Data is the most critical of resources that an enterprise can possess; second only to its people. And while it's great that data also happens to be the most abundant resource in today's time, especially the growing enterprises, very few businesses are able to use it to achieve tangible results.
That’s because most people -- including many business leaders -- lack data literacy, the ability to make sense of data and turn it into actionable information. As a result, enterprises are unable to translate data into action and ultimately, into results.
The companies that do understand data and drive their decisions based on data analytics tend to outperform businesses that don’t. For example, a Mckinsey & Company study suggested that analytics-driven businesses were able to acquire 23 times more customers than those that didn’t use data. To be able to use data to achieve such results, data literacy is an absolute necessity.
An increasing number of growing enterprises are leveraging technologies like analytics, AI, and IoT. Since these technologies thrive on data, a data-literate workforce will be able to extract the most value out of them. However, most businesses find it hard to build a data-literate workforce. That’s because making sense of data, which is often generated in the form of statistical tables and graphs, can be challenging for multiple reasons.
Why it can be difficult to make sense of data
As mentioned above, data is the resource that is abundantly available to enterprises. And more of it is created every passing second. The sheer volume of data generated by enterprises from various sources can prove to be overwhelming for non-analysts. That’s because they are not trained to know what to specifically look for in the ever-growing body of data.
They may not know the right questions to ask and where to look for answers, and as a result, they attempt to go through all the data that is available to them. Result? These workers lose a lot of time getting nowhere, and even worse, end up making decisions that are not based on sound facts.
Another challenge to understanding statistics is the inability of people to interpret different pieces of information coherently. This is why, while enterprises can understand statistics in silos, they’re unable to identify how the given information is relevant to their company, their function, and the problems they are trying to solve.
Furthermore, despite having piles of reports filled with detailed statistics, people may not know how the data is collected, analyzed, and how certain values are calculated.
For instance, many people do not know the difference between mean, median, and mode, which are different ways to generalize data and determine averages. Each of these is determined differently and used in different applications, but often ends up being misunderstood during data analysis. Similarly, people can also misinterpret percentages and probabilities due to a lack of data literacy and therefore arrive at erratic decisions.
To ensure that employees always make the right decisions, it is essential for business leaders to foster digital literacy in the enterprise.
How enterprises can foster data literacy
Building a data literate culture entails taking a multi-faceted approach that goes beyond just educating employees. Enterprises should also update their policies and technology to augment their move toward data literacy, as follows:
Promoting data-driven practices
Businesses should cultivate data literacy as an inherent part of their organizational culture so that not just analysts but the entire workforce can use data to make decisions, big or small.
To do so, businesses should encourage employees to adopt a data-driven approach towards solving problems and also demonstrate its application in different functions. Special training in data literacy can go a long way in making the organization fully data-literate.
Making data available and accessible
The most important step towards achieving total data literacy in any enterprise is by making data available to all the employees of the organization. Also, it is vital that workers are only given the information that is relevant to them and their functions to prevent information overload.
In fact, businesses should go one step further and provide data to their employees in a format that is easily consumable. Doing so would encourage employees to readily adopt data-focused practices to make even the smallest of decisions, which can have a compounding effect on the overall business performance.
Delivering data in natural language
When it comes to choosing a format that employees can easily understand, nothing comes close to the natural, conversational language that we use every day. Realizing this, leading businesses are using natural language generation (NLG) - advanced AI-technology to deliver data to their workforce. They are using NLG-based tools that make the information in their dashboards and reports more easy to grasp and act upon.
Using natural language generation tools can help enterprises convert large volumes of data into easily consumable reports. As a result, everyone can know exactly what they need to know and do without being overwhelmed by data volume or complexity.
Achieving data literacy will soon go from being an option to becoming a necessity. Growing enterprises, thus, must accelerate their efforts to make all their employees data-literate. Doing so will ensure that two of their most critical resources -- their people and data -- can be used to their full potential.
Nisarg Bavishi is a founding member of vPhrase. He has significant experience and expertise in the area of Business Intelligence relevant across functions and industries due to his numerous collaborations with industry leaders. Nisarg is now on a mission to design, build, and deliver BI solutions to help organizations enforce data-driven decision making with ease. Through his writing, Nisarg aims to provide an insider's account and understanding of BI, Data Analytics, and AI Technologies.