practice-labs

Nairobi FMCG Sales Recovery

Find the territories and product groups pulling sales down, then recommend a recovery plan.

deliverables

rubric areas

Intermediate

level

3-5 hrs

time

Live surface

Learner workspace

Project briefs, mentor feedback, and proof artifacts are always visible.

Next action

Build, submit, review

Every page gives the user a clear next step without extra narration.

Today

Mentor review queue

12 pending

Submissions

Healthy

At risk

RetailCoPractice Lab

What you learn

Turn a sales dataset into a recovery recommendation.

Deliverables

Cleaned datasetTrend analysisRecovery recommendation

Scoring rubric

AccuracyDecision qualityClarityBusiness usefulness

Skills practiced

Trend analysisCommercial reasoningRecommendation writing

Mentors check whether the final recommendation is specific enough for a manager to act on.

How submissions are judged

Data source: Synthetic FMCG dataset

Accuracy of the analysis and any calculations.

Whether the recommendation is specific and useful.

How clearly the learner explains the decision.

Whether the output feels ready for a hiring manager.

Score bands

90-100: manager-ready

75-89: strong with revisions

60-74: needs coaching

Submit

Send your work for review.

Submit a shareable artifact link so a mentor can review your workbook, dashboard, notebook, or written recommendation.

Related proof

Strong submissions surface here

These cards show what the finished work should feel like once the project has been scored.

Product Growth Funnel Analysis

Alice Mwangi

93%

A funnel readout with cohort breakdowns and a practical activation experiment.

See showcase

SME Collections Priority Model

Kevin M.

90%

A prioritized collections list with risk bands and expected cash recovery.

See showcase

Customer Support Quality Scorecard

Naomi A.

88%

A support dashboard that connects response time, quality, and coaching actions.

See showcase

Open showcase