Products
Pricing
Manage your stock
Supply Chain
Demand Forecasting
Case Studies
About Us
Newsroom
Contact Us
Farmlands sells a broad range of categories including agronomy (seeds, sprays, fertilisers), animal health, nutrition (animal feed supplements), fertilisers, apparel, water tanks, fencing and fuel distribution. They currently forecast their demand at both national and regional levels – with regional splitting the country into 10 regions, each responsible for forecasting demand for the following year.
In recent years, Farmers have come under increasing political and social pressure to change their practices, to address growing climate and environment concerns. Add to this a growing list of demands for on-farm reforms from stakeholders and commentators, and you have a huge amount of stress on the industry. This, combined with longer-term consumer trends like the plant-based diet movement and lower carbon lifestyles, means that the traditional seasonal predictability for mainstream agricultural products is becoming more volatile as farming systems adapt and adjust.
With Farmlands supplying directly to the farming industry, these fluctuating circumstances dramatically impacted demand for a number of their more traditional products.
Farmlands saw an opportunity to utilise AI to help them gain more accurate insights and make more precise forecasts. They also wanted to gather and extract relevant data from multiple data sets, to better understand how seemingly unrelated data might correlate and impact their business.
“Our planning was good enough to complete a budget, but wasn’t sophisticated enough to predict the increasing changes we were seeing in each category for longer term decision making.”
AI-driven solutions, such as Quantiful’s QU, lead to consumer-driven demand planning. QU draws on data about consumer buying behavior and turns it into accurate insights, using these to predict future trends. QU deploys some of AWS's leading-edge data management and AI technologies, such as Athena to clean data, Sagemaker to run ML training and feature engineering jobs, and Lambdas to automate workflows such as data ingestion and forecast exporting.
When this technology, trend data, and sales data are combined for Farmlands, product availability is significantly improved, with more accurate 6-monthly forecasting and better product portfolio management. QU continues to provide Farmlands with real-time insights into economic and market trends within the agricultural industry, which helps them to maintain accurate inventory and support farmers through volatile regulation and consumer buying behaviors.
