Plan Your Modern Data Management Strategy: Part One — Strategy

Throughout the last decade, data’s influence and impact on top-line revenue has skyrocketed – just look at tech giants Meta, Google and Amazon. Every day they mine your digital data and extract sensitive information and personal preferences to better understand your habits. Then, they put that customer data to work, using it to fuel key business decisions.

An article published by The Economist, aptly titled “The world’s most valuable resource is no longer oil, but data,” speaks to data’s increased value. However, the article emphasizes that much like oil in its crude form, raw data is nearly useless until it’s refined. 

This means businesses must establish a method for “refining” data and invest in personnel to oversee the process of transforming data into valuable assets. 

We’ve put together a handful of activities to guide your organization in the data transformation process, including data transformation tools you can use. However, these steps can expose several challenges for organizations, including:

  • Centralizing data from disparate or siloed sources
  • Understanding the format  and accessibility of existing data
  • Identifying a consistent structure for ingested data
  • Establishing standards and rules for data transformation to realize value of existing/future data

This four-part blog series takes you through the journey of modern data management by diving into its four phases: Strategy, Discover, Implement and Monitor. Together, these phases create a roadmap for transforming your data into quality assets. 

We begin with the Strategy phase. Below, you’ll learn how to create a strong foundation and strategy for your data management program. 

These foundational elements and activities are essential to establish a data strategy and strong data management program.

Phase One: Strategy

When it comes to data management projects and implementing a data management process, there’s a common misstep. It’s easy to immediately jump into processing existing data without clearly understanding its business value. This often results in redundant work, constant revisions and a chaotic production-support process. By taking the time to understand the business strategies and objectives, you can align data and processes to help achieve those goals.

Activities

The following activities will help build a successful strategy with your executive, business unit, technology and data leaders.

Write a Data Vision Statement

  1. Interview your leadership team to understand the current business strategies and goals. 
  2. Ask questions about which business practices or data metrics work toward your organization’s goals and which don’t.
  3. Ensure you understand what your organization needs from a data perspective.
  4. Construct your data vision statement to clearly explain what you want to achieve, why it’s important and how it will help the business. 

Vision Statement Example: Provide self-service capability to users for the high-quality data they need, when they need it, to increase customer satisfaction.

Identify Key Data Governance Components

It’s important to identify which data governance components are most important to execute your data vision statement. 

Data governance comprises data policies, data security, data architecture, data stewards, data quality, data catalog, master data, reference data, metadata and change management. 

For our vision statement example, the significant data governance components would be data quality, data catalog, data policies and security.

Assess Data Maturity Level

A data maturity assessment measures how effectively an organization uses its data. A significant benefit of assessing data maturity is that it can consistently measure the state of a program over time. It can also influence the strategic data direction of your organization.

The Stanford Maturity Measurement Tool offers a robust qualitative assessment along with quantitative measures. Once the initial assessment is complete, set a target goal for data maturity based on the data maturity model, then reassess periodically.

Data maturity assessment baseline with target goal

Build Operating Model

Operating models consist of people, their roles and an escalation path in data management and governance. You’ll need to determine who is accountable for data activities and analyzing data, who owns the data and how to escalate when you encounter issues.

Operating model

Document Data Policies and Standards

Identify relevant privacy policies and data standards. You may need to consult your legal department during this phase. Document each item with a description, benefits, risks and main data stewards. It’s important to understand why a policy is required and the risk factors for non-compliance. It’s also crucial to determine how to monitor compliance and how non-compliance can be identified, reported and rectified.

Determine Technology Strategy

High-level technology strategy needs to be determined early on to develop the ideal data structure of the future. Strategies include:

  • Data Platform: Single cloud platform, multi-cloud platform, hybrid platform
  • Data Storage: Data warehousing, data lake, traditional database
  • Analytics Platform: Artificial intelligence (AI), machine learning, insight capabilities

Deliverables

From the activities above, you should be able to deliver:

  • Data vision statement
  • Data maturity level for the organization
  • Operating model
  • Data policies and standards
  • Technology strategy

Conclusion

This blog has laid out how to create a data strategy to help your organization achieve business goals. A complete strategy should consider data policies and standards, as well as who will be responsible to execute the strategy. The last key to success is to continuously communicate the importance of data across the organization.

Read the second installment of our data management strategy blog series on the Discovery process here.

Read more

Are you ready to start your data management journey?

Contact us today

Sun Jang is a Principal Architect at 27Global. Founded in 2008, 27Global designs, builds, and operates technology solutions for businesses of all sizes. The perfect pairing of a local leadership with offshore pricing, 27Global has the business acumen to understand your vision and the expertise to build your technology solution. To learn more, visit 27global.com or connect with us on LinkedIn and Twitter.

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