1,000+
SKUs in the rolling sell-in demand forecast they own
10%
improvement in forecast accuracy (MAPE) from an AI-enabled forecasting workflow
Namya Mandalia
Demand Planning Analyst
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Demand planner who turns messy SKU data into forecasts, dashboards, and inventory savings.
5
years working
4
companies
4
roles
24
skills
Longest run: 1 year at Whisha Speciality Coffee Distributors.
the story
Who Namya is
Namya is a demand planning and supply chain analytics professional with 4+ years of experience building statistical and machine learning based forecasting models across high-SKU CPG, perishables, and distribution environments. They currently own the rolling sell-in demand forecast across 1,000+ SKUs at Whisha Speciality Coffee Distributors, feeding demand planning inputs into the monthly S&OP process and presenting forecast changes, risks, and opportunities with financial impact to Sales, Finance, and Operations leadership.
Their career has moved steadily from analysis to ownership. They started at Pheromone Chemicals automating master data generation in Python, then spent over a year at HBT Bearings forecasting 700+ SKUs across an 18-month horizon and cutting MAPE from over 30% to under 20% for critical categories. A summer internship at Meghmani Industries gave them hands-on SAP and consensus forecasting work, and an MS in Supply Chain Management at Arizona State University followed.
Namya is known for pairing forecasting rigor with practical fixes. At Whisha they reduced Days of Inventory from 15 to 6 days on perishable goods, segmented a 700+ SKU portfolio into 6 lifecycle-based strategies, and built automated Power BI dashboards that cut PO approval turnaround by 30%. They work closely with Sales, Marketing, Finance, and Operations, and they are comfortable moving between SQL, Python, and the people in the room.
by the numbers
What moved
the headline number
1,000+
SKUs in the rolling sell-in demand forecast they own
10%
improvement in forecast accuracy (MAPE) from an AI-enabled forecasting workflow
15 to 6 days
reduction in Days of Inventory across perishable goods
30%
faster PO approval turnaround after automated Power BI dashboards
35%
fewer forecast exceptions after lifecycle-based SKU segmentation
$1M
in missed sales opportunities uncovered from under-forecasting
the case
Why Namya?
Forecasting that moves numbers
At Whisha, Namya's AI-enabled workflow improved forecast accuracy (MAPE) by 10%, and at HBT Bearings they brought MAPE from over 30% to under 20% for critical categories.
Inventory results, not just models
They reduced Days of Inventory from 15 to 6 days on perishable goods and lifted in-stock position from 85% to 95% during peak-demand periods.
Builds the tools too
Namya queries and preprocesses data in SQL on Snowflake, models in Python with scikit-learn, and ships automated Power BI dashboards that cut PO approval turnaround by 30%.
Speaks finance and operations
They present forecast changes, risks, and opportunities with financial impact to Sales, Finance, and Operations leadership as part of the monthly S&OP process.
rare finds
Only Namya
They segmented a 700+ SKU portfolio into 6 lifecycle-based strategies, which cut planner touch-time by 8 hours every week.
career map
Where Namya has been
Demand Planning Analyst · Whisha Speciality Coffee Distributors
2025 to now
Owns the rolling sell-in demand forecast across 1,000+ SKUs and drives demand planning inputs into the monthly S&OP process.
- Built an AI-enabled forecasting and reporting workflow using SQL in Snowflake and a Random Forest model in Python, automating the 2-month rolling forecast cycle and improving MAPE by 10%.
- Reduced Days of Inventory from 15 to 6 days across perishable goods by tightening reorder cadence and recalibrating safety stock to vendor lead-time reliability.
- Segmented a 700+ SKU portfolio into 6 lifecycle-based strategies, reducing forecast exceptions by 35% and planner touch-time by 8 hours/week.
- Improved in-stock position from 85% to 95% during peak-demand periods by incorporating demand signals and replenishment triggers for the top 100 SKUs.
skill map · tap one
Product
13Data
6Leadership
3Languages
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Ask about Namya
Why hire Namya?
Namya brings 4+ years of demand planning experience across high-SKU CPG, perishables, and distribution environments, with measurable results in forecast accuracy and inventory health. They have improved MAPE by 10% at Whisha and brought it from over 30% to under 20% at HBT Bearings. They also build the tooling themselves, from SQL and Python models to automated Power BI dashboards.
education
Master of Science in Supply Chain Management
Arizona State University
2025
- A
Bachelor Of Business Administrations, Major in Supply Chain Management
Ahmedabad University
2023
certifications
- CSCMP Supply Chain Foundations: Inventory Management Professional Certificate
- CSCMP Supply Chain Foundations: Demand Planning Professional Certificate
written by aperture ai from Namya’s profile