Earley AI Podcast – Episode 41: Knowledge Management and AI Implementation with Ian Hook

Building Value-Driven Knowledge Management: Leveraging AI to Understand Content, People, and Business Impact

 

Guest: Ian Hook, Director of Knowledge Management Insights and Excellence at Novartis

Hosts: Seth Earley, CEO at Earley Information Science

           Chris Featherstone, Sr. Director of AI/Data Product/Program Management at Salesforce

Published on: January 22, 2024

 

 

In this episode, Seth Earley and Chris Featherstone speak with Ian Hook, Director of Knowledge Management at Novartis, about the critical intersection of knowledge management and artificial intelligence in enterprise environments. Ian shares his unique perspective on the three pillars of knowledge management—understanding content, people, and business—and how AI serves as a powerful tool for connecting these elements. They explore practical approaches to implementing generative AI, strategies for quantifying knowledge management value, the importance of starting with small pilots, and how to bring legal and compliance teams along on the AI journey.

Key Takeaways:

  • Knowledge management requires understanding three interconnected pillars: your content, your people, and your business—AI excels at helping organizations understand these relationships.
  • Organizations often procure AI and knowledge management technology without first understanding the specific business value they need to drive toward.
  • Quantifying knowledge management value in concrete dollar figures transforms it from a "nice to have" into a tangible business imperative that opens strategic conversations.
  • Starting with small, targeted AI pilots allows teams to validate value and scalability before making significant investments in enterprise-wide deployment.
  • Successful AI implementation requires bringing legal and compliance teams along as partners early in the process rather than treating them as obstacles.
  • Centralization of knowledge resources can deliver substantial cost savings—Ian's team achieved $18 million in savings by centralizing market research at Novartis.
  • Education of leadership teams about AI capabilities and limitations is essential for creating organizational buy-in and establishing realistic expectations for AI projects.

Insightful Quotes:

"Understanding your content, understanding your people, and understanding your business—if you can understand those 3 things in relation to each other, I think you're doing very good knowledge management. And that's really where my interest in AI stuff comes in, because AI is really good at helping us understand those things." - Ian Hook

"A lot of people talk about knowledge management like it's this thing that we know that we should do, like exercise—I know that I should exercise and I'll get to it at some point. But we really need to get better at putting a number and a figure of what value it is that we're driving in an organization." - Ian Hook

"The reason why organizations are getting a lot of pushback from legal and compliance is because they're as scared as anybody in this conversation. We need to bring them along, define what we're doing, and help them understand it before we've ever invested $100,000 into it." - Ian Hook

Tune in to discover practical strategies for building value-driven knowledge management programs that leverage AI to create measurable business impact while navigating organizational challenges.


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Podcast Transcript: Knowledge Management Foundations, AI Implementation Strategies, and Organizational Change

Transcript introduction

This conversation explores the fundamentals of knowledge management in the AI era, covering Ian Hook's three-pillar framework for KM excellence, practical strategies for implementing generative AI in enterprise environments, the importance of quantifying knowledge management value, and approaches for building organizational buy-in from leadership and compliance teams.

Transcript

Seth Earley:So I'm really excited to introduce our guest today. We're going to be discussing knowledge management applications and the importance of knowledge management for artificial intelligence. We're going to be talking about the benefits and drawbacks of centralization versus decentralization around things like knowledge processes and artificial intelligence. We'll talk about solving issues with generative AI, such as managing hallucinations and using corporate data to answer questions rather than the knowledge within the LLM. And so our guest today is an AI and knowledge management professional with experience leading multimillion-dollar projects. He's had patents in NLP recommendation engines and more. He has experience leading multiple GenAI projects and transforming what enterprise-level companies are capable of. Today's guest is also a keynote speaker at major events including Digital Health Conference, KM World, Mobile Monday, Mobile World Congress, and more. Currently, he's the Director of Knowledge Management Insights and Excellence at Novartis. Ian Hook, welcome to the show.

Ian Hook:Hi, everybody. Thank you for having me.

Seth Earley:So I'd like to start off with your perspective on common misconceptions about knowledge management and AI. First of all, give us your definition of knowledge management. I know people kind of have lots of different ways of interpreting that. And then we'll talk a little bit about technology, the role of technology and the role of supporting processes. But let you just give your perspective on knowledge management in the enterprise.

