Turn a history of orders, bookings or workload into a planning conversation. Compare a simple starting point with a seasonal pattern.
A possible next movePlan capacity, stock or staffing around plausible demand.
What would we need?
Dated activity records, enough history to assess seasonality, known closures or promotions, and a simple baseline. Forecasts need testing on periods the model has not seen.
Weekly ordersFICTIONAL / 16 WEEKS
Recorded ordersIllustrative projection
The projection is a sketch of an approach, not a fitted or validated forecast.
02 / CUSTOMER SEGMENTATION
Are all customers buying in the same way?
Group similar purchase patterns to find useful differences hidden by an average.
Purchase frequency × order valueFICTIONAL CUSTOMERS
A possible next moveTest different offers or service approaches with different groups.
What would we need?
Consistent customer IDs and purchase histories, clear definitions and a way to test whether a segment changes a useful decision. A cluster is a pattern, not an explanation of a person.
03 / ANOMALY DETECTION
What deserves a closer look?
Bring unusual activity to the surface so someone can investigate it in context.
Daily transaction countFICTIONAL / 30 DAYS
A possible next movePrioritise checks on a reporting error, promotion, outage or unexpected change.
What would we need?
Timestamped observations, a sensible comparison period and context about expected changes. An unusual point is a prompt to investigate, not proof of fraud or a fault.
04 / RELATIONSHIP ANALYSIS
Where are the hidden dependencies?
Follow connections between suppliers, products and locations to see where disruption could spread.
A connected supply pictureFICTIONAL NETWORK
A possible next moveInvestigate an alternative supplier or the locations most exposed to a delay.
What would we need?
Reliable identifiers and evidence of the relationships. Connections show dependency, not causation. Missing links can change the conclusion.
05 / DATA QUALITY & ENTITY MATCHING
Do these records mean the same thing?
Spot possible duplicates and missing fields before they distort the analysis.
A fictional customer list10 SOURCE RECORDS
A possible next moveReview uncertain matches and agree a trusted customer count.
Source records, matching rules and an owner who can resolve ambiguous cases. Similar names alone do not justify merging records; preserve the originals and the review trail.
06 / COHORT ANALYSIS
Are people coming back?
Compare groups that started at different times instead of blending everyone into one average.
Customers returning to purchaseFICTIONAL / 100 PER COHORT
A possible next moveInvestigate whether a change in onboarding or the customer mix warrants a test.
What would we need?
Consistent customer IDs, start dates, a definition of a return and complete observation windows. Newer cohorts have fewer observed months. Differences do not prove that a product change caused better retention.
07 / TEXT ANALYSIS
What are customers actually talking about?
Organise comments into themes so a large collection of feedback becomes easier to explore.
Themes in 12 fictional commentsHAND-LABELLED DEMO
A possible next moveRead representative comments and choose a problem worth investigating.
What would we need?
Permissioned text, sensible categories and a reviewed sample to evaluate classification. This demonstration uses hand-labelled comments; it does not run an AI model. Themes can overlap in real feedback.
08 / SCENARIO PLANNING
What if demand grows faster?
Explore a transparent assumption before committing resources. See how demand compares with a fixed capacity.
Orders versus weekly capacityFICTIONAL SCENARIO
A possible next moveCompare extra capacity, changed lead times or a smaller growth target.
What would we need?
Agreed baseline demand, realistic capacity and explicit constraints. This is arithmetic using an adjustable assumption, not a demand prediction or an optimisation model.
YOUR BUSINESS. YOUR QUESTION.
Something look familiar? That’s a starting point.
Tell us what you’re trying to understand, where the information lives and what you would do differently with a useful answer.
