How Commodity Forecasting Can Pay for Your Sustainability Initiatives

The same data that anticipates and mitigates price fluctuations can protect and enhance your environmental reputation

Overview

Key takeaway: Supply chain optimization and sustainability are inextricably linked and can both be addressed with a single solution that reduces costs, as well as environmental impact.

Machine learning combines agronomic and weather data to predict palm oil production. This model uses many of the same datasets critical to accurate deforestation and forest carbon loss estimates.
Machine learning combines agronomic and weather data to predict palm oil production. This model uses many of the same datasets critical to accurate deforestation and forest carbon loss estimates.

Geospatial Knowledge Is Power

Accurate commodity maps, forest carbon, and weather data contribute to a geospatially informed supply chain.

Using Geospatial Data to Cut Costs

Geospatial data purchasing savings chart. Saving ~3% on sugar, soybean meal, and palm oil.
Vegetation indices confirm damage to sugar production and support elevated price levels.

The Inevitability of Sustainability

Source: IPCC, 2019 (2)

Using Geospatial Data for Environmental Stewardship

References:

  1. Yakupitiyage, Tharanga. “Q&A: 17 Percent of the Problem, but 30 Percent of the Solution.” Inter Press Service, 18 Jan. 2019
  2. IPCC, 2019: Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Del- motte, H.-O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold,J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M. Belkacemi, J. Malley, (eds.)]. In press.
  3. Best, Elisabeth and Mitchell, Nikita, ”Millennials, Gen Z, and the Future of Sustainability.” BSR, October 24, 2018.

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