01
Prioritise the work that matters
Turn operational bottlenecks, commercial goals, and current AI ideas into ranked use cases with visible trade-offs.
East Africa's AI value operating system
Turn AI experimentation into measurable operational ROI.
ImpactGrid gives logistics and distribution leaders a disciplined way to choose AI opportunities, prove value, govern risk, and scale what works.
Start with one workflow, pilot, or investment decision.
Executive portfolio
12
Opportunities
5
Active pilots
3
In production
AI portfolio progress
Visible movement from discovery to controlled scale
DiscoverPilotProductionScale
Controls reviewed
Evidence and approvals in one place
Business-first
Start with workflow economics, not a model.
Evidence-led
Make assumptions, data gaps, and trade-offs visible.
Built for progress
Pilot with discipline, then scale with confidence.
A practical operating system
From AI ideas to decisions your leadership team can stand behind.
ImpactGrid brings the business case, delivery work, risk controls, and results into one executive-ready flow.
02
Measure from a real baseline
Define the operating baseline, target improvement, cost model, and attribution approach before a pilot begins.
03
Scale with control
Move promising initiatives through defined stage gates, risk reviews, adoption checks, and executive decisions.
Prioritisation that explains itself
Choose where AI can create operational value first.
Score opportunities using configurable dimensions including business impact, feasibility, data readiness, risk, time to value, scalability, and strategic importance.
Opportunity review
Route optimisation exception handling
Business impactHigh
Data readinessModerate
Delivery complexityModerate
Risk exposureReview
Recommended: pilotRationale and data gaps remain visible.
No black-box ranking
Leaders can inspect the recommendation, adjust weights, and see why a use case is ready, risky, or premature.
Built for operational context
Frame opportunities around service levels, route performance, cash flow, losses, productivity, and customer experience.
Baseline to measured ROI
Make the economic case visible before—and after—the pilot.
Capture the current process cost, hours, volume, error rate, turnaround time, revenue, losses, and satisfaction measures that matter. Then document targets, costs, measurement methods, and actual results as evidence arrives.
Estimated value
Scenario assumptions and targets that require validation.
Measured value
Observed KPI movement with the attribution method recorded.
Initiative measurement plan
Delivery exception triage
01
Baseline
Process cost, volume, staff hours, error rate
02
Target
Directional improvement and time-to-value hypothesis
03
Evidence
KPI source, measurement period, attribution method
04
Decision
Scale, iterate, or stop based on results
Pilot stage gates and governance
Treat control and auditability as part of delivery.
A valuable pilot still needs the right owner, data, controls, approvals, and evidence before it becomes an enterprise capability.
01
Opportunity
Document the decision, owner, and required evidence.
02
Business case
Document the decision, owner, and required evidence.
03
Data readiness
Document the decision, owner, and required evidence.
04
Risk review
Assess privacy, security, reliability, oversight, and failure consequences.
05
Pilot
Document the decision, owner, and required evidence.
06
KPI review
Review adoption, KPI evidence, investment, and remaining dependencies.
07
Scale or stop
Document the decision, owner, and required evidence.
Risk profile
Controls tailored to the use case.
Approval state
Clear readiness and review checkpoints.
Audit trail
Visible actions, decisions, and evidence.
Executive portfolio visibility
See what is moving, what is blocked, and where evidence is still missing.
Give the CEO and leadership team one focused picture of opportunities, pilots, production initiatives, risk exposure, investment, adoption, and estimated versus measured value.
Clear answers
Start with the decision in front of you.
A better next AI decision
Bring one active AI opportunity. Leave with a clearer path to value.
Explore the operating problem, baseline, dependencies, risk questions, and evidence needed to decide what comes next.