Lots of us jump straight from data analysis to data visualization. We don't stop to think about whether we're choosing the right visualization for the decision-making situation we find ourselves in. We don't consider if we're using a visual metaphor that will work for our intended audience. This is a course that provides you with a checklist for thinking more 'systematically' about information design, and how we can use the design of our data exhibits to connect more effectively to our audience's way of thinking.
9:30 to 11:00
Switch between patient singular and patients plural
The clinician view of the world is dominated by 'the patient that's in front of them' (patient singular) rather than 'patients in general' (patients plural). Yet data analysts focus on the latter: counts, aggregates, percentages and averages. We can bridge this gap by switching back and forth between the 'patient singular' view and the 'patients plural' view. It's individual patient stories that motivate us, rather than summaries of systems and processes. So we need to ensure we create data exhibits that make individual patients visible, as well as making the bigger picture clearer.
11:15 to 12:45
Display the whole system; not just the silo
Imagine you are reporting data for an Acute Medical Unit. Their work is sandwiched in between A&E (where all the patients get transferred from) and the specialty inpatient wards downstream of the Acute Medical Unit (where most of the patients get transferred to). It doesn't make sense to report the Acute Medicine activity in isolation; their activity only really acquires meaning if we look at what's happening either side of it. And we can look beyond the immediately-neighbouring silos. It can be helpful—for example—to look at which GP practices originally referred the patients, and it can be valuable to look at what happened to the patients subsequent to their discharge.
13:30 to 14:45
Show 'what is' alongside 'what ought to be'
When clinicians examine patients and measure things like blood pressure and weight, they don't just report back what the measurement is; they also tell them what it ought to be. In order to find these 'ought-to-be' numbers, we should seek out the data that describes systems and processes when they are working well. We can then extrapolate from that data to arrive at what the 'ought-to-be' numbers for the system are. These 'ought-to-be' numbers then need to be combined with the 'what is' numbers in designs that enable quick and easy comparison.
15:00 to 16:00
Choose different (and multiple) data camera angles
Most of the data visualizations we do can be approached from multiple perspectives. For example, if you look at A&E data from the perspective of an A&E charge nurse, you will design your chart differently from how you would do it if your customer was a GP. Or a geriatrician. Or a social worker. Yet we often—by default—choose just one perspective when we design our tables and charts. This session shows how the perspective changes the way we design our data, and argues a case for showing multiple perspectives.
Principles of Information Design can be booked as an on-site workshop for £1,250+VAT, and up to 12 participants can be accommodated in a workshop session facilitated by Neil Pettinger. Email email@example.com to start making arrangements.