The visual user manual

One product, scored across five dimensions of sustainability.

A visual companion to the KPI List workbook — a product-focused catalogue of sustainability indicators. Raw measurements at the bottom flow upward and combine into a single composite Sustainability score. Explore the live hierarchy below.

The big picture

From five domains to one score

At the very top sits one number. It comes from five domains. Each domain breaks into sub-scores, and those into deeper scores, down to the raw data points someone must supply.

Sustainability
composite of the five domains
The domains are not fully separate. A few raw inputs feed parents in more than one domain, so the structure is really a network, not five isolated trees. The same measurement can affect several aspects of sustainability.
Interactive

Explore the hierarchy

This tree comes from the actual master catalogue. Pick a domain, expand the branches, and click any indicator to see what it measures, how the engine computes it, and the standards behind it. Grey leaves marked DATA are the raw numbers a company supplies.

◆
Select an indicator from the tree to see its full definition.
Structure

Five levels, colour-coded

Every indicator sits at one of five levels. Higher-level scores are darker. The Level-5 raw data points are the lightest grey, and those are the ones you supply numbers for.

The ID scheme

Each domain has a letter prefix. EN0 is the domain score. EN1, EN2… are Level-2 sub-scores. Add a digit per level down (EN11, EN131). Raw data points take a hyphen (EN1-1). The ID itself encodes the tree.

⚠ A naming collision to watch for

In Resource Efficiency the IDs R0–R9 look identical to the circular-economy R-principles R0–R9 (R2 = Reduce) in the glossary. They are completely different things. Always read R2 by context.

How it computes

Read top-down, calculate bottom-up

You read the tree top-down to understand it, but numbers flow upward. You supply the Level-5 raw data points. Each score combines its children and feeds its parent, up to the domain score and finally the composite.

A worked example: the carbon-footprint branch
The engine

Calculation strategies

Every row's Calculation Strategy says how the row produces its value. Leaves are raw values. Above them a row is either a score (always 0–1) or a raw total (a sum or formula in kg, €, …). The number on each card is how many indicators use that strategy.

Per-company settings

Weights & normalization

Weights sum to 1

When a score combines several children, a weight says how much each child counts. Under any one parent, the weights of all direct children should add up to 1, keeping every score on the same 0–1 scale. The template ships equal 1/N defaults, and each company overrides them. If a whole branch has no data, its weight effectively becomes 0, so the branch drops out instead of dragging the score down.

1 = good, 0 = bad everywhere. The page shows scores as a percentage of that 0–1 fraction.

Normalization & direction

Min-max normalization maps raw values to 0–1: (Value − Min) / (Max − Min). The workbook has no separate higher/lower switch. Whichever bound is larger sets the direction.

Higher is better

shares, ratings, efficiency
Min = worstMax = best
Min < Max (ascending band)

Lower is better

intensity, time, cost
Min = worstMax = best
Invert: set Min > Max
Mind the direction. For e.g. energy-per-unit where 25 kWh is worst and 0 is ideal, set Min = 25, Max = 0. A 5 kWh product then scores 0.8. An ordinary ascending band would score it backwards.
For practitioners

The recommended workflow

The key sequence: understand top-down → gather data first → set weights and min/max afterwards.

  1. Read the Overview & Top-Level sheets.Orient yourself: the goal, the structure, the R-principles, and what each of the five domains means.
  2. Pick a domain and read it top-down.Read from the Level-1 score down to the Level-5 raw data points to see why each input matters and where it fits.
  3. Identify the raw inputs you must supply.They are the grey Data? = x rows. The Metrics List sheet is the flat checklist of all of them, with links back to context.
  4. Gather the data first.Use each row's Unit, Data Source (often LCA) and Life-Cycle Stages to know what to measure — before worrying about weights.
  5. Then set the per-company values.Fill in Weights (sum to 1 under each parent) and the Target Min / Target Max reference values. Mind the direction for lower-is-better metrics.
  6. Consult the References as needed.To check the basis of any KPI, follow its Reference code to the References sheet.
Reference

Glossary

R-principles (R0–R9): the circular-economy hierarchy

CodePrincipleMeaning

Product Life-Cycle (PLC) stage codes

CodeStage

Method terms

Normalized: min-max scaling onto 0–1. Whichever bound is larger sets the direction.

Inflow / Outflow: quantity entering or leaving the process scope.

LCA: Life Cycle Assessment, a common data source (OpenLCA, GaBi).

LCC: Life Cycle Costing, the data source for monetary data.

Standards & frameworks: the bibliography behind the KPIs (search to filter)

LabelTypeDescription
For editors

The 22-column row reference

Each of the five domain sheets shares these 22 columns. The Metrics List sheet mirrors only the first 18 (it is a raw-row checklist) and drops the four per-company input columns.

Show all 22 columns
ColumnPurpose