THE THOUGHT LEADER INTERVIEW
Indegene PharmaFuture: How do you think organizations should approach the content supply chain? What opportunities do you see here to create value?
Thomas: Well, Novo Nordisk and many others are looking into the opportunity of decoupling creative generation of content with the production. Moreover, the reproduction and reuse of content is becoming more and more attractive as we increasingly use digital channels. It's not about not working with the traditional agencies of record anymore, but it is about doing what is most efficient at places that offer the best opportunity to create efficiencies, not just in terms of cost but also capacity.
In terms of maximizing utility of content supply chain, we are focusing on 5 KPIs: Use of content, re-use of content, cost of content, quality of content, and time-to-market of content.
These KPIs are driven out of two needs. First, the need for efficiency, we simply need to be cost-conscious in the way we produce content. But foremost, I would say the anticipation of the content volume increasing rapidly as we embark on an increasingly digital and multi-channel communication with our customers (patients, payers or providers). I don't think it's anything new in the industry, but in terms of Novo Nordisk, we have started to prioritize this area.
We are hoping to turn marketers from being tactical project managers into more strategic marketers, to free up their mind space and physical time to focus on creating unique customer experiences instead of producing fantastic marketing tactics for execution.
In this interview, the Vice President of Commercial Operations at Novo Nordisk, contends that pharma must change its go-to-market offerings and improve efficient resource utilization across digital. An edited transcript of the conversation follows.
VP of Commercial Operations, Novo Nordisk
Indegene PharmaFuture: There is a certain amount of risk built into deploying new technologies and undertaking the digital journey. How do you ensure that these investments are fully leveraged and don’t end up as technology solutions that don’t impact the business?
Thomas: It's really not about the technology but the change of mind-set and the process in the organization. First and foremost, we're not doing any significant technology investments that are not already warranted. For example, let’s look at the need for approval of promotional material process - the benefits that we are getting from existing tools, we need to leverage them better within the organization. And that's according to me the main challenge. It’s not the
technology challenge, it's all about utilizing that technology in the existing processes and changing minds.
And how to change minds? We need to go one step at a time and show the way forward to others. So, would this be possible in Novo Nordisk 5 years ago, what we are doing in terms of optimizing the digital content supply chain? – No, because there wasn’t a burning platform to bring about these changes at that time. If it isn’t broke, don't fix it, as they say, but I think industry is kind of coming to the conclusion that this model will be broken soon if we are to embark on significantly more channels of communication.
Thomas: In the next 2-5 years, we will see a lot more data coming in on our customers. The pharmaceutical industry is lagging behind compared to other industries in terms of knowledge of their customers. I'm not talking about clinical data here. We have plenty of that. What I'm talking about is Real World data and UIRL (Use In Real Life) data on both patients and HCPs. Especially the 'Digital Footprint' of HCPs, where we will get more insights in terms of content consumption, preference, channel affinity etc.
It's up to us to treat and derive insights in a decent and ethical manner and that is not something we've had to focus on earlier because we have had great products. We still have great products, but the marketplace is changing and we need to become more savvy and insightful around how our doctors prefer to interact with us and how we stay simple, relevant, and trustworthy in our communication. We need a new insights and information around that.
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Note: The views, thoughts, and opinions expressed in the article belong solely to the thought leader, and not necessarily to the his employer, organization, committee or other group or individual.
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Indegene PharmaFuture: How can we build strong data capabilities within the commercial organization?
Thomas: Pharmaceutical companies like us with strong scientific and R&D capabilities are not really suited for this. We need data analysts and scientists. We don't want to start hiring a lot of programmers for coding, but we need data analysts and data scientists to derive information out of data, knowledge out of information, and insights out of knowledge. That’s the base of the pyramid- Data, information, knowledge, and insights. And the upper part of the pyramid - that's where the traditional marketer, with all their skills, needs to work with the data scientists, the analysts, and the business intelligence folks to get insights. The insight generation process won’t work well unless it's integrated or inherent within the person making the strategic decisions, so that's where the collaboration needs to happen.
Indegene PharmaFuture: Over the past decade, the excitement about the new innovations in technology (including AI and ML) hasn’t been matched by the rate of adoption on the ground. How do you see that playing out moving forward?
Thomas: We still lack a lot of good clean commercial data, before we can start creating any form of commercial AI. Clinically - that's another story. I believe there are huge opportunities here. So, when there's not a lot of data, some important questions you want answers to are - How do I get data in a good manner? How do I store it and build the appropriate supporting software / technology / databases to treat and clean it? How do I derive the insights?
Some companies are further down the road. We're not that far just to be completely honest in the commercial space and we need to do that before we invest too much in machine learning or AI. In terms of timeline for the industry, I see these technologies playing out actively in the next five years. However, I could be wrong, depending on major shifts that might happen within the industry.