Cleaner workflows
Data Systems
Turn messy spreadsheets, manual reports, and disconnected data sources into repeatable reporting workflows.
Boutique quantitative consulting
Clearer models and repeatable analytics for decisions that matter.
Hurst Analytics helps organisations turn messy data, manual workflows, and uncertain planning problems into clearer models, repeatable reporting processes, and decision-ready analytical tools.
Forecast desk
Planning model snapshot
Demand0.82Signal+4.1%
Revenue0.77Signal+2.8%
Cost0.69Signal-1.3%
Risk0.74SignalStable
ForecastingEconometricsAutomationDashboardsModel Validation
Services
Focused support across reporting, automation, and quantitative decision systems.
Three practical service areas for teams that need cleaner reporting cycles, automated analytics workflows, and rigorous modelling outputs they can use beyond a one-off spreadsheet.
Forecasting capability
Forecasting work designed for planning, not theatre.
Forecasting engagements can cover operational, commercial, risk, and investment contexts, with clear assumptions, benchmarks, and uncertainty communicated alongside the numbers.
Demand
Volume, seasonality, capacity, and planning forecasts for recurring operating decisions.
Revenue
Driver-based revenue forecasts with assumptions and uncertainty made explicit.
Cost
Cost and margin forecasting for budgeting, variance review, and sensitivity analysis.
Risk
Forecasts and indicators for exposures, thresholds, and changing risk conditions.
Operational
Workload, service-volume, and resource forecasts for practical planning cycles.
Financial market
Evidence-led market and investment modelling that treats uncertainty as part of the output.
Integrated systems
Repeatable analytics for recurring high-value workflows.
For recurring workflows, Hurst Analytics can help connect data intake, cleaning, modelling, dashboards, scheduled reporting, and ongoing review into a process your team can rely on.
What can be included
Data checksKPI definitionsForecast outputsDashboardsScheduled reportsReview notes
Process
A structured path from analytical problem to repeatable output.
The work starts with the decision and data reality, then moves through modelling, validation, delivery, and support with clear artefacts at each stage.
Step 1
Discovery
Clarify the decision, workflow, stakeholders, constraints, and the output that would be useful.
Step 2
Data review
Inspect available data, known gaps, definitions, update cadence, and quality risks before modelling.
Step 3
Modelling and reporting
Develop the model, automation, dashboard, or reporting workflow using methods matched to the problem.
Step 4
Validation
Compare outputs against benchmarks, test assumptions, review errors, and document practical limitations.
Step 5
Delivery and reporting
Package results into repeatable reports, dashboards, documented assumptions, or decision-support outputs for regular use.
Step 6
Ongoing support
Maintain, improve, and review the analytical system as data, requirements, and decisions change.
Build a clearer analytical workflow.
Share the planning problem, reporting process, or modelling requirement you want to improve.