Client Name

Pakistan Agriculture Research (PAR)

Faculty Advisor

Dr. Ayesha Farooq

SBS Thought Leadership Areas

Entrepreneurship and Innovation

SBS Thought Leadership Area Justification

This ELP aligns with the Entrepreneurship and Innovation thought leadership area as it develops an original, scalable market intelligence framework for Pakistan's agricultural sector, a domain that has historically lacked structured, data-driven reporting systems. Rather than relying on existing models, the team built a bottom-up Multi-Crop Supply & Use Framework from scratch, integrating fragmented data across 1,951 mills covering cotton, maize, and wheat. The methodology was designed to be replicable, meaning the same analytical structure can be applied to any crop that has an organized industrial processing chain, making it a genuinely extensible innovation rather than a one-time academic exercise.

The framework is designed to be institutionalized by Pakistan Agriculture Research (PAR) and extended to additional commodities in the future. This embodies entrepreneurial thinking: identifying a structural gap in market information, designing a replicable analytical solution, and delivering it as a foundation for an ongoing agri-intelligence operation. By transforming scattered, inconsistent, and often inaccessible industry data across 1,951 mills into a coherent and auditable balance sheet system, the project creates a new way of doing something that previously had no standardized approach in Pakistan's agricultural economy.

Ultimately, the value of this project lies not just in the numbers it produces but in the system it establishes, one that can be handed off, scaled, and built upon by PAR and other stakeholders. That orientation toward building something lasting, innovative, and institutionally useful is precisely what places this project within the domain of Entrepreneurship and Innovation.

Aligned SDGs

GOAL 2: Zero Hunger

Aligned SDGs Justification

This ELP aligns with Goal 2: Zero Hunger as it directly addresses the structural information gaps that undermine food security in Pakistan. By developing a Multi-Crop Monthly Supply and Use Framework across cotton, maize, and wheat, the project enables more informed decision-making across agricultural value chains that collectively sustain the livelihoods of millions of farmers and feed a population of over 220 million people. The absence of reliable, standardized market intelligence in Pakistan has historically contributed to supply disruptions, price volatility, and inefficient resource allocation, all of which directly threaten food security. This framework, built across 1,951 mills, provides stakeholders including millers, traders, policymakers, and procurement officials with the tools to anticipate shortages, manage stocks more effectively, and reduce the uncertainty that makes Pakistan's agricultural economy vulnerable. By institutionalizing a replicable and evidence-based reporting system through PAR, the project contributes toward building the kind of resilient agricultural infrastructure that Goal 2 calls for, particularly in a country ranked among the most climate-vulnerable in the world.

NDA

Yes

Abstract

In Pakistan, the value chains of cotton, maize, and wheat jointly support the food security situation of the country, the textile exports industry, and the poultry/livestock industry. However, all stakeholders along all three value chains have, until now, been without an efficient process of transforming industry data into valuable information through one consistent methodology. This research paper is written as part of the Experiential Learning Project and undertaken in partnership with Pakistan Agriculture Research (PAR) and the Institute of Business Administration (IBA), Karachi, as a response to this situation. The project proposes the development of a Multi-Crop Monthly Supply and Use Framework for the three crops. In the framework, all three crops follow a similar methodology: first, the demand for the crop is estimated on the bottom-up approach using capacity estimates of respective mills (spinning and weaving mills for cotton, feed mills for maize, and roller flour mills for wheat). The analysis encompasses 282 cotton mills, 65 maize feed mills, and 1,604 wheat flour mills, where cotton is reduced to a monthly balancing figure through multi-year coefficients for arrival. The results show a structural deficit in the cotton industry, where mill usage of 16.44 million bales surpasses supply of 11.34 million bales; maize feed milling activity that occurs solely in Punjab and is largely carried out by only a few very large firms; and a highly diversified milling industry that has more than 93 million metric tonnes of known milling capacity, greatly overshadowing local production levels. Punjab stands out as the consistent locus for all three commodity groups. The key contribution of this framework lies in its provision of an audit-proof analysis structure for PAR to utilise and expand into other commodities.

Document Type

Restricted Access

Document Name for Citation

Experiential Learning Project

Notes

This research was conducted in partnership with Pakistan Agriculture Research (PAR) as part of the Experiential Learning Project (ELP) for Spring Semester 2026 at the Institute of Business Administration (IBA), Karachi. The project was supervised by Dr. Ayesha Farooq (Faculty Advisor) and Ghasharib Shaukat, Chief Operating Officer at PAR. All datasets developed through this project, covering 1,951 mills across the cotton, maize, and wheat sectors, have been reviewed and approved by PAR for institutional use. The framework is intended to be adopted by PAR as the foundation for its ongoing agri-intelligence operations and is designed to be extended to additional commodities in future editions.

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