P43 · Implementation blueprint · Mappls Field Sales Intelligence

Pharma & Healthcare Commercial/Distribution Intelligence

Field teams, doctor/chemist coverage and healthcare distribution are planned with incomplete location and potential data.

01 · Target operating outcome

Define the change before choosing the technology

Which micro-markets have the highest patient/provider potential but the weakest field coverage?

More productive calls and coverage; lower travel and distribution loss; faster market expansion and service reach.

Baseline

Measure current volume, time, cost, failure, service, risk and revenue at the workflow level.

Target

Match/enrichment accepted; target coverage and travel productivity improve; field adoption achieved.

02 · Solution architecture

One connected flow from source data to operational action

Doctor/chemist/facility master enrichment, territory and beat design, field force, cold-chain/fleet visibility, access analytics and dashboards. Mappls connects proprietary map and location intelligence with doctor/chemist/facility master enrichment, territory and beat design, field force, cold-chain/fleet visibility, access analytics and 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

Market universe · Territories · Beats · Execution · Growth signals

Decision and outcome

More productive calls and coverage; lower travel and distribution loss; faster market expansion and service reach.

03 · Users and RBAC

Give every stakeholder the view and actions they actually need

Sponsor / owner

Sales Excellence

Sponsor / owner

Distribution

Manager / analyst

Commercial Analytics

Manager / analyst

Commercial Director

Manager / analyst

COO

Operator / specialist

CRM/SFA

Operator / specialist

Supply Chain

Operator / specialist

Data Science

Operator / specialist

Sales head

Operator / specialist

Territory manager

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

ClarityX Location Analytics

Market, territory, network and spatial decision analytics

Product details

InTouch / Gtropy Fleet Platform

Tracking, trips, alerts, ETA, fleet and control tower

Product details

Geocoding & Reverse Geocoding

Address-to-coordinate and coordinate-to-address

Product details

Navigation SDK

Turn-by-turn navigation, rerouting, voice and guidance

Product details

05 · Proof of value

Use a bounded implementation to answer the scale decision

Pilot one therapy/region: enrich master, model potential, redesign territories and track execution.

  • Confirm data, geography, users and workflow: What provider/outlet master and sales history exist? Which calls, reach and distribution KPIs matter?
  • Configure Mappls Field Sales Intelligence for the selected role set
  • Run baseline and intervention scenarios with real stakeholder reviews
  • Evaluate agreed criteria: Match/enrichment accepted; target coverage and travel productivity improve; field adoption achieved.
  • Package production scope and commercial model: Data/analytics project + per-user SaaS + API/IoT subscription.

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