As your business scales, you’ll have to navigate more data. Creating a comprehensive data strategy is key to ensuring your company can successfully manage thousands — or millions — of data points.
You're not alone if you have questions or concerns about developing a data strategy. Creating a data strategy for your business isn’t as complicated as it seems. In this post, we’ll walk you through what data strategy is, why a data strategy framework is necessary, and how you can start creating your own.
- What is data strategy?
- Data Strategy Must-Haves
- Start Developing a Data Strategy
What is data strategy?
Data strategy offers a comprehensive and holistic vision of how a business handles data. It combines the key components of data lifecycle management — collection, storage, maintenance, usage, and cleaning — to create an integrated approach across all applications and teams. This helps to maintain accurate, consistent, and relevant data everywhere.
One sub-section of a data strategy is a data governance strategy, which helps an organization protect its data from inconsistency and inaccuracy.
Why is developing a data strategy important?
Developing a data strategy allows you to utilize the data your business has collected effectively. “You can have all the data in the world but without a solid data strategy you will never see value from that data,” says Tammy Duggan-Herd, Ph.D., Senior Manager, Data & Tools at HubSpot. In the absence of a robust data strategy, your business's data is essentially useless — a waste of resources.
Max Iskiev, Marketer Research Analyst at HubSpot, shares, “Data strategy is key to making informed business decisions. It allows you to track and evaluate your progress towards business goals and can help you figure out what is and isn't working.”
By creating a plan, you can ensure your company makes the most of its data, leading to better decision-making. And because data strategy offers a transparent view of performance, all departments across the organization can carry out their responsibilities more effectively. This will be possible because they understand how their work contributes to the company’s overall mission.
When should your business create a data strategy?
“Every business has data, no matter how big or small, so it’s never too early to create and document a data strategy,” shares Duggan-Herd. Regardless if your business is in its infancy or is well-established, it’ll benefit from a comprehensive data strategy plan. If you’re starting a new business, begin crafting your plan as early as possible. Alternatively, it's never too late to start if your company has been around for years.
Keep in mind that your data strategy plan should be a living document. Prepare to make updates when you add new applications to your business, and revisit it regularly. With a clear strategy for managing your data, it’s possible to optimize organizational performance. This works because your data strategy helps maintain:
- Reliable, accurate data
- Ethical use of data that adheres to data protection regulations
- Actionable, relevant reporting that can impact business decisions
- Only one version of data synced between all apps
The Components of a Data Strategy
Let’s walk through the critical elements of your data strategy. Having a plan puts your business in the best position to manage and optimize your data at every lifestyle stage.
When you create your data strategy framework, use these components to guide you.
- Data collection
- Data storage
- Data maintenance
- Data integration
- Data purging
- Data usage and reporting
First, let’s discuss data collection. Your data collection manner influences all of the following steps. It’s important you get this right early on. (Don’t worry, we created a guide to data collection that can help.)
After your company garners data, what does it do with it? That’s the question data storage seeks to answer. And, of course, don’t forget about maintenance to uphold the data’s integrity. A robust data governance strategy is also necessary.
The data lifestyle doesn’t end there, however. Eventually, your data may no longer be valuable or accurate. When this does occur, it’s time to complete the data purging process. If you skip this step, you risk it impacting the quality of your database, corrupting other data, or both. Plus, with data purging, you can ensure your data is clean and manageable.
Congratulations; once you’ve optimized these components, your business is in the best position to put your data to work, such as with data reporting.
You can check out our jargon-free explanation of data lifecycle management if you’d like to learn more about the data lifecycle.
Data Strategy Must-Haves
In addition to these essential data strategy framework components, there are other data strategy must-haves on an organizational level. Let’s dive into those.
A clear business strategy.
If your company doesn’t already have a clear business strategy, take a few steps back and begin there before diving into data. “Because your data strategy should reinforce and advance your overall business strategy, you need to start there,” says Duggan-Herd.
(Psst: If you need help creating your business strategy, start here.)
For a data strategy to succeed, executive leaders must be on board and comprehend its value. “To get buy-in from top-level organizational leaders you will need to clearly articulate how a data strategy will help the organization to meet its goals and objectives (i.e., align it to your business strategy),” says Duggan-Herd. “While earning buy-in often requires significant time and determination, the more people who participate in your strategy, the higher its chances of success.”
A commitment to your data strategy.
