Blog Posts Process Analysis

Supply Chain Optimization: BASF Solves a Major Challenge

Blog: Enterprise Decision Management Blog

BASF has optimized one of the world’s largest supply chain networks using FICO® Xpress Optimization. BASF’s advanced business analytics team used the mathematical optimization software to map all of the company’s supply chains at once to weigh the economic value of an investment, a massive computational challenge.

For its supply chain optimization achievement, BASF was awarded a 2018 FICO Decisions Award for AI, Machine Learning & Optimization.

“The chemical value chain is highly complex. When making strategic investment decisions, you have to take into account multiple global production sites, interdependent plants, manifold products and various businesses,” said Franz Joachim Schwenke, head of the Advanced Business Analytics team at BASF. “Our team of data scientists is constantly searching for new opportunities, to make available data more transparent and create solutions which support strategic and tactical decisions. We created a solution that can accurately evaluate the impact of strategic and tactical decisions like investments into new production plants for an entire chemical supply chain.

“To make it easier for BASF employees to use, we integrated the solution in a FICO Xpress Insight web application,” Schwenke said. “With this interface, it is possible to generate scenarios intuitively and easily share them with other users. Our colleagues especially appreciate that input data and the optimization results are shown via interactive dashboards and network graphs, making it easy to compare several scenarios at a glance.”

FICO® Xpress Solver can consider an entire value chain at once with all its relevant constraints. Through the detailed modeling of the interdependencies between the different business units participating in the value chain, the total economic value of an investment can be evaluated faster and more accurately. The project combined strong mathematical optimization models with a business-friendly user interface.

While the data preparation as well as scenario calculation took several months in the past, the new application allows BASF to generate a scenario within a couple of minutes. In addition, the usage of mathematical programming has led to a major improvement in quality of value estimation.

“BASF showed an innovative use of technology in a supply chain optimization project with very large-scale and very complex problems,” said Sid Dash, research director at Chartis Research. “They solved challenging data representation and computational problems that just could not be addressed using spreadsheets. The judging panel was impressed by the scope and scale of their achievement.”

Thanks to BASF for their impressive supply chain optimization entry, and to our panel of judges:

BASF and other winners of the FICO Decisions Awards will be spotlighted at FICO® World 2019, the Decisions Conference, November 4-7 in New York City.

The post Supply Chain Optimization: BASF Solves a Major Challenge appeared first on FICO.

Leave a Comment

Get the BPI Web Feed

Using the HTML code below, you can display this Business Process Incubator page content with the current filter and sorting inside your web site for FREE.

Copy/Paste this code in your website html code:

<iframe src="https://www.businessprocessincubator.com/content/supply-chain-optimization-basf-solves-a-major-challenge/?feed=html" frameborder="0" scrolling="auto" width="100%" height="700">

Customizing your BPI Web Feed

You can click on the Get the BPI Web Feed link on any of our page to create the best possible feed for your site. Here are a few tips to customize your BPI Web Feed.

Customizing the Content Filter
On any page, you can add filter criteria using the MORE FILTERS interface:

Customizing the Content Filter

Customizing the Content Sorting
Clicking on the sorting options will also change the way your BPI Web Feed will be ordered on your site:

Get the BPI Web Feed

Some integration examples

BPMN.org

XPDL.org

×