Only Black Swans will swim in the manufacturing pond of the future
IoT (Internet of Things) and analytics are all the hype right now. The terms are even at the top of Gartner's hype cycle. This means (according to hype cycle logic) that the next phase will be a phase of disappointment, when companies realize that these technologies are not a silver bullet to success - that there are no shortcuts to excellence. It's going to be around five to ten years before IoT and data-driven manufacturing takes the crucial tiger's leap in performance. The big question is: why so long?
There are many fields within manufacturing where IoT and analytics can be used - R&D, logistical processes, after-sales services, etc. In this article I’m sharing my thoughts from the manufacturing (make or assembly process) perspective - specifically, the clash between existing paradigms and new technologies.
Real Time Factory
Three years ago I started Real Time Factory, an initiative for discrete manufacturing companies that are facing demand for shortening production lot sizes, expanding product portfolios, and severe cost competition. The impetus behind this was the realization that we have to provide new types of capabilities to these companies to enable flexibility (lead time reduction), cost management (reduce wasted time and materials), and customer satisfaction (on-time delivery and product quality). Providing solutions in these areas can play an important part in justifying a company's existence in the marketplace.
Typically, manufacturing companies have built up their operational capability into an ERP (enterprise resource planning) system - this has been at the core of operations. A great deal is invested into ERPs and their complementing modules. Harmonization, one way of working, process stabilization, one set of numbers: these have been the magic words that were used to justify investments within an organization, all of those words are having slow feeling, aren’t they?
Era of White Swans
To my way of thinking, these decisions and approaches have been made in the era of White Swans. Processes are mainly carried out according to the dominant mainstream hypotheses, and exceptions play such a minor role that businesses feel they can ignore them importance of them and focus to the mainstream according to Pareto analysis or such. Demand has been somewhat stable, lot sizes have been larger, and production efficiency has been an imperative, especially at a time when globalization and cost competition has started to hit European manufacturing. Stabilization of the processes and products were seen as a weapon for cost competitiveness. Companies were focusing on producing a bevy of similar White Swans. Economics of scale.
The paradox between Black and White Swans
After that era, companies began to realize that cost competition is not something that European companies really pursue - they started to understand that the focus should be on differentiation. Instead of producing products, they have to focus on producing perceived value for a customer. This is a fundamental change to the previous mode of thinking, because perceived value by the customer is unique. Instead of a standard product, customers began to demand functions and features specifically designed for their own purposes, with the effect that these products are not that repeatable for other customers. This has led to the demand of unique products in the production phase (larger portfolios and smaller lot sizes). Every order becomes a Black Swan, something that shouldn’t even be possible. This leads to a paradox - White Swans are gone, but the old manufacturing paradigms and applications are designed to produce White Swans.
In the era of White Swans, manufacturing dilemmas have been top-down and time bucket-driven. Planning has been long-term, forecasting the demand for products or product families in time buckets of months. From the monthly planning the ERP crunched the numbers into weekly buckets, combined the forecast with customer orders, and converted that into a rough plan for the production execution process. On the factory floor a production manager, based at the site and with a good knowledge of operational circumstances, has usually come up with a working plan. In an ideal world, all facets of the planning and its related processes would go smoothly and according to schedule.
Black Swans as the new normal
There is only one but - and it's a showstopper. The business environment is changing continuously, all kind of events happen; these events don't wait for planning cycles; they don't respect time intervals - they just happen. These unwanted changes, these Black Swans, are now the new normal - and they can be triggered by many things, such as a shift in demand, or a customer requesting changes to some required functions at the last moment, or even after it.
And then there's unforeseen events such as problems with quality control, material shortages, equipment failure, employee illness - the list is endless. All of these disruptions are surprises that often come without any warning signs; they just happen. Any one of these events immediately invalidates even the most carefully prepared planning cycle. The plan was outdated on the moment it was published.
IoT - an event-driven technology
IoT and analytics have been heralded as the long awaited technologies that will enable a quantum leap in productivity. IoT is an event-driven technology - small sensors constantly check machine availability, material flows, movement of tools and vehicles, and the location or position of employees. This is no longer a plan-driven approach; it is a continuous observation and interpretation of real events. Event-driven decision-making is enabled by this observation and interpretation. This is event or exception management, rather than top-down planning.
This means that in a production shop floor environment the role of production planner (and even operator) will change. They will be more like firefighters, focusing on exceptions and rapidly adapting to changes, regardless of the planning cycle. The responsiveness of the factory system will have to be much faster than today's time bucket-driven batch.
Are you ready to swim in tomorrow's Black Swan pond?
I don't believe that any of these approaches is enough as a stand-alone. These two differing methods - one top-down and plan-driven, and the other bottom-up and event-driven - need to be combined to maximize both planning and responsive capabilities.
There are already systems that are trying to combine these two distinct approaches. However, it’s not so common that customers feel prepared to make the big changeover from the existing ERP-driven environment into something totally new. The transformation will be spurred by customers considering how best to complement their existing environments.
I've recently evaluated some of the advanced planning and scheduling software, and its capabilities to support the new event-driven approach. So far, it seems that the tendency is still to support time-driven planning, while also reaping the benefits from cloud infrastructure, and optimizing computing power in order to shorten cycles and become more agile.
I firmly believe that this metamorphosis is a journey that should not get too tied up in obscure and abstract technological terms. This journey will be long lasting. Along the way companies will need to consider the full range of their capabilities, the role of applications, their employees skillsets, and the very structure of their organizations. They will even need to examine the possibility of replacing single purpose machines with multi-purpose equipment. By undertaking these measures, businesses can ensure that they are fully prepared to swim in tomorrow's Black Swan pond.
Meet us at Manufacturing Performance Days 2017 on May 29–31, 2017 in Tampere and lets discuss more.