How To Use Index

intermediate usage

slug: example-usage-how-to-use-index

The index step takes a measure's mean value and compares it to level=0 measure.mean.

• if they are equal, measure.index = 100
• if the measure.mean is 20% lower than the population's mean, then measure.index=80
• if the measure.mean is 50% higher than the population's mean, then measure.index=150

Usage

Input to the index step must always be a cube.

See the index step for more details.

Basic indexing against grand total

- index:
    dataset: salesCube
    measure: revenue
    metric: mean
    indexAgainst: level0
    significanceThreshold: 20
    includeComposition: true
    output: indexedSales

Index against parent level

- index:
    dataset: salesCube
    measure: margin
    metric: mean
    indexAgainst: parent
    significanceThreshold: 15
    output: parentIndexed

Index against specific baseline

- index:
    dataset: quarterlyCube
    measure: revenue
    metric: mean
    indexAgainst: custom
    baselineFilter: {quarter: "Q1-2024"}
    indexColumn: vsQ1Index
    output: quarterlyIndex

Multiple measures indexed

- index:
    dataset: salesCube
    measure: revenue
    metric: mean
    output: revenueIndexed

- index:
    dataset: revenueIndexed
    measure: margin
    metric: mean
    output: revenueAndMarginIndexed

Combine with pareto for powerful insights

Result: See which high-volume segments (pareto A) ALSO over-index on efficiency

- pareto:
    dataset: salesCube
    measure: revenue
    metric: sum
    level: 2
    output: paretoRanked

- index:
    dataset: paretoRanked
    measure: revenue
    metric: mean
    indexAgainst: level0
    output: paretoWithIndex

Metadata:

title: Index Analysis Step slug: index-step token: [generate with your base62 function] doc_type: step category: analytical_steps difficulty: beginner status: published tags: index,normalization,efficiency,affinity,benchmarking,targeting,over-index,under-index related_docs: ["pareto-step","contribution-step","index-analysis-topic-map"]