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Organizations with high data-literate people outperform others. They gain the ability to understand the market’s momentum, learn customer demands, and make better decisions.
Data has become part and parcel of every industry today. Companies regularly track each operation to increase efficiency and provide better services to customers. Airlines measure why flights don’t arrive on time. Supply chain firms follow the reasons why finished products don’t reach end-users, retailers check each customer’s purchase history, etc. Moreover, each organization finds ways to get more customers, increase open email rates, attract customer attention, and recruit top-notch talent.
Today, we live in an information age where data has become an essential commodity. And the best part is that you don’t need expensive data-crunching machines to realize the power of data. You can implement affordable cloud-based solutions to collect reliable data from multiple sources and draw valuable insights from it.
The role of data in today’s organizations is unquestionable, but the biggest challenge is that not most of us are digitally literate. The National Centre for Education Statistics (NCES) evaluated adults’ problem solving and data interpretation skills across 23 countries and the results were shocking. The United States, where the world’s biggest data companies are based, ranked 21st out of 23 countries.
Who is responsible for improving data literacy skills?
A cursory look at the Maths syllabus at the school or college level is enough to prove that their focus is more on core concepts such as Calculus and Algebra. Instead, data literacy requires skills in more pragmatic mathematical areas like probability and statistics.
Today, the responsibility of making a data literate society has fallen on the shoulders of organizations. Companies like Adobe and Bloomberg have digital academies that train employees to increase their efficiency by learning to analyze data.
A more comprehensive view of data skills is emerging.
About a decade ago, organizations wanted competent people for data extraction, SQL, information normalization, and other technologies like big data analysis, parallel processing, and programming languages like R.
According to a report by IBM, most of these technologies are already embedded in data. So, companies are looking for people with a completely different set of skills today. The most in-demand people are those who understand the underlying nature of data systems and how they perform in different situations. They should also have a deep understanding of how to ensure better governance, create trust, improve privacy, and increase security using data models. Another critical element that determines an employee’s data competency is that they should be able to challenge the outputs of algorithms and not take everything for granted.
A recent survey of data organizations revealed that they have the most technically abled employees who lack data-driven decision-making and problem-solving skills.
Here is a list of six skills that companies want in their employees:
a. They must have the ability to ask the right questions.
b. They must possess excellent data interpretation skills to reveal hidden insights that play a significant role in their day-to-day operations.
c. They should understand which data is relevant and must possess the required skills to test the data’s validity.
d. They should be able to create compelling visual representations that make it easy for leaders to make decisions.
e. They should be able to perform A/B testing.
A leading retailer conducted a study to understand the correlation between sales volume and employee turnover across their stores, and the results were mind-boggling. The study showed that the stores with more solutions-oriented sales teams and specialized job roles had happier employees and saw a significant decline in turnover. It was later revealed that the analysis applies only to the summer season when the retail workforce consists more of freelancers than full-time employees and the average turnover triples. Since the study hadn’t considered this context during the initial observation, the team invalidated the results.
This example shows that although technically skilled professionals are available in plenty, the expertise required to understand the business context is missing.
How can companies boost data literacy?
Data has become the backbone of companies across industries. No business can think of even surviving the market’s trials and tribulations, let alone compete with other players without getting a good grasp on data. Companies are bound to fail without developing the ability to collect relevant data and extract valuable insights. Here are a few things that organizations should focus on to boost the data capabilities of their employees.
a. Do you know that one out of every five adults still relies on Excel for data crunching and analysis? Multiple software suites provide far advanced data analysis and reporting functions, but Excel ranks top on the list for people who cannot utilize full business intelligence. Excel gives them a sense of data control and allows them to compare data available across multiple sources. Thus, you must motivate employees to learn the 100 most essential features of Excel to gain a fair understanding of data and understand its advantages in today’s day and age.
b. Build a capability academy that upgrades the data-related skills of your employees. Keep in mind that it shouldn’t be a general-purpose training institute that prepares programs for everyone and ultimately fails to deliver the desired output. Instead, focus on developing specific job-related skills that are oriented for achieving a particular result. Discuss with each department and pin-point essential data skills that employees need to increase their efficiency. Then develop a curriculum that includes videos, podcasts, articles, and live sessions that help employees to hone their skills.
c. Drive awareness campaigns that motivate employees to take the first step towards becoming data-literate. Share inspiring stories, call field experts, and hold group discussion sessions often. Whenever the senior management makes a vital decision, share the result with everyone to get a first-hand view of how data impacts program implementation. There are many examples of how data affects a companies’ decision-making. Netflix uses customer data to recommend movies and shows. Moreover, the company also decides what to create next by learning about customer preferences. Similarly, Starbucks collects and analyzes customer data to provide beverage suggestions to them.
d. Remember to share the individual and collective benefits of becoming a data-literate person with your employees. Tell them that their decision-making skills will significantly improve and that they will be able to forecast customer demands and changing market trends conveniently. Share real-life success stories about people who have found out-of-the-box solutions to challenges using data skills. Restrain using mathematical jargon such as lookups, statistics, and error checking. Such things can be off-putting and subdue their interest.
e. Assign data responsibilities to all business stakeholders, including frontline executives, managers, shop-floor workers, and supply chain vendors. Encourage them to ask the following questions:
i. Is the analysis done correctly?
ii. Are the sources reliable?
iii. Is the decision taken keeping in light the company’s interest?
iv. What is the significance of the decision?
v. What will be the impact of the decision?
Data literacy has become an essential skill in today’s market. Companies that have data-literate employees outperform those that don’t. Such people can collect necessary customer details, draw relevant insights, ask the right questions, and make better decisions at high speed. The best part is that anyone can develop data skills conveniently. They are easy to learn and help drive relevant changes in companies.
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Disclaimer: All the information, views, and opinions expressed in this blog are those of the authors and their respective web sources and in no way reflect the principles, views, or objectives of Sage Software Solutions (P) Ltd.
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