By Henry Canitz, Director of Product Marketing & Business Development , Logility
When I hear the term “Lever” my mechanical engineering side comes out and I think of the Physics and Mechanical Design courses I took some 30+ years ago. Although I didn’t appreciate it at the time, my engineering education laid a strong foundation that has helped me be as successful as possible in whatever I did. More than anything, I learned how to analyse and solve problems. So when I think of a lever I think of a rigid bar resting on a pivot or fulcrum, used to help move a heavy or a firmly fixed load with one end when pressure is applied to the other.
Back to present day and the supply chain. Two powerful levers a company can use to optimise inventory are “Working Capital” and “Customer Service Levels.” Through the effective use of these levers, you can free trapped working capital while improving service levels.
Your company’s inventory efficient frontier is a tradeoff curve between working capital and service level and represents the currently achievable service level at any corresponding inventory investment. At its most basic, start with a piece of graph paper and plot your current service level on the x-axis and current inventory level on the y-axis. Chances are you are not on the inventory efficiency curve that is theoretically possible given your current operating capabilities. When you remove inefficiencies, failures, etc. and estimate how much your service level will go up and down with changes in inventory investment you end up with a curve – your current inventory efficient frontier curve. Organisations can slide up and down along this curve by manipulating the service and inventory levers (see Figure 1).
However to create real value you have to be able to shift the inventory efficient frontier so that higher service levels can be achieved without increasing inventory or the same service levels can be achieved with less inventory. Multi-echelon Inventory Optimisation (MEIO) allows you to truly optimise your inventory across the entire supply chain and enables you to shift to a new efficient frontier for your entire supply chain (Read the eBook: The Inventory Optimization Handbook).
By modeling the end-to-end supply chain, MEIO determines not only the optimal inventory to carry at each location but also at which locations each item should be carried. MEIO looks across sales channels, distribution tiers, and even types of inventory (raw, WIP, FG) to understand how best to minimise total inventory while still providing the desired customer service levels. MEIO can take you into unexplored territory providing reductions in working capital of up to 30 percent or more. For most companies that amounts to millions of dollars in savings annually. That is an impressive use of levers.
What is important to understand is that the supply chain is a living, breathing and constantly changing organism. Your optimal inventory strategy for this month might be suboptimal next month due to changes in demand or supply, changes in competition or market health, or a variety of other factors. Modeling your end-to-end supply chain inventory is not a “one and done” activity and therefore there is always opportunity to shift that efficient frontier into new and undiscovered territory.
Do you understand your company’s service level – working capital tradeoff? Can you model your end-to-end supply chain to determine your optimal inventory locations and levels?
Henry Canitz, Director of Product Marketing & Business Development, Logility
By: Henry Canitz – Director Product Marketing & Business Development
John Glenn became the first American to orbit the Earth on Mercury-Atlas 6 on February 20, 1962, just a few days after I was born. I grew up watching the Apollo Space Program launches including the six launches that sent humans to the moon and back. Like many kids back then I dreamed of being a test pilot and an Astronaut. I partially achieved that dream by becoming an Aerospace Test Engineer and working at Edwards Air Force Base where many of the early test flights by Chuck Yeager, Scott Crossfield, and other’s took place. On February 6, 2018, 56 years after John Glenn’s historic launch, SpaceX launched their Falcon Heavy rocket with Elon Musk’s Tesla Roadster and a dummy named Starman on a journey into the solar system. The Falcon Heavy is a new class of rockets that may allow man to colonize Mars and beyond. Today, space launches are routine with launches happening on a monthly if not weekly basis. Exciting stuff for someone who dreamed of being an astronaut.
It is also an exciting time to be a Supply Chain Practitioner. Like space exploration, the supply chain has become significantly more complicated over the last 25 years. Technological advances have simplified and automated a lot of routine processes while opening up entirely new opportunities. These new frontiers require advanced capabilities to drive business value such as cost reduction and customer service improvements. Analytics, for example, today is a routine part of a supply chain professional’s job. We can now analyze the end-to-end supply chain and quickly determine the best path forward. While speaking with practitioners at industry events it is quite apparent, some supply chain teams have the ‘Right Stuff’ to fully embrace advanced analytics while others are just beginning their journey.
