The Case for Building Organization-Wide Data Literacy Via Upskilling

Discover why data literacy matters in your company — and how data skills training for your entire organization is critical for success.

One of the greatest challenges facing companies today is adapting to the rapid change in technologies and innovations. The tools, skills, and resources that a company uses may become outmoded.

Companies that learn to embrace and adapt to change appear most apt to survive and thrive. And those who know to leverage their workforce's data skills to make data-driven decisions are even better positioned.

Yet many business leaders still need help with one glaring obstacle to their data transformations: their existing workforce's insufficient data literacy.

Thanks to increasingly user-friendly technology and modern pedagogical techniques, data literacy is no longer reserved only for highly trained data specialists (e.g., data scientists and data engineers). It is now a skill, like critical thinking, that’s necessary for many roles in the modern workforce.

With the proper upskilling and practice, people holding varied job titles can become confident and capable when working with data. Enterprises are starting to recognize data literacy as valuable laterally across the entire organization.

What is Data Literacy? 

Data literacy is the essential ability to understand, communicate with, interpret, inquire about, and make inferences from data. Enterprises need their workforce to be data literate to understand data sources, perform analysis, understand results, and communicate the extracted business information to the rest of the organization so that action can be taken. Organizations cannot become data-driven without a data-literate workforce.

How Does Data Literacy Benefit Employees

Today, being "data-driven" seems commonplace as workers are inundated with data via dashboards and tools. However, having dashboards is not enough.

Teams that are not data literate will fail to discover insights that create results for their businesses. When provided via corporate training, data literacy empowers workforces with the skills required to truly become data-driven, enhancing their ability to isolate critical findings and make decisions to advance their teams' goals.

Employees Demand Upskilling - But Are Enterprises Listening?

Enterprises must meet the surging demand from their workers for improving skills, including data literacy. A survey by Amazon found that 89% of employees are "extremely" or "somewhat" motivated to improve their skills in 2023, with 76% adding that the pandemic compounded their motivation to expand their skills. For employees, the basis is not just career or income-focused - they see these skills as ultimately enabling a vital work-life balance and improving their quality of life.

What Results Does Data Literacy Create For Enterprises?

Data literacy is at the heart of many critical issues that businesses face in today's economy, including worker satisfaction, employer branding, uncovering new competitive advantages, and increased agility to support financial success. 

The need for data skills undoubtedly extends across the entire organization and should not be constrained to traditional data-centric teams such as IT or finance. At least half of all employees will need reskilling and upskilling - yet according to McKinsey, only 15% of organizations have begun to solve their talent's digital skill gaps.

Enterprises seeking to achieve greater results and increase their brand reputation should consider the following:

1. Data skills power organization-wide outputs every single day. Skill agility can positively influence expected business outcomes through more effective, daily usage of actual data-driven decision-making - enabling you to become more competitive.
2. Motivated workers via career development mean improved employee engagement and retention. In addition to known factors like compensation, autonomy, and the ability to advance within an organization, the ability to learn on the job and acquire new skills are now highly sought after by workers. This is especially true of those who want to avoid work skills obsolescence in a post-pandemic world.
3. Employer branding is fortified when workers feel positive about career development support from their company. Because talent is attracted to companies that take care of their people, upskilling offers employer branding benefits similar to reskilling (the practice of training employees for jobs and tasks with which they may have little previous familiarity) and cross-skilling (training people to work in multiple functions or skill sets).

Why Should You Take Action To Solve Data Literacy Gaps?

That's a good question, but here are two arguably more critical ones to ask:

1. How data literate is your company today?
2. How data literate do you need it to be next year — or 5, 10, or 15 years from now?
   

Surprisingly, although 93% of business leaders believe data literacy is relevant to their respective industries and that employees should be data literate, only 24% of employees feel fully confident in their data literacy, analytics, and communications skills.

That's a huge gap that data skills training can address.

The value of enterprise-wide data literacy can not be overstated. The diversity of thought across multiple disciplines also equates to the responsible use of data insights and AI-related opportunities.

Businesses should also consider the beneficial impact of diverse viewpoints in the organization's use of data. Our Co-Founder and CEO, Rasheed Sabar, identified this in The Harvard Business Review:

"By investing in data literacy across the enterprise, businesses can bring more divergent and creative perspectives to bear on both mitigating the risk of algorithmic bias — and identifying other efficiencies and opportunities that data can often reveal."

