Definition
TVO (Total Value Optimization)
Maine Pointe's methodology for synchronizing the buy, make, move, and fulfill stages of a supply chain.
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Related terms in Product & Engineering
Tier One SupplierA component manufacturer that supplies directly to a system integrator or OEM, rather than building the end product. Seven Sense positioned itself as a tier one supplier of sensing and compute to robot manufacturers — selling into the entire market rather than betting on one product category.Time to InsightThe elapsed time between a business question being asked and a reliable, actionable answer being available. AI analysts reduce this from days to under 90 seconds.TolerancesThe permitted variation in a part's dimensions. Tight tolerances mean parts fit consistently across thousands of units.TolerancingSpecifying how precise a dimension must be. Over-tolerancing — tighter than necessary — makes parts exponentially more expensive. It is one of the most common avoidable cost drivers in hardware design.Two-phase alarmLoftie's signature: a soft first phase that fades after 30 seconds, then a fuller second phase three, six, or nine minutes later.UCP (Universal Commerce Protocol)An open standard co-developed by Shopify and Google, announced January 2026, covering the full agent shopping journey from discovery through post-purchase.UI-Less Product DesignA design philosophy that removes the graphical user interface as the primary interaction layer, replacing it with ambient or conversational channels such as phone calls, SMS, or voice. The goal is to eliminate the friction of app-opening - the user never has to navigate to the product for it to deliver value. The tradeoff is reduced user control and configuration surface area. Products built on this model succeed when the value is primarily in the delivery (the call happening) rather than in user-initiated sessions. Commitify's voice accountability model is a direct application: the product arrives as a phone call with no app required.Unstructured DataInformation that does not conform to a predefined data model or schema, making it difficult to store, search, and analyze using traditional relational database tools. Approximately 90% of enterprise data is unstructured. Examples: text documents, PDFs, emails, images, audio and video recordings, scanned forms, contracts, and presentation files. Unstructured data contains enormous amounts of organizational knowledge but is largely inaccessible to automated systems without a preprocessing step that extracts structure from it. Mehul Shah at Aryn distinguishes this from the 'rooms stacked full of papers' metaphor: most enterprises have moved past physical paper but the digital equivalent - files scattered across SharePoint, cloud drives, legacy databases, and email systems - presents the same fundamental access problem.