Data culture refers to an organizational culture of using data to derive insights and make informed business decisions. Companies can build a strong data culture by arming themselves with data and the right set of people, policies, and technologies.
A data culture helps companies become more competitive and resourceful by leveraging data. And data-driven companies make better, faster, and more objective business decisions. They promote greater employee engagement and retention, and drive better financial outcomes in terms of revenue, profitability, and operational efficiency.
In this article, you’ll learn about data culture, what its importance is for modern organizations, and how you can build a strong data culture at your company.
Why you need a strong data culture
Without a solid data culture, organizations will inevitably fail to harness the power of data. As previously stated, data culture refers to a set of beliefs and practices that companies use to cultivate and drive more data-driven decisions.
Traditionally, businesses relied on the instinct and gut of a select few leaders to make strategic business decisions. However, with the accumulation and collection of massive volumes of customer and business data, domain expertise and instinct can now be complemented with data-driven insights to make more informed decisions.
There are several advantages to building a strong data culture. Some of these include the following:
- Removal of guesswork when making decisions
- Increase in employee engagement due to the adoption of data-focused strategies
- Increase in financial outcomes due to greater use of data
Every business sector, from product to finance to HR, creates and collects a lot of data from external customers or internal operations. For business heads and decision-makers, it’s no longer feasible to stay on top of the ever-increasing volumes of data to better understand and evaluate the current state of their organization. However, with data analysts and scientists embedded across each department, it is possible to tap business insights in real time and respond quickly to changes in business performance.
A strong data culture also promotes greater employee engagement and retention. When employees see that decisions are made on the basis of data and not driven just by the highest-paid executives, they feel that they can contribute more insights to influence decision-making. In the long term, this facilitates attracting the best talent in the market who can be incentivized to have a greater say in making key business decisions using data.
Moreover, there are also strong financial outcomes associated with building and promoting a data culture. Companies with data-driven cultures benefit from increased revenue, better customer services, and more operational efficiencies leading to improved profitability.
How to build a strong data culture
Building a strong data culture is a long-term endeavor that requires patient support and encouragement from leadership. Companies with strong data-driven cultures have executives who lead by example and establish clear expectations that decisions will be objective and based on data.
Data leaders can lead from the front by establishing clear goals and guidelines, investing in technology and training, as well as identifying and rewarding employee behaviors that embody a data-led culture. Beyond leadership setting a tone for the whole organization, let’s take a look at a few other components that can help build a strong data culture.
Bring business and data science together
One of the first steps in building a data culture is to build a strong data science team consisting of data analysts, data engineers, and data scientists. Having quality in-house data talent is a competitive advantage that reaps multiple benefits, including building a robust culture focused on data.
Once a data science team is up and running, it needs to be strategically embedded across various departments of the business. This helps business professionals interact with data professionals more regularly and better understand how the power of data analytics and data science can improve business efficiencies and impact profitability and growth.
At the same time, this setting enables data professionals to better understand how the business works and build intuition for developing better data and machine learning–powered tools and products. This creates a positive flywheel where both business and data science teams learn to collaborate better and benefit from their respective skill sets.
By bringing business and data science together, everyone in the organization learns to appreciate the value of data and use data-driven insights to improve the quality of their decisions, products, and services.
Leverage data when creating goals and deadlines
Driving strategic business goals and metrics by leveraging data is a key aspect of encouraging a data-led culture. When goal-setting exercises are conducted objectively and leaders regularly use data and metrics from previous business quarters or external data about competitors or the overall market, everyone in the organization will start to embrace similar data-driven approaches. Leveraging data for setting new targets also enables every stakeholder in the organization to understand and anticipate their future goals and prioritize their work accordingly.
Data-led goal setting is a more democratic and fair-minded process that encourages ownership of respective goals by every employee, as opposed to arbitrary, instinct-led, unilateral decisions made by the leadership.
Ensure everybody has access to data
A fundamental step toward attaining a data culture is to democratize access to data across the organization. Data culture is a difficult goal when employees in different parts of a business struggle to obtain data.
If you don’t give your employees access to your data, they won’t be able to utilize it when making decisions. This disenfranchises the data analysts, engineers, and scientists disproportionately, as their day-to-day work is impacted the most. Without a motivated team of data professionals, the downstream benefits of data are unlikely to materialize across various business departments.
A strong foundation of data governance and data democratization is a prerequisite to achieving the business goals associated with a robust data culture.
Keep your data technology up-to-date
A critical aspect of building a data culture is employing modern tools and technologies to make it easier for employees to access, analyze, and share data-driven insights. Building a modern data stack with newer components like a metrics layer simplifies data-based operations and analytics for everyone, especially nontechnical business stakeholders.
Technology, like data warehouses and metrics layers; data analytics tools, like Tableau or Power BI; and customer relationship management (CRM) tools, like Salesforce, are indispensable for modern businesses. Building the data architecture in a cloud environment like Amazon Web Services (AWS) further improves access to data and reduces the need for multiple tools with a steep learning curve.
The right use of tools for data, collaboration, and customer service goes a long way in fostering the use of technology to drive a strong data-led culture.
Provide training for employees
Having supportive leadership and access to data and technology is of little use if employees are not data literate and able to extract insights from data. This requires further investment in terms of learning and development to empower employees with the necessary skills to explore, understand, and share data-driven insights across the organization.
In addition to reducing the skills gap, it also encourages people from nontechnical backgrounds to become more data savvy, collaborate better with data experts, and build more comprehensive data products and solutions to benefit the business.
Encourage data-oriented decisions and behavior
The primary challenge to becoming a data-driven organization is not technical but cultural. A strong data culture is based on a robust foundation of people, policies, and technology. However, once the initial foundation is in place, data leaders need to maintain and bolster the spirit of data-driven decision-making by incentivizing and rewarding behaviors that embody the culture.
At the same time, decisions and behaviors that do not represent a holistic data-led process ought to be called out and questioned until every single employee is on board with the philosophy of using data for every decision. This includes encouraging experimentation to answer key business questions for which data does not exist yet or when the current set of data does not yield compelling evidence.
Data-driven companies are in a better position to attract and retain talent, make faster decisions with more conviction, and drive stronger growth and profitability to meet their business goals. According to research by McKinsey, data-driven companies are able to achieve their goals faster and realize at least 20% more earnings.