First Quantum Uses Advanced Analytics to Predict COVID-19-Related Supply Shocks

September 9, 2020 | by Preferred Strategies

First Quantum Minerals Ltd. (TSX:FM) is a global copper company that operates long life mines in several countries and employs approximately 20,000 people world-wide. First Quantum has an effective 90% ownership of Cobre Panama.

Using Data & Analytics to Proactively Manage the Supply Chain

The COVID-19 pandemic has brought a tremendous amount of uncertainty to businesses and supply chains around the world. To mitigate that uncertainty, the Information and Communications Technology team at Cobre Panama jumped into action. “We did something cool today—we created a live model that looks at possible supply shock risks as a result of COVID-19,” said Mario Romera, ICT Superintendent, Cobre Panama.

Their algorithm is based on the following reasoning:

  • Supply shocks are most likely in jurisdictions experiencing a rapid rise in new COVID-19 cases
  • The stock of inventory is weighted by where it is sourced from, with a five-day moving average of new cases per stock line item
  • The above assumption is then cross-referenced with current shipping restrictions and limitations due to COVID-19
  • The resulting algorithm is:
    [Stock at Risk] = [Qty on Hand] – [60 Day Average Consumption]-[Reorder Point] (Indicated where stock will fall below the reorder point in 60 days time, weighted for the COVID-19 Risk Factor)

The procurement and warehouse teams are using this model to explore and drill down to individual stock line items, by supplier and region. One use is to apply the algorithm to the most critical line items and contact the applicable suppliers to make contingency arrangements — before they become a problem.

The JD Edwards data required for this analysis is obtained from the Preferred Strategies QuickLaunch Enterprise Data Warehouse (EDW). First Quantum implemented the QuickLaunch EDW in early 2019 when they undertook an enterprise-wide data and analytics infrastructure upgrade. At the time they considered building their own EDW, however selected the QuickLaunch product with Microsoft® Power BI when they realized they could be up and running in just a few months, as opposed to the year or more that a completely internal project could take. QuickLaunch demystifies cryptic JDE data values and seamlessly connects that data to analytics tools such as Power BI—all under a secure and governed environment.

Enabling Self-Service Analytics for the Commercial Team

In addition to their timely application of predictive analytics to the supply chain, the team has also recently created a whole data suite for the commercial area, including procurement, sales and warehouse. “The commercial area went from having no visibility into their JD Edwards data to having full control over what is happening,” said Romera. This triggered a major working capital project that will use machine learning techniques to optimize inventory management as a first step. Now business analysts have easy access to data—and a better understanding of the potential of the EDW—and advanced users are even better equipped to get the best out of the tabular model and data warehouse.

Image 2: Decomposition of Inventory drill-down analysis

Contact: Mario Romera, ICT Superintendent, Cobre Panama

 
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