EXPLORE OUR CUSTOMERS'
SUCCESSFUL STORIES
EXPLORE OUR
CUSTOMERS'
SUCCESSFUL STORIES
An IBP platform to answer
KEY BUSINESS QUESTIONS
Embotelladora Andina S.A. is a holding company mainly engaged in the production, distribution and marketing of Coca-Cola products, operating Chile, Brazil, Argentina and Paraguay.
For Coca Cola Andina, an Integrated Business Planning Model was developed that allows to quickly generate the Business Plan, allowing to answer key business questions, such as: How much is the marginal contribution per Business Unit, in which production plant is it more profitable to produce, from which distribution center is it more convenient to supply every region, etc.
This tool radically streamlined the planning process by making it easier to create scenarios and allowing budget forecasts to be updated when each scenario is changed.
SALES, OPERATIONS, FINANCE
SALES
Improving the level of service and
REDUCING LOST SALES
Arcor is a global corporation focuses mainly on three verticals: food production, agricultural production, and production of packaging materials. It develops leading brands that reach customers in more than 120 countries.
Arcor has more than 40 production plants in Latin America, exporting all over the world and has more than 21,000 employees. Arcor Argentina sought to improve the level of service and to reduce the lost sales for the caramel cookies line by a more efficient planning and management purchase orders.
For this purpose, a Vendor Management Inventory (VMI) model was developed to align the caramel cookies production with supply chain with demand. Two modules were developed within the tool: Demand Forecasting Module and Stock Policy Management Module.
The VMI tool allows to make weekly Sell Out Forecasts for more than 160 distributors for the whole caramel cookie line. With this tool, Arcor improved the frequency for updating forecasts reaching 90% accuracy and drastically reducing stock-outs in the distribution chain. Thus, availability of products at selling points improved substantially.
IMPROVING DEMAND FORECAST ACCURACY
for more than 1,300 SKU’s
Nestlé is a worldwide food production company that has been operating in Brazil for more than 100 years. It produces more than 1,350 different SKUs.
A unique planning module was developed, built from previous existing Nestlé models and best practices. This module includes a Baseline Forecast, BIAS analysis, trend analysis, trade marketing alignment, risk analysis and volume broken down by SKU. The module runs approximately 6,000 data series on a weekly basis which allows for updating the Sell-In Forecast for every Nestlé’s SKU.
The Demand Planning module allowed Nestlé Brazil to improve the demand forecast accuracy for all its Distribution Centers.
SALES, OPERATIONS
SALES, OPERATIONS
A collaborative tool to empower the
DEMAND FORECASTING PROCESS
Eurofarma is a multinational corporation based in Brazil which produces biopharmaceutical products. It is one of the largest producers of medicines in Brazil and in Latin America.
A Demand Planning Model was developed focused on solving the problem of Building Blocks Collaboration. The tool delivered to Eurofarma allows the interaction of more than 27 analysts who collaborate to adjust Base Demand Forecasts of more than 395 SKU’s. The model runs on a monthly frequency, reaching an aggregate MAPE of 13.23%.
Until discovering the benefits of Pyplan, Eurofarma could not find any other tool with the flexibility and speed that Eurofarma required to carry out the collaborative demand forecasting process online.
A short and medium-term planning Model to
OPTIMIZE MILK PRODUCTION
Alpura is the second largest dairy producer in Mexico. It has a portfolio of more than 240 SKU’s that are produced in 3 different plants where more than 3.0 million liters per day are processed. These three plants are supplied by Alpura‘s more than 150 own ranches as well as by other associated ranches.
One of Alpura’s biggest challenges was to manage the variability of milk supply in the short and medium term. Alpura did not have a flexible tool capable of collecting and analyzing data, performing complex calculations in a collaborative way, nor providing insights for adapting the planning process to manage the restrictions of milk supply.
A solution especially for the Dairy Industry was developed for Alpura: The Milk Production and Balance Optimization Model, which allows Alpura to generate a collaborative production plan for the short and medium terms, considering milk supply availability and production constraints.
OPERATIONS
OPERATIONS
Improving efficiency in the compliance process
TASK AND DATA UPDATE AUTOMATION
Global Bank is the second largest bank of Panama beginning its operations in 1994. It was originally conceived as a purely corporate bank. However, due to the considerable growth during the first years and with the vision of becoming an important player in the financial sector, in 1999 Global Bank acquired 100% of the capital stock of Colabanco, becoming an important player in the retail banking business as well.
For Global Bank supported by the Pyplan Platform, a system was developed allowing the bank to automate data updates and to consolidate information from Compliance Alerts. With the new tool, the productivity of analysts in attending the alerts was doubled, the quantity of Overdue Alerts was reduced by 90% and the necessary time for generating reports for both internal and external stakeholders was reduced drastically.
A financial planning tool
TO ENHANCE DECISION-MAKING
Pirelli is a leader in tire manufacturing in Brazil and had a complicated financial planning process due to the use of different tools and spreadsheets. The company was looking for a tool that would allow it to optimize this process and facilitate report visualization at different hierarchical levels, including the headquarters in Milan (Italy).
With Pyplan FP&A, Pirelli Brasil was able to optimize its financial planning process and obtain significant benefits in terms of efficiency and decision-making. The benefits obtained include a reduction in budget preparation time, greater clarity and speed of visualization for hierarchical areas, detailed visibility of historical and forecast data, dynamic integration with other internal data sources (ERP), shorter monthly forecast update time, and the ability to generate and analyze multiple scenarios.
FINANCE
SALES, OPERATIONS
An Integrated Pricing Model
TO ENHANCE TOLL REVENUES
Supported by the Pyplan Platform, for the Panama Canal a Route Competitiveness Assessment and Pricing Model was developed. With the new tool the Panama Canal was able to optimize its Tolls Schedule paid by many different types of vessels traversing the Canal.
The implemented model is based on the calculation of transportation costs for more than 1,000 maritime routes that link the origin and destination of 200 ports around the world.
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