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A Data-Driven Culture: Organizational Culture

This research was done by Stella Kwera M.K. @stellakwera

The culture of an organization is its personality and character. Organizational culture can be defined as the underlying beliefs, assumptions, values, and ways of interacting that contribute to the unique social and psychological environment of an organization. Culture helps improve workflows, guides the decision-making process, clarifies roles and procedures.

Having a clear culture that unifies employees and promotes organized work structures helps people work together with a unified purpose. In simpler terms, Data Culture is where an organization prioritizes data-driven
decision making. This is a collection of beliefs and behavior of people within an organization. As a result, data is woven into the very fabric of the organization and begins to define its identity, mindset, and operations.

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Data decisions are then based on a combination of data analytics and business knowledge. A data-driven culture requires that data be the main source of insights and that all levels of the organization embrace this culture. Data can provide insights to support strategic, tactical, and operational decisions. Therefore, all employees must have access to data and actively use it to enhance their daily outputs.

“Data alone doesn’t get us that far, the key is thoughtful business-driven data usage which enables us to extract insight that we can use to
make business decisions.”

Samir Boualla

Organizations whose different departments and functional areas vary in culture are likely to perceive a data-driven culture differently. Organizations must remember that culture is the glue that keeps them together. Therefore, knowing your company’s type of culture helps you understand how to shape the data culture at your organization. In an organization that has a culture of siloism and pockets of data analytics, introducing a data-driven culture could also take the same form of
siloism. This results in the non-uniform implementation of organization-wide data analytics solutions, different levels of data maturity, and knowledge among staff in different groups.

The implication is the more advanced department will reap more from data analytics while those lagging behind will reap less from data analytics. For example In Revenue Mobilization, the department whose staff use data to select audit cases is likely to raise more revenue and target accurately compared to a department that uses gut feelings and non – data-based methods to
target and select cases.

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Various forms of the organizational culture may include but are not limited to; Adhocracy culture, Hierarchy culture, Purpose culture, learning organizational culture, and results in organizational culture., When choosing a Culture, you must consider the team’s working styles and the changes your business is going through. Regardless of the organizational culture, it has become increasingly critical for an organization to build a Data-driven Culture. How?

  • Start with the top – effective Data-driven culture should be driven from the top. The senior leaders followed by leaders at various levels must be converted to champions of the data-driven culture
  • Change management campaigns – Awareness, Desire, Knowledge, Ability & Reinforcement (ADKAR) is a popular change management model that could be adopted.ADKAR stipulates that one must create awareness, ignite the desire amongst your staff, provide knowledge through training and Knowledge sharing, mentor, guide staff’s ability to implement, and finally re-enforce.
  • Provide enabling structures and resources (Human, financial) – institutionalize data-driven decision-making.
  • Correct the misperception that data is just for techies – Simplify learning and encourage step by step /incremental learning
  • Develop & apply organizations’ data governance policies and documents. The organization must develop policies that support, reflect, and shape the organization’s data analytics culture.
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With the explosion of data in all areas of our lives, data is now an asset-a new oil. Companies can make conclusions, draw insights, make recommendations, identify outliers based on trends and associations from their previous data and secondary data from other sources. A data-driven Culture entails using facts (data) and not instincts to make decisions. When deploying staff in a business area, identifying which Customer brings more value to the company, establishing how to cut costs, one can look for answers in the data. In modern Customs organizations, a lot of decisions
are made based on data and this has been aided by Machine Learning and Artificial intelligence. Given the increase in trade volumes today, it’s has become difficult to rely on human intervention and therefore, Customs organizations rely on technology to identify outliers (those that under-declare, undervalue), target the risky consignments, etc.

We integrate data-driven decisions into our daily lives, for example, deciding whether to wear a coat or take along an umbrella is usually based on knowledge of the day’s weather or predictions based on the season. Culture can be observed in how decisions are made; top-down or bottom-up; and whether employees are confident to express independent thoughts and feelings without fear of being repudiated. For data analytics to take root in the organization, all levels of management must be on board. If the senior managers understand the working of data analytics and data-driven decision making, they will demand the same understanding and alignment across the organization while in a bottom-up cultured organization, the junior staff will demand data analytics culture.

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The former would be ideal and preferred since its benefits outweigh the latter. The senior leaders at one of the leading organizations have embraced the data culture and demand for data to support any decisions made. Such decisions include determining the sector to focus on based on its performance or potential, staff deployments based on workload and risks, financial resource allocation based on value or Return on Investment, etc. This was achieved through continuous engagement and training, providing positive results of a data-driven culture.

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What Next?

Leaders and managers will be better placed to implement strategy and achieve their goals if they understand the culture of their organization. Strategies that are inconsistent with organizational culture are likely to meet with resistance and will be more difficult or even impossible to implement, while strategies that are in line with it will be easier to put into effect and more likely to succeed.


Ultimately, it’s important for any organization to build the supporting cultural frameworks that enable data to be the driver for decision making, and therefore, an organization must ensure the quality of its data, provide access to the data, manage its governance of usage, skill staff on how to analyze data and provide appropriate technologies to prepare and analyze data.

Finally, mastering Data Analysis and Visualization concepts will make your job as a leader to be much easier. This can only be achieved by placing yourself in an environment where you can constantly learn and keep reskilling and upskilling to master the concepts that will enable you to remain marketable and a highly sort after talent in the dynamic job space.

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