Ian Hook:Yeah, so I think a really kind of interesting, provocative, important perspective on knowledge management is the way that I approach it is really it's about kind of understanding what your business is and what it does and how we can better facilitate it in doing that, really driving it towards value. And so when I talk about knowledge management in the business, I talk about 3 pillars, right? Understanding your content, understanding your people, and understanding your business. And if you can understand those 3 things in relation to each other, I think you're doing very good knowledge management. And I think until you understand those things, I think you are very limited in the knowledge management that you're able to do inside an organization. And that's really where my interest in AI stuff comes in, because AI is really good at helping us understand those stuff.

Seth Earley:Yeah. So when you talk about understanding the business, you know, I think a lot of—there's a lot of mistakes that are made around, you know, checking the box and procuring technology, whether it's knowledge management technology or AI technology or a combination of both. Do you want to talk a little bit about, you know, how organizations should be approaching the technology issue? It's the backbone and it's the mechanism by which we can capture and share knowledge. But what are the mistakes that people are making when they're looking at technology?

Ian Hook:You're absolutely right. And I think what you said there is right. It's the backbone, it's the structure around which we can build things. But I think what we, especially in knowledge management, need to better understand is what is the value in which we're driving towards and how do we need to leverage things like technology. I think technology is a part of the picture, but how do we need to leverage that towards driving more value? And I think we don't typically spend enough time understanding what value means, right, and what our part of that value picture is and can be and should be, right? And even when it gets down to actually putting a number figure on that, a lot of people talk about knowledge management like, oh, it's this thing that we know that we should do. And, you know, it's kind of like exercise, right? I know that I should exercise and I'll get to it at some point. But I think we really need to get better at putting a number and a figure of what value it is that we're driving in an organization. And when we start to do that, the conversations open up and people really start to understand, oh yeah, this is tangible, right? This is something that we need to do. And now technology, we can bring technology in to facilitate that business value. Right. And that's where you get the right technology applied in the right way. And that application of it in the right way is really important.

Seth Earley:So you mentioned the $18 million savings that you achieved. Can you talk a little bit about what that was and how you were able to demonstrate that and make the case for that?

Ian Hook:Yeah, so that was around market research. So we had a lot of market research that was being done across the organization in a very decentralized manner. And so what we did was we basically brought all that together into a centralized location where we could manage it, where we could understand what was being bought, what was being used, and then be able to rationalize that across the organization. And through that process, we were able to identify significant redundancies and be able to save that $18 million.

Seth Earley:So it sounds like there's a lot of benefit to centralization, but there's also—I know in other parts of the conversation we've had—there's tradeoffs with that as well. Can you talk about the benefits and drawbacks of centralization versus keeping things more distributed?

Ian Hook:Yeah, absolutely. I think centralization, you get a lot of economies of scale, you get a lot of visibility, you get a lot of control. The drawback is you can become a bottleneck, right? You can become slow. You can become less responsive to the business needs. And so I think the key is finding that right balance between centralization and decentralization. And I think what we've tried to do is centralize the things that make sense to centralize—the things that are common across the organization, the things that we can get economies of scale on—and then keep decentralized the things that need to be responsive, that need to be flexible, that need to be able to respond to specific business needs. And I think that's where you get the best of both worlds.

Seth Earley:One of the things that we talk about a lot is this notion of getting started with AI and generative AI specifically. And I think a lot of organizations are struggling with where do we start, how do we start, what's the right approach? What's your advice on that?

Ian Hook:I think starting small is really, really important. And I think a lot of organizations get into trouble because they try to boil the ocean. They try to do everything at once. And I think what we've learned is start with a small pilot, start with something that's very focused, that has a very clear business value, that you can demonstrate success with. And then once you've demonstrated that success, then you can start to scale it out. And I think that's been our approach at Novartis. We've started with very small pilots, very focused pilots, and then we've been able to demonstrate the value of those pilots. And then we've been able to scale them out across the organization. And I think that's been a really successful approach for us.

Seth Earley:And when you're doing those pilots, how are you thinking about the metrics that you're going to use to evaluate success? Because I think that's another thing that organizations struggle with.

Ian Hook:Yeah, I think that's a really good question. And I think it depends on what the pilot is. But I think generally speaking, we're looking at things like time saved, we're looking at things like cost saved, we're looking at things like quality improvement. And I think those are the three big buckets that we're looking at. And then within those buckets, we're getting very specific about what the metrics are. But I think those are the three big categories that we're looking at.

