Data has long been described as the new oil, but many businesses are struggling to make the most of their data because of a lack of data literacy
A minority of people are confident in their data literacy skills, despite its increased importance to business decisions.
In 2017, the average person made 300 data-driven interactions per day, whereas today there are up to 4,758 daily data interactions made by the average person.
But the number of people who are able to utilise this massive increase in data points collected every day is not matching the pace of change.
Only one in five people are confident in their data literacy skills, according to a data literacy survey of 11,000 respondents by business intelligence software provider Qlik.
Only 24% of business decision makers and 32% of C-level executives would describe themselves as data literate, while with 16 to 24-year-olds this figure drops to 21%.
What is data literacy?
Data literacy is the ability to read, work with, analyse and argue with data, according to Jordan Morrow, global head of data literacy at Qlik.
“The ability to read data is the most important – if you can’t do that you can’t work with it or analyse it,” he says.
“For individuals to be able to comprehend the data, they must be able to read it before they can use it to take action and make decisions.”
The democratisation of this skill is a key idea behind the data literacy project that Mr Morrow now runs.
He adds: “When we speak about the democratisation of data, the human element is the most important part.
“Those that are data literate were happier and more comfortable in their jobs.
“It establishes confidence, they know they can back up their decision making and aren’t just going off gut instinct.”
The importance of data literacy
However, many businesses still struggle with the concept.
Research by Gartner predicted that by 2020, 50% of organisation will lack sufficient AI and data literacy skills to achieve business value.
Mr Morrow says: “We live in a generation where information is so rapidly available, it’s hard to find the right insights.
“Most organisations are stuck in descriptive analytics.”
This means that businesses are simply using data to describe what is happening rather than using its full potential.
But this has been marred by what he describes as “data cynicism”.
“We have to make sure that we are taking data cynicism out of the equation because the world is doing a very good job of increasing data cynicism already,” Mr Morrow says.
“Google allowed you to opt out of being followed, but it turns out that Google was still doing it.
“The result is that people have become very cynical about data and information.
“My mission is to create data sceptics, who are curious and ask questions of the information.”
He believes that social media has contributed to a growing inability for people to interrogate the data put in front of them.
“The 16 to 24 generation are digitally and technologically literate but don’t always understand the numbers.,” he adds.
“The social media age allows people to get information sent instantly but information also leaves instantly meaning they aren’t thinking critically on what they have read.”
The importance of data literacy for UPS
American delivery service UPS is a prime example of how data has transformed industry.
The company has an unusual rule that dictates that drivers make no left-hand turns.
The reasoning behind this is that – although this may sometimes make drivers take a longer route – it will mean the vehicles will never have to drive into oncoming traffic, thus cutting the amount of time spent idle and reducing the chances of an accident.
In countries that drive on the right-hand side, UPS drivers typically take a left-hand turn 10% of the time.
As a result, the company claims it saved 144 million gallons of gasoline in 2014.
Mr Morrow says: “When we’re talking about the price of gasoline for a logistical copany like that, that’s quite literally millions of dollars in savings.
“This is how data can make big wins.”
Its predictive analytics tools have now been extended to determine routes and the vehicle parts that are most likely to break.