Seasonality, which refers to regular, predictable fluctuations that recur year over year, has traditionally been a major factor in automotive manufacturing. Since car sales often spike in spring and autumn (when new models are traditionally released) and drop off in winter and summer, manufacturers can and do factor seasonal slow-downs and increases in demand (potentially including demand for new parts) into their production processes. With the rise of Industry 4.0 and the emergence of an increasingly global supply chain, however, the nature of seasonality is rapidly changing. Let’s take a look at how seasonalities operates in modern manufacturing.
Industry 4.0 and Seasonality
The rise of Industry 4.0 has already expanded our understanding of supply chain management, bringing increased visibility across the entire value stream. The result is that manufacturers can expand their ideas about seasonal phenomena to include not just shifts in demand or annual slowdowns, but yearly cycles in costing, capacity usage, transport planning, and other areas that impact the entire production stream in myriad complex ways. For instance, a European manufacturer with a Canadian supplier might notice that weather-related transit delays in, say, Ottawa were causing suppliers to miss parts shipments during especially inclement winters. With real-time integration in pricing and transport logistics, it might be possible to make seasonal adjustments to the supply stream by dynamically utilizing different hubs, warehouses, or vendors depending on weather forecasts and historical trends.
Of course, weather-related delays are among the more obvious seasonally recurring disruptions, but the cyber-physical systems that characterize Industry 4.0 allow businesses to gain greater insight into the wide-reaching effects of these disruptions and the flexibility to mitigate those effects. A global supply chain means more annual disruptions (not just from weather but from shifting trade relationships, holidays, and other cultural practices), but it can also mean a more adaptable, responsive value stream, enabling companies with a robust understanding of their own needs to take advantage of new possibilities and engage in more dynamic sourcing and transport processes.
Rogue Seasonality
Though we often think of seasonal production changes as the result of external forces like product demand, manufacturers also need to cope with seasonalities that originate in their own internal workflows, also known as rogue seasonalities. These can arise from numerous causes, including:
- Siloized decision-making, resulting in perennial resource shortages
- Inventory restocking rules that fail to account for periodic fluctuations in demand
- Static transport routing and container management strategies that don’t optimize usage
- Over-reliance on “just-in-case” stock holdings
- Poor vendor or IT choices
Essentially, rogue seasonalities can hide more serious supply chain issues under the guise of seasonal shortfalls. What may appear to be an external disruption might prove to be the result of a subtle flaw in supply chain design.
In an Industry 4.0 environment, increases in transparency can unmask many of these potential hiccups. A robust transport logistics solution, for example, would help to make one’s routes and freight usage leaner and more dynamic, thereby helping to eliminate bottlenecks that might otherwise be difficult to identify as such. By the same token, a similar solution could provide a significant boost in supply chain visibility, leading to a more holistic understanding of one’s value stream overall, including any potential rogue seasonalities.
Predictive Analytics
It’s common in the automotive industry for an expected summer lull in sales to have wide reaching effects on throughput and production systems during other times of year. But what if, in a given year, the annual summer slowdown never occurs? This isn’t an unheard of turn of events, but it can leave manufacturers scrambling for parts and struggling to meet demand. In the era of modern manufacturing, however, businesses can take steps to avoid being blindsided by unpredictable turns of events. A more flexible Industry 4.0 supply chain can help mitigate disruptions, but one of the most powerful risk-management tools a given company might have at its disposal is advanced analytics.
By opting for an increasingly digitized supply chain, manufacturers can integrate predictive analytics into their supply chain planning. Not only can advanced supply chain analytics add significant value in terms of intelligent planning, it can drive more accurate, comprehensive forecasting. In this way, companies can gain a more future-oriented perspective on seasonality, relying less on past demand fluctuations and more on the complex sequence of factors that predictive analytics can take into account when determining the need for seasonal adjustments. While seasonalities will certainly remain a factor in the world of modern manufacturing, they will morph from a set of rote conventions into a dynamic reimagining of global value chains.
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