Supercharging Advanced Analytics: Process Manufacturing
Understanding The Value of Fast-Pivot Manufacturing in Industry 4.0
Companies are shifting from a traditional product-driven manufacturing model to a more consumer data, demand-driven manufacturing model.
This shift is critical in the adaptation of a data-driven manufacturing model, which includes the horizontal and vertical integration of the value chain and the improved management of data across the whole product life cycle.
Today’s winners are introducing a variety of higher value products, often consisting of frequent changeovers, and shorter production runs.
Companies such as Proto Labs are incredible efficiency and happily take on quick-turn short run manufacturing jobs that nobody else can afford to take on. The success of companies such as Proto labs is largely due to process engineering, driven by automation and proprietary technology.
The ideal Proto Labs customer is an engineer on a product development team who needs a physical prototype, or even a production part. They don’t want to send it overseas and wait eight weeks, only to find out that they need to make some changes. These product development customers are engaged in an iterative process, so delays in prototyping can kill the team’s time to market. Proto Labs solves that problem with delivery times as short as one day.*
This new environment of manufacturing requires advanced process control strategies and model predictive control (MPC) technology.
Traditionally, fast-pivot manufacturing process-management and information-technology capabilities were not as advanced as they are today leading to a less agile production strategy.
In recent years, modern yet affordable IT-driven internet of things (IOT) manufacturing solutions have emerged. Solutions such as Rockwell Automation’s Pavilion 8 help manufacturers face ongoing pressure in order to reduce costs and complexity, while leveraging existing technology investments. Companies looking to embed a risk managament or down time prevention strategy can look to intelligent assets within their systems to prevent manufacturing downtime and predict productivity. Intelligent assets are sensors, application software, controllers, and security components capable of built-in intelligence, self-diagnosis capabilities, connectivity to support analytic software solutions.
An example of short-run production successfully maximized at scale is Nike. In recent years Nike has made significant gains in monetizing what consumers refer to as color-ways. This trend was first proven lucrative within Nike’s Air Jordan brand. When the Air Jordan team initially re-released new color-ways, consumers responded with money in hand time after time causing re-sale conditions to spike. With such am agile manufacturing process, brands are able to align their brand with celebrity efficiently to maximize partnerships and quarterly profits. This is demonstrated perfectly by Nike when they announced a new limited run — Justin Timberlake x Air Jordan collaboration (due to his Superbowl Halfime scheduled performance).
This go-to-market startegy has now been perfected and applied to the modern-day product strategy as every Nike shoe will release in a single or limited color-way and periodically follow up with incremental re-release schedules containing the same shoe in a different color-way once sales data and online PR crown it a winning product.
On the contrary, the trend of short run (typically aggressive in color, design, and pattern selection) offerings has led companies such as Toms and Allbirds to slowly increase their marketshare within the lifestyle (less punch-you-in-the-face style) shoe division amungst some consumers.
To achieve strong revenue gains, manufacturers must double down on go-to-market strategies by focusing on consumer behavior and market conditions.
Balance is a key performace indicator from a macro POV. Companies that infuse consumer data into their production teams will see significant gains in revenue moving farward.
However, the future of analytics-driven production will only be as efficient as the products and consumer triggers being delivered by the internal product team.
Interested in chatting a bit more about IOT applications within your business?
I look forward to hearing from you!