Charting a Data-Driven Future: Set A Course To Accelerated Business Growth

Want more value from your data faster? A data strategy maps how to make informed decisions, develop competitive advantages, and identify new growth opportunities while accelerating your progress with the tools and data you already have.

A comprehensive data strategy begins with understanding the business objectives that need to be addressed and creating a plan to unlock the data you need to meet those objectives. Chart your course to data-driven business in four essential steps:

Step 1 – Find your North Star

What are you trying to achieve with your data, and what are your priorities?

To develop an effective data strategy, pinpoint the key areas where information is necessary for critical business decisions and identify the individuals involved. This initial step lays the foundation for success, ensuring that the correct data is in the hands of the right people at the right time.

  • What data do you need to meet your top business goals?
  • What drives the sales cycle and revenue generation?
  • What are your most significant cost drivers?
  • What insights do you need to make your operations or supply chain more efficient?
  • What are your most significant business risks, and how do you track them?

The answers to these questions quickly illuminate which data is most critical to meeting your business objectives. Knowing where the biggest need lies helps you decide what NOT to do and avoids wasted effort on lower impact work.

Step 2 – Map the Icebergs

How does data flow and change throughout your organization and systems?

Understanding where data comes from, how it changes throughout your organization, and how it is used helps focus data efforts and is the key to deriving value from data. Business process models uncover the source of critical data elements, highlight where data quality issues arise, and visualize conflicts in ownership and usage that lead to a need for data management.

Customer data is an example of where business process mapping can shed light on data gaps and data management needs. If customer data availability and accuracy are essential to your business goals, identify data gaps by understanding the source of customer information and how it is updated along the business process lifecycle. As you follow the flow of customer data, ask

  • Where is customer data generated, changed, and used?
  • Are all sources of customer data in sync? Or are there siloed and disjointed repositories of customer information?
  • If multiple departments use the same data source, is there transparent governance and ownership around how the data is sourced and updated?
  • Is customer data accessible when and where you need it to run your business?

Knowing where data obstacles lie is the starting point for a data management plan to navigate potential data hazards of incomplete, incorrect, or confusing data.

Step 3 – Chart the Course

What enablers do you already have that you can deploy more effectively and what are the gaps?

Data alone cannot get you where you need to be.

The ability to operationalize analytics is the key difference between companies that dabble in data versus those that win with data. Your data investments must include the infrastructure and organization to scale and maintain your analytics.

Look across your data ecosystem at the technology and organizational landscape. What data platforms, analytical tools, and skillsets do you need to accomplish your goals?

For example, will you rely on advanced analytical models? AI requires more than data scientists. All too often, powerful analytical models are built on manual data pipelines and poor-quality data and tools. Without the right tools, operating model, and data ecosystem, data scientists’ valuable time is consumed by sourcing, cleaning, and maintaining data pipelines instead of exploring new ideas.

Once you’ve identified your critical data, how it is generated, and how you plan to deploy it, you can focus your technology and governance investments for the highest impact to data quality and availability giving you the data foundation you need to meet your most important business challenges.

Step 4 – Full Speed Ahead

How can you move faster?

Building a competitive advantage with data will not happen overnight. Turning a ship takes time and investment. How can you justify the tenacity and endurance it takes to build a data driven culture and foundational technologies?

The steps above will help you find capabilities that can be redeployed quickly by uncovering existing assets that can be used to better effect. As you build your long term data strategy, you will also learn what data, tools, and skillsets you can unleash immediately. With creativity and the right skills, you can achieve more than you think with what you already have.

In Summary

Data strategy charts the course to using the data you have to its fullest potential and to building a sustained advantage through focused investments in tools and capabilities.

As illustrated in the four steps, understanding your core objectives, knowing the flow and sources of your data, ensuring the right enablers are in place, and having the agility to pivot swiftly can make the difference between merely having data and truly harnessing its potential.


Leslie Thomas

Solution Manager, Data & Analytics

Bryant Griffith

Senior Solution Director, Data & Analytics

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