Big Data Technology: Impact on supply chains

Sources

https://www.supplychaindive.com/news/what-Big-Data-supply-chain-application-primer/435865/

https://www.mckinsey.com/business-functions/operations/our-insights/big-data-and-the-supply-chain-the-big-supply-chain-analytics-landscape-part-1

 

What is Big Data

Big Data as a concept requires three distinct layers before application: more data, processing systems, and analytics. If Big Data only recently entered the supply chain management spotlight, then, it may be because the technology only recently reached the last layer to deliver insights.

Information processing

Businesses are no stranger to data; supply chain managers have been producing reports, tracking trends and forecasting for decades. So when data exploded to become Big Data, companies were quick to rise to the challenge of collecting it for future use.

“What the CIOs and IT organizations were asked to do, early part of this decade – probably even the latter half of the last decade – was ‘hey there’s a lot of value in data, let’s actually keep on collecting data,’” Suresh Acharya, Head of JDA Labs told Supply Chain Dive.

But even if a pedometer generates bits and bytes each second, the information created remains unpalatable unless it is stored with previous data to be analyzed over time.

Therein came the need for information processing systems more powerful than spreadsheets.  Many of these are now known by their three letter acronyms (e.g. ERP, CRM, TMS or WMS), but their purpose is similar: to store, collect and simplify information for the average user. Such processors became so ubiquitous, it is now common for a company to boast nine or ten distinct systems supporting supply chain management in a single plant.

Insight and decision-making: The next frontier

There’s a new wave of data processors on the market promising to reap the benefits of Big Data for supply chains.

Supply chain solutions companies often offer to integrate the various systems from the previous generation, allowing companies to visualize data sets at each corporate level for the increased granularity and analytical capacity desired from Big Data.

Yet, Big Data is not only the ability to process more information, but the ability to innovate, automate and use data for enhanced decision-making. The toolkit is meant to be applied, not simply possessed.

A look back at our pedometer example may help illustrate the difference between having a software solution and actively unpacking Big Data. At first, the pedometer could only track information – making it a data generator. If connected to the Cloud and transmitting to a data processor, the device could be considered as helping to generate Big Data. But it was never a Big Data device because it never actively helped a user make decisions.

Meanwhile, the Fitbit – which tracks steps, heart rates and other biometrics – can analyze and apply the data it collects to guide the wearer to better health habits; for example, it alerts the user when they have been sitting too long and reminds them to go take a walk.

 

 

Big Data applications in supply chain

Manufacturing

Big data and analytics can already help improve manufacturing. For example, energy-intensive production runs can be scheduled to take advantage of fluctuating electricity prices. Data on manufacturing parameters, like the forces used in assembly operations or dimensional differences between parts, can be archived and analyzed to support the root-cause analysis of defects, even if they occur years later. Agricultural seed processors and manufacturers analyze the quality of their products with different types of cameras in real-time to get the quality assessments for each individual seed.

The Internet of Things, with its networks of cameras and sensors on millions of devices, may enable other manufacturing opportunities in the future. Ultimately, live information on a machine’s condition could trigger production of a 3D-printed spare part that is then shipped by a drone to the plant to meet an engineer, who may use augmented reality glasses for guidance while replacing the part.

Warehousing

Logistics has traditionally been very cost-focused, and companies have happily invested in technologies that provide competitive advantage. Warehousing in particular has seen many advances using available ERP data. One example are “chaotic” storage approaches that enable the efficient use of warehouse space and minimize travel distances for personnel. Another are high-rack bay warehouses that can automatically reshuffle pallets at night to optimize schedules for the next day. Companies can track the performance of pickers in different picking areas to optimize future staff allocation.

New technologies, data sources and analytical techniques are also creating new opportunities in warehousing. A leading forklift provider is looking into how the forklift truck can act as a big data hub that collects all sorts of data in real time, which can then be blended with ERP and Warehouse Management System (WMS) data to identify additional waste in the warehouse process. For example, the analysis of video images collected by automated guided vehicles, along with sensor inputs including temperature, shelf weight, and the weight on the forklift, can be used to monitor picking accuracy, warehouse productivity and inventory accuracy in real time. Similarly forklift driving behavior and route choices can be assessed and dynamically optimized to drive picking productivity. The data can also be used to conduct root-cause analysis of picking errors by shape, color, or weight, to help to make processes more robust.

