Baseline
Measure current volume, time, cost, failure, service, risk and revenue at the workflow level.
P58 · Implementation blueprint · Mappls Location Analytics Studio
GeoAI, Spatial Analytics & Decision Intelligence
Critical decisions ignore spatial relationships because business, sensor and external geospatial data are not modeled together.
01 · Target operating outcome
Define the change before choosing the technology
Which recurring decision would materially improve if location context were modeled rather than viewed?
Faster, repeatable decisions; better targeting and resource allocation; reduced manual analysis and blind spots.
Target
Model lift and explainability accepted; decision time reduces; operational owner and monitoring agreed.
02 · Solution architecture
One connected flow from source data to operational action
ClarityX/mGIS, spatial data engineering, GeoAI/ML, risk/demand/accessibility models, scenario analysis, alerts and decision dashboards. Mappls connects proprietary map and location intelligence with clarityx/mgis, spatial data engineering, geoai/ml, risk/demand/accessibility models, scenario analysis, alerts and decision dashboards. We start with one measurable workflow, prove the operating impact, and scale through reusable data, APIs and SaaS rather than a one-off implementation.
Data foundation
Map, customer, asset, sensor and enterprise data
Intelligence services
Search, routing, GeoAI, rules and spatial models
Role workflows
Data workspace · Catchments · Models · Scenarios · Decision board
Decision and outcome
Faster, repeatable decisions; better targeting and resource allocation; reduced manual analysis and blind spots.
03 · Users and RBAC
Give every stakeholder the view and actions they actually need
Sponsor / owner
Analytics
Sponsor / owner
Strategy
Manager / analyst
Operations Excellence
Manager / analyst
Chief Data/Strategy Officer
Manager / analyst
COO
Operator / specialist
Data Science
Operator / specialist
GIS
Operator / specialist
BI
Operator / specialist
IT
Operator / specialist
Strategy leader
The shared Mappls identity is separated from application membership. A user can be an administrator in one app, an analyst in another and a viewer elsewhere.
04 · Data and integration
Connect the minimum information needed to make the workflow real
Location foundation
Map, road, address, place, imagery, boundary and terrain layers appropriate to the decision.
Enterprise context
Customer, order, asset, vehicle, incident, task, sensor or transaction records from systems of record.
Integration pattern
APIs, SDKs, secure batch, streaming events, webhooks, files or on-premise integration depending on architecture.
Security and control
Least-privilege RBAC, audit events, encrypted transport, tenant separation and cloud, private or offline deployment.
Recommended Mappls building blocks
GeoAI & Spatial Decision Models
ML/AI, risk, demand, accessibility, image and anomaly models
Product detailsClarityX Location Analytics
Market, territory, network and spatial decision analytics
Product detailsAsset & Personal Trackers
Battery/portable/asset location and alert devices
Product detailsPOI, Address & Building Data
Places, building-level addresses and location identity
Product details05 · Proof of value
Use a bounded implementation to answer the scale decision
Decision diagnostic and back-test for one use case, followed by live shadow recommendation cycle.
- Confirm data, geography, users and workflow: What decision, outcome history and spatial/business data exist? How will model recommendations be operationalised?
- Configure Mappls Location Analytics Studio for the selected role set
- Run baseline and intervention scenarios with real stakeholder reviews
- Evaluate agreed criteria: Model lift and explainability accepted; decision time reduces; operational owner and monitoring agreed.
- Package production scope and commercial model: Analytics project + platform/data subscription + managed model service.
06 · Rollout and operating model
Move from proof to governed adoption
Week 0–2
Discover
Baseline, data, stakeholders, security and architecture
Week 3–6
Configure
Data connection, role workflows, rules and dashboards
Week 7–10
Prove
Live users, measurement, change support and decision review
Production
Scale
Phased geographies, integrations, service model and continuous improvement