Organizations want a solid and usable Data Strategy template – a well-thought-out plan for a set of decisions that form a pattern, charting a high-level course of action – but face challenges. For example, only 30% of companies have impactful data strategies that align with some operations, resulting in wasted investments in improving analytics and business insights.

Instead, most companies have managed data sporadically through disjointed strategies. For example, projects with more mature technologies or departments typically have more solidified data strategies, leading 59.4% of organizations to report successes.

However, without an overarching corporate Data Strategy, achievement becomes limited. Work activities tend to happen at cross purposes on projects with misaligned or no data strategies, which slows down the business. 

As Donna Burbank, the managing director of Global Data Strategy, stated in a recent webinar, business and data strategies are interdependent and closely related. When failing to coordinate business and data strategies, data remains in silos and becomes difficult to integrate into operations shared between different groups.

The result? Business operations generate unhelpful or unneeded products or services, and employees return to Excel spreadsheets, available at their fingertips, to get their work done. Creating a Data Strategy that aligns with the business efficiently means finding a systematic approach that works.

Data Strategy templates give companies a tried-and-true methodology when figuring out how to create or update an existing one to cover the entire business. While applying a Data Strategy template may not work for every company, it can start idea generation on how the business would like to approach such an endeavor.  This article will help organizations understand what a Data Strategy template can do and give examples to present for future planning meetings.

What Is a Data Strategy?

According to the DAMA International DMBoK, a Data Strategy describes a “set of choices and decisions that together chart a high-level course of action to achieve high-level goals.” This includes business plans to use their information to compete and support enterprise goals.

Burbank eloquently stated that a Data Strategy is:

“The opportunity to take your existing product line and market it better, develop it better, use it to improve customer service, or to get a 360-degree understanding of your customer. A Data Strategy is driven by your organization’s overall Business Strategy and business model.”

Data strategies benefit businesses by exploring the underlying relationships between the overall business, technology, and Data Strategy goals. Data Management activities stay on track using a Data Strategy that works for operations. Finally, a good Data Strategy provides good measurements.

Why Use a Data Strategy Template?

First, many companies may confuse Data Management (e.g., ensuring databases are running, technologies optimized, and smooth day-to-day operations) for a Data Strategy. As a result, businesses may not be thinking long-term and strategically in managing data, but instead, they may just be surviving because they get overwhelmed.

In addition, business contexts can quickly alter with the introduction of new technologies and marketplace pressures. As a result, the detailed Data Strategy six months ago may not be adequate. 

Consequently, an unstable framework that supports a Data Strategy starts to break down, especially with newer technologies. According to a KPMG study, 48% of corporate executives admitted that their Data Strategies fell significantly behind their digital transformation deployments. 

A Data Strategy must stay current for the entire organization to acquire, organize and analyze data to meet its business objectives. Moreover, as AI implementations grow in the marketplace, external customers will increasingly become interested in accessing other businesses’ data, and a good Data Strategy becomes more valuable to stay competitive with other offerings.

Data Strategy templates address these issues. First, they provide a place to start quickly without much effort and get to a well-thought-out plan. Next, Data Strategy templates can be reused and adapted to keep up with ever-changing business lines and goals. 

Also, with some guidance sooner, a manager can pay more attention to effectively implementing newer technologies and broaden how an organization can profit from its data. Finally, a template keeps Data Strategy planning from being too long or too short and in check with business strategies.

The Visual Presentation 

In her webinar, Burbank advocates using a visual presentation as a starting place to develop and communicate a Data Strategy. This imaging could take a proof-of-concept talk format using Adobe Slides, an online white paper, a skit, a combination of these, or any other creative medium.

She recommends considering a Data Strategy as a lever to achieve its objectives. For example, picture someone using a counterweight to move a boulder on a stone wall. 

Similarly, she considers how business data works as a fulcrum to support profitability and risk management. But, as she emphasizes, an organization must know the business objective and capabilities to pivot data well.

Once people know how business data works, they can fill in the details with her five-step Data Strategy creation or upgrade process. The steps are:

• Align the Business Strategy with the Data Strategy: Identify business goals and objectives needing data and match these to the Data Strategy. Consider five conceptual levels when completing this objective. See the figure below:

• Assess the Current State of Data Management: Understand the current maturity and environment. Then, if a Data Strategy exists, measure it to the business strategy. DATAVERSITY has tools to help with maturity assessments.
• Make the Business Case by Projecting ROI and Benefits: Generally, Burbank finds Data Strategy use cases fall into one of four categories: decreasing costs, increasing revenue, reducing risk, and protecting reputation. She recommends advocating for a Data Strategy using a combination of these rationales, with the risks of keeping to the status quo and not using the strategy.
• Future State Recommendation: Propose future state capabilities, processes, and organizational structure for how data activities will support business. In this step, connect Data Governance, a foundational pillar implemented by a Data Strategy, and map envisioned organizational capabilities, structures, and roles to Data Governance.
• Roadmap and Next Steps: Prioritize efforts and identify “quick wins” to get buy-in from stakeholders. Burbank provides a visual on how to get a good roadmap. 

Data Strategy Use Cases

Bernard Marr, a world-renowned futurist, influencer, and thought leader, suggests using a Data Strategy template based on business use cases. As a first step, fill out a Data Use Case Template (Figure 2). 

Marr recommends developing three to five use cases, including those identified as major or which take up more time and quick wins. The quick wins help demonstrate a Data Strategy’s value and get stakeholders’ buy-in.

He explains how to fill out the data use case template and the different sections on his blog. See a visual of his template below.

Fill out a new template for each separate use case and order each completed form in the priority to tackle first. To identify priorities and strategic components, use Marr’s Data Strategy Template.

Marr explains how to fill out his Data Strategy Template on his blog.

Data and Analytics Template: A Six-Step Approach

Gartner analysts created a data and analytics template focused on the data story and the audience. They suggest identifying and communicating the why (business objectives) and for whom (the stakeholders). 

Technology and architecture come later. See the graphic below:

Alan Duncan, a Gartner Distinguished VP Analyst, bases this data strategy template on explicitly developing the value proposition and hashing out the details with the SMART approach.

The end Data Strategy result gets buy-in from business investors, even when resources are tight. Additionally, it “sells” the data vision and strategy using measurable outcomes while handling push-back from skeptics.

Summary

Data Strategy templates provide a methodology for ensuring the data is aligned with business strategies. This reduces the tendency to create a document that no one will read – or not get started. 

However, one Data Strategy template does not fit all. This article has covered only three templates; others may be available.

Of the Data Strategy templates discussed, the visual presentation approach simplifies aligning data with business strategies and seeing the process unfold over time. It also provides an easy way to update existing data strategies and fill in missing conceptual pieces.

The Data Strategy template based on use cases is similar to using Agile sprints toward developing a larger software product. Still, instead of breaking each sprint into development goals, it chunks the larger Data Strategy. 

The six-step template, by Gartner, focuses on Data Strategy as a sellable product leading into immediate next actions. All approaches provide Data Strategy templates on hand to get started.

Image used under license from Shutterstock.com