# Teams that need an accurate picture of a data center Investors, OEMs, EPCs, utilities, operators, and public-impact teams face the same problem from different angles: the claims are loud, the evidence is scattered, and the wrong decision is expensive. ## Customer pain ### Data center challenges are massive Data center challenges show up as power constraints, water questions, community opposition, delayed projects, reliability risk, pursuit waste, and capital exposure. > “chips sitting in inventory that I can't plug in” ### Power constraints are now a board-level issue Satya Nadella used this phrase when discussing AI infrastructure constraints. ### Resource use can become the public issue A 100 MW hyperscale data center can consume about 530,000 gallons of water per day, roughly equivalent to 6,500 homes. ### Local acceptance is no longer automatic Gallup polling reported by technology press found broad opposition to nearby AI data centers, higher than opposition to nearby nuclear plants. ## Market opportunity ### Data center opportunities are massive too ### Global demand keeps rising IEA projects global data center electricity demand could reach about 945 TWh by 2030. ### Capital is moving into the sector McKinsey projects global data centers could require $6.7T in investment by 2030. ### U.S. electricity use could jump DOE/LBNL estimate U.S. data centers could use 325-580 TWh by 2028, up from 176 TWh in 2023. ### Scarcity rewards better screening CBRE reports North American vacancy at 1.6%, with 74.3% of capacity under construction already preleased. ## Cost of wrong decisions ### Lack of visibility leads to wrong decisions | Customer | Lack of Visibility Creates | What Goes Wrong | | --- | --- | --- | | Financial teams | Lack of Visibility Creates Capital moves before power, permits, sponsor evidence, or timing are sufficiently validated. | What Goes Wrong Overpaying, mispricing risk, weak covenants, delayed closing, or stranded exposure. | | OEM / EPC teams | Lack of Visibility Creates Pursuit teams chase announced MW instead of deliverable MW. | What Goes Wrong Wasted proposal effort, missed better accounts, mispriced risk, and reserved windows that do not convert. | | Utilities | Lack of Visibility Creates Load planning relies on unstable timing, unclear phase definitions, or optimistic owner claims. | What Goes Wrong Overbuilding, underbuilding, ratepayer tension, service disputes, or delayed upgrades. | | Operators and public reviewers | Lack of Visibility Creates Public, customer, or lease commitments harden before dependencies are visible. | What Goes Wrong Schedule resets, legal fights, community backlash, reliability events, or poor public decisions. | ### Local opposition can block real capital Fortune reported that at least 48 data center projects representing $156B were blocked or stalled by local opposition in 2025. ### Reliability failures are expensive Uptime Institute says one in five recent major outages reported by respondents cost more than $1M. ## Why this is hard ### Data centers are complex, dynamic, and hard to assess from outside **Delivery slippage** Can depend on interconnection status, substation work, transformers, generators, cooling systems, permits, tenant fit-out, and commissioning. **Investment return** Can depend on power price, capex per MW, lease timing, preleasing, tax incentives, water/cooling design, and customer demand at go-live. **Public approval** Can depend on water, emissions, noise, land use, jobs, tax base, ratepayer exposure, public records, and how credible the developer's claims are. **Outside-in gaps** Some variables are not directly observable. They need to be modeled, labeled with confidence, and checked by analysts and domain experts. ## Status Quo ### No good solution ### Internal functional teams Sales, business development, analysts, and strategy teams do one-off reality checks without dedicated data center evidence infrastructure. ### Generic SaaS dashboards Dashboards can show data, but they rarely combine evidence, confidence, hidden variables, and human judgment around a named decision. ### AI chatbots Chatbots are useful for exploration, but outputs are hard to reproduce, audit, refresh, or defend in a diligence conversation. ### Gut feel and relationships Experience matters, but intuition alone breaks down when power, permits, capital, community, and delivery timing all interact. ## Value of the Right Solution ### Accurate and up-to-date assessment prevents mistakes ### Faster decisions The right solution would reduce the time needed to collect, reconcile, and explain the evidence. ### Better use of capacity The right solution would help teams spend capital, engineering time, and pursuit effort where the evidence is strongest. ### Higher-confidence ROI The right solution would separate data centers with real deliverability from projects where the story is ahead of the facts. ### Sharper bids and terms The right solution would help teams price risk, structure commitments, and decide when to walk away. ### Less ad-hoc diligence The right solution would let sales, finance, strategy, and operations focus on their core work. ## Inventurist solution ### Data center reality delivered as a scorecard service Inventurist generates, updates, and interprets Data Center Scorecards for named campuses, phases, loads, accounts, and target data centers. The scorecard gives a repeatable assessment with evidence, confidence, gaps, and action guidance. ### Full-stack data Gather raw public and partner signals across power, permits, water, schedule, financing, demand, and local response. ### Auditable numbers Tie scorecard dimensions back to source evidence so the answer can be inspected and challenged. ### Humans in the loop Analysts check input quality and AI analysis before results are used for decisions. ### Expert judgment Domain experts review what the numbers mean and where the decision still needs validation. ## Bring us the data center decision you need to make Tell us the named data center, campus, phase, load, account, or target you want assessed. We will scope the scorecard around the evidence that can change the decision.