Automation ROI

Executive summary of metering-fleet automation impact — coverage, data quality, savings across ten directions, ROI, TCO and payback.

A summary report for the head of a utility (resource-supplying) company or an investor. It answers five questions in a single document: what in the metering fleet is automated, how well it works, how much money it brings, what gets in the way, and what to do next. Written for people without a technical background — the headline numbers are visible in 30 seconds, the details and caveats follow below.

This is a management assessment for decision-making (whether to expand the automation program, and by how much), not an accounting statement. Every figure is honestly tagged with a confidence level — see below.

What it shows

The report consists of seven blocks, top to bottom:

Block	What it contains and why
30-second summary	five headline numbers: fleet coverage, connection reliability, annual savings, return on investment (ROI), payback period
Infrastructure	which types of correctors are deployed in the fleet and in what condition — shows how homogeneous the fleet is
Telemetry quality	how reliably nodes come online and how clean their data is — the foundation of trust in all the figures
Economic effect	the main block: savings across 10 directions, grouped by confidence level (see below)
Return and payback	ROI, payback period, total cost of ownership (TCO) over 5 years
Risk map	nodes and groups that need attention first
Problems and recommendations	what is critical, what is under observation, what can be improved

Three confidence levels for savings

This is the report’s key principle — it guards against inflated promises:

Confirmed (base) — a measurable effect on the fleet’s real data. Only this is used to build the payback and ROI calculation.
Scenario — a model estimate based on industry norms, requiring verification against a specific company’s accounting policy. Shown separately, not included in payback.
Possible (optional) — potential revenue if a condition is met, for example selling CO₂ credits. Counted only with a confirmed contract; disabled by default.

Ten directions of savings

Direction	Confidence	How it is calculated
Reading-collection visits	confirmed	remote reading removes regular crew visits: number of active nodes × visit cost
Prevented emergency visits	confirmed	early signals prevent some incidents: ≈0.4 incidents/node/year × cost of an urgent visit (×1.5)
Gas losses	confirmed	automation reduces losses by ≈2% of the fleet’s real annual volume × tariff
Office labor	confirmed	less manual entry and reconciliation: hours saved × engineer’s rate
Battery optimization	confirmed	scheduled replacement upon actual discharge instead of “just in case”: savings per node × active nodes
Reaction time	scenario	problems are found and fixed faster: hours saved × rate
Billing accuracy	scenario	less undercounting in bills (the same physical gas as in “Gas losses” — not double-counted)
Metrology	scenario	fewer unplanned verifications/calibrations thanks to data-quality control
Compliance	scenario	readiness for regulator inspections: estimate per node
CO₂ credits	possible	monetizing methane reduction — only with a carbon-market contract

Directions with a single physical source (gas losses, billing, CO₂ credits all sit on the same ≈2% of gas) are tagged as alternatives and enter the total only once — this eliminates triple-counting of the same money.

How it is calculated

First, “empty” nodes are filtered out — otherwise the total is overstated. A node is excluded if it has been offline for a long time, consumes almost nothing over the year (a dummy device), or does not provide a monthly consumption archive at all. Everything remaining is the live fleet, and the economics are calculated on it; the report shows how many nodes were filtered out and why.

Gas losses and billing are not calculated as “average consumption × number of nodes” — that is misleading, one plant equals a hundred apartments. The actual sum of real annual consumption from each node’s monthly archive is taken. If there is no data, the item is honestly tagged “no data” rather than filled in with an estimate.

Payback and ROI are calculated only from confirmed savings. The logic is simple: annual net benefit = confirmed savings minus annual maintenance; payback = investment ÷ net benefit × 12 months; ROI = net benefit ÷ investment. Scenario and possible effects do not participate in these numbers.

Connection quality is measured on a sample of nodes (200 by default) — for a fleet of a thousand nodes this is sufficient for a reliable estimate. Optionally, a short management summary written by AI can be added (it does not affect the calculations).

Run parameters

Parameter	Default	What it means
Period from / to	last 30 days	analysis window; for annual return, take a year
Nodes for connection assessment	200	how many nodes to poll for connection quality (0 = all)
Parallel fetch workers	4	lower to 2-4 on a download error (HTTP 429)
Cost per field crew visit	5000	price of one crew visit
Engineer hourly rate	500	for estimating labor savings
Gas tariff	6.95	gas price for losses and billing (per m³)
Cost per automation device (CAPEX)	30000	cost of one automation device (investment)
Subscription / OPEX per device	6000	annual maintenance of one device
Exclude long-silent, days	90	offline longer than N days → node not counted
Exclude micro-consumption, m³/year	50	consumption below N over the year → dummy device
Exclude without monthly archive	yes	nodes without a monthly archive are not counted
Display currency	RUB	RUB / USD / EUR / UZS / KZT / CNY
Exchange rates	default	can be overridden manually (JSON format)
CO₂ contract	no	enables the CO₂ credits block in the economics
AI executive summary	no	a short management summary written by AI
Utility company	from context	filter the fleet by resource-supplying company

How to read the result

Start with the 30-second summary: coverage, reliability, annual savings, return, payback. Then — the economic effect by direction.

What counts as good: ROI from 50% and a payback period up to 24 months is a strong argument for expanding the program. A negative ROI is a reason to reconsider maintenance costs or the fleet’s composition.

What to pay attention to:

Coverage decides everything. If less than 30% of the fleet is covered by data, the report is flagged as premature: first grow coverage, then count the money.
Look at which savings the conclusion rests on. Payback is calculated only from the confirmed part; scenario and possible are given for reference and require separate validation.
CO₂ credits are disabled by default and do not affect payback until a carbon-market contract is confirmed.

Typical questions to be ready for when defending before an investor: “why exactly this much savings” (the answer is in each row’s formula), “isn’t the same gas counted twice” (no — alternative rows are tagged and not summed), “what happens as the fleet grows” (the 5-year TCO shows recurring costs).