Moving up the analytics maturity curve takes a combination of the right talent, processes and enabling technology. Unfortunately, the people component is often not adequately addressed. As supply chain planning incorporates more data, supply chain roles need to be redefined to support analysis and decision making. Just as Chuck Yeager had to acquire new abilities and skills to break the sound barrier, companies have to define new skills and roles to meet their envisioned advanced analytic enabled processes.
Below are a few of the new analytic roles for leading supply chain teams today:
- Business Analyst: understands business needs, assesses the business impact of changes, captures, analyses and documents requirements and communicates requirements to relevant stakeholders.
- Supply Chain Analyst: responsible for improving the performance of an operation by figuring out what is needed and coordinating with other employees to implement and test new supply chain methods.
- Artificial Intelligence Specialist: work on systems that not only gather information but formulate decisions and act on that information. Software that determines Sentiment from Social Data is one example of the work of Artificial Intelligence Specialists.
- Data Scientists / Big Data Analyst: analyzes and interprets complex digital data, such as the usage statistics of a website, especially in order to assist a business in its decision-making.
- Database Engineer: responsible for building and maintaining the software infrastructure that enables computation over large data sets.
As our enterprise systems continue to produce volumes of data, we need to make smart decisions faster to drive the business forward. Does your current team have the ‘Right Stuff’ to embrace advanced analytics? What new roles do you need in your supply chain team? How should your team be organized to efficiently run the business while also driving innovation? Are your current supply chain systems sufficient to leverage new data sources and enable advanced analytics? Can you automate routine activities? These are just a few of the questions you should ask as you embrace all that analytics has to offer to keep your supply chain team engaged in value-creating activities.
About the Author:
Henry Canitz is The Product Marketing & Business DevelopmentDirector at Logility. To read more of Henry’s insights visit www.logility.com/blog.
There’s currently a digital supply chain transformation that’s happening faster than the physical supply chain can react, requiring hybrid solutions in semi-automated environments where humans and robots work in tandem. New incentives to modernize operational capabilities should be added that capture efficiencies not previously achieved, while laying the foundation of a digitalized supply chain, continuously re-evaluating plans and evolving for performance.
Automation has been looked at as a solution to operational challenges, but trends in the marketplace signify an unprecedented rate of adoption taking hold in the coming decade. E-commerce is driving service expectations to levels that may not be achieved without the use of highspeed picking alternatives to manual operations. The aging generations in mature economies and challenges securing a loyal millennial workforce for repetitive tasks are creating increased disruption to staffing, forcing employers to look to automation to offset risk of labor shortages. Continued innovation has reduced costs of entry for automated capabilities, delivering improved business case justification for automation of many forms.
With such a strong justification, operations leaders across the globe are seeking ways to capture the potential that automation offers. Large scale transformation of distribution networks is capital intensive, however, and rarely warranted given the pace of change – however rapid – and market uncertainties. Therefore, we’re forced to look within existing environments to identify opportunities to introduce automation into existing facilities, combining automated equipment with manual operations, which requires the added complexity of orchestrating work across semiautomated operations. This scenario introduces the question of how to create an optimal environment allowing warehouse management systems (WMS) to orchestrate work across manual and automated areas to ensure efficient operations and maintain quality and service levels.
Part 1 of this 2-part blog series will take a deeper dive into today’s automation systems landscape and retrofitting today’s supply chain with automation. Part 2 of the series will cover disruptive technologies and digitalization and next generation capabilities.
The Current Landscape of Automation Systems
In automated environments, WMS often work alongside warehouse control systems (WCS) that manage the routing of containers as they traverse the material handling equipment, and warehouse execution systems (WES) which often have basic task management capabilities but not the level of control or optimization of a WMS. Below are a few general groupings of automation that typically leverage these entities in different ways.
- Conveyors and sortation equipment receive destination / routing information from the WMS and leverage the WCS to divert containers to the appropriate location.
