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Data literacy necessary amid COVID-19 pandemic

Data literacy is perhaps more important now than ever before as healthcare organizations, governments and enterprises struggle to deal with the effects of COVID-19.

Data literacy is no longer an option; it's a necessity.

That was the message of Valerie Logan, CEO and founder of The Data Lodge, a data training services provider, who spoke on Thursday during a session at Beyond.2020, BI and analytics vendor ThoughtSpot's virtual user conference.

Some organizations began adopting data cultures in 2017, according to Logan, and the trend continued to slowly gain momentum through 2019. They developed data literacy programs, educating employees beyond IT departments and data analysts in the language and usage of data.

But data literacy wasn't a high priority for many businesses until 2020, when data became critical to survival in numerous ways.

When COVID-19 began to spread in March 2020, healthcare facilities were suddenly dealing with patient surges, governments were forced to shut down local economies, and many businesses were faced with almost a complete loss of revenue.

Data and analytics were crucial to making decisions that would ensure healthcare organizations had enough ventilators and personal protective equipment on hand to deal with potential patient surges, that government agencies could reopen economies, and for businesses to make decisions to stay afloat.

"Data literacy just got real. It can no longer be ignored," Logan said. "The pandemic has made this personal for all of us, not only in our work roles but in our personal lives with our friends and families trying to make critical life decisions."

Valerie Logan, founder and CEO of The Data Lodge
Valerie Logan, founder and CEO of The Data Lodge, discusses the importance of data culture.

Steps toward data literacy

Organizations, however, can't simply adopt a data culture in one fell swoop. It takes time, including a shift in mindset and the learning of new skills, both of which can be difficult and scary.

As a result, even though data is as important in the current climate as it's ever been, many organizations still resist the development of a data culture. Logan calls those organizations procrastinators. She calls the ones that go forth despite difficulty and fear pioneers.

The procrastinators, she said, say things like 'it's not the right time' and 'other things are more important,' and make up reasons for delaying the development of a data culture, such as not knowing who to put in charge.

The pioneers, meanwhile, say data culture is critical and try to figure it out, that they don't have any other option but to figure it out, that the program needs a lead and someone focusing on it, and that they need to work smart with a launch and scale.

"Not taking an action is a choice," Logan said.

Once organizations commit to data literacy, there are seven key steps to changing the culture and upskilling the workforce, Logan said.

7 steps for developing a data culture.

One of the keys, before taking the steps, is to acknowledge that data is a language all its own, and becoming data literate -- developing the ability to read, write and communicate with data in context -- is akin to learning a new language.

"That creates permission for people to say they don't know how to speak this language but can try," Logan said.

Another key is to convey the message that data literacy is no longer just for specialists; it is meant to maximize the talent of everyone in the organization.

Data literacy just got real. It can no longer be ignored.
Valerie LoganCEO and founder, The Data Lodge

"This is a mindset shift," Logan said.

When the time ultimately comes to pragmatically implement a plan for developing a data culture, Logan's seven steps are as follows:

  • identify a sponsor and a lead;
  • develop a clear and compelling case for change;
  • craft a blueprint that makes data literacy part of developing a data culture rather than a separate skill;
  • explore data literacy with pilot workshops that replace fear with fun;
  • launch pragmatically with 3-5 quick wins;
  • ignite bottom-up momentum by engaging leaders at all levels of the organization; and
  • refine the plan for scale by teaming with HR and other key departments.

What data culture is not, Logan stressed, is simply training and the attempt to make everyone a junior data scientist. It's about shifting to an insight-driven philosophy, fostering collaboration between data scientists and business analysts, enabling comfort and confidence through data-driven decisions and maximizing talent.

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