GWI Australia

Data Literacy – what difference does it make?

Written by :

Tags :

As consultants, we have the privilege of working across a diverse range of industries and sectors with clients at all levels of maturity in the way they collect, manage, use and leverage data.  This includes those struggling to implement the basic foundations of data management as well as those developing new business ventures based on intelligent and actionable insights.

Data is the lifeblood of business

In this age, data is critical.  It is the lifeblood of business and an element common across every industry.  But, the capability of individuals to read, work with, analyse and argue or communicate with data varies dramatically within organisations – even within those with high levels of data maturity.

Gartner defines data literacy as the ability to read, write and communicate data in context. This includes understanding data sources and constructs, analytical methods and the techniques applied, and the ability to describe the use-case application and resulting value.

So, what difference does data literacy make?

Let’s look at a few examples.

In healthcare, an ability to analyse, interpret and use patient data can mean the difference between life and death, or recovery versus prolonged illness.   Clinical reasoning and decision support are influenced by a diverse range of objective and subjective data including, but not limited to, biographic, patient surveys, and laboratory tests, vitals, pathology, pharmaceutical. Clinical intelligence cannot be gained without considered data analysis and interpretation of the wealth of data available to clinicians.

In environmental science, data informs increasingly complex global issues such as climate change.  Yet the lack of a commonly shared data language may be contributing to the diverse interpretations of climate data and climate science concepts including causes, effects and solutions.

In the resources industry, how the workforce interprets data and associated terminology informs where to drill, how deep to drill, what to extract, what to import/export etc.  If it is mis-interpreted, economic prosperity, sustainability and liveability, safety and the environment may be at risk.

In the world of corporate and commercial governance, all board members and executives must, at a minimum, understand the data reflected in the financial reports and charts required to guide the strategic direction of their organisations.  This is just as important as the ability to prepare a well-constructed business case for future investment based on concrete, accurate and relevant figures.  

Data literacy underpins all of this.

Poor data literacy can often hinder success

Across every industry, being able to recognise discrepancies in data, interpret visualisations and communicate confidently with data is paramount and the cost of not understanding the context of data is enormous. Despite this, building a culture of data literacy remains a challenge for most 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.  Gartner also predicts that by 2020, 50% of organisations will lack sufficient data literacy skills to achieve business value.

So, how do we improve data literacy?

Not everyone needs to be a data scientist. Data literacy is not about being the expert.  It is about building and sharing a common language amongst your workforce, remembering that each workforce has unique requirements. This common language enables consistency in interpretation, storytelling and communicating with data and enables your team to identify and ask the right questions.

It is important that all leaders take responsibility for data and the competency of their teams in using and understanding it. Data is not just the responsibility of the analytics team!  Different roles require different skills and levels of data literacy.  For example, the literacy requirement for a data scientist will be much higher than that of a data creator.

To truly leverage your data assets and become a data-driven organisation, a basic level of data literacy is required across the entire organisation. Understanding the level of literacy different roles require will enable you to baseline organisational data literacy and measure the improvement over time. It will also help you to recruit the right talent.

There are many ways to improve data literacy including internal partnering, online training, on the job training, developing skills in using the tools available, ensuring company decisions are informed by data. Investing time and resources into developing your workforce’s data literacy will enable you to reap the rewards.

Data Literacy enables digital agility, but first must come a mindset of being able to succeed with data.

Related blogs

Stuck on where to start with AI?