The Imperative of Data Literacy in a Digital Age

There is no underestimating the importance of data. Data provides organisations with insights that can drive strategic decisions, enhance operational efficiency, and encourage innovation. Organisations know their data is important, and often put large amounts of money into technical tools, into dashboards, and the training of “analytical” staff in technical, IT skills. However, the true potential of the data they hold can only be unlocked if their workforce is data literate. And yet it is one of the main skills that organisations, often willingly, overlook.

Data literacy goes beyond the technical proficiency of an organisation; using the tools, writing the code, building the warehouses, using the AI, etc. Instead, it is based on a deep understanding of data, its origins, its limitations, and its implications. Being data literate means that you can read and interpret your data correctly. It means that you can communicate with data effectively, using the best techniques to get your message across to the people who need to hear it. While the technical aspects of data analytics and data science are obviously important, focusing solely on the technical aspects of data without supporting the development of data literacy among all employees can lead to significant challenges and risks.

Data literacy isn't just about extracting insights from data. Being data literate means that you understand the nuances and complexities that underpin your datasets. It means you are able to critically appraise the source, context, and reliability of the data, ensuring that any information derived is complete, accurate, relevant, and timely. Without an informed appreciation for the importance of data quality, organisations risk basing their decisions on incorrect or incomplete information, undermining the reliability of their insights. Data provenance, or the understanding of the origin and history of the data, is equally important. Ignoring, or misunderstanding, the provenance of your data can result in the adoption of misleading information or an unintended dissemination of unseen biases within the data.

Data literacy means that you understand the end-to-end process of data—from its inception to its analysis, interpretation, and dissemination. It requires an in-depth understanding of how your data is collected, processed, and transformed. Organisations that do not understand this, often reorganise data processes in a siloed fashion, where staff operate within isolated departments, each responsible for only a small part of the data journey. This usually results in a fragmented approach, where individuals focus solely on their specific tasks without comprehending the broader implications for the organisation. Many large organisations have followed this approach, and most have run into problems. The lack of coherence leads to misalignment between departments, conflicting interpretations, an impact on timeliness, and an overall degradation of data quality. This siloed approach opens the door to misunderstandings, misinterpretations, and, in the worst cases, misuses of data. Such misuses of data can be, and have been, critical to organisational survival.

Data literacy is critical for an organisation to thrive. Misinterpretation of data can lead to misguided strategic decisions, eroding trust in data-driven approaches. Inaccurate insights may impact customer relationships, hinder innovation, and compromise an organisation's competitive edge. Many organisations have had such bad experiences with data that they now do not use the data they collect, preferring to use anecdotes and sales tactics to win business and increase their reputation. Others stick their heads in the sand, or invest in more technology, assuming that their data insights will get better. Unfortunately, all of these approaches are not sustainable in the long term.

Data literacy and data governance go hand in hand. Without an understanding of data governance principles and their importance, organisations may, inadvertently, breach data privacy regulations, resulting in both legal consequences and reputational damage. Establishing clear guidelines for data management, ensuring compliance with regulations such as GDPR, and fostering a culture of responsible data use are essential components of effective data governance. Without a commitment to robust data governance practices, organisations expose themselves to risks such as data breaches, regulatory non-compliance, and compromised data integrity. Yet a workforce that is lacking in data literacy will not understand the importance of data governance and in some cases regulations may be breached purposefully, assuming that the usefulness of the data is more important than any data governance responsibilities.

Data literacy empowers employees at all levels to ask the right questions, to understand their responsibilities, to handle data correctly, to interpret data accurately, and to communicate insights effectively. An organisation that is data literate will use data in an appropriate way to measure change, to evaluate interventions, to benchmark performance, etc. It will use dashboards in a meaningful way, with the data being understood and seen as important and insightful.

Data literacy is the necessary link between technical expertise and safe, practical application. Data literacy serves as the practical implementation of data ethics. An appreciation of data, and how it can be used (or misused) means that organisations can move away from doing what is legal, to what is ethical. Again, some large organisations have decided in the past to ignore data ethics, assuming, incorrectly, that their reputation wouldn't be harmed if what they did with data was legal. A data-literate workforce will understand the ethical considerations that need to guide the processing and dissemination of data. It will ensure that the data is handled in a way that respects individual rights, promotes fairness, and upholds ethical standards. This is crucial to an organisation's reputation.

Data literacy is a collective responsibility. It necessitates comprehensive training programs that extend beyond the technical and IT departments to encompass all areas of the organisation. These programs need, at the least, to focus on critical thinking skills, data governance, fundamental data analysis skills, and how to communicate effectively with data. It is only in this way that organisations can ensure that every employee, regardless of their role, is empowered to use data appropriately and make sensible, informed decisions. This approach will not only enhance the overall agility and adaptability of an organisation but also enable an environment where data is not just something discussed and used by the “techies”, but a shared language spoken and understood by all.