New 3D modelling technologies can also help to optimize warehouse design and simulate new configurations of existing warehouse space to further improve storage efficiency and picking productivity. German company Logivations, for example, offers a cloud-based 3D warehouse layout planning and optimization tool.

Transportation

Truck companies already make use of analytics to improve their operations. For example, they use fuel consumption analytics to improve driving efficiency; and they use GPS technologies to reduce waiting times by allocating warehouse bays in real time.

Courier companies have started real-time routing of deliveries to customers based on their truck’s geo-location and traffic data. UPS, for example has spent ten years developing its On-Road Integrated Optimization and Navigation system (Orion) to optimize the 55,000 routes in the network. The company’s CEO David Abney says the new system will save the company $300 million to $400 million a year3.

Big analytics will also enable logistics providers to deliver parcels with fewer delivery attempts, by allowing them to mine their data to predict when a particular customer is more likely to be at home. On a more strategic basis, companies can cut costs and carbon emissions by selecting the right transport modes. A major CPG player is investing in analytics that will help it to understand when goods need be shipped rapidly by truck or when there is time for slower barge or train delivery.

Point of Sale

Brick and mortar retailers—often under heavy pressure from online competitors that have mastered analytics—have understood how data driven optimization can provide them with competitive advantages. These techniques are being used today for activities like shelf-space optimization and mark-down pricing. Advanced analytics can also help retailers decide which products to put in high value locations, like aisle ends, and how long to keep them there. It can also enable them to explore the sales benefits achieved by clustering related products together.

Search engine giant Google has acquired Skybox, a provider of high resolution satellite imagery, that can be used to track cars in the car park in order to anticipate in-store demand. Others have explored the use of drones equipped with cameras to monitor on-shelf inventory levels.

Questions:

Q) What role can Big Data play in the optimization of Supply Chains across industries?

Q) What are the cost implications in companies leveraging big data to organize their supply chains?

Q) How is Big data different from data analytics?

 

 

Digital twins in supply chain

What is a digital twin

A digital twin is a virtual image/software representation of a real product, process, asset or service. For example, a digital visualization of an organ used to simulate an upcoming operation. A digital copy can be used for monitoring and control, as well as for planning and forecasting the outcomes of various scenarios. This makes it possible to understand, predict and optimize performance.

For the digital twin to be truly a twin, all available information/data must be linked one-to-one. In some cases, individual digital twins are connected to each other in order to reproduce and optimize twins of an entire construct.

Advantages of digital twins

he benefits that digital twin technologies offer your business include:

  • Increased reliability of equipment and production lines
  • Improved OEE through reduced downtime and improved performance
  • Improved productivity
  • Reduced risk in various areas including product availability, marketplace reputation, and more
  • Lower maintenance costs by predicting maintenance issues before breakdowns occur
  • Faster production times
  • New business opportunities such as mass customisation, mixed manufacturing, small-batch manufacturing, and more
  • Improved customer service as customers can remotely configuring customised products
  • Improved product quality, and enhanced insight into the performance of your products, in multiple real-time applications and environments
  • More efficient supply and delivery chains
  • All the above combined will result in the ultimate benefit of improved profits

 

How do digital twins work and where can they be used?

Digital twins act as a bridge between the physical and digital world. With the help of intelligent sensors integrated into physical elements, all necessary data can be captured and transmitted. In conjunction with relevant business data, this data is then analyzed and, in the best case scenario, can uncover opportunities that may otherwise have gone undetected.

NASA has been using digital twins for many years. This is mainly because the systems it needs to monitor are located at an unattainable distance. John Vickers, NASA’s leading manufacturing expert and manager of the NASA National Center for Advanced Manufacturing, describes NASA’S vision to be able to create, test and build their equipment in a virtual world in the future.

Installing IoT sensors can not only help the company itself, but also increase the efficiency of  its supply chain partners and prevent possible disruptions. But where can digital twins be used in practice? Practically everywhere: You can recognize existing customer requirements, simulate the effects of corresponding trends and thus obtain a comprehensive view of the broad spectrum of customers. In production, current state analyses can be carried out, adjustments can be made if necessary and untapped potential can be identified. In logistics, digital twins can be used to optimize stocks and to track and monitor them through geolocation. Digital twins enable companies to meet their supply chain partners’ requirements to the best of their abilities .

