What is data integrity? How to achieve it?

Data & Reporting

Ensuring that your data is consistently reliable, complete, accessible, and securely stored—the true mark of data integrity—is no small task. After all, there are a number of forces working against you. Staff come and go. Integrations break. New data sources become available. And the list goes on and on.

We have the data, but we can’t rely on it because…

How often do staff make statements like this? If your company struggles with data integrity issues, it may be a more common occurrence than you think.

With today’s rapid pace of change and uncertain market conditions, staying ahead of data challenges can feel insurmountable. As a result, many businesses stop trying altogether and settle for data that’s “good enough.”

So, what’s your next move?

Is “good enough” data actually good enough? Or, is it time to take a more proactive approach toward achieving data integrity? If you’re tired of unreliable or downright bad data, the following tips should set you on a better path.

Achieving data integrity

As the old adage goes, “A journey of a thousand miles begins with a single step.” Achieving data integrity may seem like a massive undertaking, but getting started doesn’t have to be complicated.

1. Assess your greatest threats to data integrity

You can’t fix something unless you realize that it’s broken. Sure, your people are quick to express their skepticism about your data. But skepticism is a symptom of a much deeper problem. Start asking “why” questions and get to the root of your data integrity issues.

For example, why doesn’t your marketing team trust the open and click-through data in your email marketing system? Does a setting just need to be adjusted, or is the software incapable of providing better data? What do your users think? Dig deeper.

While you’re at it, ask team members to share any other data integrity challenges that they’re struggling to solve. Engage users to understand how data limitations inhibit operations and stifle decision-making. As new issues are surfaced, add cards to your data integrity kanban project board for future sequencing. Then, focus your efforts on the data integrity issues that, if solved, deliver the greatest impact for the least amount of effort and resources.

2. Look at your data more often

Data’s impact to your company is significantly reduced when it’s underutilized. Surprisingly, many companies make the mistake of rarely (or only occasionally) using data to inform their decisions.

Your CRM is, of course, an excellent platform for measuring sales output and pipeline value. But what about all of the other business intelligence data that goes unused? How often does someone within your organization review (and use) other data-driven insights housed within your CRM, such as:

  • Project and task throughput
  • Productivity by team member
  • MQL-to-SQL ratios
  • User activity in the system (or lack thereof)
  • Customer lifecycle data
  • Web-to-lead trends

Incorporating more data into your organization creates a virtuous cycle that naturally elevates data integrity. As data begins to influence more decisions, the desire for greater data integrity organically increases across the board. Your people will begin to ask their own “why” questions and seek out ways to overcome roadblocks.

3. Staff up with data experts

Not everyone in your organization is destined to be a data scientist, and that’s OK. As data becomes an integral part of your daily operations, however, you may need to bring on additional data-minded people to solve complex data integrity problems.

Recently, I was feeling frustrated by a client’s advertising campaign that seemed to be underperforming. No matter how I sliced and diced the data, my web analytics reports kept showing a low conversion rate—despite anecdotal client feedback that seemed fairly positive. After partnering with a data analytics expert to perform an in-depth review, we realized that a poorly written regular expression had artificially deflated my lead conversion data. In short, we had a data integrity issue that was only identifiable (and fixable) by working with a data expert.

So, who at your organization is a “data expert”?

If you don’t have any, now’s the time to start looking for at least a fractional resource.

4. Build data integrity into your way of doing things

Whether they’ll admit it or not, your users can be a major cause of data integrity issues. Errant data uploads, accidental record deletions, bad habits, and laziness can quickly erode the reliability of your corporate data.

As with any company-wide initiative, maintaining data integrity should be hardwired into your organization’s way of doing things. Here are a few ways to infuse data integrity best practices into your company culture:

  • Limit user access to only the systems and permissions they need to perform their jobs
  • Create work instructions and operating procedures for collecting and modifying data
  • Use out-of-the-box system functionality and limit custom fields whenever possible
  • Integrate data integrity into your onboarding process for new hires
  • Host regular training sessions to keep staff informed and committed
  • Establish clearly defined roles so everyone knows who is in charge of data uploads and integrations
  • Regularly solicit feedback from users to understand their data challenges
  • Make it easy for users to request custom BI dashboards and reports (if they are not permitted to build their own)
  • Identify and monitor data integrity metrics to proactively resolve issues
  • Appoint a data integrity manager, who will own data integrity at your organization

5. Simplify when possible

Maintaining data integrity is especially difficult when silos exist or integrations keep breaking. As cloud-native solutions continue to advance and evolve, you may be surprised by the amount of system overlap in your tech stack.

Look for ways to simplify your data infrastructure. Do you really need a separate system to send out your monthly newsletter when your CRM offers the same functionality? Could a unified system be more cost-effective—and better from a data integrity standpoint, too?

Ask tough questions. Challenge the status quo. Be an advocate for data integrity.

Data integrity as part of your strategy

No doubt, data will continue to play an increasing role in every aspect of business. Therefore, smart organizations remain laser-focused on maximizing data integrity. And, as we’ve explored in this post, achieving data integrity is not a “check the box” proposition. It takes a long-term perspective and a commitment from every user and team.

Looking for more real-world examples? Check out this data management guide to see how six midsize companies leveraged modern technology and processes to overcome their data integrity issues.

Ready to explore a unified CRM that can help you better manage customer data throughout the entire customer journey? Request a free demo and needs assessment with the Insightly team.


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