DATA LITERACY, WHY IT COULD MAKE OR BREAK YOUR ORGANISATION
MIT defines data literacy as the ability to read, work with, analyse and argue with data. It’s a skill. One that empowers all levels of workers to ask the right questions of data and machines, build knowledge, make decisions, and communicate meaningful information to others.
In the digital dark ages 20 years ago, companies had transactional systems with little or no reporting. Fifteen years ago, the business intelligence (BI) market began to evolve and we started using slice and dice reporting with near real-time data functionality. Ten years ago, there was a shift towards improved visualisation and simpler functionality, passing the tools directly into the hands of the business user (operational, sales, marketing and finance). Five years ago, there was an even greater shift in analytics and reporting with multiple data sources, more user-friendly dashboard designs, and the emergence of Predictive Analytics.
Data literacy is the ability to read, understand, create and communicate data as information.
Currently, the world is sitting in a digital and data revolution, one that just a few years ago wouldn’t have crossed our minds. As we go about our everyday work, phrases pertaining to this revolution are commonly referenced such as Big Data, Augmented Intelligence and so on; so many things are being described as data or data-driven that it is hard to find an organisation where it is not top of mind. The accelerator that has driven this revolution is the speed and size of data today.
As data volumes increase, companies ability to create amazing data analysis has also. With this surge in data and the desire to be data-driven organisations, there has been one unfortunate aspect that still lags: the proper skill-set to fully utilise this data. Back in 2012, the Harvard Business Review said: “The shortage of data scientists is becoming a serious constraint in some sectors.” Fast forward to today, where even more data is being produced, the shortage of skilled workers has created a skills-gap. We don’t all need to be Data Scientists, but we all need to be data literate, especially if we’re expected to keep up with the pace of digital change.
So where does Data Literacy fit in?
As systems generate, collect, and analyse more data and make recommendations about this information (sometimes automatically), it is increasingly critical that we add value to the process. We are striving to understand what data is telling us. We should use our newfound data literacy skills to add value as well as critique any proposed actions from our tools and systems.
As much as the battle lines have been drawn in the war between man and machine, the clear winner is man augmented by machine. Whilst we may have gut feelings and best guesses based on experience, we will be in a much better position to make decisions when this is augmented by the knowledge that comes from our digital tools and machines. It’s been proven that this symbiosis works far better than machines alone. If you want to learn more, watch the below video “The Future of Augmented Intelligence: If You Can’t Beat ‘em, Join ‘em” from the World Science Fair 2017.
Why is this important?
In order to maximise the value of our data analytics solutions, we must understand the abilities of end users. Can they manage and understand the data and tools at their disposal? Data Literacy is about understanding the strengths and weaknesses of the audience receiving data and how best to provide it to them.
This is achievable as many data tools are flexible and can be presented in a way that can be of value to each individual user. It is important to realise that a person’s ability to comprehend information comes from the way in which the data is presented. For some, this will mean simple visualisations to facilitate decision-making processes, while for others it requires deep and broad data sets for further analysis.
Data Literacy is the ability to understand who is receiving data, when they need it, what format is required, discern what they are supposed to do with the data, and grasp how this data will add value to the individual and the greater organisation. It is essential that the way in which the data is presented matches the skills and needs of the user. This optimises the value generated from data insights and unleashes the hidden potential of your workforce.
The most important aspects of Data Literacy are :
- The objective is to provide information for people to learn and understand in order to make more informed decisions; and
- Everyone learns differently. Understanding how users learn and where they are in their data understanding will be critical in meeting this objective
If you want to be provided with a free, no obligation product-agnostic approach of understanding your Users Data Literacy, please get in touch.
Getting this right can support greater adoption of your analytics solutions resulting in improved ROI and better outcomes for your organisation.