Building data expertise should not be confined to a specific team within an organization. It is now a vital skill for all employees, regardless of their role. In today’s data-driven world, every department — from marketing and sales to finance and human resources — can benefit from leveraging data to make informed decisions, optimize processes, and drive innovation.

Organizations should strive to democratize data access and provide resources that enable all employees to become data literate. Here are some key strategies organizations can adopt to democratize data and foster a truly data-driven culture:

Strategies to build data literate organization:

1. Create an open data ecosystem: Create a data ecosystem that breaks the data silos across departments while making it easily searchable and discoverable throughout the organization.

   The ecosystem itself could leverage industry-known data architecture models like data lake, data mesh, or data fabric while leveraging well-known industry patterns like marketplace to make data assets searchable across the organization.

   It is imperative to ensure data is governed (quality, metadata, lineage, ownership, etc.) and secured (data classification, privacy, privileges, etc.) through a well-established onboarding and publishing process into the data ecosystem.

2. Promote a data-driven mindset: Building data literacy requires cultural change across the organization. It can’t be achieved without the support from the executive leadership along with continuous advocacy to promote the mindset.

   This could be achieved through newsletters, townhalls, and communities of practice (CoP) to share case studies, success stories, and best practices to change the mindset, or could be through hackathons to build or enhance data products or solutions.

3. Enable through training and development: While advocacy helps with changing the mindset, the training ensures it is acted up on the ground by the employees. Organizations can start by identifying different personas such as business data users, data analysts, data product owners, etc. that are required to transform itself into a data-driven organization.

   This needs to be followed up with skill gap assessments to devise a tailored training plan with metrics/KPIs to measure its impact on the ground.

4. Create an easy-to-use tools environment: Deploy tools and technologies that promote citizen development (low code/no code) so that simple data stitching and consuming data assets are not limited and or dependent on the specialized data engineering teams.

   Also, take an engineering approach to deploy platform capabilities such as data contracts, data contract-based access provisioning, etc. that can hide data engineering patterns and complexities from end users while ensuring compliance with data governance and security.

Benefits of data literacy:

1. Improved collaboration: With a shared understanding of data, cross-functional teams can collaborate more effectively to achieve business goals. Data becomes a common language that bridges gaps between teams, products, and departments to deliver an agile data-driven organization.

2. Increased efficiency: Data-literate employees can identify inefficiencies and areas for improvement in their teams, products, and departments. It could start with simple team efficiency tracking and proceed with how well a campaign has performed, how efficient the customer onboarding process is, and where the bottlenecks are. Overall, this will lead to streamlined processes and increased efficiency across the organization.

3. Enhanced decision-making: Data literacy improves business outcomes through evidence-driven well-informed decisions. For example, well-designed sales analytics could guide the business development team to focus on products/segments where salability is high against focusing on all products/segments equally.

   Similarly, it could help detect high-risk loan applications upfront to mitigate default risks leading to better outcomes and/or reducing business risks associated with gut-feel decisions.

4. Fostering innovation: Data literacy empowers employees to experiment with new ideas, analyze results, and iterate on ideas based on data-driven insights. For example, how transactional data could be used for improving digital adoption through better behavior-based pricing (like incentives) over the traditional product-based pricing model.

   Another example would be to identify the customer’s contacts to predict reasons for their calling and then use it to better service them and/or cross-sell. 

About the Author:

Anandh Asokan is Vice President, Data Engineering, Management and Enablement at Thrivent. Asokan is an experienced digital transformation specialist dedicated to leveraging technology for customer-centric value delivery. He is proficient in creating and enhancing integration products like APIs, data streaming, and bulk load assets, and establishing data strategy and vision to shape the build-out of solid foundations for analytics and machine learning.

A recognized thought leader in crafting pragmatic organizational transformation strategies, Asokan has a proven track record of delivering exceptional products across diverse tech domains and industries, earning a reputation for execution excellence and mentorship. He is a passionate engineering professional holding a Bachelor’s degree in Computer Science and a Master’s degree in Software Engineering.