- Pick execution equipment, including pick-to-light, carousels, or A-frames will receive pick instructions from the WMS and rely on the WCS to control the MHE. At times, these devices will manage task distribution and user interfaces for the performance of picks, though often, the WMS will manage the tasks through prioritization, and provide a common user experience (using consistent equipment where appropriate) for work performed in the pick modules and in bulk storage which feeds it (this work would include putaways, cycle counting, and picks where appropriate). Often, a WES has been sufficient for high volume outbound operations in retail, but with increasing emphasis on service levels, the advanced functionality of a WMS specific to inventory accuracy, pick module replenishment, cross-docking, and exception handling, the WMS brings a strong justification for a two-pronged approach.
- Automated guided vehicles (AGVs) and automated storage and retrieval systems (ASRS) are well established, though adoption is increasing as more forklift providers offer driverless units. These units can take direction from a WMS (typical when involved in semi-automated environments) or WES (often used in ASRS racking systems where materials are commingled or when the vehicles can follow multiple routes to alleviate congestion). In either scenario, a WMS is often utilized to manage inventory allocation to customer and order.
- Palletizers use visual determination for pallet building capabilities, but most in use require some level of consistency in product dimensions at the layer level. Advanced pallet building and robotic arm picking capabilities are increasing in use, but require some consistency in dimensions. Improvements in digital sensing will soon be changing the game here.
Retrofitting Today’s Supply Chain with Automation
Automation adoption will continue to accelerate in response to advanced service level expectations and e-commerce, with a focus on scale and speed, whereas a continued migration of margin focused businesses will drive adoption of driverless vehicles and high-density storage modules, especially in cold storage or mega-cities with high volume real estate. The introduction of automation into the existing facilities will bring challenges, such as:
- Traditional footprints, system capabilities, and business processes will be challenged when faced with the introduction of conveyance, sortation, and pick execution equipment. A natural inclination to delineate businesses, and potentially create channel-specific operations, can result in artificially inflated inventory levels and/or reduced service levels in increasingly sensitive environments to failures in this area. Multi-channel capabilities can be achieved, often driving operational leaders to adopt pick execution capabilities to distribute work without recognizing the backlash to overall service levels of having disparate capabilities with traditional WMS controlled processes. The results, if not thought through, can have repercussions on inventory accuracy, exception management, and operational efficiency.
- The introduction of driverless vehicles (AGV or ASRS) offer strong advantages in terms of scale and cost, ROI projections in union environments can often deliver break even points less than a year after go-live, even in new projects. However, legacy storage equipment and material flow can introduce limitations. The environments best prepared for the introduction of driverless forklifts are those managing full pallets in bulk locations (where dimensions are predictable and stack requirements are well documented), or those where racking capacity is capable of managing fixed locations that can be tracked in the WMS (if locations can be dedicated to a specific lot), or in the WCS (where multiple pallet locations can be managed by the WCS but the WMS can manage storage/allocation in concert with non-automated areas). In more complex operations, the WCS can take a more active role in determining work and allocation, but this often drives customization and redundancy with WMS functions specific to the needs of the business.
- More robust, piece level management in advanced pick modules controlled by ASRS such as goods-to-person automation, offer advanced capabilities for high volume distributors and e-tailers. Often, this will require tote storage of product to standardize the storage capabilities, though concessions for non-conveyables must be considered. Integrating pick and pack operations with traditional areas of the same operation also force decisions on how to integrate inventory management with shipping capabilities, adding complexity to projects as WMS and WCS providers offer similar capabilities.
Check back for part-2 of the blog series, where we’ll go into more detail around the technologies driving next generation warehouse automation and digitalization and next generation capabilities.
For more information download the Future Series white paper, “Adopting automation in the digital age.”
About the Author
Matthew Butler, Industry Strategies Director, JDA Software
More more information contact, 0414 966 232.
You receive a notification on your phone that a critical shipment from your China factory has missed its filing deadline with the customs broker.
Your logistics manager is alerted that there is an 80% chance that the components he’s waiting for are likely to be delayed another 48 hours by excessive port traffic and your GTM software advises diverting the shipment to an alternate port facility.
