Quantrix Delivers Dynamic Forecasting to Molymet

Materials-intensive businesses need numerous 'what if' financial scenarios to manage purchasing decisions effectively. For Molymet, a global metallurgical firm headquartered in Chile, switching from spreadsheets to Quantrix enabled the company to develop multiple scenarios for income statements, create more insightful forecasts, and have greater confidence in its data and models.

Molybdenum and Metals, SA (Molymet) delivers molybdenum products and transformation services to customers around the world. The firm must purchase materials in the long term, but multiple variables impact its daily business, including the price and timing of purchases. It created its initial business models with spreadsheets, but over time the models became increasingly difficult to manage. “We loaded data by hand, retrieving information from different systems, and executed calculations and transformations needed to incorporate information into the model,” says Juan Cristóbal Valenzuela, New Business Manager, Molymet. “The process took around eight hours - an entire workday - and the spreadsheets were always vulnerable. We had excessive formulas, and unrequited modifications.”

The company worked with Quantrix Consulting Partner, Ingemax, based in Chile, to find a way to create forecasts using dynamic pricing, to better use its historical data, and to create a more stable modeling environment. “Molymet needed to develop forecasts based on changes in income and expenditures, but its forecasts were not connected to its income statement or cash flow data,” says Max Jungjohann, Proyect Director, Ingemax. “We introduced Quantrix, which enabled Molymet to create multiple ‘what if’ scenarios based on price and timing of purchases.”

The switch from spreadsheets to Quantrix immediately reduced the time required to develop insightful forecasts, and enabled Molymet to push forecasts out multiple years. “Before, it took more than a month to do a projection. It was so time-consuming Molymet only projected one year out,” says Jungjohann. “Now, Molymet can create scenarios in the same day, and has developed three-, four-, and five-year forecasts.”

In addition, Molymet can link its projections to past history to develop a base case for forecasting. “They can leverage their history, making decisions more dynamic, and really enhancing their ‘what if’ analyses,” says Jungjohann.

For Molymet, the benefits of switching to Quantrix are clear:

  • More efficient modeling: Unlike spreadsheets, Quantrix is designed for financial modeling activities like budgeting, forecasting, planning and 'what if' analysis. Molymet was able to eliminate many spreadsheet formulas due to the simple, transparent and orderly logic of Quantrix Modeler.
  • Improved data management: Quantrix links to multiple Molymet data sources, and streamlines data integration and management. While the extraction, transformation, and data loading of the old spreadsheet model took an entire workday, in Quantrix the process is reduced to 10 minutes.
  • Greater confidence in data and calculations: Excessive formulas and limited data access made Molymet’s spreadsheet models vulnerable and unsound; with Quantrix, the company has more confidence in its models' calculations and data accuracy.
  • Model replication: Molymet’s success with its new Quantrix model enables it to replicate it for other companies within the group.

“The main contributions of Quantrix are the increased efficiency of developing forecasts, increased certainty of the data in the model, and easy development of different scenarios,” says Valenzuela.

Molymet is now in the process of reviewing the transfer of other data and calculation-intensive spreadsheets to Quantrix. “This will allow us to manage the information in a much more productive, safer and easier way,” says Valenzuela.