Flat per-hub pricing assumes every production hub solves the same operational problem. A 25-year-old high-pressure Gulf field and a three-year-old subsea development do not solve the same problem.
At a major global deepwater operator with 70+ production hubs spanning the Gulf of Mexico, West Africa, Australia, and the Middle East, the pricing question wasn’t “how much per hub?” It was “what does this software do differently across asset ages?” Older fields focus on integrity and predictive maintenance. Newer fields drive optimization and cost control. The software value is not identical.
When you price every hub the same, you’re either overcharging the operator for the low-value asset class or underpricing the high-value one. The buyer will sense this misalignment before you do.
The answer is to make the pricing model transparent about what you’re actually delivering at each asset stage. Clarity on value by asset class beats a lower price that masks the misalignment.
Field-age tiers force the conversation
A tiered pricing structure (fields <10 years, 10-20 years, >20 years) made the value case explicit. A three-year-old field with immature subsurface data needed data integration and systems connectivity. A 20-year-old field with decades of operational history needed pattern analysis and anomaly detection. Same platform, different problems, different value.
The model was tested across two commercial scenarios. All-In onboarding: board all 70 hubs in 2025 at a single price per hub across all age cohorts. The appeal is simplicity. The risk is that one side of the portfolio feels overcharged. Step-Up onboarding: bring in hubs gradually (4, 8, 16, 32, 70 over five years) with field-age tiers and stepped pricing that increases as data matures and the operator’s return accelerates.
The scenarios weren’t abstract. They were modeled across named hubs: Anchor and Tahiti in the Gulf, Mafumeira Sul and the Sanha Complex in Angola, Wheatstone in Australia, Leviathan in Israel. Per-hub value reached $1 million annually once the system was live, driven by reduced unplanned downtime and faster operational decisions. The two paths to get there were different in structure and in how they deployed capital.
What changed in the room
When field-age tiers are explicit, the account executive stops negotiating the price and starts discussing the buyer’s readiness for each asset class. Instead of “Can you lower this number?”, the conversation becomes “Which asset classes should we prioritize in Year 1?” The buyer owns the sequencing decision.
The value model quantified what happened when you got the sequencing right. Running Cost Assist integrations inside a digital twin gave the operator earlier cost confidence for new developments. Publishing operations data to a unified system kept maintenance crews aligned. The patterns that mattered were measurable. The tiers forced the model to show where the ROI actually came from.
This works because tiered pricing is not a tool for capturing more value. It’s a tool for showing where the value is. The buyer benefits from the clarity. The seller benefits from a defensible explanation of what costs what and why.
The metadata requirement
Field-age tiering assumes you can reliably classify assets by their operational profile. In a portfolio with clean subsurface data and current metadata, this is straightforward. In a legacy portfolio with spotty asset classification or outdated production histories, tier assignment becomes fuzzy. The cleaner the operator’s asset metadata, the sharper the tiers can be.
This is a real constraint. Not all portfolios have the data hygiene required for precise tier assignment. If you cannot confidently classify an asset into a tier, the model breaks. Worth documenting upfront.
The alternative is to keep pricing flat and let the buyer negotiate away the misalignment. That conversation happens anyway. The tiered model just makes it visible earlier and shifts the negotiation from “Is this price fair?” to “Which assets matter most to your operations?” That is the outcome.
