How Organizations Can Implement a Culture of Data Literacy
This is part of Solutions Review’s Premium Content Series, a collection of reviews written by industry experts in maturing software categories. In this presentation, AtScale Co-Founder and CTO Dave Mariani offers his perspective on how you can implement a culture of data literacy in your organization.
As the global analytics market grows, 60% of companies cite corporate cultures that “do not fully understand or value evidence-based decision-making” as their biggest barrier to successful implementation analytics. This opposition to data literacy makes it difficult for organizations to invest in the analytics tools and people they need to gain actionable insights from their data and improve business results. So how can leaders encourage a culture of data literacy in their companies?
Current Barriers to Data Literacy
The amount of data businesses are generating today is unprecedented, which is great for improving opportunities, but it also means there’s more information for employees to sift through. Data governance is a major barrier to data literacy, as many organizations do not know what data they have or where it is stored. Businesses need a central repository for the data they collect. They should also integrate this repository with their third-party applications to capture all relevant data.
Additionally, some employees may object to learning data literacy as a skill because they see analytics as something outside of their area of expertise. Leaders need to tout the benefits of data literacy for everyone in the organization, starting with the ability to get queries answered faster and make data-driven decisions for their department.
Even with employees on board, many companies lack the analytics tools that make data literacy worthwhile. If employees don’t have access to analytics software or if it’s too difficult for non-technical people to use, they will be frustrated by their inability to access the data they need to make important decisions. Although analytics software can be expensive, it generally has a good return on investment when paired with a culture of data literacy.
Data literacy starts at the top
For companies to create a culture of data literacy, their leadership team needs to be on board. They not only need to be prepared to invest in analytics tools and data literacy training for their employees, but they also need to become data savvy themselves in order to set an example for their team. When managers are data savvy, they put an intrinsic pressure on individual contributors to become data savvy as well, so they can contribute effectively to the team.
Leaders also need to make sure their teams understand what is expected of them when it comes to data literacy. Mariska Veenhof, Head of Analytics at bol.com, explains, “Implementing data governance involves determining the correct owners of certain data sources and ensuring they understand the responsibilities that come with their ownership. data owner role.” Giving employees data ownership roles can make them more invested in the data literacy process because they feel leadership is investing in them.
AI is a crucial part of self-service BI
When analysis is confined to technical teams, these employees can quickly become overloaded. “When an organization has weak analytics tools and/or low data literacy, they come to rely on their data and analytics teams for low-level requests,” said Megan Brown, director of knowledge management and data literacy at Starbucks. “This can be problematic – it’s not possible for an analytics team to scale enough to compensate for limited data tools and skills.”
Instead, organizations should equip employees across all departments with the tools they need to make data-driven decisions. Providing a semantic layer gives business users the ability to extract information using business-friendly language queries against SQL or a coding language.
Brown goes on to say, “Additionally, your business analytics professionals may be too far removed from business decisions to put insights into action – they depend on their business stakeholders to understand and apply the findings.” While having an analytics team is great, they probably won’t know how to use all the insights they are able to gather from the data. Data literacy empowers users of all technical skill levels to ensure they are making informed decisions for the business and that none of the BI team’s efforts are wasted.
Organizations should institute training and quality controls
In order to institute data literacy throughout the organization, companies should create educational programs that teach employees how to use data and analytics software in relation to their roles. They don’t need to know how the data relates to every aspect of the business, but they do need to be able to gather information about their respective departments. Employees need to know how to access data and summarize it using the analytics tools already in place.
In addition to educating employees, regular data quality checks ensure employees are pulling accurate information from the right sources and analyzing it correctly. It helps if there is a single source of truth for an organization’s data. Managers should use mistakes as a learning opportunity to further coach employees and help them achieve the ultimate goal of data literacy.
Successful organizations need both analytics and data savvy
While data analytics and literacy are important on their own, they provide businesses with the ability to make data-driven decisions. Creating a culture that prioritizes data literacy enables organizations to reduce reliance on technical data teams for low-level data requests, while giving business users the tools they need to get valuable information about their business. And once employees master the data, organizations can add artificial intelligence and machine learning algorithms to further improve business results.