Faller Packaging had long relied on manual, intuition-based forecasting, with sales representatives and customers providing personal estimates. This system resulted in forecasts that were backward-looking and often inaccurate. As Gerardo Rendina, Vice President IT & Digitization at Faller Packaging, explained, “Our forecasts were based on past trends and subjective estimates from sales people. There was no data-driven approach.” This posed significant risks for the business, particularly when key decisions—such as investments in production lines—were made based on these flawed numbers.

In addition, for some time Faller Packaging had only been able to fulfill its lead time promises with increased effort - a situation that has become increasingly acute in recent years. In order to position the company sustainably and competitively and to better meet the increasing demands of its customers, Faller saw the need to introduce a scalable, data-based solution. Nils Hoepker, Manager Logistics & Demand Management at Faller Packaging, articulated the vision behind the project: “We wanted to move from relying on subjective forecasts to being able to generate neutral, AI-driven numbers that offer us a future-oriented perspective in order to better and more easily meet the needs of our customers.”

Paretos introduced a comprehensive, data-driven forecasting system to Faller Packaging, supplementing the traditional gut-feeling approach with an automated model based on five years of historical sales data. The new system enables regular, reliable sales predictions that can be easily reviewed by the sales team.

The solution was built with scalability in mind. Gerardo emphasizes, “With paretos, scalability is built-in. We started with one use case and a small team, and from there, we can scale by simply adding more product groups or even extending to new production sites.”

A key component of the new system is the rolling forecast, updated monthly, which provides predictions up to 17 months ahead. This enables Faller Packaging to react more swiftly to market changes and optimize resource allocation, aligning perfectly with their goals of improving delivery reliability and reducing warehouse costs.

Gerardo’s priority for fast time-to-value and low total cost of ownership also played a role in choosing paretos. He noted, “The focus was on action and results, not endless discussions about ROI.” Thanks to a quick and iterative implementation, the project achieved time-to-value in just four months.

Implementing paretos' forecasting model brought immediate improvements. Forecast accuracy improved by 50%, providing a far more reliable basis for decision-making. The new system also freed up considerable time for the sales team, allowing them to focus on strategic tasks rather than manual forecasting – all achieved with a short time-to-value of only four months.

Faller no longer relies solely on customer forecasts, instead using the objective predictions from paretos to engage in more informed discussions with their clients. “The paretos forecasts provided us with a neutral, AI-driven input that we can use to guide our discussions with customers. It’s a completely different level of engagement now,” Nils noted.

Although specific savings figures are still being calculated, the improved forecasting accuracy and efficiency have already led to a reduction in financial risk and operational inefficiencies. The return on investment will be achieved within the first year of the collaboration, further underscoring the solution’s economic viability and added value.

Faller’s journey with paretos is only just beginning. Following a successful test run with a limited product group, the company is now looking to scale the solution to cover additional products, locations, and even integrate AI-driven forecasts into production planning. As Nils sums up, “This is just the beginning of an optimization journey. We’re already thinking about how to apply these insights to procurement and other logistics processes.”

A planned next step is to use the increased forecasting accuracy to further optimize processes and reduce costs - particularly in warehousing and logistics. More precise predictions of stock requirements will help to reduce excess stock and minimize storage costs.

With paretos, Faller Packaging has transformed its forecasting from a manual, intuition-based process to one that is automated, scalable, and data-driven. This shift has not only improved operational performance but also positioned the company for continued innovation and growth.