Best-in-class upskilling providers are led by data professionals who know how to finely tune lessons and provide reinforcement that supports divergent data knowledge gaps and skill competency requirements. By implementing training with such a provider, you may be able to upskill the entire organization, from your hourly staff to C-suite executives.

Why Self-Driven Online Courses Don't Enable Data Literacy

Several big-name digital training services offer massive libraries of low-cost, high school, college, and graduate-level courses that anyone can take from the comfort of their homes. For companies hoping to enhance workforce data literacy, the appeal is understandable.

Yet there are four major problems with this approach, however:

1. Most people need more discipline or motivation to complete online courses. That's why completion rates are low, which undermines well-intentioned upskilling efforts. What happens in an online course or MOOC when an employee encounters a sticking point with a complicated course problem? With no peers, instructors, or teaching assistants to lean in with them in real-time to tackle a problem, odds are decent that a trainee — even someone with a college or graduate degree — will throw up their hands in frustration and give up.
2. Online training content is typically too far removed from a trainee's industry to be relatable. Context matters — especially in a complex field like data science. For example, a quantitative finance professional taking an online Python course that uses weather pattern data may struggle with the course content thanks to a lack of familiar, relatable, and relevant context. Offer instead this same adult learner a real-life problem relevant to their daily work as part of the curriculum, and it's likely to build self-efficacy faster, with greater efficiency.
3. Cookie-cutter, one-size-fits-all approaches to data training fail to reflect learners' previous knowledge, experiences, or day-to-day work responsibilities. Your C-suite is going to learn and process information differently than junior staff members. Your managers will have different knowledge gaps and concerns than your new hires. Shouldn't your upskilling program reflect those differences?
4. Online training platforms and similar programs (e.g., MOOCs) display poor track records when it comes to retraining and upskilling employees. Sure, they appear affordable and convenient, but in practice, they can come up short for workers - and the enterprise.

In our experience, those four training obstacles can be mitigated when companies select a corporate data science training provider that offers the following:

• Synchronous learning environments
• Engaging, context-specific coursework
• Collaborative and social learning
• Relevant case study and capstone content, often involving client-specific data sets
• Training solutions that reflect workforce composition, from entry-level to senior leadership

Does Data Literacy Deliver ROI?

It's no secret that improving the data literacy of employees requires both a financial and time investment. Naturally, ROI is a consideration — especially if you're a data advocate who has identified corporate data science training as being the final step to realizing your company's data transformation goals.

According to the Harvard Business Review, many companies focus on measuring completion rates, satisfaction scores, and employee feedback when considering training ROI. Yet costs (including the value of building skills through investment versus not doing so, in everything from low morale to errors), productivity, people, and in-house sponsor satisfaction metrics may be more accurate ROI metrics.

There may be significant tax benefits and grants available to help offset costs related to upskilling talent for highly technical fields.

What about Data Upskilling for Technical Employees?

We’ve discussed data upskilling for generalist and non-technical workers. There is also significant value in more hands-on and in-depth upskilling for technical workers. Many organizations possess talent with strong foundational technical skills who may be in roles that need to become more digital. For example, you may want to create pathways for your mechanical engineers to become data scientists, pathways for your software engineers to become data engineers or pathways for your business analysts to become data analysts, and so on.

Upskilling is a smart solution to these skills needs: it is cheaper than hiring external talent and creates more retention among your existing employees. Josh Bersin notes that while upskilling a data specialist “may cost $20,000 or less, the cost of hiring often costs $30,000 for recruitment alone, in addition to onboarding training. And new hires are two to three times more likely to then leave.”

The Takeaway

It takes time, effort, and money to nurture data literacy in your current workforce.

And while the returns and rewards of data upskilling may only sometimes be evident after the completion of training, there's value in selecting a top-flight provider willing to help you identify and develop custom outcomes, KPIs, and ROIs.

A worthwhile provider will also be receptive to tailoring your program's design and curriculum to your company's specific needs, goals, and objectives. They'll be willing to walk alongside you as you transform data literacy into data fluency for employees who need an advanced level of knowledge.

Through our work with renowned companies, government leaders, and prominent data professionals in industries such as finance, health care, manufacturing, and tech, Correlation One is helping companies empower their employees with data literacy by providing foundational and advanced training.

Is your organization data literate?  Learn how Correlation One can help you upskill your workforce's data skills to increase data literacy.