Improving Data Fluency

It’s been 15 years since mathematician Clive Humby coined the phrase “data is the new oil” and since then the value of data has only become clearer to businesses. But while the power of data to transform how a company operates is well-documented, less understood is the importance of data fluency.

As the golden age of data continues, and the amount of data amassed by enterprises grows, not ensuring that employees in all parts of a business are fully versed in data best practices and know how to extract actionable insights will have considerable negative impacts on the bottom-line.

According to a study by data consultancy M&C Saatchi Fluency, the combination of low ratios of skilled data roles and a deficit in employee confidence when working with data is costing leading UK brands an average of £4.1bn in lost revenues every year.

There is no single reason for the low level of data literacy, with a lack of basic education in this area during schooling and university playing a part. The rapid development of new and innovative technologies is constantly increasing the data skills required by staff. In the past, companies highly valued skills in programming languages, data extraction and big data analysis.

Today, many of these technologies are in-built in data platforms and a radically different skill set is required. With the rise of AI and automation technologies, understanding contemporary issues around data governance, security and privacy are paramount, as is knowing how to interpret data.

Soft skills

At its core, data fluency means knowing how to use and interpret data, as well as being able to communicate the meaning and relevance of data you encounter. While this may appear to be a relatively simple to achieve skill, in reality, businesses face many barriers when attempting to enable their workforce to get on top of data. It is not enough to just offer optional training on data fluency, with a data culture program necessary to reap the most benefits.

Data fluency goes beyond technical talents and includes problem-solving skills around data. For example, a marketing manager at an online retailer may have access to cutting-edge technologies that can, if utilised correctly, unlock powerful customer insights. But if they don’t know what questions to input into the software, they stand to lose its benefits.

Moreover, a lack of data fluency could make it difficult for this manager to quickly translate the data results to others in the business and lead to a lack of understanding of what exactly decision-makers need to do.

Online data science learning platform DataCamp conducted a survey that found the vast majority of businesses view data fluency as an urgent priority, due to its ability to create positive business outcomes. The most striking result from the report was the fact that 89% of companies say building data fluency is a priority for their business. Among enterprises that say they have immature data fluency competencies, a shocking 68% admit they have inefficiencies in the workflows due to this.

Working with a client in the insurance industry, DataCamp provided their learn-by-doing methodology to help staff understand data concepts more deeply. Through gaining skills like data manipulation and visualisation with Python, as well as learning with real-world datasets, all employees can be part of a company culture that focuses on continuous data learning.

Starting with a data literacy assessment is a strong step towards understanding data weaknesses within a business. Once the results are in, a personalised training scheme can be put in place to fill in education gaps. There are countless online data fluency education platforms that offer a range of data science programs for all types of businesses and all levels of experience. But training is not a one-off process with ongoing data training plans needing to be discussed and implemented.

Practical data experience

To effectively democratise data in an organization, comprehensive training should be paired with practical business simulations that give employees first-hand experience of how to interact with data in their unique business context.

It’s now common knowledge that up to 70% of digital transformation initiatives fail to meet their goals. Many different issues can derail transformation programs with low data literacy also playing a role in holding organisations back in their digital transformation journey. Data scientists are of course vital in establishing the backbone of digital transformation initiatives, yet solely relying on data experts is unsustainable as transformation programs require the buy-in of the entire workforce to succeed.

The past few years have seen major enterprises make big investments in data fluency for their employees. From Airbnb creating a ‘Data University’ in a bid to democratise data science to Amazon launching their own ‘Machine Learning University’ to give all developers the chance to access the same machine learning courses used to train engineers; investing in data fluency is viewed as essential by market leaders.

Integrating data literacy and fluency learning programs into the rollout of digital transformation programs can be an effective way of getting workers to gain an understanding of new technologies in a new business context.

Data is only going to become a more integral part of business operations as we continue the shift to a fully data-centric world. The skills gap can be found in virtually all enterprises with upskilling hard and soft data skills going a long way to address this longstanding challenge. No business can deny the power of data fluency to improve how employees utilise data and transform it into actionable insights.