DACS EXECUTIVE BRIEF
Your systems produced the answer. Can you defend the decision?
Why Defensible Analytics Requires More Than Data, AI, and Governance
Most organizations can explain how data, analytics, AI, and automated processes contributed to a major business decision. The harder question is whether the information supporting that decision was appropriate, sufficiently verified, and authorized for that specific use.
If the organization cannot demonstrate that basis, it may face repeated reconciliation, costly investigations, unresolved exceptions, delayed AI initiatives, and decisions that are difficult to defend when challenged.
THE EXECUTIVE OPPORTUNITY
DACS offers a practical way to identify these gaps before they create larger consequences - without asking leadership to replace its technology or commit to an enterprise-wide program.
THE LIMITED REQUEST
Consider authorizing Day One of a DACS First Look for one important decision. Require useful findings at the end of that day. Continue only when the evidence supports further work, with a maximum of five business days.
For executive sponsor review | Editorial revision for DVA approval
Founding authors and committee leads: Daniel Linstedt, CEO, and Cindi Meyersohn, Chief Operating Officer, DataVaultAlliance Holdings LLC.
Official publications: https://dacs.datavaultalliance.com/documents/executive-brief
DataVaultAlliance maintains the authoritative DACS Specification. Verify the current approved version before relying on a redistributed copy.
1 The leadership question
A report can be numerically accurate, an AI recommendation can look reasonable, and an automated process can run exactly as designed. Yet none of those outcomes alone establishes that the supporting information was suitable for the business decision or that its use was authorized.
Consider a familiar example. Finance counts active billable accounts; Operations counts households receiving service. Both counts may be accurate for their respective purposes. If leadership approves an investment using a customer-growth measure, which definition was appropriate for that decision - and could the organization demonstrate why?
This is the DACS problem. It is not a claim that the reporting system failed. It is the possibility that information was relied upon for a consequential decision without an explicit, testable, and reconstructable basis for that use.
WHAT AN EXECUTIVE SHOULD BE ABLE TO ASK
What information did we use? What did it mean? Was it appropriate at that time? Who had authority to approve its use? What was uncertain or restricted? Could we demonstrate those answers months later?