Sync NI sat down with Liberty IT’s Steven O’Kennedy, Director of Architecture Data and Cormac Bradley, Senior Data Solutions Architect to find out about the importance of data literacy and the impact it can have on businesses.
Together, Steven and Cormac have over 40 years’ of experience in the tech industry. They will be taking to the stage at the Big Data Belfast Conference to discuss the impact and importance of data literacy for the modern enterprise.
Steven is part of Liberty IT’s architecture group, working primarily in the big data space for the industry leader in digital innovation’s parent company, Liberty Mutual’s, commercial insurance business. He helps to create an efficient set of data capabilities that allow the business to make decisions quickly.
Over the last decade,Cormac’s primary focus area has been across the data space. He currently supports a number of teams working on Liberty Mutual’s Data Science Platform. These teams are focussed on delivering key data science capabilities empowering consistent adoption of MLOps across a diverse range of domains in a secure manner.
Sync NI sat down with Steven and Cormac to find more about the importance of data literacy and the impact it can have for businesses.
Is there evidence to suggest organisations have a problem to data literacy?
A number of industry surveys conducted over the last five years have consistently shown both the existence and persistence of a Data Literacy skills gap.
There has been a sustained consensus among C-suite level respondents on the importance of data literacy for business, 89% of whom expect team members to act based on data informed decisions. There is, conversely, a lack of confidence across all workers in their fundamental data skills - only 11% of staff have confidence in their ability to work with data - hence the Data Literacy skills gap.
It is also worth noting that this gap even exists among decision makers - junior managers and above - only 24% of this cohort have confidence in their ability to read and understand data.
Current data training tends to be focussed on tools and largely targets data specific roles - data scientists, data analysts and directors etc. This results in a skills and enablement disparity which can give rise to bottlenecks in decision making or pursuit of instinctive decisions.
What impact can data literacy have on a business and its employees?
A Gartner report has predicted that only one-third of companies will have achieved data literacy among their employees by 2023, resulting in a competitive disadvantage for companies lacking these skills.
This competitive disadvantage manifests across revenue, profit, customer satisfaction and loyalty and employee productivity.
Companies with a thriving data culture and data literacy programme all improved by between 17% - 20% across each of these areas. Staff retention has also improved for businesses where data literacy skills have been rolled out.
Data literacy has a tangible, realisable impact on a business.
Moreover, the benefits of Data Literacy extend beyond the business to all employees as well - it is estimated that staff members with proven data literacy skills can command a salary increase of up to 20%.
What are the key barriers to improving data literacy?
There are a number of socio-technical barriers impeding data literacy improvements.
Data literacy is an enabling step towards organisational cultural change - shifting a business from traditional means of working towards being a data informed and driven business. Cultural change is hard, taking both time and focussed programmes to overcome innate organisational resistance to change.
Executive sponsorship of a programme is key with regards to driving data literacy initiatives, ideally these would be a key pillar within the data strategy.
Other challenges include awareness and understanding of what data literacy is. For example, it isn’t simply working with data, numbers and statistics - it spans a broad set of soft and technical skills. Moreover, these skills are role and level specific - there is no one size fits all.
Clearly articulating the breadth, depth and variety of skills encompassed by data literacy, the range of learning pathways - and the purpose and value of these learning journeys - is another critical facet in removing barriers.
Lastly, truly empowering teams and employees to embrace data literacy requires supporting technical capabilities to be in place e.g. tooling enabling easy access to data, while ensuring regulatory compliance, is critical, as is tooling supporting working with data - from analysis through to visualisations and reports.
How can organisations best bridge the data literacy deficit and instil a data culture?
Highlight the value of data - and the role played by data literacy in unlocking this value, for all teams - is a critical step. As per above, this can start with a clear articulation of Data Literacy and how it relates to specific roles and level within an organisation - this helps highlight the relevance of Data Literacy for all.
Education, training and support are the key building blocks of a data culture based on data literacy.
Education and training should be viewed and enabled as perpetual learning - with appropriate learning paths and feedback supporting this by mapping out routes forward for employees.
Variety in education and training materials is important - self-serve learning materials should be supplemented by workshops and presentations.
Many organisations have found using “champions”, data literate experts, is a successful means of promoting Data Literacy.
Lastly, provision of tooling to make data access and working with data is a central underpinning for a successful data literacy programme.
What methodologies and tools should data scientists embrace in the age of AI?
It’s an unfortunate cliche, but as often, it depends! This is often going to be very specific to both a data scientists workplace and also their particular domino or expertise.
The boring answers still hold true here - as much as possible sticking to tried and trusted tools will mean a broader breadth of community knowledge and support can be drawn upon. A clear grounding in the fundamental methodologies of data science and machine learning continue to form the foundations of successful data science in the age of AI.
What role do cloud technologies have in realising greater value from ‘Big Data’
The key capabilities of cloud technologies, when used appropriately, continue to play a key enabling role in realising great value for Big Data. These capabilities include scalability, cost-effectiveness, agility, security and integration.
This article appears in the Big Data edition of Sync NI magazine. To receive a free copy click here.
