As companies rely more and more on data, and it creeps into more parts of business, data literacy is a skill that everyone has to have now.
But, evidence suggests that most companies are still struggling to build this skill, even after they’ve identified it as critically important: just a quarter of employees report feeling confident in their data skills. Here are five strategies to help companies expand their data literacy:
1) Make it an organization-wide priority
2) Develop a common language for speaking about data and talk about how it connects to your business
3) Create spaces where you connect business concepts and data concepts
4) Incentivize data-driven decision making, and
5) Teach data literacy in the context of your specific business — and use tools and programs that actually engage your employees.
Building up data literacy in an organization can also help diversify the data teams who are at the forefront of making critical decisions about how data will be collected, processed, and deployed. The importance of diverse data teams is something I learned firsthand over more than a decade as a quant fund manager. It’s a commonly held belief that more diverse portfolios outperform because they reduce risk. But it is analogously true that diverse teams outperform because they reduce the risk of groupthink. 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.
But a look at the data tells us that most companies are still struggling to build data literacy. Ninety percent of business leaders cite data literacy as key to company success, but only 25% of workers feel confident in their data skills. Not only that, but some estimates suggest that nearly nine in 10 data science professionals are white, and just 18% are women. Research from General Assembly indicates that when it comes to diversity, data science lags behind even other tech-oriented disciplines, like digital marketing and user experience design.
Make data literacy an organization-wide priority, not just among people within the technology org.
Data literacy is not a technical skill. It is a professional skill. Encourage all of your employees — marketers, sales professionals, operations personnel, product managers, etc. — to develop their data literacy through quarterly engagement sessions that you host, where you cover topics like data-driven decision making, the art of the possible in AI, how data connects to your business, ethics & AI, or how to communicate using data. This kind of organization-wide emphasis is the basis for a transformation to a data-first culture.
Develop an internal common language for speaking about data, how it intersects with your business and industry, and how it is changing specific roles at your company.
The world of data is big, filled with buzzwords and misunderstanding. Develop a view as an organization which components of data literacy matter most to your organization — if you are a financial services firm, it may be probability and risk measurement; if you are a technology firm, it may be experimentation and visualization. In your L&D sessions, develop learning content that uses this language and demonstrates how it connects to your business in multiple departments, so employees can connect all the dots between data literacy and their workflows.
Create spaces within your organization for workers to connect business concepts and data concepts.
One thing we recommend to all of Correlation One’s clients is to empower employees to generate new business ideas that apply their data literacy. For example, suppose your company is in the music industry. As part of your L&D program, have employees develop project proposals that leverage their newfound understanding of data literacy — combining it with the knowledge they have of the industry, they will generate surprising new ideas for cost savings or revenue generation. Just as importantly, you will be empowering them to drive a new data-first culture from the bottom up.
Create incentive structures to reward data-driven decision making.
Take your current process for approving ideas or setting budgets. Then add mechanisms that reward data-driven thinking. For example, require managers to include clean visualizations in their proposals, or to build dashboards that track their KPIs quantitatively and in real time. If you can shift your managers’ decision-making from intuition to data by granting faster project approvals or larger budgets for proposals made using data-driven thinking, you will quickly get the behavior you seek from your managers through incentive alignment.
Deploy L&D programs that teach data literacy in the context of your business problems — and that actually engage your employees.
Subscriptions to education and training platforms like Coursera often fall flat in organizations that are looking for lasting transformation. That is because learning is much more effective when it is social (done with others), personalized (done with expert feedback), and contextual (connected directly to the business problems you are solving). Developing these personalized, social, contextual learning programs is more resource intensive, but the benefits in terms of employee engagement with the material, employee retention of the material, and empowering your employees is worth it.
Perhaps most importantly, my experience both before and during Correlation One has helped me understand that data is not a vertical — it is not just one job family, like a data scientist or data engineer. Instead, data is a horizontal — it is a skillset that cuts across a growing number of jobs in every field. A marketer is a better marketer with data skills. A product manager is a better product manager with data skills. And so on for operations, engineering, sales, and even HR. Not everyone needs to know how to code. But soon everyone will need data literacy.
Ultimately, data literacy is about much more than machine learning and data science. And it’s about more than AI. Data literacy is simply about humans coping better in a data-infused world — which is why we need it now more than ever.
About TechX Corp.
TechX Corporation is “AWS Partner of the Year” 2021 – 2022 in Vietnam.
TechX Corporation is a young startup, founded in 2020 by a team of well-established technology experts, with years of experience in multi-national enterprises and VN30 corporations with the mission of supporting Vietnamese companies in their digital transformation journey. TechX’s team of cloud experts possesses a comprehensive insight of Vietnam market, especially in major industry such as banking and finance, technology, E-commerce, etc.
Became AWS Advance Consulting Partner in less than 1 year since its establishment, TechX has been leveraging AWS advance cloud services and technology to provide tailored cloud transformation solutions our customers. Currently, TechX Corp. proud to be cloud consulting partner to top banks and financial institutes in Vietnam, such as Maritime Bank (MSB), Vietnam International Bank (VIB), VietinBank, FE Credit, etc., and many other companies in different industries.