Your compliance officer is informed that there is a 95% chance that a shipment of parts from Malaysia is likely to be held for up to three days to be subjected to a detailed customs inspection.
If you think this type of information would be of great assistance to your supply chain business planning and operations, you are not alone. It is this type of integrated data and communications that are becoming the backbone of the Big Data led revolution underway in the supply chain.
The human brain can only process and make use of a limited amount of information before it becomes overwhelmed and unable to effectively recognise patterns and trends. But powerful algorithms and the software platforms they drive can take in almost unlimited numbers of data points and process them to generate insights impossible for an individual or even an entire organisation of individuals to identify. And powering this technology-driven transformation of the supply chain is Big Data.
Big Data vs Small Data
To really understand how technology is transforming supply chain, it is important to understand how Big Data differs from any other form of information gathering. Data has always been crucial to efficient supply chain operations so what has actually changed in recent years? How is “Big Data” different from the analysis of “small data” that has always occurred in the industry?
Big Data refers to sets of both structured and unstructured data with so much volume that traditional data processing systems are inadequate to cope with it all. It can be further defined by some of the basic properties that apply to it:
Variety – data being generated from a wide number of varied sources
Volume – while there is no set distinction between where small data stops and Big Data starts, Big Data requires large storage requirements for the data, often measured in many multiples of terabytes
Velocity – the speed at which the data can be acquired, transferred and stored
Complexity – difficulties encountered in forming relevant relationships in data, especially when it is taken from multiple sources
Value – the degree to which querying the data will result in generating beneficial outcomes
The most important property related to Big Data is as the name implies, volume. We normally think of data purely in terms of text or numbers but it can include everything from the billions of emails, images, and tweets generated every day.
In fact, data generation is expanding at a rate that doubles every two years. And human and machine-generated data is growing at 10 times the rate of traditional business data.
IT World Canada projects that by 2020, you would need a stack of iPad Air tablets extending from the earth to the moon to store the world’s digital data.
But the real focus behind a preference for Big Data analysis over small data systems is the ability to uncover hidden trends and relationships in both structured and unstructured data. In most cases, using small data collection and analytics processes simply cannot identify crucial information in a timely manner to allow key decisions to be made or opportunities to be taken advantage of. In other cases, using small data systems is simply a waste of resources and leads to disruptions to supply chain operations.
By contrast, if used correctly Big Data is the key to enhancing supply chain performance by increasing visibility, control, agility, and responsiveness. Making decisions based on high-quality information in context can benefit the full range of supply chain operations – from demand forecasting, inventory and logistics planning, execution, shipping, and warehouse management.
Big Data possibilities
Big Data analytics becomes a vital tool for making sense of the huge volumes of data that are produced every day. This data comes from a whole range of activities undertaken by people associated with supply chain, whether they be customers, suppliers, or your own staff. The range and volume of this data are continuously increasing, with billions of data points generated by sources we see as directly linked to supply chain such as network nodes and transaction and shipping records as well as other areas that more indirectly impact supply chains such as retail channels and social media content.
But it is increasingly becoming necessary to harness this data in order to remain competitive. This is evident from statements such as the below:
“Big Data is certainly enabling better decisions and actions, and facilitating a move away from gut feel decision making.” -Anthony Coops, Asia Pacific Data & Analytics Leader, KPMG Australia
At the same time, he recognises that solutions need to be put in place that allows for people and organisations to have complete faith in the data so that managers can really trust in the analytics and be confident in their decision making.
The need for confidence in the analytics is evident when considering the examples such as where GTM software has the information and capabilities to advise ahead of time to divert shipping stock to an alternate port or that a product is likely to be held up in customs. These types of decisions have potentially large financial consequences but when implemented correctly, it is easy to see how supply chain operational efficiency can be significantly boosted by effective use of Big Data analytics.
Many organisations are also using Big Data solutions to support integrated business planning and to better understand market trends and consumer behaviours. The integration of a range of market, product sales, social media trends, and demographic data from multiple data sources provides the capability to accurately predict and plan numerous supply chain actions.
