What do you do with your healthcare marketing data?

Natasha Cowan, Pany Koizi, Will Frostick, David Wood, Sarah White|9th July 2018

Data analysis is often pitched as the solution to all our marketing problems. In the next three years, marketers are predicted to increase their spending on analytics by a mammoth 198 per cent, with healthcare marketers estimated to spend 21 per cent more than they do now, according to a recent survey conducted by Duke University’s Fuqua School of Business.

However, while most healthcare organisations revere data, many marketers do not know how to translate the raw information into analysis that will help them meet their marketing goals and improve their strategy. In fact, the same healthcare marketers surveyed by Duke University gave the effectiveness of their data analysis a meagre 4.7 on a seven-point scale (1 = not at all effective and 7= highly effective).

So why are pharma companies spending more on analytics if they aren’t reaping the rewards? Senior Content Marketing Executive Natasha Cowan sat down with four of Blue Latitude Health’s very own BOBI Analyst of the Year finalists – Will Frostick, Pany Koizi, David Wood and Sarah White – to explore the challenges, opportunities and common mistakes pharma marketers make when delving through data.

What are the biggest challenges around collecting and analysing data in healthcare?

Pany: Pharma and healthcare companies have collected thousands of terabytes of data in the last couple of years, the difficulty is in understanding how to leverage it. This is both in terms of how to treat patients, and how to maximise commercial effectiveness. We’re finding that pharma companies need support in understanding how to structure and question data, which can be developed into actionable insight.  

David: To compound the issue, there is not always consistency across the data collected from different sources. There’s often a challenging mapping step that needs to take place before you can even look at the data you wish to use. 

Will: One of the major challenges for our clients and their data is credibility. Sales reps generate a fair amount of information during their visits, but the reliability is poor, and it’s often coded incorrectly. This is partly due to human error but also partly systematic limitations in the technology. As a result, clients don’t believe the conclusions are worth the paper they’re written on – getting quality input is a real issue for them.

What are the dangers of misunderstanding data or making mistakes in the analysis?

Sarah: It’s important to understand that data analytics is just one tool we can use to help us solve a problem. Data can give us a false sense of certainty, and the danger is that we become too reliant on it. Data gives us clues, not answers, and we would be smart to take it with a pinch of salt and put equal weight on other tools for insight gathering. This gives you a window into your customers’ requirements and helps you design messaging that speaks to each group.

David: The credibility of data sources can always be challenged. Given the nature of the industry, there is often an element of bias due to the sourcing process having been funded in part (if not entirely) by a pharma company. There is always a risk of skewed results, which can be easily misinterpreted.

Pany: I agree, using objective, quantitative sources of data to inform the development of commercial activities is a challenge. At the moment, there is a huge focus on collaborative decision-making and conception of tactical ideas, and quite rightly. However, this ultimately ends up being informed by tacit knowledge and is largely shaped by whoever shouts the loudest in a group. We need to incorporate data into every single step of the decision-making process, from ideation to implementation, to measurement and refinement.

Data, information and insight all sound similar, is there really a difference?

Pany: Data is the individual numbers captured under some defined parameters. In pharma, it could be considered as an individual physicians’ response to a message they’ve experienced (good, bad, neutral). This is typically a single cell in an excel spreadsheet. Information is a collection of data points that can be used to understand a certain situation. For example, seven out of 10 physicians responded favourably to this message. Insight is taking information to the next level by applying context and understanding the “why”. It's about asking the right questions so you can analyse the information and draw actionable conclusions.

 

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