A Demand-Driven Supply Chain that can quickly adapt to market changes
DiaSorin S.p.A. works in the field of biotechnology, within which it develops, produces and sells tests (reagents and analyzers for blood analysis) for the diagnosis of alterations in the patient’s health status of infectious, hormonal or tumor origin. At the beginning of 2020, with the spread of the new Coronavirus outbreak, DiaSorin promptly developed a molecular diagnostic test to detect all known variants of COVID-19 as well as having developed serological tests to detect the presence of specific antibodies.
Objectives
The increased complexity of the supply chain both from the point of view of the distribution network and from the point of view of the managed product portfolio has prompted the company organization to quickly pursue the needs of the business, however, encountering some critical issues. In fact, the planning system was not fully aligned between its various components (commercial branches and production sites), causing on the one hand disruptions to final customers and on the other side causing obsolescence both at branch level and at production site level; a planning process that was also cumbersome because it was not supported by a structured system.
The company therefore wanted to invest in a Sales & Operation Planning system that would allow greater monitoring of the demand signal and greater coordination between the commercial branches and production sites.
Solution
The modules identified as the building blocks of the solution refer to the following components of the sedApta suite:
- Demand Management
- Inventory Management
- OSA – Analytics
Benefits
The main results achieved by the project can be summarized as follows:
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Increased frequency of pipeline reviews across the entire supply chain
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Automatic updating of various system inputs such as sales and orders → End-to-end consensus process across the entire supply chain
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Ability to create forecasts on aggregated views and subsequently propagate the data proportionally to lower levels
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Forecast accuracy calculated on ordered quantities rather than shipped quantities
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Possibility for demand planners to begin forecast review starting from the data saved in the previous month
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Greater central visibility on the management and planning policies of individual branches
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Improved visibility for branches regarding shipments in transit
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Automatic calculation of potential scrap.
