Why Ongoing Data Maintenance Is Critical for an Outcome‑Driven Enterprise Data Strategy

As part of the enterprise data strategy series, this article explores the importance of leadership and accountability in guiding an overall data strategy that is tied to business outcomes.

People are being relocated, transferred, and changing jobs; companies go bankrupt and merge; email addresses change. If you have data, it will decay – that’s a given. In fact, 94% of enterprises suspect their customer and prospect data is inaccurate (Zoomdata). Yet continuous data maintenance is the most easily overlooked aspect of a results‑driven enterprise data strategy.

That’s why, in the fourth part of our data strategy series, I will dive deep into continuous, proactive maintenance: why it matters, what it includes, and how to get started.

Why Ongoing Data Maintenance Is Important?

If the quality is poor, data provides no benefit; it is worthless and can be costly. Gartner reports that poor data quality causes enterprises to lose an average of $15 million per year, and as information environments become more complex, the problem may worsen—a challenge faced by organizations of all sizes.

When building an analytics platform or moving data from legacy systems to new solutions, companies often invest heavily in analyzing, cleaning, and enriching data. However, building a continuously online data‑maintenance capability is frequently ignored, even though change is inevitable, making it a risky proposition.

Crucially, your outcome‑driven enterprise data strategy defines how you will continuously manage the company’s most critical data, especially:

Data‑quality business rules and data operations

Data‑maintenance shared services

Service‑level agreements (SLAs)

Required data‑maintenance processes and key performance indicators (KPIs)

Ownership responsibilities

What Are the Keys to Success?

The first key to success is ensuring your maintenance plan is proactive, coordinated, and always effective. Automation is recommended, but you still need accountable business and IT owners who are responsible for:

Creating and updating business rules

Reviewing current data operations and quality reports for issues that need to be addressed

Establishing remediation for discovered problems

What Is a “Problem”?

The biggest problem is assuming that if you give people tools, they will keep their data clean. This rarely happens unless they have a motivation, such as payroll or invoice payments that depend on accurate information. Even when they maintain required fields, other critical fields may be ignored because they are less important to the individual.

For example, employees usually keep their bank information up‑to‑date, but may not update their business unit; sales managers may be motivated to maintain billing contact information but not shipping address details. This is why responsible business and IT owners are needed to oversee the effort.

How Do You Get Started?

When you established business rules in the organization and governance part of the data strategy, you already did a lot of work. Many of the rules created for preparing large‑project data are the same as those that should be used when maintaining fields.

The second thing you should do is turn your workflow‑based system into a proactive, always‑on process. What’s the difference? A workflow‑based system requires a workflow to run before anything happens. In contrast, an always‑online process has a program that runs monthly or yearly to perform tasks such as email verification.

Building this approach requires a mindset shift. We tend to assume people keep all their accounts clean everywhere, but do you update your phone number, address, title, etc., everywhere? Probably not. That’s why tools and workflows alone are insufficient to prevent data decay. As part of the overall data strategy, you need a continuous, proactive data‑maintenance plan.

Original article: https://www.digitalistmag.com/cio-knowledge/2019/06/13/outcome-driven-enterprise-data-strategy-ongoing-data-maintenance-06199003

Full text: http://jiagoushi.pro/outcome-driven-enterprise-data-strategy-ongoing-data-maintenance

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