Product development and sales planning are both fundamentally linked to the stages of the product life cycle: introduction, growth, maturity, and decline. Before a new automobile or truck is brought to market, product developers need to consider the potential for growth and the expected turnaround times between maturity and decline, in order to choose the features, materials, production strategies, etc. that will best fit the needs of an evolving market. Once the product is in showrooms and ready for consumers, sales planners need to consider the typical demand progression for a new product when reserving production capacity and managing the supply chain.
This is a complex high wire act under the best of circumstances—but in the modern era it’s a more challenging task than ever. Technology is evolving more rapidly than ever before, just as consumer buying behaviors and supply chain realities are doing the same. The result is that the tactics that served you well in previous product life cycles might not cut it anymore—and the tactics that would best serve may require new technology integrations that most supply chains simply don’t have. This isn’t necessarily a reason to give up hope or throw in the towel, but it is a reason to take stock of your current sales planning workflows, consider the ways product life cycles in the automotive industry are changing, and figure out what your company and your supply chain can do to keep pace.
How to Grapple with Accelerating Cycle Times
Perhaps the most obvious and pervasive trend in the automotive life cycle is the acceleration of cycle times over the course of the past couple of decades. Even before the era of Industry 4.0, this process was well underway: the average vehicle platform life cycle was about 8.6 years in the ‘80s, and since then it has contracted to a mere 6.7 years. The cause of this change can be chalked up to any number of factors, from increased global competition, to changing regulatory environments, to new and emerging technologies—but the effect is the same either way. Automakers have to generate new products more quickly, and they have less time in which to sell them to consumers, meaning that their windows for recouping development investments are shorter than ever.
This is obviously a risky situation to be in, and right now the upshot for manufacturers is that they simply have to improve performance across the board. They need to leverage smarter technologies and data-driven processes in the design stage, and then match demand and capacity with increasing levels of precision throughout the entire cycle. Even under normal circumstances, matching capacity to demand can be tricky—since the first task involves forecasting demand, which has historically often been a matter of guesswork. With increased pressure being put on this demand-capacity balancing act, it’s becoming more crucial than ever to adopt an S&OP (sales and operations planning) workflow that turns digital data from a variety of sources into smart, actionable forecasts that reflect emerging trends.
Evolving Mobility Means Evolving Product Life Cycles
With accelerating cycle times, you essentially need to predict the future on a quarterly time-scale—luckily, advanced analytics and AI make it possible to do that with real accuracy within the context of an integrated digital supply chain. Unfortunately, that’s not the only factor that planners have to grapple with in the current automotive product life cycle. Looking ahead to the next few years, it doesn’t take a machine learning algorithm to predict that innovations like self-driving cars and the increasing prevalence of electric vehicles have the potential to change mobility completely. For instance, mobility-as-a-service could potentially become the domain of car-makers themselves, meaning that the sales cycle would continue long after any given car had left the lot. If and when this happens, automakers will have to find some way to adapt product life cycle management to keep up.
While it’s tough to envision exactly what this new state of affairs could look like, it’s probably safe to imagine that connectivity and integration will be more important than ever before. Automakers will need to collect not just operational data from factory floors and logistics routes, but from cars that have already been sold in order to better understand changing usage patterns and translate them into new products and service offerings. Here, the ability to collect, store, and analyze huge quantities of information will be mission critical. If you have the infrastructure in place to receive alerts from IoT devices and RFID chips up and down the value chain, to sense demand through a variety of real-time market indicators, and to execute on supply chain plans with the push of a button from your centralized control tower, you can gain a clear-eyed view of emerging trends and adjust your both your product design and your demand-capacity planning accordingly. If not, you may have some work to do.
How Industry 4.0 Powers Smarter Processes
If the kind of connected IT environment we described above made you think of Industry 4.0, you’re on the right track. Smart factories and smart supply chains will be key if you’re going to keep pace with the demands of accelerating life cycles. Why? Because they’ll help you to reduce waste, cut lead times, and generally bolster efficiency in such a way as to best capitalize on short-lived demand spikes or trends in consumer behavior. In this way, you can translate operational agility into cost reductions across the entire life cycle.
Of course, there are also specific Industry 4.0 technologies that can help make these shortened and evolved life cycles more workable. Additive manufacturing (aka 3D printing) presents just one example: with rapid prototyping powered by 3D printing workflows, you can get immediate design feedback in the early stages of creating a new product, helping you to work out the kinks that much faster and avoid disruptions further down the road. As it happens, this same kind of rapid fabrication can increasingly be used in the production process itself, e.g. for specialized tools that might otherwise take time to acquire. Thus, you reduce disruptions within the context of production flows that are already smarter and more thoroughly digitized. This is just one example of how these different elements of Industry 4.0 can work synergistically—for companies that are able to take advantage of them.
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