The uncertainty of the markets and the resulting difficulty in sourcing materials/products have challenged the effective functioning of the Supply Chain by bringing it to the attention of corporate management and enhancing its strategic centrality.

Many companies have reviewed their Supply Chain strategy, considering:

  • More inventories;
  • More back-up suppliers;
  • Reassessment of local suppliers.

The resulting risks are increased management complexity, higher costs (inventory capitalization, raw material prices, …) and a reduction in the service level (because of insufficient measures in uncertainty management).

Considering that, is essential a planning model towards excellence to address the current uncertainty.

Reshaping the planning model means acting simultaneously on six key areas:
  • Logistic-productive Network: the planning model must take into consideration the company logistics-production footprint in terms of materials and suppliers, products, production models and markets covered;
  • Processes: one of the critical points to achieve planning excellence is to design a structured but flexible planning process and ensure an effective coordination and integration with other supporting processes in place;
  • Roles and Responsibilities: all the impacted roles/functions must be involved in the planning process; it determines the need for the definition of coordination models that optimize the process and reduce the “effort” of the resources involved;
  • Rules, Parameters and SLAs: the effectiveness of an integrated planning process is strongly determined by a correct and effective definition and sharing of SLAs, management policies and logistics and planning data and parameters;
  • KPI: to guarantee the adherence of the planning process to business objectives (which may change over time), the implementation of KPIs control models consistent with business strategies is essential;
  • Tools: systems must ensure support and added value for planning activities, integrating and facilitating communication between roles and business functions continuously involved throughout the process. More and more systems supporting planning are being equipped with AI and machine learning capabilities to leverage internal and external data and provide increasingly accurate forecasts. To ensure their correct functioning, it is essential that predictive algorithms integrate with proper Data strategy and Data governance.
The proposed approach is based on three main phases articulated into a series of activities:
1.  Design
  • Assessment and Diagnostic: interviews with key person and data collection/analysis;
  • Challenge and Guidelines: key process guidelines and quick wins identification;
  • To Be Model: definition of new operating model;
  • Plan: prioritisation of improvement actions and change management.
2.  Implementation (preparation and deployment):
  • Quick wins implementation;
  • Preparation;
  • Launch of the new model.
3.  Follow-up (roll-out and fine tuning):
  • Monitoring and control;
  • Change management;
  • Model fine-tuning.

A planning review model that exploits this approach manages market variability while still maintaining a high degree of flexibility in business decisions.

The expected benefits can be many, including improved customer service, improved risk and criticality management and better coordination among supply chain actors in terms of effectiveness. While in terms of increased efficiency, a planning model towards excellence can lead to stock optimization and obsolescence reduction, production optimization and reduction of process duration.

For further information, please contact:

Antonio FOIS

Valentina BARTOLO