Make Good Data Great: Building A Data Strategy Roadmap

Every company already utilizes data to some degree. However, capabilities are often siloed by department and system. With a proper data strategy roadmap, data is utilized to move business initiatives forward and align with overarching goals.

So, how can you better harness data? Where should you start?

This blog will cover the foundational elements of a data strategy roadmap, so you get to a place where data is accessible to the organization and used to make informed business decisions that drive growth.

Here we go!

What is a Data Strategy Roadmap?

A data strategy roadmap is a strategic plan that outlines how an organization will harness its data to achieve specific business objectives. It serves as a compass, guiding your data initiatives toward business objectives.

A well-conceived data strategy enables companies to:

• Align with Business Goals: A roadmap ensures that your data initiatives are closely aligned with your overall business strategy. It connects the dots between data and organizational success.
• Effective Resource Allocation: By mapping out the journey, you can allocate resources effectively—whether it’s budget, talent, or technology. This prevents wasted efforts and maximizes impact.
• Measure Progress: A roadmap provides milestones and timelines, allowing you to track progress. It’s like a GPS for your data-driven transformation.
• Manage and Extend Relationships: Data can alert you to changes in customer behavior, such as declining sales at a retailer, allowing you to address issues proactively and maximize relationships.

A solid data strategy can provide a competitive edge for any business, regardless of size.

Do You Really Need a Data Strategy?

Ask yourself - “Are you deriving full value from your data and that to with no roadblocks?”

Over and over again research shows that most businesses are not confident when answering the above question. Or, you get different answers depending on the department. The truth is most companies fail to fully capitalize on the data they possess at some point in time. Valuable insights remain buried while decisions are made based on hunches rather than accurate facts.

Here are signs it’s time to take the next step and invest in a true data strategy:

• Fragmented data: Key business data lives in departmental silos. There is no "single source of truth" to enable enterprise analytics.
• Ad hoc architectures: Teams independently adopt SaaS point solutions. This leads to disconnected systems and data discrepancies.
• Lack of data ops: No consistent processes exist for managing and governing data as an enterprise asset. Data quality issues arise.
• One-size-fits-all strategy: It may be effective for a small size firm but for mid and large-scale companies, it will not suit. Different business units need tailored approaches aligned to a unified vision.

How to Create an Effective Data Strategy

Before diving into planning the how. You must start with determining the ‘why’. There are countless opportunities to better leverage data. Each business will be different. Start with finding the high-impact use cases that will get you organizational buy-in.

When you’re in planning phases of building the data strategy, ask yourself and the team these 6 questions before starting:

• What business objectives are we trying to achieve?
• What data do we currently have and what additional data do we need?
• What are our current data analytics capabilities?
• How will we measure the success of data initiatives?
• What data skills and resources will be required?
• How do data security, compliance, and privacy factor in?

Lewis Services, a vegetation management company, took a major step in their data journey by tackling their time entry and invoicing processes. They went from manually processing tens of thousands of spreadsheets to having a fully automated process with real-time information. This type of transformation touches everyone in the company and has inspired them to continue their data journey. Read their story

Re-evaluating these fundamentals aspects time to time keeps your strategy actionable. With a dynamic plan, companies can fully leverage data to drive decisions and growth.

Building a Data Strategy Roadmap Step by Step

1. Define business goals and data strategy objectives

• Outline 3-5 top-level business goals you want to achieve with data analytics (e.g. increase customer retention).
• Define specific, measurable objectives for your data strategy that will support those goals.

2. Assess current data footprint

• Document existing data sources, infrastructure, and capabilities.
• Identify strengths, weaknesses, gaps, and pain points.

3. Profile data stakeholders

• Identify key roles who manage, analyze, or consume data.
• Understand their needs, challenges, and pain points.

4. Develop data-focused strategic initiatives

• Based on goals and assessment, define key initiatives to enable goals (e.g. build data lake).

5. Create execution roadmap

• For each initiative, detail owners, timelines, milestones, and resources required.

6. Build in data governance and processes

• Develop frameworks for data governance, policies, quality, security, and compliance.

7. Plan for culture shift and adoption

• Enable training, communication, and change management.

8. Establish metrics and measure progress

• Define KPIs to track progress on roadmap and measure business impact.

Data Strategy Pitfalls and Mistakes to Avoid

When developing and implementing a data strategy roadmap, organizations often encounter various pitfalls and make mistakes that can hinder their progress and diminish the potential benefits. Here are some common pitfalls and mistakes to avoid:

• Lack of Executive Buy-in and Support – Data is everyone’s responsibility. To truly pivot that thinking requires a shift in culture which starts from the top. Failure to secure buy-in and active support from executive leadership can lead to inadequate resource allocation, lack of organizational alignment, and resistance to change.
• Siloed Approach and Lack of Collaboration – Developing the data strategy roadmap in isolation within a single department or team can result in a narrow perspective, overlooking interdependencies, and hampering organization-wide adoption.
• Underestimating Data Security and Privacy Risks – It is your responsibility to make sure data is secure wherever it goes. Failing to address data security and privacy concerns can expose the organization to legal and reputational risks, as well as potential data breaches and regulatory fines.
• Unrealistic Expectations and Timelines – A data strategy is a journey, not a destination. Make progress in manageable phases and measure results before moving to the next phase. Setting unrealistic expectations or overly ambitious timelines can lead to frustration, loss of momentum, and potential failure to achieve desired outcomes.

Crafting a data strategy roadmap may seem daunting and overly complex. Especially if you don’t have the internal skills and bandwidth to get it done. That’s where a partner like ProArch can help. Wherever you are on your data journey, our data analytics and AI services transforms data from a hurdle to an asset.