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The Importance of Data Literacy in the Modern Workplace
May 14, 2020
Adriaan Hubinger, Engagement Manager: Data, Information and Analytics, Decision Inc.
Data and analytics fuel digital business and play a vital role in the future survival of organisations worldwide. This, however, means very little if employees are unable to assess the value of the data they have on hand, interpret it properly, and use it to drive better business outcomes, a core skill for digital business.
But what is data literacy and why does it play such an integral role? In the context of a business, it is the ability of employees to derive meaningful insights from data and apply those insights in a way that benefits the organisation. It allows employees and decision-makers to communicate in one common data language.
As data becomes an increasingly valuable organisational asset, it forms a fundamental difference between successfully deriving value from data and analytics, and losing out to competitors who have made it a core competency in their organisations.
Poor data literacy is ranked as the second-biggest internal roadblock to the success of the office of the chief data officer, according to the Gartner Annual Chief Data Officer Survey.
In other recent studies it was found that only 24% of business decision makers are considered to be data literate. And when one considers that only 32% of C-suite leaders and 21% of the future workforce (aged 16 to 21 years) are data literate, business and the global economy is faced with a significant struggle, whilst business has been provided with a golden opportunity to get a head start and start upskilling their staff on data literacy. There has never been a more opportune season to imbed data literacy as a core competency within your organisation.
Data Literacy is the Ability to Read, Analyse, Argue, and Work with Data
When it comes to reading data, the focus must turn to whether people understand the basic data table they are looking at, the graph they received in their email this morning, or simply the key performance indicators (KPIs) that are measured within the organisation. This requires working with data workers to establish whether people can transform the data they are working with, present it in meaningful ways to colleagues, understand how to transform it, and why it is presented in different ways.
For its part, analysing data deals with whether there is an understanding of what the data is trying to tell the person or what trend it is revealing. It is all about how to uncover insights hiding within data and how it can help each employee to take better action to grow the business. Finally, arguing with data is centred on how to use concrete data and information to demonstrate a point, motivate an action, and influence positive change.
Concerns around the low level of data literacy extends to how ineffectively new technology adoption has been embraced over the last decade. Legacy systems and processes have become so embedded and the cultural challenge to accept change, so entrenched that even business intelligence tools have only enjoyed a 30% effective adoption rate over the last few years. This is largely driven by lack of understanding the importance of the correct data. Not to say that all employees need to be data scientists to get value from data, but they all need to be data-literate.
“The prevalence of data and analytics capabilities, including artificial intelligence, requires creators and consumers to ‘speak data’ as a common language,” says Valerie Logan, Senior Director Analyst, Gartner. “Data and analytics leaders must champion workforce data literacy as an enabler of digital business and treat information as a second language.”
There are numerous inexpensive tools and resources available to drive enterprise data literacy, assisting in the development of the data-literate core competency within an organisation.
Enabling the Workforce
Companies should not stare themselves blind to the challenges that exist. Instead, they must examine how many within their existing leadership can explain the output from the systems they use and identify the employees who can interpret the data from sales systems, operational indicators, and monthly KPIs.
Building from this, the organisation must assess how many of its managers can build effective business cases using accurate data as opposed to basing their decisions on speculation or intuition. Fundamentally, the company should consider how its data scientists can explain the output from the machine learning algorithms or statistical processes they use every day.
Once there is an understanding of what the foundation of data literacy looks like within an organisation, decision-makers can focus on the programmes that must be implemented or the actions needed to be taken to make it easier for people to effectively learn during the transition to a modern workplace. This will help drive innovation and provides a critical competitive advantage.
Working cohesively, an organisation can not only improve its data literacy but also the productivity of employees while providing better learning opportunities for its staff. It is therefore critical to begin this journey sooner rather than later.
Working with our clients, we start by helping them assess their workforce and data literacy proficiency to establish a baseline from where we can design a customisable six-phase program to upskill, deliver learnings and equip the broader workforce to become more data literate for the future.
“Data in the hands of a few data experts can be powerful but data at the fingertips of many is truly transformational.” This reflects the true potential of democratised data in business. If organisations can empower everyone to gather, interpret and use data to their advantage, the benefits promise to be huge.