The rule
Spend data gave you coverage. Activity data gives you accuracy. You only need accuracy where the numbers are big. A category worth 0.3% of your total does not repay a week of chasing. Getting it perfectly right changes your footprint by a rounding error. Meanwhile the category worth 40% is still running on an industry average that cannot see your actual suppliers.What upgrading means
Replacing dollars with physical quantities:
Full detail on each in the organisation data checklist.
Do it in this order
1
Energy and fuel first
Electricity, gas, and vehicle fuel. Few documents, usually one or two people hold them, and they convert your least reliable estimates into measured figures. This is the highest return per email you will send.
2
Then your top three from lesson 3
Whatever the rough pass told you. If travel is one of them, ask your agent for leg-level data rather than a spend summary. If purchased services is one, look for the few suppliers who publish real figures.
3
Stop
Genuinely stop. Everything else stays spend-based this year and that is a complete, standard-compliant position.
When you swap spend for activity data
Two things to watch, because both quietly break the number. Remove the matching spend. If you enter electricity as kWh and the ledger still contains payments to your retailer, that electricity is counted twice and your Scope 2 roughly doubles. Expect the number to move. Sometimes a lot. An industry average replaced by your actual consumption can go either way, and a category getting bigger after an upgrade is not a mistake. It means the estimate was low.What to do about what does not arrive
Some requests will not come back. Estimate from the best proxy you have, a comparable site, a comparable period, floor area, or headcount. Then write down what you estimated, the method, and why the real figure was unavailable. A documented estimate is accepted practice under every standard. A blank is not, because a blank reads as zero, and zero claims those emissions do not exist.You are done when
- Your three largest categories are on real measured data
- The matching spend has been removed wherever you upgraded
- Every remaining estimate has its method written next to it
- You have deliberately left the long tail alone