Data is the new oil’. You must have heard that statement many times.
However, tech literacy and data analytics must be improved across verticals and functions to harness and profit from data. At present, this isn’t the case.
A study of 1,000 workers in Singapore found that businesses are losing a massive S$5.1bn in productivity every year because the workforce is not data literate. On average, local companies are losing over seven working days (56.5 hours) per employee.
That’s the cost of low-tech literacy. It’s something that no company can afford, especially at a time of increased reliance on AI, ML, data and business analytics.
It’s not just business performance that can be affected. Employee morale and corporate culture can suffer, too.
The study shows that 84% of employees feel overwhelmed or unhappy when working with data.
40% of surveyed employees noted they prefer to find other ways to finish tasks that do not use data.
Seven in ten respondents reported that workplace stress is exacerbated by data-overload, culminating in 47% of the local workforce taking a minimum of one day of sick leave.
Given the importance of this issue, what steps can corporate decision-makers take to address it?
Bridging the Data Skills Gap
Business leaders need to assist employees in becoming more confident about using data insights. In this way, they can take advantage of the many ways that artificial intelligence and machine learning are becoming essential in making informed business decisions.
Whether it is competitor and business analytics, sales and marketing, customer service, advertising or much more, it’s big data that is going to makes the difference.
Here are some ways to ensure that your employees stay data-literate, happy, and successful.
You can take new approaches to training and skills development with your existing workforce, and boost this with previously untapped talent pools. This means setting aside budgets for development programs, as well as taking on new employees with the relevant abilities.
Think of reskilling and upskilling as a continuous process rather than a one-off exercise. One way is to check online learning platforms such as Coursera, Udacity, and Udemy. All of them offer courses in areas such as data science, ML and AI. This is an effective way to scale up organizational L&D.
Ongoing training programs of workshops and internal courses led by those within the organization who are trained in data analytics and insights are also effective. In such cases, plenty of examples from the company itself can be used to explain how AI and ML can power data insights.
Making the Power of Data Work for You
The study referred to earlier had some valuable recommendations for business leaders. These go a long way in taking advantage of the usefulness of data analytics and promoting data literacy among employees.
They are:
Understanding and defining: Recognize business objectives and understand how data analytics can be leveraged to drive transformation.
Democratizing: Do away with divisions within departments when it comes to data, and make it easily accessible each time someone needs to use it.
Communicating: Explain to your employees how data is a valuable resource, and how it can help not just with business decisions but in their careers as well.
Engaging: Actively use data wherever possible in everyday work, so that its importance is understood at all levels.
Balancing: Data is to be weighed against human insights and experience to get the best possible conclusions. Balancing the two is the best approach.
In a Nutshell
Data literacy is crucial. No matter which business you are in, artificial intelligence and machine learning are going to shift the playing field by using data to throw up new insights and ways of action. Making tech and data literacy a priority, then, is more essential than ever before.