Why Is a Data-Driven Culture Important?

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Many modern organizations are recognizing how important it is to develop a data-driven culture. A data-driven culture typically describes a workplace environment and involves making information readily available to staff. 

The general idea in promoting a data-driven workplace culture is to increase profits by developing a business that functions in a streamlined, efficient, and friendly manner. This type of culture should present a variety of advantages, which in turn makes it a more attractive business option than less efficient, less friendly competitors. 

Data and data analytics have become an integral part of successful modern businesses.

Many organizations that have not shifted to a data-driven culture embrace an unnecessary philosophy of restricting access to data, which translates loosely into only allowing managers access to it. To support a data-driven culture, there must be a high degree of transparency, making most of the data available to all staff, in turn helping them to schedule day-to-day tasks more efficiently. (The personal information of customers, for example, should not be made available on a casual basis, but should be restricted to a few trusted managers.)

Being competitive in today’s modern, fast-paced global marketplace requires more than new software or a few individuals in management embracing data. It requires converting the entire staff. 

Businesses that develop a thoroughly data-driven workplace culture will have a significant advantage over businesses that have not made the transformation. A data-driven culture has the tools to maximize business outcomes and performance, and it uses them.

A data-driven workplace values the insights it can obtain from the different types of analytics that are available – data analytics focused on finances, marketing, and productivity.

The rapid adoption of computers and the internet across all industries has produced an ever-expanding amount of data for businesses to access and use. In the last decade, most businesses have invested in data technologies and analytics software, with the hope of making their business more profitable. However, without a culture supporting the use of data in day-to-day operations, the improvements from data use will only be partially realized and profits will not be maximized.

Shifting to a data-driven culture involves change (new habits, new people, new situations) and will involve spending money (new software, staff training, new employees).

The Advantages of a Data-Driven Culture

A data-driven culture is, in part, about humans making decisions based on researched data, and in part, about using automation to collect customer data and make real-time decisions regarding customer transactions and targeted advertising based on previous and current purchases. A data-driven culture does not use assumptions or gut feelings but rather relies on statistical information based on facts when making decisions.  

Becoming a data-driven organization not only improves decision-making but also improves efficiency and user-friendliness. Some of the more basic advantages are listed below:

  • Increased productivity and team effectiveness: Software can be used to track the progress of various projects and improve overall coordination through the use of dashboards. This type of software allows departments to clarify and define the scope of their work clearly and align their day-to-day tasks for greater efficiency. With this advantage, a data-driven culture can define the constants, as well as identify and measure the dynamic, constantly changing elements. 
  • Improved transparency and workforce engagement: Confusion, or a lack of information, often results in a diminishing amount of interest. Businesses often see the energy levels of their workforce drop due to a lack of interest by employees who have no knowledge or understanding of the “big picture.” A data-driven culture supports both understanding and ownership. Transparency provides a holistic view of the organization’s processes. 
  • Automation improves coordination and consistency: The automation of mundane and time-consuming tasks minimizes mistakes, completes the tasks much, much more quickly, and can improve coordination between support, marketing, sales, and other departments. Automation improves how a process, service, or product is delivered to the customer.
  • Data-driven cultures save money and increase profits: The combination of more efficient automated services, increased transparency (better communications), and superior decision-making typically has the effect of reducing overhead and increasing profits.

Creating a Data-Driven Culture

Software alone may make an impressive impact on the efficiency of a business, but this is only a partial solution. The workplace culture must also embrace the use of data in its day-to-day operations and use it in the decision-making process. Creating and maintaining a data-driven culture requires a significant commitment.

The Harvard Business Review has published an article describing the shift of Kuwait’s Gulf Bank to a data-driven culture.

Trust and commitment are two important features in a data-driven culture. Trust in the data is exceptionally important, but trust in other staff, for purposes of collaboration and teamwork, is also quite important. Dealing with internal conflicts and misinformation disrupts the smooth flow of doing business.

There are a number of issues to consider when creating a data-driven culture. These considerations are both technical and behavioral. Listed below are the steps needed in developing a data-driven culture: 

Clearly define the organization’s goals: As a first step, list the changes the business needs to make to become a data-driven culture. For example, one goal might be improving customer service and reducing churn. Using the appropriate software can show the patterns of the average customer during the different stages of the purchasing process. 

Selecting the appropriate software: After the goals have been clearly defined, select and invest in the right tools for collecting, analyzing, and visualizing the data as it flows through the system. It is important to ensure the organization’s computer system can handle the complexity and volume of data flowing through the system.

Automation should be used whenever possible. This will save time and minimize errors. 

Hiring and training staff, dealing with people: In a data-driven culture, everyone should be involved, and this should be communicated to staff and management (exceptions are allowed, for example, the janitor). Everyone using data in doing their job should understand they are also creating data that can be used later for research. When people understand their roles, they can work together as an efficient team to find and eliminate sources of bad data. 

The process of locating and repairing sources of poor-quality data acts as an educational process for staff and empowers them to be proactive, taking responsibility when they notice a data flow problem (as opposed to ignoring the problem).

Shifting to a data-driven culture may result in having to hire a few specialists – individuals who are skilled in Data Management, data visualization, and data analysis. Current employees should be given the opportunity to take classes (or attend in-house seminars) that will update their skills and enable them to collect, analyze, and process data. This includes training on data analysis tools, data visualization techniques, and Data Management best practices. Also, prioritize effective communication of data insights within the organization. 

It should be emphasized that staff and management are now working as a team. In-house competition might be useful in a car dealership, but in a data-driven business, collaboration and teamwork should be emphasized. Creating a workplace environment that encourages the sharing of data insights and collaboration to solve problems is an important part of the data-driven culture. Anyone supporting a habit of keeping secrets and hidden agendas should be retrained or removed.

Explaining the reasons why, telling a story: Simply presenting staff and management with numbers and statistics may not provide an understanding of the changes about to take place, nor an understanding of why. Many people are not number crunchers. Presenting a narrative, or a story, may make the changes more easily understood.

When developing the storyline, explain the organization’s goals, the problems being experienced, comparisons with the competition, and how a data-driven culture will resolve problems and support achieving those goals. Be aware of the audience – a story that contains examples that are relevant or relatable to the audience will help to keep their attention. Using real people and real problems can help to make a story more interesting.

Make the changes: This step involves first making sure the money is available for setting up the software contracts, training staff, and hiring new people. Once the money is assured, it’s time to take action. 

Maintaining a Data-Driven Culture

After creating a data-driven culture, maintaining it becomes a problem, but there are behaviors that can be used to sustain it. Listed below are some steps that can help to ensure the organization’s data-driven culture not only continues, but also to grows and evolves:

  • Monitor and measure progress: Regularly track key metrics (sales, customer feedback, conversations with staff) and assess the success of achieving those goals. Note areas needing improvement and make the necessary changes. (Some responsibilities may be assigned to marketing, while others can be assigned to the data steward.)
  • Celebrate staff successes: Recognizing and rewarding employees who make a meaningful contribution to the business using data-driven decision-making should be identified and rewarded in some small way. This behavior will reinforce the importance of using data and encourage others to use it.
  • Encourage continuous learning: This behavior supports a sense of open-mindedness that might otherwise be lacking in a business. Additionally, ongoing training and educational opportunities keep staff updated on the latest technology and techniques used in Data Management, analysis, and visualization.
  • Promoting innovation: This isn’t about creating new inventions or new algorithms (although those ideas should not be ignored). This is more about replacing three steps in a process with one more-efficient step, or suggesting the use of a new, more efficient open-source piece of software. By encouraging staff and management to experiment, an organization can stay ahead of the competition.