Build an effective data management strategy in 7 steps

Build an effective data management strategy in 7 steps

Data is necessary to stay competitive in today’s economy, but collecting, analyzing, and managing data is challenging. That’s why creating a strategy for managing data is one of the key principles of data management.

“A data management strategy is the foundation of any data management program,” writes Wes Flores, cofounder of business advisory company Simatree. “The strategy provides both the framework and the architecture that will last throughout the life of your program.”

The following seven steps are key to building an effective and lasting strategy for managing data.

1. Identify business objectives

Data can’t serve its purpose if business objectives don’t inform it. That’s why the first step in building a strategy is to explore business needs and challenges, and then use that information to define business objectives.

“By starting with a business objective, you can uncover the knowledge that your organization must build and cultivate,” writes Neal Fishman, distinguished engineer and CTO for data-based pathology at IBM.

To identify objectives, ask questions that explore the organization’s overall goals, the data needed to achieve those goals, and the insights needed to meet those objectives. Seek input from various stakeholders in the organization, and use that information to build a long-term strategy that addresses specific use cases to guide the organization.

2. Determine data requirements

What data is required to achieve the business goals, and where will you collect it? It’s important to answer both of these questions in the second step of creating a data management strategy.

The business goals will determine the type of data you need, most commonly, internal or external, structured or unstructured, or a combination of the two. The bigger issue will be locating and gathering the data once you identify it.

Create a framework to which you can add information. This helps identify missing data and provides a structured approach to data gathering, which is the next phase of this step. For example, website or social media analytics may provide the necessary information, or you may need to purchase it through a third-party provider.

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3. Create sustainable data processes

The next step in a comprehensive strategy is to develop processes for collecting, preparing, storing, and distributing data. Each of these processes is essential to ensuring an organization handles data consistently.

“Processes help us focus. They streamline our work. And they unite us towards a single goal,” writes Tina Rosario, chief data officer at SAP.

The keys to success when building these processes, notes Rosario, include ensuring all processes are user-friendly and timely, and have automation built in, where applicable. Assigning a “data steward” for each process is also important, she says, in order to balance the quantity and quality of data.

4. Establish data governance

Data governance is one of the most important elements of a data management strategy. As the volume of data available to an organization grows, how the organization handles it becomes crucial. “Data governance is necessary in order to handle data effectively and instill data quality across the organization,” writes Michael Ott, senior vice president at Innovative Systems, Inc.

Data governance policies and procedures address a variety of areas, including data quality, security, privacy, transparency, ethics, access, and ownership. Good governance policies ensure everyone in an organization uses the data properly. You should communicate these policies to everyone — not just those directly involved in data management.

5. Adopt the right technology

Having the right hardware and software is key for companies building a data management strategy. Technology is one of the core components of a successful strategy, writes Information Age’s Nick Ismail, because without it, an organization can’t properly collect or analyze data.

When building the strategy, organizations must evaluate their technological needs for collecting, storing, and analyzing data; then they need to communicate insights from that data. Tech tools can streamline the flow through each of these stages in the data process and ensure that parties get the information they need to drive their business decisions.

6. Build a knowledgeable team

A lack of knowledge by data owners is often an issue organizations face when executing a data management strategy. Company leaders need to provide opportunities for their teams to acquire the skills necessary to use data effectively.

How can companies build stronger data skills among their staff? Global industry analysts Josh Bersin, founder of Bersin by Deloitte, and Mark Zao-Sanders, CEO of Filtered, suggest that leaders make it a priority to ensure everyone knows how to properly use a company’s tools.

They should stress the value of improving data skills and foster a data-driven culture that embraces the use of data in all business decisions. In doing so, organizations will build more knowledgeable data teams that are capable of maximizing the benefits of a data management strategy.

7. Execute the strategy

The final step is actually implementing the data strategy. A key component here is identifying any potential roadblocks. Once you identify those, making specific changes necessary to overcome those problems is paramount, as is determining who will spearhead the changes. As company needs change over time, aspects of the strategy might change as well.

“The power of a data strategy is that it positions you to deliver the best possible solution as your organization’s needs grow and evolve,” writes the team at business analytics software vendor SAS. “Your data strategy is a road map and means for addressing both existing and future data management needs.”

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