What does the future look like?

Forbes describes the current state of digital twin technology as the threshold to a digital explosion in which significantly more companies will develop and introduce their own digital twins in the future based on success stories of others. The number of digital representatives of physical objects is estimated to be in the billions, which simultaneously opens up the opportunity for cooperation between product experts and data scientists. Gartner predicts that by 2021, half of the major industrial companies will be using digital twins, resulting in an average efficiency increase of 10%.

In addition, experts predict that future developments will be much more likely to involve the combination of individual twins than at present. The fact that the use of digital twins can open up new business fields and models arouses curiosity about the unknown potential of innovative solutions in the future.

Supply Chain 4.0 – the next-generation digital supply chain

Over the last thirty years, logistics has undergone a tremendous change: from a purely operational function that reported to sales or manufacturing and focused on ensuring the supply of production lines and the delivery to customers, to an independent supply chain management function that in some companies is already being led by a CSO – the Chief Supply Chain Officer. The focus of the supply chain management function has shifted to advanced planning processes, such as analytical demand planning or integrated S&OP, which have become established business processes in many companies, while operational logistics has often been outsourced to third-party LSPs. The supply chain function ensures integrated operations from customers to suppliers.

Experts would usually claim that supply chain management is about delivering the right quality at the lowest cost, with the agreed service level, right? Well, not anymore. As the two examples above show, it is also about increasing sales and profits; the supply chain is no longer just about efficiency, working capital reduction and inventory management.

Adidas

Adidas is the leading sports’ shoe brand in Russia with more than 1,200 stores. As part of its strategy to please customers, Adidas is implementing an omni channel strategy, allowing people to buy in a number of ways.

Initially, Adidas implemented a trial of click and collect in Moscow expecting that just a few consumers would choose this option – to buy on-line and collect the product at a store. They expected around 10 to 20 orders per week, but consumers embraced the idea and orders reached 1,000 per week. Adidas was forced to stop the experiment and build the supply chain infrastructure needed to support such demand. Today, up to 70% of online sales are through click and collect.

For Adidas Russia, the supply chain is no longer about reducing costs: It is – more importantly – about increasing sales. All of this is possible thanks to the technology being used in the supply chain. Most of these technologies belong to Industry 4.0, a high-tech strategy promoting the computerisation of manufacturing.

 

Digitization brings about a Supply Chain 4.0, which will be

  • Faster. New approaches of product distribution reduce the delivery time of high runners to few hours. The basis for these services is built by advanced forecasting approaches, e.g., predictive analytics of internal (e.g., demand) and external (e.g., market trends, weather, school vacation, construction indices) data as well as machine status data for spare-parts demand, and provides a much more precise forecast of customer demand.
  • more flexible. Ad hoc and real-time planning allows a flexible reaction to changing demand or supply situations. Planning cycles and frozen periods are minimized and planning becomes a continuous process that is able to react dynamically to changing requirements or constraints
  • more granular. The demand of customers for more and more individualized products is continuously increasing. That gives a strong push towards microsegmentation, and mass customization ideas will finally be implemented.

 

Questions:

What are the challenges in the implementation of Digital Supply Chain?

What will be the future of supply chains due to the technology trends?

 

Source:

https://www.mckinsey.com/business-functions/operations/our-insights/supply-chain-40–the-next-generation-digital-supply-chain

https://www.imd.org/research-knowledge/articles/supply-chain-4.0/

 

3D Printing Impact on Supply Chain

 

What is 3D printing

 

3D printing, also known as additive manufacturing – AM (the terms 3D printing and additive manufacturing have become interchangeable), is an additive technology used for making three dimensional solid objects up in layers from a digital file without the need for a mould or cutting tool. 3D printing uses a computer aided design (CAD) to translate the design into a three-dimensional object. The design is then sliced into several two dimensional plans, which instruct the 3D printer where to deposit the layers of material. Additive process, of depositing successive thin layers of material upon each other, producing a final three dimensional product

Impact of 3D printing on the Supply Chain

 

The impact of AM technologies on the global setup of supply chains can be very disruptive. The technology has the potential to eliminate the need for both high volume production facilities and low-level assembly workers, thereby drastically reducing supply chain cost. In terms of impact on inventory and logistics, we can print on demand. Meaning we don’t have to have the finished product stacked on shelves or stacked in warehouses anymore. Whenever we need a product, we just make it. And that collapses the supply chain down to its simplest parts, adding new efficiencies to the system. Those efficiencies run the entire supply chain, from the cost of distribution to assembly and carry, all the way to the component itself, all the while reducing scrap, maximising customisation and improving assembly cycle times.