IoT and AI-based analytics are used to predict asset maintenance requirements and avoid unscheduled downtime. IoT can also provide real-time production and shipping data while GPS driven data combined with traffic and weather information allows for dynamically planned and optimised shipping and delivery routes. These types of examples provide a glimpse into the possibilities and advantages that Big Data can offer in increasing the agility and efficiency of supply chain operations.
What is driving these possibilities is the development of numerous disruptive technologies as well as the integration of both new and existing technologies to create high-quality networks of information. Disruptive technologies impact the way organisations operate by forcing them to deal with new competitive platforms. They also provide them with opportunities to enter new markets or to change the company’s competitive status.
By identifying key disruptive technologies early, supply chain organisations can not only be better placed to adapt to changing market conditions, they can also gain a distinct advantage over others in the industry that are reluctant to embrace change.
In terms of Big Data based disruptive technologies, these are largely driven by the effects of constantly evolving and emergent internet technologies such as the Internet of Things combined with increased computing power, AI and machine learning based analytics platforms, and fast, pervasive digital communications. These technologies then act as drivers that spawn new ways of managing products, assets, and staff as well as generating new ways of thinking about organisational structures and workflows.
After being talked about for many years, we are now starting to see the Internet of Things really taking shape. There will be a thirty-fold increase in the number of Internet-connected physical devices by 2020 and this will significantly impact the ways that supply chains operate.
IoT allows for numerous solutions to intelligently connect systems, people, processes, data, and devices via a network of connected sensors. Through improved data collection and intelligence, the supply chain will benefit from greater automation of the manufacturing and shipping process becomes possible through enhanced visibility of activities from the warehouse to the customer.
Cloud-based GPS and Radio Frequency Identification (RFID) technologies, which provide location, product identification and other tracking information play a key role in the IoT landscape. Sensors can be used to provide a wealth of information targeted to specific niches within supply chain such as fresh produce distribution where temperature or humidity levels can be precisely tracked along the entire journey of a product. Data gathered from GPS and RFID technologies also facilitates automated shipping and delivery processes by precisely predicting the time of arrival.
Big Data analytics
Big Data analytics encompasses the qualitative and quantitative techniques that are used to generate insights to enhance productivity. The more supply chain technologies are reliant on Big Data, either in their business model or as a result of their impact on an organisation, the more organisations have to rely on the effective use of Big Data analytics to help them make sense of the volumes of data being generated. Analytics also helps to make it possible to understand the processes and strategies used by competitors across the industry. Using analytics effectively allows an organisation to make the best decisions to ensure they stay at the forefront of their particular market sector.
As corporations face financial pressures to increase profit margins and customer expectation pressures to shorten delivery times. the importance of Big Data analytics continues to grow. A Gartner, Inc. study put the 2017 business intelligence and analytics market at a value over USD$18 billion, while the sales of prescriptive analytics software is estimated to grow from approximately USD$415 million in 2014 to USD$1.1 billion in 2019.
Over time, the effectiveness and capabilities of analytics software also continue to improve as machine learning-based technologies take forecast data and continually compare it back to real operational and production data. This means that the longer an organisation operates its analytics software, the iterative nature of artificial intelligence powered algorithms means that the performance and value of the software improve over time. This leads to benefits such as more accurate forecasts of shipping times or supplier obstacles and bottlenecks.
Consumer Behaviour Analysis
Although it may not initially seem as vital to supply chain as other disruptive technologies, consumer behaviour analysis can have a huge impact on businesses working in supply chain, especially e-commerce businesses. Known as clickstream analysis, large amounts of company, industry, product, and customer information can be gathered from the web. Various text and web mining tools and techniques are then used to both organise and visualise this information.
By analysing customer clickstream data logs, web analytics tools such as Google Analytics can provide a trail of online customer activities and provide insights on their purchasing patterns. This allows more accurate seasonal forecasts to be generated that can then drive inventory and resourcing plans. This type of data is extremely valuable and is crucial for any organisations operating in the e-commerce space. While retailers and consumer companies have always collected data on buying patterns, the ability to pull together information from potentially thousands of different variables that have traditionally been collected in silos provides enormous economic opportunities.
