6 Tips To Build A Strong Data Culture At Enterprises

6 Tips To Build A Strong Data Culture At Enterprises

December 26, 2018 0 By shopia wilson

Corporations have understood the value of data in improving their efficiency but most businesses feel that implementing software solutions and analytics tools completes the initiative. A strong data culture is not made of technology only but needs significant human involvement too. Enterprises need a data governance strategy for monitoring the whole initiative and make sure that their workforce is aware of the importance of information assets. Business owners have to lead the way by using data themselves for making key decisions. Only then the value of information assets will be understood by the rest of the staff members. Here are a few suggestions on how a data-centric environment can be created in enterprises.

1. Alignment Of Data With Business Goals

It is common knowledge that the identification of business objectives is necessary before starting a data management program. Data must be a part of all goal-oriented tasks whether it is the sales target or the project management objectives. Companies must establish metrics to track the performance of the different sections and measure the progress made towards achieving the goals. Incorporating analytics into the digital ecosystem of the organization is essential for the purpose. Recognize the specific needs of each section as only then the appropriate data elements, processes, and tools can be identified. Devising a framework based on the foundation of data will automatically ensure that the organization starts treating the end goals in specific figures rather than vague targets.

2. Select The Right Software Tools

Software solutions and tools are key components of any information management program. These tools help in the storage, transformation, sharing, and security of the assets. The organization depends on these solutions to assess the genuineness of information and ensure that they remain consistent throughout their stay at the enterprise. Choosing the right solutions that can add value to the analysis of information is essential. Another important factor to be considered while selecting these tools is the preparedness levels of the stakeholders who are going to work with them. A common cause of resistance to data is the inability of the workforce to work with complex solutions. The Information Technology personnel are capable of working with these applications but it is the business department which faces issues in getting familiar with the products. Try to adopt a middle of the road approach and choose efficient tools that are not too hard to comprehend so that they can be used easily by everyone.

3. Create A Data Dictionary

Data governance consulting experts insist on documenting all the processes involved in the program. They also advise that the manner in which data elements must be treated apart from the necessary steps that must be taken in the case of issues are also laid down in writing. Creating a data dictionary, therefore, is a logical step for making the staff members familiar with all the data fields and metrics. In absence of clearly-defined metrics, the same information will be interpreted differently by separate departments. A document must be created which contains precise definitions of all the key metrics. For this, discussions must be held with all the major stakeholders and data management experts to eliminate any doubt regarding the definitions. This will help remove any ambiguity in the interpretation of different elements and the metrics associated with them.

4. Make All Information Easily Accessible

For a strong data culture to exist in an organization, the information must be easily accessible by all stakeholders. People can very quickly lose interest in the initiative if they cannot get the element they are looking for, in time. This will also reduce the efficiency of the whole program. EIM consulting professionals suggest that even data of the highest quality will be rendered useless if it is not analyzed in time. Make sure that information is freely available to all authorized personnel at every level in the company. This will prevent the formation of data silos and the efforts of different sections will also be synchronized. The benefits of free-flow of information within the enterprise will be seen in improved collaborative efforts of the different teams and better workplace culture.

5. Make The Organization Data Literate

An enterprise can hire the best experts and employ the best tools to generate precise information but it will be of no use if its human resources do not have the necessary skills for managing it. Business owners must make every effort to make their organization data literate. They can devise specific training programs according to the roles and responsibilities of different personnel. A data can appear differently in diverse sets even if it concerns the same users and has been gathered over the same period of time. People working in the information management program must know about such details. Improved data literacy levels will have a direct impact on the efficiency of the initiative.

6. Incorporate Data In The Decision-making

The objective of having a data management program is to enable better decision making at the organization. Most of the time the top executives are not directly involved in the process. This is a big hindrance in creating a adat-centric environment at the company. The decision-makers must use the analyses generated from the evaluation of information to bring necessary changes to different business processes. There must be a data-enabled decision-making process in place so that the top-down effect can reach employees at lower levels.


Data has moved beyond being a simple reporting accessory and has become the key factor which dictates the path an organization must take to improve its performance. A strong data culture in which every employee understands the importance of information assets has, therefore, become a necessity for modern enterprises.

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