As in almost every manufacturing sector, interest in AI is growing rapidly in life sciences, with more than half of supply chain leaders expecting a return on investment in AI and machine learning (ML) within the next 2-3 years. The LogiPharma AI Report 2024, which surveyed 100 supply chain leaders in key positions such as logistics directors and planning managers, revealed that the top investment areas are:
– Inventory management and optimization (40 percent)
– Supply chain visibility and traceability (34 percent)
– Risk management (32%)
Note that a rate of12% is even more optimistic, expecting a return as early as within the two-year period following implementation.
The problem of segmentation
Despite the promise of AI, there is no shortage of difficulties: on the one hand, AI offers tremendous potential for improving inventory management, visibility, and sustainability; but on the other hand, significant obstacles still remain to be overcome. The problem most strongly felt by respondents is that of gaps in data integration.
In fact, 55 percent of the sample report that incompatibility between IT systems and the resulting data siloing hinders effective pharmaceutical supply chain management, especially in the cold chain. Data quality is a crucial factor:over 90 percent of the data needed to fully leverage AI resides outside of traditional business systems, making close collaboration with supply chain partners essential.
An integration yet to be achieved
Yet, most survey participants (55%) said they receive continuous, real-time information from just 11-25% of their business partners. An additional 39% indicated that they had slightly better coverage, receiving real-time data from 26-50% of partners.
Dependence on fragmented data and isolated systems can cause increased operational costs due to delays, wasted inventory, and logistical inefficiencies.
Difficulty in responding promptly to problems can cause disruptions and additional costs for urgent shipments, while ineffective inventory management increases the risk of surpluses or shortages. In addition, lack of complete traceability can prevent compliance with regulations, leading to penalties and compliance costs. However,only 1 percent of respondents reported receiving real-time data from more than 50 percent of partners in their network.
Different solutions
Improving connections between nodes in their network is therefore a priority,and 44% of companies focus on internal planning optimizations (e.g., S&OP) while 38% are committed to strengthening collaboration with partners through data sharing.
On the latter point in particular,38% of respondents prioritize third-party logistics providers to improve metrics such as inventory visibility and service levels, while 34% focus on contract manufacturers to optimize other metrics, such as working capital, through product tracking. Other solutions include agreements with carriers and direct suppliers.Only 1 percent plan to leverage customers (pharmacies, hospitals, etc.)to improve integration of data from point-of-sale and health services so as to be able to anticipate demand and speed up communication.
Implementation costs and the need for staff training are additional barriers to widespread adoption of AI. However, strategic vision and targeted investment could overcome these challenges and achieve significant operational improvements.
AI and cold chain
A section of the study is specifically dedicated to the cold chain, which “is at a crucial point, balancing sustainability, visibility and control. On the environmental sustainability side, the industry is mainly engaged in tracking greenhouse gas emissions: all respondents said they monitor this parameter, and52% of companies use specific tools to calculate CO₂, aiming for a kind of standardization of measurements.
Many systems and many doubts
.
However-although 78 percent show some confidence in the calculations, only 5 percent are highly confident of their accuracy, and are aware of the limitations of current ISO and GLEC standards. On the real-time visibility and control front, 69% of companies use automated alerts for temperature deviations, while 59% have centralized visibility into shipments, transport modes, and partners, and 52% are able to take real-time action to adjust packaging or routing.
However, obstacles such asfragmentation of systems and lack of predictive analytics persist, reported by 55 percent and 44 percent of respondents, respectively. Regarding future implementations, the top priority seems to be related to increasing sustainability (average rating 3.42) followed by improving real-time visibility and tracking systems (3.15).