Potential drawbacks and challenges
Despite the huge opportunities presented by implementing Big Data powered solutions, there can be intimidating barriers to entry when it comes to putting in place Big Data collection and analytics solutions. This can emerge across a range of areas including the complexities around data collection and the difficulties of putting in place the technologies and infrastructure needed to turn that data into useful insights.
Getting complete buy-in
One impediment to adopting a holistic Big Data approach centres around having unified support at all levels of your company to adopt comprehensive Big Data systems. Management commitment and support is crucial and large-scale initiatives of this type usually occur from the top down. However, Big Data analytics type initiatives usually originate at mid-level, from people who actually collect and use data day to day. This means that for this issue, the need for implementation must often be sold upwards. In some cases, upselling the importance of Big Data to management that doesn’t understand why that type of expense is necessary is extremely challenging.
Sourcing clean data
One of the other main challenges is undoubtedly sourcing appropriate and consistent data. There’s no use getting high-quality data if it doesn’t directly apply to your particular market sector. Nor is there much benefit to be gained from obtaining high-quality data but being unable to consistently source it at the same regularity to enable it to build a long-term profile of the company’s operations and market forces. These challenges are often related to technical issues such as integration with previously siloed data or data security concerns.
Richard Sharpe, CEO of Competitive Insights, a supply chain analytics company, believes that the data quality problem is a complex issue that can have many different causes. However, he believes that these challenges can be overcome by management having a clear understanding of what they’re trying to achieve. “You have to show that what you’re ultimately trying to do with supply chain data analytics is to make the enterprise more successful and profitable.” This then leads to support being provided by company leadership who, in tandem with operations managers, can develop the processes required to govern quality data collection. This includes proper consultation with subject matter experts who can help ensure that all data is properly validated.
Managing data volumes
New technologies make it possible for supply chain organisations to collect huge volumes of information from an ever-expanding number of sources. These data points can quickly run into the billions, making it challenging to analyse with any level of accuracy or lead directly to innovation and improvement.
This means that despite many organisations embracing Big Data strategies, many do not actually derive sustainable value from the data they’re accumulating because they begin to drown in the sheer volume of data or don’t have the appropriate software and management tools to make use of it. A common phrase used to summarise this effect is “paralysis by analysis”. Without a thorough understanding of the technologies and systems needed to process and store the data collected, this can be an easy condition for an organisation to become afflicted by.
Building the infrastructure
Companies need to invest in the right technologies to have a true 360-degree view of their business. And in many cases, these technologies can involve large initial capital outlays. Getting the infrastructure in place is key to being able to collect, process, and analyse data that enables you to track inventory, assets and materials in your supply chain.
Putting in place the infrastructure may also require additional training expenses, so that staff are properly trained in how to use new software platforms or to maintain sensors and other new IoT devices. In some cases, this will extend to requiring hiring new talent capable of using and interpreting new analytical tools.
Big Data offers huge opportunities to supply chain organisations, as vital information contained within multiple data sources can now be consolidated and analysed. These new perspectives can reveal the insights necessary to understand and solve problems that were previously considered too complex. New insights can also encourage organisations to scale intelligent systems across all activities in the supply chain, embedding intelligence in every part of the business.
There is also no doubt that implementing comprehensive Big Data solutions can involve new and significant challenges. However, once the new infrastructure and processes are in place, the nature of modern Cloud-based networks allows for data to be accessed easily from anywhere at any time. It also allows for other benefits beyond cost reduction and production gains to be realised over time, such as ongoing rather than just one-off efficiency gains and improved transparency and compliance tracking across the entire organisation.
About the Author
Bastian Managing Director, Tony Richter, is a supply chain industry expert with 7+ years executing senior supply chain search across APAC. He works exclusively with a small portfolio of clients and prides himself on the creation of a transparent, credible, and focused approach. This ensures long-term trust can be established with all clients and candidates.
