How AI-Powered Planning Will Drive Demand Forecasting
The electric vehicle (EV) market is surging forward as top automakers, including Porsche, Toyota and General Motors, make strides towards refining their EV offerings. Yet, as the automotive sector embraces sustainable mobility, a host of challenges await on the path to better demand planning, efficiency and profitability.
Automotive demand planning teams especially face hurdles.
According to Salim Shaikh, Corporate Vice President of Industry Strategy at Blue Yonder, who elaborates in his blog, Automakers, it’s Time to Check Under the Hood of Your Demand Planning Solution.
"It’s difficult to get the product mix right — across EVs, internal combustion engines (ICEs) and hybrids — by channel and region," Salim notes, highlighting the complexity of shifting demands across multiple segments.
Further complicating this landscape is a growing consumer appetite for customisation, as buyers now expect smart features and personalised options in their vehicles.
With continuous developments in electric and hybrid technologies, accurately anticipating market demands and preferences has become essential for manufacturers. Inaccurate demand predictions can result in overproduction, leading to unsold inventories and price cuts that cut profitability.
Adding to these challenges: "Consumer preferences and demand vary greatly across global markets," Salim points out.
"Getting the mix wrong can lead to excessive, ageing inventory on the one hand and missed sales opportunities on the other. OEMs that can accurately assess consumer needs and adapt their supply chains accordingly will be the ones to remain profitable."
For many automakers, this means substantial investments in new plants, advanced technologies and diverse distribution channels. Yet the benefits of these investments remain uncertain, especially as manufacturers face lasting impacts from the global chip shortage, a challenge that persists despite recent recovery.
"While the global chip shortage is firmly in the rearview mirror, automakers still face supply shortages, partly due to the large component inventories needed to simultaneously produce EVs, ICEs and hybrid models," Salim explains.
Such shortages can stall production, affecting margins, sales and brand loyalty. Therefore, effective demand planning becomes vital to ensure efficient production and sustained profitability.
AI-driven demand forecasting: A necessity for modern automotive planning
Salim argues that outdated planning solutions no longer suffice in today’s dynamic automotive industry. An ideal solution, he suggests, would integrate advanced technologies like artificial intelligence (AI) to streamline forecasting processes and align production with consumer demand.
"To keep pace with all the changes in the marketplace, while also identifying and managing disruptions, automotive planners need an advanced solution, enabled by artificial intelligence," says Salim.
The ideal AI-powered solution would handle vast amounts of real-time demand data alongside critical economic indicators, such as the consumer price index (CPI), inflation rates, gross domestic product (GDP) and fuel prices. Leveraging AI to create dynamic, rather than static, demand forecasts would allow planners to stay aligned with the latest market trends.
To meet this standard, an advanced planning solution would use predictive analytics and machine learning (ML) for in-depth demand forecasting across various regions, channels and vehicle types. It would compress the decision-making timeline from days to mere minutes and simulate “what-if” scenarios to help manufacturers navigate volatile market shifts, a capability Salim emphasises.
"The ideal solution would not only leverage advanced artificial intelligence (AI) and data science but also machine learning (ML), cloud computing and predictive analytics to compress the time horizon between planning and decisions from days to minutes," he explains.
Key features of Blue Yonder’s cognitive demand planning solution
Blue Yonder’s Cognitive Demand Planning solution offers an AI-powered approach that enables automotive manufacturers to forecast demand accurately and streamline production. Here are its three core features:
Advanced Scenario Planning
Blue Yonder’s solution enables demand planning teams to incorporate, refine and evaluate demand assumptions quickly, allowing them to better anticipate and react to fluctuations. With the ability to create, test and analyse multiple scenarios, planners can form actionable strategies faster. This fosters a continuous planning process that updates within minutes rather than on a daily or weekly basis, improving responsiveness.Real-Time Data Integration
By leveraging machine learning and advanced statistical models, Blue Yonder’s Cognitive Demand Planning can forecast demand across various regions and channels while considering demand drivers like inflation, GDP and fuel prices. These insights help adjust forecasts dynamically, aligning them with current market needs and reducing the risk of unsold inventory.Integrated Planning Framework
This solution unifies disparate decision processes, promoting a collaborative approach across departments. Enhancing supply chain visibility ensures a seamless alignment of production with demand across global markets, allowing teams to work from a shared, up-to-date data model.
With these tools, automotive manufacturers are better equipped to adapt their production to market demands, thus optimising investments and improving decision-making processes.
A changing industry and the role of AI-driven demand planning
The automotive sector is rapidly evolving as EVs reshape consumer expectations. To stay competitive, manufacturers need agile, data-driven demand planning solutions that can respond to fluctuating preferences.
Blue Yonder’s Cognitive Demand Planning leverages AI and machine learning to empower automotive companies to make timely, data-backed decisions. Salim underscores this necessity for change in the face of uncertainty and opportunity as the industry shifts towards a sustainable future.
"Automotive supply chains face significant challenges due to shifting customer preferences, inventory shortages and higher costs due to new technology investments, driving the need for more comprehensive, agile demand planning," says Charlotte Diener, Marketing Director at Blue Yonder.
"Blue Yonder’s Cognitive Demand Planning uses AI and ML to deliver advanced analytics, real-time simulation and integrated collaboration, helping predict demand, optimise product placement and manage uncertainty."
For automotive manufacturers looking to navigate these challenges and optimise their demand planning processes, Blue Yonder’s solution offers a promising path forward.
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