Wicked Problems & Messy Data

Horst Willhelm Jakob Rittel was a university professor best known for coining the term “wicked problem”.

In policy, a wicked problem is a problem that is difficult or impossible to solve because of incomplete, contradictory, and changing requirements that are often difficult to recognise.

Homelessness is a classic example of a “wicked problem”; there are an infinite number of causes, and there isn’t a ‘one size fits all’ approach to solving it. For community-based organisations in the health, homelessness and social services sector these wicked problems are further exacerbated by poor, incomplete and haphazard data collection. If organisations don’t know what the best ways measure their objectives are or focus to much on outputs over outcomes, how do they know if they are making an impact on homelessness?

Watch the event here

Shannen Vallesi is a Research Associate from the School of Population and Global Health at the University of Western Australia. She works with organisations on their data and has built up a repository of knowledge of best practice when it comes to collecting it.

Shannen Vallesi

“As researchers we are often called in halfway through the program delivery to assist with a service evaluation,” Shannen said. “This happens quite a lot.” Shannen explained how organisations will get close the end of a program funding cycle and realise it would be good to use data they’ve been capturing for a report, infographic, or to build up evidence to back them on how successful a program is working and to advocate for ongoing funding, but the idea of evaluation is often an “afterthought”.

“We are often called in halfway through the program delivery.”

Poor Collection

The importance of evaluation by analysing data is increasingly recognised by community-based organisations, but there are challenges. Many small not-for-profits resources are stretched, and there is little or no money for evaluation. Staff are busy providing a service to the client have no time to routinely collect any form of data. Sometimes data has been collected but the data systems in place are not set up with an evaluation in mind down the track.

We sometimes get too focussed on outputs not outcomes. Such as, ten people supported or 100 referrals made. Rather than ten people permanently housed who have all sustained their tenancies for one-year, or that only 10% of referrals were accepted.

Think Spot

Shannen encourages us to reflect on how the following challenges and solutions can impact your organisation, service, or your role.

You Have Data …. But!

Have a think about the current data you are collecting. Could it be messy?

Shannen reflected on the work she has done with Homeless Healthcare, Perth’s largest provider of primary healthcare services to people who are homeless or marginally housed. The data were rich, but it was messy.

“They run eleven different services or clinics that they run,” Shannen said. “Each clinic was collecting their own separate Excel spreadsheets, each of those was being entered into by multiple people. We found the same people had been entered into the system multiple ways. One person in there had fourteen different spellings of their name.”

As shown the pragmatic solutions are to tweak the way a user enters the data through a dropdown menu or proforma fields of capturing dates or categories. There are many simple solutions that can be implemented to save time for everyone. “We understand as researchers it not always possible to collect everything that is ideal for an evaluation while you are busy in the field, but there are small changes we can assist with to make the whole process more streamlined” Shannen said.

A Little Tweak

Have a think about who will see the data. Data is power and funders do want to know the actual “difference you are making”. You don’t want to get to the end of a program to realise you have not collected the right data. A small reframe of your data can have a big impact.

Shannen has kindly shared her entire Slide Show from her presentation with us. View it here to get some great ideas on how to improve your data.