Over the last decade, data has become an important part of any organization. But over the last few years, it has become essential for the growth, productivity, and success of companies across the globe. We are gathering an immense amount of data, which provides insights into everything from consumer behavior to company finances when used in the right way. Business intelligence (BI) techniques and Predictive Analytics are undoubtedly helping organizations manage data; however, this still requires data literacy.
Data literacy is considered a Key Performance Indicator (KPI) for companies in today's market. Whereas not so long ago, it was limited to the ability to read and write, the skill set required by employees has now expanded.
For an employee to successfully and accurately solve problems, they must be able to read, write, and communicate data in the relevant context.
They also need to understand the sources of data, how it is constructed, and the methods used to analyze it. On top of this, it's essential to know how to explain use cases, applications, and resulting values.
It is more than likely that most companies have begun the process of creating a data-driven organization and are already taking advantage of better decision-making. They have also managed to incorporate the ethical and legal side of data protection and transparency. As much as 90% of data and analytics decision-makers are aware of making data insights in decision making a priority. Nevertheless, this is still a huge struggle for most.
Why Is Data Literacy a Struggle?
While everyone is aware of the importance of data, not everyone is aware of its role in their job. It can no longer be done to the data analysts to be responsible for data literacy. As data becomes more important, everybody within an organization will need to know how data impacts their work. It is also possible that data professionals don't have a clear enough understanding of their work in the business context.
As the volume of data continues to grow, it is becoming more and more difficult for those without the technical knowledge to keep up with those who are data-savvy. Censuswide reported data literacy findings after surveying over 7,000 business decision-makers worldwide:
76% of decision-makers aren't confident to work with data
32% of senior leaders are considered data literate
Only 21% of 16-24-year-olds are data literate
78% of employees would be willing to invest their time to improve data skills
How to Improve Data Literacy Within Your Organization
It's much wiser to begin creating and implementing data literacy strategies now as the amount of data your company acquires is only going to grow. While the main goal is to assist the data decision-makers, it is also necessary to improve the knowledge of those employees who aren't quite so tech-savvy. Here are six ways to start improving your data literacy:
Make data a business matter.
Employees companywide need to be aware of the importance of data. Being data illiterate is not just a technical problem; it is one that will, at some point, spread across the entire company. Making everyone see that it is a company issue rather than just down to the tech department will enhance employee engagement. This drive-in data literacy importance needs to come from the top, so it is the executives, managers, and leaders' responsibility. To develop data-driven mindsets, employees will need to understand why data is necessary and how it is used across all business processes.
Appreciate that it's not an overnight process
If you wake up one morning and say, "From today, we are all going to be data literate," you run the risk of putting non-technical employees off the transition. This is a process that requires starting small. You might feel that there is a rush, but when significant changes go about too fast, mistakes are made, and this reduces employee enthusiasm. It is better to start small, allow other employees to see the success so that they are more inclined to want to be a part of it. Aside from this, there is no room for error regarding confidential data, so only those with experience should be handlining it.
Put data into context.
For those who aren't familiar with data or the associated technologies, it can be an overwhelming experience, especially for massive amounts of data. It is important to contextualize the data for them based on their role, experience, and background so that they are better able to effectively use the data.
Gradually increase employee access to data.
Data literacy is a skill that will continue to grow. Once employees and teams master their data sets, provide access to more data so that they are able to explore and learn independently. People will need the opportunity to learn from their own mistakes by trying different strategies so that they are better prepared. That being said, certain data cannot be used for learning purposes, for example, confidential information.
Access alone is not enough. Employees are to be taught how to use the data to the best advantage. After all, anyone can have access to data; this doesn't make them literate. As the statistics suggest, most employees are keen to learn essential data skills, so it is unlikely that there will be resistance. Ensure employees know how to interpret data as well as provide critical thinking training.
Choose the right systems and tools.
Not every system or tool will be suitable for your company's needs. The system you choose needs to allow data analysts to share data across the company to relevant departments. Simultaneously, the systems you put in place need to be user-friendly for non-technical employees. If they cannot use it, the investment won't be used to its full potential.
Why is Graphite the Ideal Data Literacy Tool
With Graphite, it becomes easier to uncover hidden patterns, identify problems sooner, and see opportunities in your raw data. To run predictive analytics, without writing a single line of code!
And the icing on the cake is - all team members can see the story of your data.
An analyst can prepare a beautiful data story in Graphite Notebook, combining visuals and narrative. Then, they share that insights and conclusions with all decision-makers and senior leaders that aren't confident to work with data and need help to understand it.
This blog post provides insights based on the current research and understanding of AI, machine learning and predictive analytics applications for companies. Businesses should use this information as a guide and seek professional advice when developing and implementing new strategies.
At Graphite Note, we are committed to providing our readers with accurate and up-to-date information. Our content is regularly reviewed and updated to reflect the latest advancements in the field of predictive analytics and AI.
Hrvoje Smolic, is the accomplished Founder and CEO of Graphite Note. He holds a Master's degree in Physics from the University of Zagreb. In 2010 Hrvoje founded Qualia, a company that created BusinessQ, an innovative SaaS data visualization software utilized by over 15,000 companies worldwide. Continuing his entrepreneurial journey, Hrvoje founded Graphite Note in 2020, a visionary company that seeks to redefine the business intelligence landscape by seamlessly integrating data analytics, predictive analytics algorithms, and effective human communication.
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