In modern business environment, to leverage data for making more informed decisions, there needs to be a cultural realignment. Data if put in the centre of the decision-making process, elevates its value to a higher level. Organizations who can adjust to data culture at the earliest will gain a competitive advantage resulting from being early adopters of business intelligence technologies. Even a junior marketer should have accurate data if they want to be competitive. Data Culture is a prominent aspect of how far a data is viewed and used across organizations, how far relevant data is collected, or democratized. In other words, data culture is a combination that involves data quality, designing metrics, understanding and analyzing the available data, decision-making, A/B testing and more.
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Building a Data Culture
Becoming data-driven requires investment in effort, money, time and technology. Organizations must be involved in more forward-looking analysis. To build up a proper data culture, business units need to partner with the data teams to find the appropriate data sources, minimize collection bias and maximize quality of data. Building an efficient data culture requires three major components:
A. People. People at all levels within the organization must be a part of the data. Staff should have the knowledge of what is a relevant data. Regular meetings are held to maintain transparency in information, if needed.
B. Process. Findings and insights from prior decision-making are kept track of to avoid similar circumstances arising in future. Firstly, measurable goals should be set. Flow of data should continue. Then staffs should regularly share learning experiences and try to improve on it.
C. Product. Without adequate tools, it becomes difficult to achieve the goal. Constant Contact, for example, is a web service that the content team uses to e-mailing clients. It allows test out different subject lines with your audience and check which one leads to the highest open rate. Another tool used by web designers is Optimize.ly. This service allows experimenting with different content and layouts on web pages and compares their performance.
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Barriers in Building a Data Culture
Just as any other organizational change, data culture also faces some barriers. Some of them are:
A. Being unaware of data’s potential. Data can be qualitative or quantitative. Every data speaks differently. It is very important to recognize and understand the feel of it. Otherwise, it will remain raw and unutilized.
B. IT-Centric Approach. Just because data is related to the IT department, it does not necessarily mean that they own it. Building a data culture signifies that all departments and not exclusively the IT guys should be able to utilize the data in their own way.
C. Data boredom. Raw data might seem useless and boring. Proper data-crunching and creative story-telling with data can make it impactful. It will help end-users clients to understand and expand their business, improving on their strategy.
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Improving on the Culture
Almost all organizations, small or big, have the ability to create and improve on data culture. This is done by focusing on the following ways:
A. Being creative about metrics. In order to be successful, institutions and organizations should be creative with the measurement. Understanding the business problem, interpreting the data correctly is necessary. Every parameter needs to kept track of, in order to get proper results. Today, we know that data is like crude oil. The more we refine it, the more its value increases.
B. Discovering dark data. The data which remains unused, unanalyzed and unstudied can be defined as the dark data. It can be found in the past records, in messy or unstructured data or even in the dark web. If these data can be utilized, then also some meaningful patterns and trends can be found.
C. Preserving the data. Every organization collects data in some way or the other. Data can be impactful to such extent was unknown earlier. Thus, storage of data wasn’t of much significance. Apart from analysis, data storage is given equal or more importance. Privacy of data is very important. We must ensure that there is no leakage.
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Cultural change in any aspect is difficult. Data-driven cultural change will also take some time to inculcate. It will be easy and smooth if every departments of the workplace gets involved in its functioning. Trust within employees, data literacy and powerful leaders go a long way to propel data-driven culture forward.
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