Chris Featherstone:Ian, one of the things that I find interesting is this whole legal and compliance piece. Because I think a lot of organizations—they want to move forward with AI, but then they run into these legal and compliance roadblocks. How have you approached that at Novartis?

Ian Hook:Yeah, I think it's a really important question. And I think the way that we've approached it is we've brought legal and compliance along from the very beginning. We've made them part of the conversation from the very beginning. We've educated them about what we're trying to do, why we're trying to do it, and what the benefits are. And I think when you do that, when you bring them along from the beginning, they become partners rather than obstacles. And I think that's been a really successful approach for us. And I think the reason why a lot of organizations are getting a lot of pushback from legal and compliance is because they're as scared as anybody in this conversation. We need to bring them along, right? Define what we're doing, help them understand what's going on here as well as we build it and help give us an understanding of is this something you would ever want to scale across the company before we've ever invested $100,000 into it. They are super happy, right? And that's, I think, also critical to remember.

Chris Featherstone:Define irony that most organizations now have most of their critical data sitting in a cloud-based environment. So what in the hell is the difference between your most critical data sitting in a hyperscaler's cloud and you're freaking out about what a large language model can and can't do? Good Lord. Like, you know, can we please pull our heads out and actually think about this like adults and say, okay, I get it, risk vector here. However, you're past that risk vector. Like, you're already down the river through the hardest part of the rapids, and now you're worried about what's ahead? Come on.

Seth Earley:Yeah, I mean, there are a lot of ramifications to compliance. We're right at the end of our time here, so, Ian, before we go, I wanted to just learn a little bit about you, how you got to where you are, and what's your career path been, and then what do you do for fun? What do you do outside of work?

Ian Hook:I like to say I'm the least qualified person to be in this position. And so I have a degree in biblical studies, and I was a preschool teacher and then went into startup building apps for preschool kids, and then I ended up in Accenture doing some gamification stuff there. And that's where we ended up building a bunch of the AI stuff with a couple of colleagues there. It was great fun. And so that's why I came here, is basically to do similar kind of stuff over in Novartis with the AI and the KM background. And it is a really very lucky point.

Seth Earley:How did you get to Accenture from your background? And I missed that part.

Ian Hook:So I was building games for preschool kids. And Accenture at the time had a gamification program, and so I jumped over to help them run the gamification program.

Seth Earley:So preschool and consultants and clients and customers are pretty much similar kind of—

Ian Hook:Pretty much the same. Hey, hey. Ian, react to the same way and to games and pleasure from that.

Seth Earley:And what do you do for fun? What do you do in your spare time?

Ian Hook:So I just recently moved to Basel in Switzerland, so I had to sell all my stuff, but I was a blacksmith and I used to make kitchen knives. That was kind of what got me going. So my whole garage used to be a whole workshop with anvil and a forge in there and stuff.

Seth Earley:So where was that before you moved to Basel?

Ian Hook:In Prague.

Seth Earley:In Prague. Okay, wow, that's quite an interesting hobby.

Chris Featherstone:Yeah. I got one question for you, Ian. Was there a question that we didn't ask you that we should have? Was there something that is like, you know, if you think about all the things we talked about, was there something that maybe we missed or that we should have asked before we go?

Ian Hook:Yeah, I think we covered a good chunk of it. The only other thing which I'm doing right now which I think is important is education of leadership teams. So I spend a lot of time talking to leadership teams. Actually, before Christmas, went away to China to educate the leadership team over there over just what it is and how it works and how we should be a part of it. And that's really, I think, part of this conversation of owning the conversation around ChatGPT.

Seth Earley:Absolutely. Absolutely. Well, Ian, it's been a pleasure having you on the show. I really appreciate your time. Thank you so much for being with us.

Ian Hook:Thank you very much. I really appreciate it.

Chris Featherstone:And if you're at MWC, you know, I think I'll be there too. Then we're definitely, you know, get your beer or get you something so that we don't have any gallbladder attacks. But I'll take you up for dinner, whatever, right?

Ian Hook:Yeah, my wife's put me on a diet now, so there you go.

Seth Earley:That's been another episode of the Earley AI Podcast. Thank you to our audience for listening. And again, thank you to Ian, of course, Chris, and then Liam and Carolyn behind the scenes. So thanks, everybody, and we'll see you next time.

 
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