Projects
Each project documents the business question, source data, analytical logic, evidence state and limitations.
The Bitumen Effect
A completed Stats SA case study showing how the treatment of bitumen changes the inflation signal for road activities, and why weighted inputs matter more than headline percentages.
Choose the most relevant price signal for road-material exposure instead of relying on one blended construction headline.
Construction Materials Intelligence
A monthly material-risk system using Stats SA CMPI/CPAP/CIPI data to detect unusual movement, volatility and divergence across road, concrete, steel and other civil-engineering inputs.
Prioritise which input risks need procurement, contingency or commercial attention without exposing project monetary values.
Cape Town Asphalt Demand Pressure Monitor
A procurement-pipeline model that classifies road tenders and awards to estimate future asphalt demand pressure in Cape Town and the Western Cape without claiming supplier inventory.
Anticipate procurement pressure early enough to review programme sequencing, supply strategy and escalation risk.
Civil Infrastructure Tender Intelligence Engine
An OCDS data pipeline that turns public procurement releases into a searchable civil-infrastructure market view: sector, stage, location, buyer, cycle time and outcome.
Convert procurement records into a reusable, queryable infrastructure pipeline instead of manually checking tender pages one by one.
Infrastructure Activity Radar
A multi-source view combining municipal capital activity with procurement pipeline signals to identify where roads, stormwater and water infrastructure activity is strengthening or weakening.
Identify infrastructure activity using multiple independent signals instead of ranking municipalities on one headline number.
Engineering Information Performance Lab
A large synthetic CDE/BIM reporting environment modelled on real construction information-management work: RFIs, submittals, deliverables, packages, ageing, cycle time and data-quality controls.
Detect information bottlenecks before they become programme or coordination problems.
Yatify Data Reliability Monitor
The operational layer behind Yatify: source checks, release freshness, validation state, schema-change detection and a publish gate that protects dashboards from silent source failures.
Know whether a dashboard is fresh and trustworthy before using its result.
Project Controls Performance Lab
A portfolio-safe project-controls environment with 800 activities across 24 monthly reporting snapshots, WBS/packages, planned vs actual progress, forecast finish, float, milestones and resource-hour variance.
Identify package slippage, float erosion, milestone risk and resource variance early enough for a project team to investigate and recover the programme.
Data Quality & UAT Lab
A practical validation layer that turns data-quality rules into inspectable test results across Yatify’s published and portfolio-safe datasets.
Determine whether an analytical output is safe to publish and identify exactly which rule failed when it is not.
The Approval Gap
A real public-data case study comparing building plans passed with buildings completed, testing real-price movement, building-type and province divergence, and whether the available monthly window supports a defensible construction lag.
Can building approvals be used as a forward signal for completed construction activity without confusing same-period values with a true conversion rate?