Procurement teams are being asked a harder question than they used to. Not only what does this cost, but what will it cost to own, and what will it actually do once it is running?
For IT hardware, the honest answer has usually arrived after the contract is signed. A digital twin moves that answer to before.
What a digital twin is
In IT, a digital twin is a model of your estate that behaves the way your real estate behaves. You can change it, run options through it and compare the results without touching a live system or committing a penny.
The quality of a twin depends entirely on what sits underneath it. A model built on thin data gives you thin answers, confident on screen, unreliable in the real world. A model built on real measured performance, across a large enough dataset, tells you what the hardware will actually do. The more measured data underneath it, the closer the twin behaves to reality.
What it isn't
A digital twin is not a 3D rendering of a data hall, and it is not a spreadsheet with a few assumptions in it. It is also not a replacement for engineering judgement. It gives that judgement evidence to work with.
Why procurement is paying attention
Total cost of ownership has become one of the biggest drivers in IT purchasing. Energy costs, carbon reporting, space and the pace of hardware change all make the cheapest bid a risky place to start. Procurement leaders want to validate a decision well before they commit to it.
Simulation lets them do that. Model each option against how the estate really behaves, compare them like for like, and go into negotiation knowing what each one will deliver.
A worked example
One healthcare provider received six proposals for the same server and storage refresh, with a 250% gap between the cheapest and the most expensive. Without a technical benchmark, nobody could say whether the low bids would under provision or the high ones were inflated.
The organisation baselined its estate first, including forecast data growth and the seasonal peaks healthcare has to plan for. It then ran all six proposals through a digital twin against real peak loads, with vendor names removed.
Four bids fell away, including one of the most expensive. Two met the requirement, and energy and carbon came down 34%. Procurement went into negotiation with evidence rather than instinct.
Measured first, then modelled
Interact's digital twin is built on nine years of measured server data, across more than 500 data centres. That is what lets Interact Verify return a right-sizing solution, a platform comparison or a compliance position in minutes.
It is also the principle the wider industry is now formalising. Interact's Stephen Clement is a lead author of the Open Compute Project's white paper Digital Twins for Data Centers, and Co-Chair of the OCP Digital Twin Strategic Initiative, working alongside authors from NVIDIA, Cadence and Dassault Systemes. The paper sets a shared definition for what a digital twin actually is, and makes the same point this one does: a twin is only ever as useful as the measured data underneath it. It features a hardware-refresh case study powered by Interact, showing a digital twin turning a refresh into a circular, evidenced decision.
If a refresh, consolidation or migration is on your list, start with the evidence. Buy a simulation at interactdc.com/buy-a-simulation, or read the full healthcare case study at interactdc.com/case-studies/healthcare-procurement.