For your data strategy to be successful, your organization must decide who’s responsible for what. “Your strategy should make clear who does what with your organization’s data,” shares Duggan-Herd. “Your strategy should not only include roles for those whose primary responsibility is implementing and enforcing your data strategy (i.e., data engineers, data analysts, business managers) but anyone who uses data in any way (i.e., sales reps, account managers). You also want to specify who ‘owns’ each dataset and are therefore responsible for its storage, security, and interpretation.”
In addition to identifying directly responsible individuals (DRIs) who are committed to the data strategy, it’s equally crucial that the company is invested in it overall.
Iskiev shares, “You have to collect data consistently and accurately over a meaningful period of time for it to be useful. A week may not be enough time to measure the increase in brand awareness you got from your latest influencer marketing campaign, but you can gain meaningful insights from analyzing weekly follower/subscriber growth on your social accounts and tying it to your influencer marketing efforts.” Once you’ve successfully collected data, it’s equally important to store, maintain, and integrate it.
A commitment to data architecture and governance.
Without data architecture, it’s easy for data to get lost or wholly disregarded by mistake. According to Duggan-Herd, “A data architecture…documents how your data is managed and flows from initial collection to ingestion, storage, analysis, and consumption.” Data governance is also crucial as this ensures the data your organization uses is both secure and reliable.
Key Questions to Answer in Your Data Strategy
A successful strategy streamlines the process of data collection, maintenance, and use. Plus, you can rest assured that your operations are taking care of your data, so it’s reliable and secure.
Yes, crafting a data strategy framework (and enacting it) is a bit of a lift, but it will simplify everything. Plus, your business will make the most of its resources and can even save money in the long run. Regardless of your industry or your business size, it’s worth the effort to develop a data strategy. Answering these key questions will help set you up for success.
1. Which data is valuable to your organization?
Begin by identifying which data points are helpful for your organization. Once you do, you can determine what’s worth collecting in your lead generation forms and other channels you use to garner information.
Evaluate which of these general data types are helpful:
- Lead data
- Customer data
- Website data
- Social media data
- Product data
- Market data
2. How will you collect high-quality data?
Once you’ve decided which data points are helpful, you must ensure it’s high-quality. Dirty CRM data is worse than unhelpful; it could be harmful. Quality data is accurate, complete, relevant, consistent, accessible, and timely. You can harness it to make data-driven decisions to help your business reach its goals.
3. How will you store and maintain data securely?
Simply acquiring data isn’t enough; you must secure, analyze, and manage it. This falls under your data governance strategy, which is one critical portion of your overall data strategy. Don’t forget to select an adequate data storage solution.
4. How will you maintain a single source of truth in your data?
Data synchronization ensures alignment between apps. If disjointed, your data could do more harm than good. Think of data synchronization as connecting the dots between your apps — from your CRM to your automation software and accounting system. It also communicates data changes between them. With real-time updates, you’ll always have access to the cleanest, most up-to-date data. Plus, you won’t have to worry about pesky manual updates.
5. How will you remove low-quality or outdated data?
When we refer to ‘low-quality data,’ we’re talking about incorrect, expired, or otherwise corrupted data. Your strategy should determine:
- What qualifies as ‘bad data’ to your organization
- How you'll identify it (ideally with automated processes)
- How you’ll remove it
- When you will remove it
Here’s an example: You may create an automated list in your CRM that's populated with contacts with bounced email addresses. You can identify a DRI that reviews this list monthly and purges the contacts you're sure you don't need.
You should also decide how your company will navigate communication opt-outs and the process for removing a contact's data if requested.
6. How will you adhere to data protection regulations?
Data protection is relevant for every stage of the life cycle. For organizational compliance, your data must be secure by design. Data protection isn’t an afterthought — it should be intrinsic to your strategy. Get started in the right direction by following the other key steps on this list. GDPR compliance software and reading up on best practices can also help ensure your company ticks every box.
7. How will you use your data?
Organizations store data for one primary reason: To turn it into information. (No, data and information aren’t the same!) Data becomes information when it is processed, interpreted, and organized. Then, you can use the information to create insightful reporting dashboards, inform business decisions, and deliver optimized customer experiences.
Start Developing a Data Strategy
There’s never a wrong time to implement a more robust data strategy. Start by getting clear on how your organization collects, maintains, disregards, and uses data. You can also look at how other companies manage their data with data strategy examples to gain additional insight. As Iskiev says, “The world is changing rapidly, and data can help you understand your customers' shifting attitudes and habits. This will help you figure out how your business can meet their interests, solve their challenges, and/or fill their needs.”
Editor's note: This post was originally published in December 2020 and has been updated for comprehensiveness.