Making sure your goods reach the customer at the right time, and in the right quantity, means taking into account a wide range of factors including production scheduling, distribution planning, and getting the right balance between demand and supply.
Supply chain planning (SCP) can help predict future requirements to balance supply and demand, enabling the business to reduce inventories and operate more efficiently. SCP tools may may include supply chain modelling, and design, distribution and supply network planning, according to TechTarget.
These solutions use complex algorithms, optimisation techniques and heuristics to solve supply chain problems that occur in the planning horizon (one week to one month for operational planning, one month to several months for tactical planning, and one year to multiple years for strategic planning).
In the market for SCP software, artificial intelligence (AI) and machine learning are becoming key differentiators, according to new research by ARC Advisory Group.
Analysing the global supply chain planning market, ARC found that it is well on its way to moving over from a software licence model to Software-as-a-Service (SaaS) pricing, and customers are rolling SCP projects into wider digital transformation efforts.
Customers are also expressing interest in SCP solutions that leverage AI and machine learning. Machine learning has long been used to improve demand planning solutions, and now it is being explored in the realm of supply planning and for updating core parameters in SCP engines, ARC reported.
Machine learning is the battlefield in the “arms race” between software vendors to achieve differentiation, the research firm said.
While the progress so far can be characterised as “incremental rather than revolutionary“, SCP companies have “interesting product development” going on in these areas, said Steve Banker, VP of Supply Chain Services at ARC Advisory Group and key author of the Supply Chain Planning Global Market Research report.
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