Continuous changes and a succession of critical issues impacting markets have created a “new normal” for companies: volatility has now become a constant that they must inevitably deal with. In such a complex context, it is essential to develop increasingly sophisticated planning capabilities by rethinking supply chains and processes.
However, Italian companies still seem to neglect proactive risk management. This is what emerges from the results of the Supply Chain Planning Observatory of the Politecnico di Milano. According to the research, the majority of companies manage supply chain planning with a reactive rather than proactive approach to turbulence. While 82% of companies monitor the main risk factors, only 26% of large companies and just 5% of SMEs have revised their risk management models. Only one in ten companies develops structured contingency plans and alternative scenarios, highlighting a still widespread fragility.
Supply Chain Planning projects and results achieved
According to the Observatory, around 60% of Italian companies have recently started digital transformation initiatives, especially in the areas of demand and production planning. However, these are projects that aim to act more at an operational than a strategic level, for example to resolve production issues (misalignments with production targets, quality problems, machine downtime, etc.). Other projects already underway involve adapting forecasting algorithms to market fluctuations and expanding the planning team.
As for initiatives for the near future, process automation is attracting the most interest among companies: 13% are planning projects in this area. In particular, SMEs are focusing on simple types of automation, such as Robotic Process Automation (RPA) tools that automate repetitive, rule-based tasks, increasing efficiency and accuracy in daily operations. Larger companies, on the other hand, are aiming to automate more complex processes, for example through Intelligent Robotic Process Automation. This is the evolution of RPA: it uses AI and Machine Learning to manage not only repetitive processes but also complex and variable ones.
Further projects to invest in the short term concern the area of training. SMEs are focusing primarily on technical training on planning tools and management systems. For large companies, on the other hand, the goal is to upskill the planning team to develop familiarity and the ability to use these tools for complex activities. Finally, other initiatives include training on statistical methodologies and Machine Learning, or cross-functional training and workshops to encourage participation in integrated decision-making processes.
Training and engagement of people
Training is certainly a key issue, as is the engagement of people in promoting change in Supply Chain Planning. The results of the digital transformation initiatives already underway clearly demonstrate this. Sixty-nine percent of large companies and 64% of SMEs have fully or largely achieved their objectives: only a small proportion have not achieved improvements. The reasons? As explained in the Observatory, the main obstacle in cases of failure is the human factor, i.e., staff resistance, the perception of systems as constraints, and unrealistic management expectations regarding the time it takes for new solutions to mature.
The support of technological tools
The technological evolution of Supply Chain Planning is linked to three key aspects: integration of information systems, data governance, and targeted applications of advanced technologies to automate activities and improve the quality and resilience of decisions.
With regard to the first aspect, connecting management systems (such as ERP, WMS, and TMS) allows for the alignment of forecasts, inventory levels, production flows, and transportation, reducing delays and misalignments. However, most Italian companies still work with partially integrated systems: only one-third of large companies and one in five SMEs have achieved full integration, with tangible benefits in terms of end-to-end visibility. The lack of full integration affects 15% of large companies and 36% of SMEs. The Observatory points out that this translates into high costs and loss of operational agility.
Behind these limitations is often a lack of clear data governance. According to the research, more than 20% of large companies and over 40% of SMEs do not have formal rules on data ownership, with consequences for the accuracy of plans, reporting, and consistency of metrics. Those who have already started data integration and governance processes are gradually exploring the potential of Artificial Intelligence.
