Data Literacy: How to create a learning program?

Data is becoming the universal language of technology as we become more tech-driven. Companies are adapting to change and investing more in data. Many fail to recognize the importance of data literacy. Data literacy training is mandatory for all companies.

Companies with a higher rate of data literacy can better understand their customers and use data to help them. This data allows them to design better products and offer a more enjoyable customer experience. This knowledge drives higher revenue and accelerates business development.

But how can data literacy be achieved?

Building data literacy

Data literacy, as with all other projects, requires a plan.

One of the most important things to do is to have data-driven leadership. First, leaders need to embrace the concepts of data analytics. This will allow them to guide the company towards becoming data-driven.

A five-step approach is required to ensure that data literacy is built in a company that has data-driven leadership.

It is important to determine where your company stands with regard to data literacy. Data culture assessment (also called this step) will require you to ask questions such:

How mature do you think your company’s data access is?

This will let your company know where it is struggling to achieve its goal of building a culture of data.

How can you plan a lesson?

Once you have defined the current level of data literacy and what you desire, you are ready to start pushing data analytics into your company.

Begin by defining the learning pathway for each desired level in data literacy. The learning path covers the training needed by the cohorts as well as the time it takes to improve their data literacy. These cohorts can be classified as HTML-driven executives or data enthusiasts.

The duration and length of each training course will vary depending upon the individual cohorts. After this, you’ll need to map out the learning path of each of your cohorts.

Once you are done with that, you can begin to evaluate the effectiveness of the plan. The success metrics, as well as the learning path level, are defined here. This allows you to measure the program and make any necessary adjustments.

Once you have this information, you can begin to implement the plan.

A few tricks

It is important that you plan training to not only develop data literacy but also to teach data analytics to the company.

Companies follow a structured plan, but they fail to pay attention to what is most important – the data that should lead to insights. Companies should put emphasis on improving the decision-making process for employees, in order to boost revenue.

Also, companies should evaluate the success rate to determine how helpful the training was. Are the employees at the required level of data literacy? Do their decisions lead to insights? What speed can they get insights from data to help them make decisions? These questions can be helpful in evaluating the training.

One thing companies can do is plan how they will deliver the training. They can choose to start training one area and move on to the next one, or they could focus on the entire organization at once.

It is a good idea for employees to be divided into groups and assigned coach leaders to lead them. The size and composition of the group will vary from company to company.

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