Thank you. Identity resolution and consolidation is super important and not talked about enough considering its wide surface area for potentially occurring in any organization's records.
Take your point about business-calibrated cutoffs one step further. Identity doesn't have one resolved state. Two records that are the same person for a marketing audience can be different people for a compliance audit. The three layers resolve that mechanically. Where to draw the line, they can't. The cost of a false merge versus a false split is a business call that shifts by decision. In most orgs no one owns that call. That's why identity stays unresolved, long before the ML gets hard.
The customer who is three people and one ghost is the whole problem in one sentence. A data contract validates each product at its own output port. Identity lives across products, so no single contract owns it. That makes resolution a trust contract, not a quality check. Same person, and the stack can't agree. Customer product says Jennifer Park, transactions say Jennifer Kowalski, the agent counts three. Which layer reconciles that?
Thank you. Identity resolution and consolidation is super important and not talked about enough considering its wide surface area for potentially occurring in any organization's records.
Take your point about business-calibrated cutoffs one step further. Identity doesn't have one resolved state. Two records that are the same person for a marketing audience can be different people for a compliance audit. The three layers resolve that mechanically. Where to draw the line, they can't. The cost of a false merge versus a false split is a business call that shifts by decision. In most orgs no one owns that call. That's why identity stays unresolved, long before the ML gets hard.
The customer who is three people and one ghost is the whole problem in one sentence. A data contract validates each product at its own output port. Identity lives across products, so no single contract owns it. That makes resolution a trust contract, not a quality check. Same person, and the stack can't agree. Customer product says Jennifer Park, transactions say Jennifer Kowalski, the agent counts three. Which layer reconciles that?