Orchestrated Analytics
IQVIA Orchestrated Analytics connects actionable, intelligent insights across commercial teams to empower improved strategic decision making.
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Americas
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EMEA Thought Leadership
Developing IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
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Middle East & Africa
EMEA Thought Leadership
Developing IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
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Americas
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Asia & Oceania
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Europe
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Middle East & Africa
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Americas
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Asia & Oceania
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Europe
Europe
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EMEA Thought Leadership
Developing IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn more -
Middle East & Africa
EMEA Thought Leadership
Developing IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn more
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SEARCH JOBSVideo
Making sense of data: Focusing on solutions over inputs to maximize value
Apr 28, 2022
If you look into the last 10 years, the boom of the data, the most important thing is understanding both positive, as well as negative. The negative being, you have too much of data. The positive being, now you can actually do something with this data.
If you think about the data, it's like an orchestra. There's a lot of noise, a lot of data. Everybody's talking about data. And the data analyst is the conductor trying to create the symphony of this data. So, they are trying to create harmony that gives you that insight that you can take action upon.
I think the major challenge of the business and IT is to come together to realize the potential of what data can bring, but also work together to bring their vision to life.
The first thing I would always say is, instead of thinking about “how”, start talking about “what”. What is that you're trying to solve? What is that insight that will drive your business? Once you understand the “what”, then you try to answer “why” before you go to “how”. Every time, we tend to lead towards the “how” part of it, should we bring all the data in, but for what purpose? What is that insight that's going to help me drive that? So that might help you filter out some of the noise and focus on the data that you actually, and that might not be so big, that might not be so scary.
The most important thing for data managers is to think about that end goal in mind. If you know that I'm trying to generate an insight that's going to help my reps to be more effective in the field, or you're trying to generate an insight that's going to help you select the sites to run your next clinical trial. So, once you know that end result, then you start tracking it back. What are the data sets that today we have available in the country or in the company? Then, from there, you try to understand in order to pull that data in order to integrate the data, do I have the right tools available? And once you have answered these things, then you try to actually go in and start working with this data assets. As a data manager, as an IT infrastructure leads, your first important thing is not to just consolidate this data from different sources, but really putting that governance model. And this is where IQVIA as an omni-channel vision in our connect framework, we emphasis on this data quality metrics.
I think the problem of data silos, within each of the customer's regions and in the business unit, and trying to get integration of those data assets, is the first major problem that our customer faces. Second thing is understanding those data so that you can actually take insights and take analytics on top of that data. So, you've organized that data, you've structured that data. And the third part is, when actually generating those insights out of this data, how do you send those insights back into the end user applications. Because your end users, your customers, your reps or your clinical trial administrators, are not sitting on the data platform, they're sitting on their end-user platforms. So, as you're generating those insights, you bought the data, you've generated your insights, and now you want to make sure those insights go back to those applications.
Whenever we are interacting with customers, we are trying to understand what are those key aspects of omni-channel that you're trying to sell. Because the important thing, the way market has shifted, we were in an era where we were looking into one single channel, that is the rep driven market in the commercial space. Then we moved into the era of multichannel. We wanted to interact with the customer in different channels. Now we're in an era where we are looking into how this channel actually works together, because end of that, it is not about channel, it's not about the data, it is the customer at the center. You are trying to reach your customer the most effective way you can. So, you need to orchestrate those channels in such a way that it doesn't feel like you are trying to impact that customer or trying to influence that customer but try to bring the right value to that customer.
Healthcare life sciences is our bread and butter. When we understand what our customer is trying to do, then bringing our data, technology and services, we can help accelerate those visions that our customers are trying to realize.
I think when you combine this data, consolidation, data integration, and this analytics on the data, having that structured approach of looking at the bigger picture and then drilling it down to the core value proposition, will definitely help the data analysts, data managers to get to that success. This actually helps our data analysts and the IT to come together and try to do some innovative things with the data. I'm really excited with this marrying next between the data for new expansion and the technology to support that. It will be the next generation for us to develop insights.
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