Adoption is architecture: Data-quality ownership
Why this deserves attention
Data quality is an operating responsibility supported by technology, not a cleanup project owned only by administrators. A sound design makes this explicit before implementation begins.
Validation rules alone cannot resolve unclear definitions, missing accountability or incentives that reward incomplete capture. On 31 January 2026, this archive entry records the principle as a practical design concern rather than a product announcement.
Design the human system
Look at data-quality ownership through how the user experience and operating model determine whether the capability is used. The objective is not to introduce more process; it is to expose the few decisions that determine reliability, ownership and future change.
Define critical data elements, assign owners, measure defects at source and make correction part of normal work. Record the decision close to the solution so that delivery, support and future architecture reviews work from the same intent.
What good looks like
Reporting and automation rest on information the business is prepared to defend. The team can describe the expected behaviour, the owner, the evidence of success and the response when reality differs from the design.
A useful next step is to review one live implementation against this principle, identify the largest unowned assumption and turn it into a bounded improvement with a measurable outcome.
Official reference
Salesforce Architecture: Integration Patterns