Developing rigorous demand forecasts
Demand forecasts impact investments in R&D, infrastructure, personnel, and partnerships that will be necessary to participate in and accelerate the alternative protein sector.
- Plant-Based
- Cultivated
- Fermentation
- Ecosystem
- Commercial
- Investment
- Business Services
- Demand Generation
- End Products
- Production
- Raw Materials, Ingredients, & Inputs
- Industry
- Academics
- GFI
- Investors
- NGO’s
Current challenge
Suppliers of raw materials, ingredients, key inputs, equipment, and services for alternative protein production find it difficult to predict what demand will look like in the short- and long-term future. The inability to effectively forecast demand with a reasonable degree of reliability prevents companies and investors from committing resources to expanding R&D, production, or additional capacity.
This challenge is compounded by the position of key suppliers, who are often several layers removed from end consumer markets that ultimately determine demand for products and services at intermediate levels of the value chain. This adds complexity to the task of performing demand calculations and increases uncertainty, which compounds progressively for companies further upstream in the supply chain.
Proposed solution
Publicly available demand forecasts for novel and existing raw materials, ingredients, and inputs, as well as specific end products, would address these key knowledge gaps. These forecasts would be especially valuable if segmented by product type, region, and consumer demographics. Scenario analyses, influence diagrams, and Monte Carlo calculations would enable more effective second- and nth-order estimates about what will be required from upstream suppliers in the value chain and inform technical, regulatory, and consumer demand milestones.
The resulting estimates of consumer demand and market share could then be used to make estimates of demand for first-order inputs such as cell lines, media, scaffolds, and bioreactors. From there, additional estimates can be made for second and nth-order inputs such as growth factors, key nutrients, energy usage, and R&D needs. This analysis could integrate historical case studies such as recombinant human insulin, rennet production, and the growth of other alternative proteins such as plant-based milk.
Anticipated impact
While demand forecasting is difficult and unlikely to be completely accurate in a category as fast-changing as alternative proteins, the process of modeling and creating measurements is still invaluable for planning and providing insights for the key players in the supply chain. Models and measurements represent a quantitatively expressed reduction of uncertainty, and they force expectations, biases, and cause/effect assumptions to be made explicit. Often the most valuable part of the forecasting process can be decomposing the demand calculations into their constituent parts, making calculations and estimates smaller, more manageable, and more reliable. Rigorous demand forecasts would better enable investors and companies within the alternative protein supply chain to plan for and justify the necessary investments in R&D, infrastructure, and partnerships to meet future demand.
Related efforts
GFI is planning to partner with a consulting and/or market research firm to conduct a demand forecast, total addressable market (TAM), cost analysis, and production volume modeling analysis. Please contact us if your organization would be interested in participating in any of these projects.
Several market research firms and financial institutions have released their own market projections, including:
GFI resources
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