Building a Predictive Analytics and Machine Learning Movement

Key Outcomes

Trading teams consistently sell within 5% of peak market prices
Increased year-over-year contract gains by over 15%
Established an Analytics Center of Excellence "CoE" for group-wide adoption beyond core project team

Fortune 250 Agricultural Company

Predictive Analytics and Machine Learning Positions Agricultural Company as Industry Leader

We helped a Fortune 250 agricultural company solve operational pain points and bottlenecks by building a predictive analytics foundation. The organization partnered with Inspire11 to make way for the design and launch of a business insights center. Now through improved analytics, the organization has shifted its thinking from reactive to proactive. By leveraging a full suite of data science capabilities, the firm is consistently trading within five percent of the top of the market, driving 15% year-over-year gains in revenue. 

Opportunity the client was faced with

The food and agriculture industry is a game of commodities where buying low and selling high is essential to long-term business success. The client, with a complicated supply chain of hundreds of partners, was selling commodities at sub-optimal price points. Analyzing contracts and their impacted terms in a timely manner was a challenge due to disparate and disconnected data storage and collection. The organization engaged Inspire11 to overhaul homegrown analytics tools, provide real-time financial market insights, and create sustainable data-based solutions that flexibly scale over time. 

Why they turned to Inspire11

The client was seeking a partner that could provide not only multi-disciplinary data and analytics capabilities, but also bring a financial and business mindset. Inspire11 was uniquely qualified due to our functional knowledge, experience with the selected technology tools such as Snowflake, and our proven track record of delivering innovative solutions. 

Additionally, due to the nature of the industry and business challenges, the potential outcomes and impact were clearly measurable and significant. When margins are thin and volume is high, as was the case with this client, incremental improvements can have a major impact. Inspire11 saw the opportunity to dramatically transform the way the client operated, and thus realize substantial year-over-year revenue gains. 

How we built a predictive analytics foundation

During the first phase of the engagement, Inspire11 focused on creating a strong data foundation by leveraging Snowflake services to consolidate data into a single point of consumption (i.e., data warehouse). As part of this migration, Inspire11 cleansed and enhanced existing data, building automated data pipelines to refresh the organization’s data from multiple legacy systems.

Consolidating, automating, and cleansing the data was essential to the partner leveling up its analytics. Initially, Inspire11 performed the following activities:

  • Centralized the data from over 80 manufacturing sites, internal master data sources, and market/ reference data.
  • Developed a centralized platform displaying trade positions by leveraging PowerBI and Snowflake data warehouse.
  • Enabled aggregate analysis and drill-down capabilities to real-time contract status.
  • Developed tools to visually present ongoing movement and volatility within the market.

The development of analytics capabilities enabled our partner to gain a more in-depth understanding of current market perspectives and positions while avoiding any blind spots across the organization.

After the initial analytics foundation was established, the Inspire 11 team developed predictive financial models to recommend specific strategies based on historical contracts and pricing decisions. These predictive models include:

  • Automated transactions based on agreed-upon business rules and scenarios with high confidence.
  • Hedging rules created by running hundreds of thousands of simulations, allowing traders of various experience levels to drive consistent performance.
  • A historical benchmark for comparable years and market conditions to augment trader subject matter expertise and to deliver additional value.
  • A more holistic view of profitability founded on hundreds of models for commodity-shipping locations blended with freight costing data.
  • Push notifications to highlight and prioritize high-value opportunities requiring attention and management input.
  • Forward-looking predictive analytics tools to forecast trends and long-term market behavior.

Impact and Outcomes

With the help of Inpsire11 and the new predictive analytic foundation, the client was able to realize value aligned with the following areas: 

  • Revenue Gain: The organization leveraged this foundational data platform and predictive financial model to increase year-over-year contract gains by over 15%! The client recouped the project costs within three months of launching the solution. After launch, trading teams consistently sell within 5% of peak market prices.
  • Organizational Enablement: Our partner established an Analytics Center of Excellence (“CoE”) for group-wide adoption beyond the core project team, conducting dozens of PowerBI training sessions to further advocate the power and availability of analytical insights.
  • Paradigm Shift: The organization’s new capabilities allowed our partner to shift from reactive historical analysis and explanations to proactive, long-term strategic planning.

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