Among other things, blockchain can introduce an element of transparency in the supply chain--another demand that wears heavily on the apparel-fashion industry. Where does blockchain fit into both ERP and PLM solutions?
Charness: ERP and PLM will not need to handle actual blockchain chains. But they will need to accept information from those chains to use, and will need to be able to pass information to write to a chain. Blockchain solutions themselves will handle the reading and writing. ERP/will pass the information along. ERP doesn’t care about the specifics of who has the inventory in transit, it just needs to know which PO, how many, and what is the estimated arrival date. As different parties update the chain as product moves from a manufacturer to truck to export to dock to ship to import to dock to truck to distribution center… as each party writes to the blockchain, blockchain passes the most relevant summary information on to ERP. It might be up to an ERP to flag that this data came from blockchain, so it is more “trusted” than other sources, but that would be the extent of it.
A PLM solution might see that a factory is on the blockchain they use, or that the last audit was collected via blockchain vs one that was not. But PLM itself does not need to handle blockchain data directly. If PLM is outputting items that are going to go into production in a factory, it might pass item data to a blockchain solution that would then create a new chain to track that specific item’s lifecycle. But PLM would trigger that by passing information it already passes on to other parties, which a blockchain solution would receive and do with it what it needs to do.
Munro: Adopting a common secure platform across the value chain is the best way to maintain transparency. In situations where a common platform cannot be adopted, blockchain provides a common methodology for supply chain verification across platform boundaries. This provides a choice between adopting a common methodology, or adopting a common platform. Bamboo Rose advocates for a common platform while recognising that 100 per cent adoption is never a truly achievable and blockchain provides a means to cross the platform gaps when necessary.
Jarry: Right now, we're not seeing a lot of demand for blockchain technology in the apparel industry, although that may change in the future as consumers become increasingly aware of supply chain issues and look for more watertight assurances about the origins of the products they buy. The exception is in luxury goods, where companies are looking into blockchain technology to prove the provenance or authenticity of goods. PLM/ERP vendors serving that market will have to consider the integration of blockchain technology if there is a significant demand for it.
Chidrawar: If it is a high-fashion brand, authenticity is a major benefit. Companies are looking to offer sustainable products, tracking farm to product. Many vendors and global suppliers can collaborate and conduct business leveraging the blockchain. Brands can connect and work with more trusted suppliers. Workflows need be integrated to PLM/ERP. For example, relating to payments, blockchain can facilitate payments and the ERP can complete the entire transaction. In addition, ethical compliance related to sustainability, documents can be part of the blockchain (connected to the ERP) and have system of record for audit trail.
George: Blockchain is an intriguing technology—more for its potential than current applications. Everyone should watch George Gilder talking about "cryptocosm" to understand the possibilities of blockchain. ERP solutions have long since provided the apparel industry with the immediate solution it needed to streamline its much complex and labour-intensive processes at the most primitive level. However, after over two decades of playing around the same concoctions of simple "data recording systems" and handling the manual errors afterward (the cost of data entry errors sums up to $600B annually in the US alone), I think it's time for an upgrade. In simpler words, the peer-to-peer network technology of blockchain will bring utmost data visibility at all stages of a supply chain; supplier contracts will become transparent, highly secure and unbreachable with Smart Contracts and every financial transaction will be virtually risk-free and quick
Similar is the case with PLM. Blockchain technology allows the people involved in a product development cycle to collaborate with the right data, putting the product at the heart of the system. It adds "proof of work" and "timestamps" at every stage of a process, which makes this technology perfect for managing lead times. Additionally, for end-to-end collaborations, copyright protection, system integrations, and supply chain, blockchain could do wonders. Further, in luxury value chain, authenticity of any product could be ensured and guaranteed through blockchain.
Burstein: New technologies such as blockchain will be integrated into the digital supply chain; blockchain technology will shorten lead times and reduce friction throughout the overall supply chain, helping companies quickly deliver products to consumers. Blockchain is already proving its value in other industries, and it will have a similar impact in fashion.
How do you see the landscape changing with AI/robotics coming up in a big way? What are the changes that we may expect to see?
Charness: AI/Robotics have the potential to enhance supply chain speed and consumer responsiveness, but may challenge existing long value chains. Knowing that there is an opportunity from AI will not result in being able to exploit that knowledge, if companies can’t add agility into the mix. If I can identify a trend and through robotics and other automations reduce the time to manufacture, then I have achieved some of the speed needed to keep up with today’s consumer.
Munro: I have mentioned a few areas where AI and robotics will impact the industry in responses earlier. Robotics within distribution and store operations are largely outside of the space supported by Bamboo Rose, however as mentioned above just-in-time data capture and verification is critical for the successful delivery of such systems. AI is being adopted largely in the areas of forecasting to improve buying decisions and allocations, but this is also being adopted in CSR and sustainability, decision support in logistics and leveraging forecasts as part of the postponement strategies within sourcing and order management.
Jarry: Many industry leaders are responding to market pressure by adopting new technologies brought on by the fourth industrial revolution—from AI, the Internet of Things (IoT) and 3D to digitally connected tools and applications. While these things certainly enhance business processes, the secret is in finding the right solution that will impact your entire end-to-end value chain, resulting in a faster time to market, reduced costs and increased product margins.
Chidrawar: Robots are going to be pervasive in warehouses, working and supporting people in the warehouses. RPA (robotic process automation) allows companies to automate repetitive tasks, even in a legacy environment, and can be applied to take manual work out of the process. This is an area where we see the ability to shorten implementation time by using business-focused questionnaires to pre-define setup. By standardizing and consolidating the decision-making process, companies have an opportunity for automated configuration, allowing for more consistent, and efficient timelines to implement. Also, adjusting configuration for changing requirements or adding a new line of business can take advantage of the same automation. Increased reliance on machine learning for anything related to images, attribution of images, and for searching, matching, designers looking for images. Product development consumes images (creates images); machine learning will make it better and faster. Pattern recognition will be applied even from a planning perspective. Machine learning will be beneficial as a company maps more and more data, whether it is in a retail store or online, takes all of the data and starts looking at shopping patterns (shopping habits), for example looking at zip codes, the company can tell what is selling, what is not in a given region.
George: AI has seen many applications at the retail end of the industry, but very few AI applications have sought to change the operations side of the industry. Robotics definitely has been used to do some heavy lifting, repeated jobs in the manufacturing but hasn't made an impact on tasks that have variations and need continuous adjustments. Cyber-physical systems (CPS) are being built to handle these variable tasks. AI and Robotics are building blocks of CPS, which will change the way the manufacturing industry works as of today. We already have seen Speedfactory by Adidas, which is the first automated shoe factory. Though material handling of fabrics has been a challenge to automate and use robotics to stitch a garment completely. But there have been many advances in this field by using resins for stiffening the fabric for handling by the CPS. We should see light-out manufacturing for basic garments very soon. Also, more focus needs to be paid on automating the decisionmaking processes by using AI tools to imitate human intelligence. We need to overhaul the industry that has been operating on the same lines for two decades now.
Burstein: Companies that incorporate AI to quickly make decisions throughout the operations ecosystem will get the right products from concept to customer much faster. Unlike the analog, linear supply chain, a cognitive supply chain continually analyzes situational data, determines optimal outcomes, and automatically executes transactions. AI technologies have matured to the point where they can be incorporated into supply chain decision-making. As a result, cognitive supply chains are rapidly becoming reality.
