Stage 3 Consulting

Capability 03

Data Analytics & Decision Intelligence

Move from numbers to meaning.

Thirty years of statistical practice — from Aftab to Nielsen — applied to the question of what the data actually licenses you to do next.

The problem it solves

Volume was never the constraint.

Most organisations already hold more data than they use. The work that turns it into a decision — processing, validation, testing — is the part that gets compressed when the timeline slips, and it is the part nobody can see has been skipped.

What comes back is either late, or last quarter's framework with new numbers in it. Neither one tells you what the data licenses you to do next. We analyse against a stated decision, and we test differences before we call them differences.

02

Insight that arrives too late

Timelines slip. The answer lands after the moment it was commissioned to inform has already passed.

04

The same report, every time

Typical research reports with no newness and no advancement — one framework applied regardless of the actual question.

The people who run the analysis

What's included

Five pieces of analytical work.

Applied to data we collected, or to data you already hold and have not been able to use.

  • Statistical analysis & testing

    Thirty years of it, from Aftab through to Nielsen, under our head of data analytics.

  • Segmentation modelling

    Segmentations sit in the head of quant's remit alongside brand health tracking and central location tests.

  • Data processing & validation

    Data processing, input, validation and control — over twenty years of the discipline that decides whether anything downstream can be trusted.

  • Descriptive analysis

    Part of the founder's own delivery remit, so the analysis and the recommendation are written by the same person.

  • Insight synthesis

    Findings are taken through to what should be done about them, rather than stopping at the tables.

What the data is checked against

How it runs

Clean, then test, then decide.

The order matters more here than anywhere else, because every step inherits the errors of the one before it.

  1. 01

    Outsmart

    Fix the decision first

    Analysis with no decision attached to it produces description. We agree what the output has to settle before opening the file.

  2. 02

    Outsmart

    Process and validate

    Data processing, input, validation and control come before any finding is quoted — the least visible work and the most load-bearing.

  3. 03

    Outsmart

    Test rather than assume

    Differences are significance-tested before they are described as differences, and the same standard applies to every wave.

  4. 04

    Outpace

    Model the options

    Segments and models are built to separate the choices in front of you, not to demonstrate technique.

  5. 05

    Outperform

    Set the baseline

    We agree what will be measured after the decision, so the next round of analysis has something to be judged against.

See the full approach

Related

Proof, once it can be published.

The slots below are built and wired. Nothing appears in them until Stage 3 supplies the engagement and the client agrees to it being named.

Case studyData Analytics & Decision Intelligence

Related case study

A dataset, what was wrong with it, what the testing showed once it was clean, and the decision that changed as a result.

Client approval required

InsightData & Analytics

Related insight

Editorial writing on significance, sample and the difference between a movement in the data and a movement in the market.

Awaiting first article

All case studies All insights

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You have the data. What is it supposed to settle?

Send us the question and what you already hold. We will tell you whether it can answer it, and what is missing if it cannot.