We've seen so very much in the media recently about IIoT and its potential to benefit consumer and manufacturer alike. Trends around IoM (Internet of Manufacturing) and Industry 4.0 are all largely focused on operations but where does the potential lie for big data within the supply chain?
Without doubt one of the largest benefits, and one of the key requirements, of any data based modelling is the ability to take a holistic view. Much of the product realisation process has previously taken place in silos, design, planning, purchasing, manufacturing, fulfilment and after market service. With big data and IIoT we are offered the full genealogy of a product throughout its entire life cycle from concept to end of life, cradle to grave as many like to say.
Design is the best time to ‘get it right’
The design process is where the real DNA of a product is defined and as such is the time to ‘get it right’, avoiding mistakes or compromises that will encumber the entire product life cycle and the supply chain. Starting the genealogy here using CAD data that is then available throughout the process adds a great deal of value to every step that follows and ensures that we constantly refer to the right data, and not some derived from that. But it is not a one way street, big data, well mined and properly delivered from previous product life cycles can inform and influence design in a way that can improve in-market performance, manufacturability, inventory control, rick management and supply chain agility.
Transparent and traceable
The biggest benefit of IoM or IIoT is the sheer volume and completeness of the data available and as a resulting ability to achieve complete supply chain visibility and traceability effortlessly!
‘Effortlessly’ is the key word here! Full traceability in the supply chain has been requested and in many cases required for sometime and systems and software have been developed to deliver that traceability, but with a real IIoT enabled and integrated supply chain it should come as a by product, allowing basic, but detailed genealogy of any product from the device in the consumer’s hand, right back through sub-assembles and PCBAs (Printed Circuit Board Assemblies), to the components on the BOM (Bill of Materials) and even the raw materials that make these up. Simple dashboards and the ability to interrogate data points, can make even the most arduous traceability requirement a walk in the park.
With this traceability comes transparency, the ability to see through all processes to every part of the supply chain, allowing the user to understand the impact of any change, be that an engineering or design change, a products specification change, a demand change or a change caused by supply chain disruption.
Brands are increasingly, and rightly, held accountable for their supply chains, and IIoT can help them insure supply chains comply with requirements around labour regulations and conflict materials. A brand really needs to know where everything in its supply chain comes from. Recent TV exposés on the supply chains of some of our favourite brands have shown the damage to reputation that can occur because of poor supply chain visibility, something the apparel industry suffered with in the past and is still has challenges by.
Control, control, control
Every supply chain manager should be a control freak, measuring and monitoring as much as possible and using data to plan, to mitigate risk and to be ready to answer a question like “if we phase out this product is Asia, double volumes with a two for one offer in the Americas and change the specification in Europe, how will our lead times and costs be affected?” Being able to answer that question is where the supply chain manager really earns his corn. Big data from IIoT, properly processed should put this kind of information at the executive’s fingertips.
What’s more this data should make for better supply chain design in future. Understanding the impact of certain selections, like manufacturing geography, whether to make or outsource, component sets, materials and transport, stock and fulfilment strategies.
I mean the supply chain, not the Tom Cruise movie. Supply chains are made up of a ridiculously large number of nodes all of which have their own inherent associated risk and most of which are critical to successful product fulfilment. This makes risk management essential and complex. IIoT and big data provide information and the ability to model risk and plan for disruption. In an ideal world when occurrences like floods in Thailand or volcanic dust clouds over Iceland are spotted the impact and a mitigation plan should be quickly and easily available, ensuring a calm and calculated decision making process rather than panic.
The cost of inventory is often underestimated and the design of the supply chain impacts on that cost hugely. Tied up cash, risk of inventory overhang and cost of changing vendors all contribute to inventory cost, and good data recording and analytics can help reduce all of these. Low inventory isn’t always the solution and any reduction has to be balanced against the risk of supply chain disruption, but there’s no doubt good inventory control make for a more agile and efficient supply chain.
After market and end of life
The role of data doesn’t end when the product is shipped or even when it reaches the hands of the user or consumer. IIoT can provide huge value to analyse returns or field failures and manage recalls or upgrades, providing information for speedy corrective action and feedback into the supply chain that impacts on future product development and vendor selection. Thus the supply chain is a learning intelligent system, a ‘cyber physical system’ if you will, improving and enhancing its own performance.
Beyond all of these after market services comes the end of the products useful life and again IIoT has a role to play here, providing data on what can and can’t be recycled or on any hazardous materials that might need specific handling.
So, from cradle to grave and in that elusive recycled ‘life after death’, IIoT has a role to play and value to add. Good data saves money and creates improved supply chains that benefit everyone involved including the consumer.
Better data, better decisions.
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