the case study in a nutshell


Lead Time
?? days

Related Solution
Production Planning

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This client is an agile and pragmatic pharmaceutical Company whose business is suffering from excess of stock, low equipment saturation and inadequate service level. A situation that in time could seriously jeopardise its leading position within the Italian and European industry. To face this risk, we have initially identified the main gaps in the IT systems and master data management and planned a set of quick actions to improve the overall data quality and information flows. Then we have implemented an AI-based production planning tool that achieves better saturation and better service level than a human performing the same task, in a fraction of the time.

Up to +5% equipment saturation on average w.r.t. the same plan done manually

Up to +8% OTIF on average on existing 2-years plans

1/10 of time spent on manual planning operations

Reduction of the WIP stocks

We tell you a story


Customer Profile

Amplifon S.p.A. is an Italian company that deals with the design, application and marketing of hearing aids. It is present in 29 countries and on all 5 continents, with more than 11,000 points of sale and around 16,000 employees and collaborators, and a turnover of 1.4 billion Euros. With the acquisition of GAES plant (Barcelona, Spain) in 2018, - has consolidated its worldwide leadership reaching a global market share of 11% of the retail hearing care market.



To design, validate and formalize a methodology in the Barcelona plant expandable to the whole EMEA region, with the following goals:

  • develop an earmolds integrated EMEA supply chain, capable of up to 600k earmolds per year;
  • reduce cost by 4.6 mEUR per year by improving sourcing and production effectiveness and efficiency, lowering the per full industrial cost from 13.9 to 10 EUR/unit;
  • maintain/improve current Service Level



We have developed from scratch a Digital Twin in order to:

  • simulate all possible future scenarios, obtaining precise calculation of lead times, service levels and saturations;
  • validate the re-layout/material flow hypothesis before any intervention;
  • find the optimal configuration in terms of allocated FTEs and shifts for any possible demand which yield maximal throughput.

We have also designed an OCR-based real-time digital traceability and jobs scheduling system, integrated with the existing ERP, for guaranteeing the optimal scenario in case of unpredictable demand and jobs priorities.



Customer profile

The client is a Pharmaceutical Company authorized by the Italian government to produce more than 100 APIs of various therapeutic classes. It has a GMP capacity that positions it as No. 1 in Italy and one of the leaders in Europe in the production of active ingredients for the pharmaceutical industry, with 1.750 highly specialized personnel across three different production sites and commercial offices all around the world.



The client is trying to emerge in a very regulated business environment and has asked for help in dealing with increasing complexity in production processes to avoid the risk of having its business killed. Tons of different, custom production processes and equipment resources makes production planning and asset management a nightmare, and this complexity is not well managed by existing tools. As a consequence, equipment resources utilization and service levels (OTIF) are unsatisfactory, and stocks are accumulating well above the needs.

This resulted in five company’s goals to be achieved through our intervention:

  • to receive an immediate support to manage the complexity in planning;
  • to improve service level and equipment utilization by better scheduling of production resources;
  • to improve efficiency in production planning operations that are now performed manually;
  • to identify the main gaps and define a set of quick-wins to improve the overall master data quality;
  • to support the improvement initiatives in the medium and long term.


Our solution

We have performed an in-depth analysis of the production planning processes, interviewing company’s experts and boiling down to the most granular level of detail possible. At the same time we have inspected the existing IT systems and databases, identifying the main gaps and focusing on how to improve data models to better represent the planning processes.

Subsequently we have designed and implemented a new digital tool for production planning, aimed to enhance planning operations and to be integrated with the existing systems (ERP/MRP) and S&OP cycle.

Leveraging on Artificial Intelligence algorithms, our tool allows to automatically schedule production plans on a 24-month horizon, finding optimal plans and alternative scenarios is a matter of minutes, and leading to improved saturation and service level while decreasing WIP stock at the same time.

After confirming the validity of the tool, we have eventually planned a set of initiatives to ease and improve data management, and to support the adoption of the new tool in all the plants.

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