Mon. Sep 28th, 2020
How to create a data management strategy?

Have you ever wondered how ads on websites target their customer groups? Why you and your friend do not receive the same ad suggestions? Well, this customization of ads for specific customers is enabled through the collection and storing of data by organizations.

However, with the world turning into a global village through the digital revolution, the growing volume of data can often lead to problems, for organizations, especially if they do not treat data as a corporate asset that requires comprehensive strategy.

So, what exactly classifies as ‘data’? Data is raw or unorganized information that refers to or represents, conditions, ideas, or objects. So, for data to be useful, a strategically developed data management policy must be in place. Data Management Strategy refers to the development and execution of architectures, policies, practices, and procedures that properly manage the full data lifecycle needs of an enterprise. Studies suggest that effective data management strategies have revolutionized the way business is being conducted and positively impact productivity, growth, and innovation in organizations.



The primary objective of a Data Management Strategy is to help an organization gain the best benefits from its data assets while adhering to the relevant data privacy laws. Different teams within the same organization are often found to collect, create, store and manage their datasets. But data sharing within the organization leads to problems, due to the lack of standardized management practices. Effectively managed data helps to store, consume and process the data as required by the organization and thus save time.  Storing and sharing of data in internal platforms is an example of data management best practice. Secondly, effective data management helps in data integration by allowing easy access to data. It also aids Data integration, which helps in using tools for automation. Categorization and standardization of the data, using defined and known data classification and quality frameworks further helps in the effective use of data. Thirdly, data management strategies control, monitors and protects an organization’s data using data governance and security processes and policies.

How to Create a Data Management Strategy

There is no pre-defined rulebook for creating data management strategies. It varies depending on their size, infrastructure, budgets, geographic locations, etc. However, some of the proven and effective strategies for data management are discussed below:

Setting the Right Goals

Identifying the business goals that an organization aims to achieve is the first and foremost step towards developing a successful data management strategy. Establishing the primary goals along with the time frames for achieving each of them helps determine what is the nature of data to be focused upon, how will they be processed, utilized and stored.

 Finding the Right Data

‘Infobesity’ or information overload often makes it very difficult for an organization to effectively utilize information and convert them into usable information. It is important to identify the kind of data required – structured or unstructured data, or a combination of both. That would help in determining the source of the data (internal/external), whether the data is accessible easily and if not, what is the appropriate data collection method.

  • Data Governance

The global social media giant, Facebook was recently in the news for the alleged data security breach of its 2.45 bn users. Data security is an integral part of strategic data management as it protects employees and companies from various data losses, thefts, and breaches.

Data governance training of employees helps to effectively monitor data accuracy, data security, data privacy, data storage, and ownership issues. Ethical use of data and permissions related to data are defined by data governance policies, along with the implications for a data breach.

Well-devised data management policies further help in preventing potential cyber-attack and helps organizations comply with data laws and regulations, for example, GDPR.

 Technological Implications

After identifying the source and method of data collection, strategic decisions to identify the technology and infrastructure is very important. It helps in data analysis, through reporting and data visualization.

  • Establish a Data-Driven Culture

To manage organizational data effectively, complete adherence to the devised strategies and an ability to adapt to the changes is extremely important. Organizations that invest in imparting professional data management training to their employees have recorded a higher percentage of productivity and growth. Giving opportunities to employees to take their data-driven decisions independently will boost their confidence while working autonomously with different data types.

If employees do not have the required skill set, the Management must decide whether to train in-house staff or hire external experts to architect their data management strategies. A decision regarding the capital investment for training new skills and capacity must be determined. 

  • Implementation and change management issues

Regular testing of devised strategies is necessary to confirm if they can rapidly and productively collect valuable data to accurate conclusions is very necessary. Identifying the stakeholders for respective action plans, along with steps to fill the gaps in implementation is also important.

Data management strategies, if implemented successfully, can help organizations use their data as an asset rather than a liability.

By saahilk

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