Image result for Metal 3d printers in supply chain

Traditional supply chain vs AM model

 

The supply chain traditional model is founded on traditional constraints of the industry, efficiencies of mass production, the need for low cost, high volume assembly workers, and so on. But 3D printing bypasses those constraints. 3D printing finds its value in the printing of low volume, customer specific items, items that are capable of much greater complexity than is possible through traditional means. This at once eliminates the need for both high volume production facilities and low level assembly workers, thereby cutting out at least half of the supply chain in a single blow. From that point of view, it is no longer financially efficient to send products across the globe when manufacturing can be done almost anywhere at the same cost or lower. The raw materials today are digital files and the machines that make them are wired and connected, faster and more efficient than ever. And that demands a new model of supply chain . With support local sourcing, the 3D printing technology has the potential to tear established global supply chain structures apart and reassembles it as a new, local system. Furthermore, the technology creates a close relationship between design, manufacturing and marketing. The technology could transform the global supply chain to a globally connected, but totally local supply chain

Image result for Metal 3d printers in supply chain

 

Questions:

What is the future of 3d printing?

What are the challenges in using 3 D printing in supply chains?

 

Sources:

https://www.researchgate.net/…/320927657_The_Impact_of_3D_Printing_Technology

https://www.stratasysdirect.com/resources/infographics/3d-printing-impact-supply-chain

 

How Analytics is Transforming Supply Chain Management

 

 

Supply chain management is a field where Big Data and analytics have obvious applications. Until recently, however, businesses have been less quick to implement big data analytics in supply chain management than in other areas of operation such as marketing or manufacturing.

Of course supply chains have for a long time now been driven by statistics and quantifiable performance indicators. But the sort of analytics which are really revolutionising industry today – real time analytics of huge, rapidly growing and very messy unstructured datasets – were largely absent.

This was clearly a situation that couldn’t last. Many factors can clearly impact on supply chain management – from weather to the condition of vehicles and machinery, and so recently executives in the field have thought long and hard about how this could be harnessed to drive efficiencies

Image result for supply chain analytics

 

Why is it so Important?

Relying on traditional supply chain execution systems is becoming increasingly more difficult, with a mix of global operating systems, pricing pressures and ever increasing customer expectations. There are also recent economic impacts such as rising fuel costs, the global recession, supplier bases that have shrunk or moved off-shore, as well as increased competition from low-cost outsourcers. All of these challenges potentially create waste in your supply chain. That’s where data analytics comes in.

Data analytics is the science of examining raw data to help draw conclusions about information. It is used in many industries to allow companies and organization to make better business decisions and in the sciences to verify (or disprove) existing models or theories.

All businesses with a supply chain devote a fair amount of time to making sure it adds value, but these new advanced analytic tools and disciplines make it possible to dig deeper into supply chain data in search of savings and efficiencies.

The supply chain is a great place to use analytic tools to look for a competitive advantage, because of its complexity and also because of the prominent role supply chain plays in a company’s cost structure and profitability. Supply chains can appear simple compared to other parts of a business, even though they are not. If we keep an open mind, we can always do better by digging deeper into data as well as by thinking about a predictive instead of reactive view of the data.

