The metaphorical data explosion of the current age has changed how organizations function. Today, with the right amounts of effort and investment in technology and expertise, business heads can take operational and other major decisions with greater success as they’re based on cold statistics and empirical evidence instead of—as was the case in the days of yore—inadequately supported gut feelings and instinct. The application of business intelligence is also much more widespread now, with organizations in several sectors using machine learning, computer vision, NLP, IoT and other data-oriented technologies to collect, process and analyze the data collected before putting it to use in a variety of ways. An often-overlooked aspect of business intelligence is the need to incorporate a long-term data-driven culture at the workplace in a way that complex analytical terms and working mechanisms become second nature for all stakeholders in any organization. Only organizations with high data fluency can foster such a culture for the long term.
Employees at every operational level in your organization must possess data fluency to be considered valuable resources.
As a concept, data fluency involves much more than the capabilities of data scientists and other data experts in your organization. Data fluency is collectively enhanced in organizations when every employee possesses the ability and, more importantly, the confidence to understand, interpret and use data proficiently. Every stakeholder in a highly fluent organization acts as a data translator for workers in other roles. For example, a line manager can simplify and convey the business intelligence-derived insights pertaining to their role to another manager—who may not organically understand them without adequate simplification—if they are collaborating for specific projects or if there is any present or future requirement in either line of work.
Without data fluency, businesses cannot accurately interpret data results or use them for meaningful business applications. Without adequate data translation, end-users do not have the basis to effectively use business intelligence-derived data results. Most importantly, without data fluency, a data-driven culture cannot be established or reinforced in an organization.
Areas that Need Data Fluency the Most
Data fluency requires upskilling of all employees in your organization to widen their data and analytical knowledge. However, upskilling them all at one go is impossible as the cost and, more importantly, time needed to do so will be incredibly high and overwhelming for businesses. So, organizations can prioritize certain areas that arguably need data fluency the most. Some such areas are:
In 2021, data scientists who can help with HR analytics are still hard to find, even for highly data-driven organizations. Personnel shortage and skills gap in this area make the upskilling of HR managers a priority for data-driven organizations. With HR analytics becoming increasingly prominent in all organizations, HR managers and associates need to have a greater level of data fluency and analytical skills. Details such as applicant test scores, retention and turnover rates and productivity-related statistics keep changing in real-time. So, data fluency becomes critical for talent, hiring and workforce management.
To become data fluent, there are a few things that HR personnel in an organization will need to do—firstly, they need to understand the true value of data and HR analytics. This lets HR workers know why the exercise is being conducted in the first place. Secondly, they need to closely monitor the provenance of human resource-related data they receive. This will enable them to know its validity and what data to use for analysis. Then, they need to analyze the collected HR data, draw insights and use them to take major decisions.
