With data holding massive potential, learning how to use and interpret data yourself is a key step to making the most of it. While data does not necessarily lie, it does not always tell the truth, and data literacy is the ability to coax out genuine insights.
However, it is only recently that the importance of data to a modern business has become evident. Recent developments such as smart assistants demonstrate what good data management can enable. Data can solve challenges in many fields – logistics, commerce, sports, and healthcare, among others.
Take the coronavirus pandemic, for example. Data science was instrumental in helping set government policy. The ubiquitous term ‘flattening the curve’ was ultimately derived from the field.
Even today, there is a constant stream of Covid data – cases, deaths and vaccination rates – which helps policymakers and healthcare practitioners to better-understand the crisis. Whether it was making predictions, providing advice, or helping develop vaccines and treatments, data science helped tackle the greatest health crisis in decades.
However, discourse around Covid-19 has been rife with misinformation and misinterpretation of data. The pandemic provides an illustration of how important data literacy is, not just as a specialised skill, but as a universal one.
To better understand the importance of data and data literacy, DIGIT spoke with Jo Watts, CEO and founder of data analytics company Effini, along with the company’s COO and head of data, Sam Rhynas.
The Edinburgh-based company was recently recognised as Analytics Company of the Year at the British Data Awards.
“Data literacy is getting to the stage where it’s almost as important as basic literacy,” Watts said.
Demand for data literate professionals is growing. A 2019 report from the Royal Society revealed a massive rise in demand for data scientists – 231% since 2014. With that came a 22% rise in salaries.
However, for companies looking to take advantage of their data, the best first step is not always immediately hiring a data scientist. As data becomes crucial to a modern business, everyone needs data literacy as a skill.
Leadership needs to have a clear understanding of data to ensure they properly understand the benefits it can offer.
As data literacy becomes an essential skill in a digital world, Effini works to help all members of an organisation to understand their data. This helps close the skills gap between leadership and data scientists.
“For data scientists, it’s learning the business skills to talk effectively to the business,” Watts said. “Whereas for the businesses, it’s learning enough data skills to be able to do things they need themselves.”
It is only with a firm understanding of data that leadership can start taking their first steps. This enables them to gain insights from their data and identify first projects.
“It’s not just teaching people to interpret information, it’s teaching them to ask questions,” Watts explained. “We encourage organisations to think about the right types of questions to ask of their data.
“That’s one of the skills gaps that we’re trying to address – getting people to think about what they expect to see. Then, are they seeing what they expect to see, or does it look different.”
In our digital world, creating data is not difficult. Most organisations already produce vast amounts of it, siloed and waiting for use on their systems. But accessing that data is the challenge. If its sitting in a spreadsheet, it provides no value. Ultimately, a human touch is needed.
“You’ve got to start looking at your data,” Watts said. “Some of the key challenges are actually getting it out of the system that it’s sitting in and starting to use it. But you need ask the right questions, and you need to be identifying problems.
As such, it is essential for organisations to ensure they have high-quality, up-to-date, and properly stored data. An essential data literacy skill is good data management.
“Without it, you’ll never have good quality data and you’ll never do as well as you possibly could if you just took a few relatively straightforward steps to help you get started,” Rhynas stated.
“Sometimes we’ll do an initial data audit to establish a baseline as to where an organisation is. Then we’ll build on that and start creating data strategies and roadmaps to help them move forward.”
The benefits of data can often be overstated, and with good reason. Tech giants are using data in highly visible projects that are changing the nature of our society and economy – and often the temptation can be to ‘go big or go home’.
“The challenge is that sometimes organisations then try and go too fast,” Watts said. “We encourage people to take small steps and then build up skills and learn as they go with smaller and smaller questions.”
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However, there are still many ways small organisations can use small data projects to make their operations more efficient – through automation or identifying bottlenecks in processes, for example.
“I think the biggest benefit is the control and oversight data offer,” Watts said. “If people don’t know what they’re doing, something is wrong.”
With greater data literacy, leadership will be better equipped to understand where to take their data projects. They can identify roadblocks and the solutions need to remove them.
“They can think about upskilling their own employees – it’s not all about employing data scientists, that’s not what makes a company data driven,” Rhynas explained. “It’s about understanding how data affects the whole business.”
Tentative First Steps
As a field, data science offers many benefits to companies. While the sheer scale of these projects may seem daunting to smaller companies, there are some basic initial steps all organisations can take to prepare themselves to begin their own data projects.
Watts advised that companies start by looking at their data. “The answer is not to hire a data scientist, it’s to analyse the data yourself.
“And then you need a question to ask the data. Make sure you’re trying to solve a real problem that will show benefit.”
Once the organisation has drawn some real insight from looking at its data, then it can take the next steps. “Start to look at upskilling yourself in different tools or different languages,” Watts added. “It’s not about starting with the upskilling – it’s starting with the data and the business problem.”
To this, Rhynas added the importance of a slow and steady pace. “Learn little chunks at a time – don’t feel that you have to take a massive leap forward,” she said.
“Then, think about where your next step forward will be and move on to the right tools. But you need to look at your data. That’s the part where you will discover things you had no idea of before.”
By taking these steps, every member of an organisation can understand the role that data plays. Data literacy provides the insight needed to take the next, transformative steps.