 

https://www.industryweek.com/blog/supply-chain-analytics-what-it-and-why-it-so-important

https://www.forbes.com/sites/bernardmarr/2016/04/22/how-big-data-and-analytics-are-transforming-supply-chain-management/#3a01760339ad

Questions

  1. Q) What are the applications of analytics in supply chain?
  2. Q) What are some of the pain points in supply chain addressed by analytics

 

 

 

Blockchain a Game Changer for Supply Chain Management Transparency

 

What is Blockchain?
Blockchain is a distributed database that holds records of digital data or events in a way that makes them tamper-resistant. While many users may access, inspect, or add to the data, they can’t change or delete it. The original information stays put, leaving a permanent and public information trail, or chain, of transactions

If the entire blockchain were the history of banking transactions, an individual bank statement would be a single “block” in the chain. Unlike most banking systems, however, there is no single organisation that controls these transactions. It can only be updated through the consensus of a majority of participants in the system

How Will Blockchain Technology Affect the Supply Chain?
If blockchain technology allows us to more securely and transparently track all types of transactions, imagine the possibilities it presents across the supply chain.

Every time a product changes hands, the transaction could be documented, creating a permanent history of a product, from manufacture to sale. This could dramatically reduce time delays, added costs, and human error that plague transactions today.

Some supply chains are already using the technology, and experts suggest blockchain could become a universal “supply chain operating system” before long. Consider how this technology could improve the following tasks:

  • Recording the quantity and transfer of assets – like pallets, trailers, containers, etc. – as they move between supply chain nodes
  • Tracking purchase orders, change orders, receipts, shipment notifications, or other trade-related documents
  • Assigning or verifying certifications or certain properties of physical products; for example determining if a food product is organic or fair trade
  • Linking physical goods to serial numbers, bar codes, digital tags like RFID, etc.
  • Sharing information about manufacturing process, assembly, delivery, and maintenance of products with suppliers and vendors

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Benefits in a Nutshell
Regardless of the application, blockchain offers shippers the following advantages:

  • Enhanced Transparency Documenting a product’s journey across the supply chain reveals its true origin and touch points, which increases trust and helps eliminate the bias found in today’s opaque supply chains. Manufacturers can also reduce recalls by sharing logs with OEMs and regulators
  • Greater Scalability Virtually any number of participants, accessing from any number of touch points, is possible
  • Better Security A shared, indelible ledger with codified rules could potentially eliminate the audits required by internal systems and processes
  • Increased Innovation Opportunities abound to create new, specialised uses for the technology as a result of the decentralised architecture.

Questions

  • What is Blockchain?
  • What are the applications of blockchain in supply chain?
  • What are the risks of Blockchain technology?

https://www.supplychain247.com/article/why_blockchain_is_a_game_changer_for_the_supply_chain

 

Advanced Analytics in Supply Chain

The sole role of analytics is to support decision making. Through Advanced Analytics, a supply chain can leverage more insights with more accuracy. This empowers to take decisions better, faster and/or with more confidence. Specific use-cases include the following:

Create inventory visibility and visualise which products rotate at which speed through your warehouse and why (decreased sales, increased returns). Use the available data to segment your products in high- and low-rotating units and provide this as input to your warehouse manager to relocate goods and alter safety stock levels.

Derive root-causes of delivery promise failures such as vendors who deliver to late, fulfilment partners who exceed average delivery times – and identify supply-chain improvement initiatives.

Get smarter into product development by leveraging data-driven insights on your customer- and order base: what are my customers segments, how did they grow over time, how are they in one region vs. another region, what are their shared preferences, which products features do they like

Reduce lead time by understanding when which drivers impact lead-time at what impact: which parts increase the risk of production delay, which parts require a strategic inventory? With no IT investment, a solid data-mining exercise through your supply chain order-, production- and delivery data can likely already identify low hanging fruit opportunities.

Optimise inventory space and value by forecasting demand with accuracy. Do you overestimate, you will likely overproduce and stack up inventory; do you underestimate, you’ll miss sales. Through analytics we can analyse your historical sales data and assess patterns driven by seasonality, partner activity, marketing activeness, offline sales agents, weather or even country-specific GDP. Turning these patterns into inputs, we predict sales and thus prescribe needed inventory levels.

Locate geographical growth opportunities by visualising all order, delivery- and customer-locations and deriving sweet spots for new sales hubs, production sites or warehousing depots. Assess supply-chain merger potential by visualising overlapping supply-chain networks, assessing overlap and thus assessing strategic added value.

Assess failure patterns of production machines to understand which drivers are recurrently causing failure (volumes, #batch switches, temperature, speed, operator). Then translate these drivers into inputs building an early-warning-trigger tool/model to pre-empt failure (first steps of predictive maintenance).