Hiding in plain sight
26 Oct 2017
By: Brad Howarth, researcher, speaker and author
Data is the lifeblood of modern organisations. But as the tools and techniques used to derive insight from data have evolved, the need for the right data skillsets has also risen dramatically.
The result is a shortage of skilled data professionals, and a tendency to segment them away in dedicated data functions.
But if data is becoming more important to all aspects of an organisation, is it still wise to have data science squirreled away as a separate capability? And where will the next generation of data professionals come from anyway?
Perhaps the time come for all of the workforce to have some degree of data literacy.
Natalie Evans Harris is the chief operating officer and vice president of ecosystem development at BrightHive, a US-based community-focused data integration company. She says that for the social sector to draw the insights necessary to improve outcomes at the community-level, organisations must build their capacity to leverage data as an asset and integrate data literacy into the workforce culture at all levels.
“You know you’ve reached true data literacy when everyone in the organisation understands their role in transforming data into valuable insights that lead to informed actions,” Evans Harris says.
Evans Harris believes the role of data literacy is often undervalued when delivering data solutions. Hence one of her motivations for taking the leap from working in the US Federal Government to co-founding BrightHive was to train customers on what it meant to be able to use data in interesting ways, and what kind of insights could be drawn from it.
“That is hugely important, because you want them to be able to do more than click a button, you want them to be able to think and move differently because of the data,” Evans Harris says. “Everyone in the organisation doesn’t need to be able to program, but they need to have an understanding of what data can do for them.”
On the flipside, she says while those people tasked with the technical aspects of data science still need the math skills to understand and manipulate data, they also require the sector-specific skills to understand how data can generate useful insights.
“You need data scientists that can communicate and draw questions and insights, and really have some of those collaborative skills necessary to ensure the diverse set of stakeholders needs are brought into the data lifecycle,” Evans Harris says.
It is these non-technical skills that are often the hardest to find. Evans Harris has at times hired based on a candidate’s ability to look at unstructured complex challenges and create structure, such as how they would organise 100 unlabelled MP3 files, rather than just their programming skills.
“Just being able to see how they think and how they go about operating makes a huge difference, because the rest of it you can train them on,” she says. “Someone we hired who was fantastic was actually a math teacher. He had strong maths skills, but hadn’t developed a lot of the programmatic skills. So we taught him that. But because he had the math and communication skills, he ramped up quickly and was incredibly effective in working with our other primary customers.”
Brett Goldstein has first-hand experience in creating the next generation of data professionals through his work with the University of Chicago in creating the Master of Science in Computational Analysis and Public Policy.
A former chief data officer for the City of Chicago, Goldstein says the course is a response to the tendency for data specialists in public organisations to operate remotely from policy and technology professionals.
“We are creating the next generation of government workers who are able to both analyse the data and provide near-real time decision support, but at the same time can brief the executive by talking in a way that makes sense,” Goldstein says.
Refusing to pigeon-hold people is another factor that has enabled Goldstein to avoid skills challenges, such as the one he faced when implementing the data strategy for the City of Chicago. At that time the city’s CIO had a strong complement of traditional database professionals on staff, but little experience with newer technologies such as NoSQL and MongoDB.
“Everyone said ‘you’re going to have to hire outside people’, and I said, ‘I have great talented folks who want to learn new things’. And so in the biggest conference room in City Hall I started teaching classes in MongoDB and R. And people thought it was completely nuts that a commissioner was doing that, but that was how we made Chicago into a data-driven city.”
Evans Harris says programs such as these will become increasingly important as organisations seek to get the most out of data.
“I want to see a world where we get beyond dashboards,” Evans Harris says. “I want to a world where we use data to not only increase efficiency and improve processes, but to build connections that we never saw before, to change the way we view, understand and take action. But you can’t do that if you don’t have the subject matter experts smart on the value of data, as well as the data scientists smart on what those people need.”