Shawn McKenna

Shawn McKenna is a senior director of analytics at Currax Pharmaceuticals.


When you think about the different types of research that you do, can you talk about how things like primary, secondary, internal data, external data, all these different things come together to answer the questions that you're responsible for in your role? 

That's a huge question, first of all, but it's a good question. In general, we will try to get as many lenses as humanly possible on most things.

So we'll take it as far as we can using internal resources or desk research or anything that's available to us from a secondary aspect. 

But then when we switch into why something is happening or what we could do to improve, that's when we tend to need to switch over to actually talking to folks with primary as well.


So taking stock of what you have at your disposal, what's “known,” and then you would go and verify and validate with actual people?

Maybe not even necessarily validate – if we are moving into a new space, there's nothing to validate. So maybe just trying to figure out what's the best way to do something. 

You can look at secondary data before you do any exploratory journey mapping to make sure you're asking a lot of the right questions, and then do the qualitative exploratory journey work to really understand your customer journey, which will then inform a lot of downstream work as well.


When you get started on a project or whatever big assignment you might be tackling, however it works in your workflows, where do you typically start? Is it a hard and fast rule to say we always start with, for example, it sounds like desk research is coming up? 

Does it totally depend on the stakeholder or the project or different dynamics?  

It totally depends on the project. You could start with secondary data to get a sense for the opportunity. And then a lot of times you don't know what the questions are you want to ask yet. So, it totally depends. But you'd start with defining the problem you're trying to solve very clearly, maybe answering that question six different ways before you start any research.  

It's really hard to say. Some questions are really big, some questions are really small. Some you can kind of get away with having a best guess at, some require a lot more commitment and certainty about. So it's super tricky to find a one-sized answer for that one.


When you think about desk research and different tools you may or may not use to get answers from whatever's publicly available, what types of tools, resources, partners do you tend to leverage?  

So you can't really be just sitting down and spending a bunch of time on Google, so you push that as far as you can.

There is a lot of value in social media as well, seeing what's out there. 

In pharma, there are certain resources that companies utilize that do work on a background, secondary basis that we can kind of dial up and look at.

So there are a lot of basic products like that and Google – just sitting down doing it yourself.  


What's the hardest part about that? 

The hardest part of that is knowing when you're spinning your wheels – to know nothing else really exists to answer this question that you've been asked vs. did you try hard enough and figure it out for yourself first? 

I think that's the hardest bit, knowing when you've really exhausted it all.

When you need to move on and move into secondary, move into analytics, or we might need to move into primary. Knowing when that point switches is tricky. 

It just depends on the project. Again, the problem that you're trying to solve should point you towards some sources and not others. 


Last final question for you. Speed round!

When you think of AI and research, what one word comes to mind? How do you feel about it? What's the first emotion that comes up for you?  

I was going to say a very nerdy word: inchoate. It's in the beginning, we're only trying to figure it out. I know a lot of folks are here with somewhat different degrees of polished solutions or ways to follow it. But in my opinion, it's still just very much in the inchoate stages of trying to figure out what's the best way to tackle some of these problems.

Oversight. I can’t think of a single thing that it doesn't require oversight to do. It needs to be man-assisted. I'm optimistic, and at the same time, we’ve got to wait and see. 


Feels like humans are not going anywhere, which is also true for your businesses. Thanks so much.