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What happened, why, what happens next, and what to do

Most dashboards answer the first question and stop. We build the layer that answers all five — so the meeting starts at the decision instead of the chart.

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12 metrics derived from raw sensor data

THE PROBLEM

Most dashboards report. Nobody needs another chart that says traffic was 14% lower last week; they need to know why, and whether to act. The analysis step is the part still being done by hand at 7pm on a Sunday.

WHAT YOU GET

Data pipeline & warehouse

Metric definitions

Dashboard build

Anomaly detection

Automated reporting & alerts

How we run it

01

Fix the pipeline first

A dashboard on top of unreliable data is worse than no dashboard, because people act on it.

02

Define the decisions

We build backwards from what someone needs to decide, which is usually four numbers rather than forty.

03

Automate the commentary

Anomaly detection and plain-language summaries so the analysis arrives with the numbers.

04

Close the loop to revenue

Marketing activity joined to pipeline and revenue, so channel decisions are made on commercial contribution.

PROOF

See this work in a client case study

Read the case study →

RELATED SERVICES

Intelligent Workflow & Process Automation→ Custom AI Applications→ Connected Products→

NEXT STEP

Tell us the number you need to move

Ready to take the first step towards unlocking opportunities and realising goals? Tell us the outcome you need and we will bring the marketing, data and engineering capability to deliver it.

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