Data Culture: 5 Hallmarks of a Data-Driven Organization

Part of blum’s Data as an Asset Series

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Part of blum’s Data as an Asset Series

In today’s business climate the word “culture” is constantly thrown out there. When you hear the term, most tend to think of office happy hours and dress code standards. That type of culture certainly has an impact on your business but I’m here to talk about a different type of culture—one that can give you a strategic advantage and help position your organization for future success.

What is Data Culture?

A data culture is made up of people with this common goal: wherever important business decisions are made, data and analytics should be available.

Data culture refers to a shift in mindset within an organization, initiated by a desire to enable better, more data-driven decision making. A strong data culture is important to any organization that wants to make better informed business decisions.

Having this culture in place allows for leaders to focus on facts and changing market and industry conditions – not gut. Organizations with a strong data culture rely on data for decision making because they know that evidence is more reliable than human instinct.

So, what is a “Data Culture”? And how can data leaders work to promote one?

What Elements Make up a Strong Data Culture?

Since data culture is made up of people, promoting a data culture begins with supporting the activities of those people. Certainly, a thriving data culture is supported by strong leadership.

Without executive leadership, people and the organization will fall back to default behaviors: siloed information, distrust in the value of data, multiple versions of the truth, etc.

Leaders looking to promote a strong data culture should consider the foundational elements. These five elements are requirements for building a strong data culture.

#1 – Trust in the Data

People in the data culture need to have trust in the data used to make business decisions. Poor data quality undermines data culture, leading to distrust and inefficiencies for the data culture we are promoting. Data stewardship with strong governance processes present opportunity for operational efficiencies. Data culture wants access to the highest quality data possible.

While transactional data is usually authoritative, how we organize the data can become unwieldy. This speaks to the need for a Master Data Management program in complex organizations.

#2 – Consider Relevance When Sharing

A data culture empowers employees at many levels of the organization. Each employee has a different timeframe for information. Finance professionals may prefer a monthly update, while the operations team needs information in more real-time. Data cultures recognize this need for flexibility and plan for data delivery to be relevant for all.

#3 – Establish Secure Access to Information

While we need to make data and analytics available wherever decisions are made, people in a data culture understand that valuable assets must be secured. This requires partnership: data and technology leadership working to ensure that databases, data discovery tools, reports and analytics are all managed under a common security framework. This means that security best practices should be adhered to, and a single common location for data assets should be subject to security. As an example, users should be able to use Single-Sign-On to access curated data assets, reports and dashboards.

#4 – Choose the Right Tools

A data culture requires data management tools deployed to suit business needs. Two “must-have” tools include a Metadata Catalog, or system that describes the location, attributes and use cases for company datasets, and a Self-Service Reporting platform. These essential tools are in broad use throughout a data culture because data culture requires collaboration and discovery.

#5 – Equip Your Team with the Right Analytical Skills

Participants in a data culture must have some analytical skills. This is often overlooked, but essential. The people in a data culture must be prepared to interpret the information, to gain Insights.

For leadership, analytical skills include identifying and defining Key Performance Indicators (what they measure, and how they are calculated) in order to monitor the business at a strategic level. For analysts, analytical skills include the ability to present financial or operational information in a report that is both informative and without bias. For organizations investing in AI (artificial intelligence), analytical skills include the ability to evaluate a predictive model.

The Road to a Data Culture

Our Enterprise Data Assessment (EDA) is a major step towards advancing your company towards a data culture and a key segue into digital transformation. The purpose of the EDA service is to discover, or uncover, opportunities to drive business value, then recommend an accelerated roadmap for achieving that value. A strong data culture is an essential foundation that leads to Insights and Business Value.


EDA Checklist

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