HONG: Absolutely. Structured data is really the purview of traditional data warehouses. You can imagine – there are software products and research products online in my world that may collect usage information that’s then connected to customer databases for order processing. Structured data means that there is an identifier that can easily collect and collate information across all these different sources and provide, let’s say, a single view of the customer, which is what we strive for, at least – in my role when I think about big data, it really is about value creation and about specifically understanding the customer better. Many of the data warehouses that we have within Wolters Kluwer and many other companies really strive towards not only processing those transactions, but really getting a clearer view of the customer across this landscape.

KENNEALLY: And I think you are fond of saying, Grace Hong, that it really doesn’t matter whether the data is big or little. In fact, the data itself is not valuable on its own. What’s really important? Where do we get the value as publishers from the data?

HONG: Yeah, I think the world has become a lot more complicated, especially when it comes to big data and especially when we think about organizations like traditional publishing organizations. Data in and of itself is not valuable. It’s really about the insights and the problems that you’re able to solve. That really varies depending on the context in which you’re thinking about data.

Today, much of the unstructured data that exists is produced via machine logs for operational intelligence. There is data that is – for example, I think of it as – I wouldn’t call it trapped in text, but you may think about journal publications in the tax area that seek to produce explanations and answers for professionals. This is text, but all of this text can be mined to provide greater actionable insights to our users.

For me, from a product standpoint and from a customer standpoint, it’s about asking the right questions and then really deeply understanding how this information can provide value to the customer, not only just mining the data that currently exists. It’s really about creating that meaning through asking the right questions.

KENNEALLY: Right. I can imagine that this is a process that’s very exciting, but also perhaps, at least in its initial stages, a little bit frustrating, because you have to learn what are the kinds of questions that are going to be best addressed through the analysis? What are the concerns the business has? And then you get to the data. It’s really, as you point out, sort of marshaling all the information you have outside of that pool of data, outside of that ocean of data, and then diving in.

HONG: Exactly. It is about marshaling the data – that you can get into a state fairly easily of analysis paralysis, where you find very interesting insights, but really it should be driving action. And it’s not about, as you said, the size of the data, whether it’s little data, whether it’s big data. The way that I’ve approached this effort has been through a process of not only inventorying what already exists with our data, but going through the process of using that data to profile our users and then thinking about those profiles and segments of users and tailoring the analysis from there specifically to those users so that we can either understand them better, deliver better products, understand how to reach them. Those are some of the applications that kind of come into play.

KENNEALLY: Right. We are speaking right now with Grace Hong, who is vice president of strategic markets and development and general manager of learning solutions for Wolters Kluwer’s tax and accounting division. I wonder if you can give us an example, Grace Hong, of where that kind of analysis has really moved you to help to better place your products before your customers or to, in fact, develop new products.

HONG: Sure. One very good example, I think – as I mentioned earlier in this interview – was the application of personalization. As we are all very much overloaded with different types of content, it’s much more important that it be on point. Specifically with regard to learning solutions, Wolters Kluwer is integrating user information to drive personalized recommendations on learning courses that people should take. We’ve found that the dichotomy between software and research or software and learning and research and learning really is kind of a false dichotomy. It really is about getting people to the information that they need to make the right decisions. So at Wolters Kluwer, one of the things that we’ve done is to surface our courses in the learning area through our research products as one avenue to bring people to the information and insights that they need when they need it.

KENNEALLY: Right. Grace, as you make the argument with your colleagues that data is really the new product that publishers have, how does that go over? Is this such a sea change for the industry that it’s really taking time to be felt across the business?

HONG: I think everyone recognizes that it’s true, but it’s a process. It’s an evolution. And I think it is being felt across the organization that particularly in the publishing space, there has been this paradigm, especially in professional publishing, of going to a research product, to a research engine, typing in a search or browsing through a browse tree to retrieve information, whereas the way that customers do want to search for this information or have this information provided to them is in the tools that they use on a day-to-day basis, whether it’s through Google, whether it’s through software products that they may be using, like for tax compliance. Those are the areas where it’s important for us to integrate content and tools together so that we can provide great value to our customers.

One example of the way that we have done this is, for many years, we heard that customers did not want to conduct research. They were going to Google for answers on tax. And we made a pretty bold move at the end of 2014, where we said, OK, we’ve been hearing this for years. Why don’t we, instead of fighting Google, integrate with Google? And we developed a plugin that, really, when people were searching, they could search side by side Google results and our databases. This made a huge difference in overall retention, in the overall search volumes, and product usage overall. That was a big success for us.

KENNEALLY: I think what that says, Grace, is that the data has to lot to say, but you have to be prepared to listen.

HONG: Exactly. (laughter) Yeah, data has a lot to say, but data in and of itself can only take you so far. You have to couple the findings with data with qualitative aspects, as well. It is about also listening to your users and your customers. The data can help you either formulate hypotheses, or when you have hypotheses, test them. But you need a multifaceted and more holistic approach, I think, to kind of get to the right answers.

KENNEALLY: And the strength that publishers have is that they do hopefully understand their customers and they understand the material. They’re in the position of being able to make recommendations.

HONG: I think it is about not only making recommendations, but also getting people to an answer faster. In the professional publishing space – I think this is true across tax, certainly across legal, and I’ve seen it in health – people have less time to read a document and formulate their hypotheses or their conclusions, and they want to be brought to an answer as quickly as possible. So I think there’s a lot of promise for publishing organizations like Wolters Kluwer and others to partner with or develop their AI capabilities and change the DNA of the organization to provide not only intelligent recommendations, but to get people to an answer more algorithmically, potentially, than through traditional publishing means.

KENNEALLY: Well, we appreciate the answers you’ve given us today, Grace Hong. Grace Hong is vice president of strategic markets and development and general manager of learning solutions for Wolters Kluwer’s tax and accounting division. Grace Hong, thanks for joining us on Beyond the Book.

HONG: Thank you, Chris. I enjoyed speaking with you.

KENNEALLY: Beyond the Book is produced by Copyright Clearance Center, a global rights licensing technology and content workflow organization. At CCC, we serve more than 35,000 customers and 15,000 copyright-holders worldwide. We manage over 950 million rights in the world’s most sought-after journals, books, blogs, movies, and more. You can follow Beyond the Book on Twitter, like us on Facebook, and subscribe to the free podcast series on iTunes or at our website, beyondthebook.com.

Our engineer and co-producer is Jeremy Brieske of Burst Marketing. I’m Christopher Kenneally. Join us again soon on Beyond the Book.

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