Production capacity growth
Business capacity increased from 300 to 5,000 units per day during the engagement.
← Work index / PT Gajahpangan Jaya Makmur
Professional Experience FMCG
FMCG Operational and Profit Optimization
Used operational and commercial analysis to support production scaling, channel expansion, and more coordinated supply-chain decisions.
Published with protected details
- Organization
- PT Gajahpangan Jaya Makmur
- Role
- Data Analyst
- Timeline
- March–October 2024
- Stack
- Python · Looker Studio · Excel
Business-level outcomes
Impact during the engagement.
Team outcomes supported by my analysis and broader operational execution.
Monthly profit level
Business-level monthly profit increased from below IDR 100M to above IDR 700M during the engagement.
My role
My contribution.
Work I directly owned or delivered within the broader team effort.
- 01
Analyzed production and profit bottlenecks to support operational scaling, including production-capacity planning and profit-oriented decision-making.
- 02
Used product, channel, and supply-chain analysis to guide commercial decisions, including B2B actual-versus-target evaluation and marketplace audience comparison.
- 03
Built decision-ready reporting that helped coordinate production, sales, and after-sales teams through shared views of units sold, revenue, daily performance, and inventory coverage.
- 04
Led the analysis, visualization, recommendation development, deck production, and stakeholder presentation end-to-end within the Gajahpangan Data team.
- 05
Developed a structured Wispish social-media activation plan covering audience direction, content themes, activation timing, and campaign recommendations.
- 06
Translated B2B performance and Shopee, Tokopedia, and TikTok Shop user research into channel-specific recommendations supporting Modern Trade, General Trade, and marketplace expansion.
Analysis frame
Assumptions / constraints
- Published production and profit outcomes describe business performance during the engagement, not solely individual contribution.
- Operating metrics require explicit definitions, baselines, comparison periods, and owners.
- Commercially sensitive supplier, SKU, margin, and transaction details cannot be disclosed.
Technical judgment
Decision log
- 01Connect production, distribution, and profit analysis rather than report them separately.Why
The business needed coordinated operational and commercial decisions.
- 02Use dashboards and recurring analysis to support production and channel decisions.Why
Operational execution required shared visibility across functions.
- 03Report outcomes at business level with team attribution.Why
The results occurred within broader operational execution and should not be presented as individual-only impact.
Selected decision decks
Analysis made actionable.
4Approved internal decks
Led analysis, visualization, recommendations, deck production, and stakeholder presentation end-to-end within the Gajahpangan Data team. Four approved examples spanning weekly sales, B2B performance, marketplace research, and social-media activation.
Social Media Activation Wispish Snack
Wispish Sales Report, 15–21 April 2024
B2B Indomaret Report, January–March 2024
Shopee, Tokopedia & TikTok Shop User Analysis
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Domain referenceMetric dictionaryView definitions +
- SKU
- Stock-keeping unit; unit-level operating data remains withheld.
- Business-level outcome
- Result attributed to broader company or team execution during the engagement.
Snapshot
This professional case study covers operational and commercial analysis supporting production, distribution, and profit-oriented decisions. Approved business-level outcomes are shown with team attribution; commercially sensitive operating details remain withheld.
The situation
An FMCG operation was scaling production and expanding distribution beyond Modern Trade into General Trade.
The problem
Production, channel, and commercial decisions needed a shared analytical view to support coordinated action.
My responsibility
I led operational and commercial analysis, visualization, recommendation development, deck production, and stakeholder presentation end-to-end within the Gajahpangan Data team. My work connected production planning, weekly sales monitoring, B2B performance, marketplace research, and social-media activation using Python, Excel, and Looker Studio.
Approach
I combined production, sales, channel, inventory, and profit data; compared actual performance with targets and prior periods; and identified bottlenecks, inventory risks, and channel opportunities. I also researched marketplace audiences and activation requirements, translated findings into decision-ready visualizations and recommendations, and presented the resulting decks for coordinated follow-up.
Solution
The output was a practical analytical workflow connecting production and profit analysis, weekly sales monitoring, B2B channel reporting, marketplace user research, social-media activation strategy, and stakeholder-ready decision decks.
Outcome
During my engagement, daily production capacity increased 1,567%, from 300 to 5,000 units per day, while monthly profit grew from below IDR 100M to above IDR 700M. My analysis supported these team-level outcomes through bottleneck review, product and channel analysis, supply-chain mapping, and decision-facing reporting; it was one contribution within broader operational execution.
What I learned
Operational metrics need explicit definitions and owners. Strong outcomes are most credible when the baseline, comparison period, and team-versus-individual attribution remain visible.
Outcome Validated evidence
What changed.
Published outcomes stay within what can be supported by project evidence.
Supported production capacity growth of 1,567%, from 300 to 5,000 units per day
Supported monthly profit growth from below IDR 100M to above IDR 700M
Informed Modern Trade to General Trade expansion
Evidence Selected frames
Selected evidence.
Published views are selected for clarity and privacy. Open any frame to inspect it at full size.
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