To find out more about the challenges and opportunities offered by Big Data to supply chain, or to gain a deeper understanding of the technology and Big Data trends currently underway in the industry, talk to an industry expert at http://bconsult.io/
By Karin Bursa, Executive Vice President, Logility
Now that the holiday season is behind us, retailers can sleep easy, right? Well, no. Seasons are now both shorter and more frequent which means you quickly move on to the next one. However, a large and rapidly growing issue has emerged: the cost of returns. Unwanted gifts, incorrect sizes, styles and fits that didn’t match expectations, the reasons are countless. To attract and retain customers, many retailers strive to make the return process as frictionless as possible. But at what cost? The ease of returning an online purchase has turned the bedroom into the retail fitting room. Consumers now purchase multiple variations of the same product to “try on” at home and then return the rest.
Following the 2017 holiday season, several industry pundits proclaimed retailers would lose about $90 billion (yes… billion!) in returned merchandise that could not be resold (Good news for FedEx and UPS: People just opened $90 billion in unwanted gifts). Recently, another report published claiming this number reached $107 billion for 2017 ($107 Billion Lost In Returns). Regardless of the final number, we are talking about a lot of money that simply should not be “thrown away to erode margins.”
Returns can be forecasted and much of that inventory can be placed back onto store shelves or made available through ecommerce, discount locations, etc. So, if retailers know the returns are going to happen, why are the losses so high? I sat down with retail industry veteran Jim Brown to learn more.
Karin: Are you surprised at the high cost of returns?
Jim: Not at all. When I was in the shoe industry, we experienced a higher-than-average rate of returns that could not be sold. Today, the consumer’s mindset has evolved and applied the same logic we saw in the shoe industry, try on a wide variety before you find the right one, to the rest of their purchasing habits. Consumers today are more comfortable ordering more and returning most of that order. It is too easy to add items to an online shopping basket knowing you have the option to return the merchandise with free shipping. And, since you used a credit card, you’ll never have to pay out-of-pocket.
Karin: Based on your experience, what happens to this merchandise?
Jim: Basic items typically do not make up the bulk of the returned merchandise. So, if the items are re-saleable, a lot of them will move into a markdown status by the time they make their way back to the store, or into the available warehouse inventory due to selling seasons. Unfortunately, it’s not as simple as taking it from the initial customer and placing it back on the shelf. Often, there are many hands that will interact with the merchandise—tags may have been removed, packaging may be defective, etc. All of this takes time, resources and investment to re-create and ready the merchandise for resale. Time is money and each ‘touch’ depletes your margin.
Karin: Why are retailers not able to place the merchandise back in circulation?
Jim: Most retailers will try, or have a process that should accommodate getting the product back into the inventory. The reality is most retail supply chains are optimized to bulk move allocated or replenished goods to the stores/locations. Handling one item at a time is a very labour-intensive activity. Determining if the item is damaged, repairable, tagged, packaged appropriately, etc. all adds to this cost. If you consider the margin on a single item, the least costly option may be to not handle it all. Of course, this is dependent upon the cost and margin of the item, so you need policies in place that accommodate all types of merchandise sold. This is the same reason why reducing store-to-store transfers is so important for retailers.
Karin: Are certain industries more prone to this issue?
Jim: Definitely. Health and beauty is a good example because this industry is heavily regulated. Once a safety seal is broken, that item is off the market for resale. Ready-to-wear is another good example due to its specific sizing which is also prone to returns. Technology becomes obsolete quickly, and the packaging is almost impossible to return to its’ ‘factory fresh’ condition. This forces the majority of these returns to be sold at a markdown, contribute to that staggering number you mentioned earlier and result in ‘open box’ promotions and discounts.
Karin: What are some of the ways retailers mitigate this issue?
Jim: This has become increasingly more difficult. In the past, retailers could require return authorizations or a short return window. However, in today’s competitive environment where shoppers have more options, retailers are hesitant to put up any customer service barriers. The prevalence of social media means one bad experience can be amplified across a broad audience and impact future sales. If I know the return process will be a hassle, chances are I will shop elsewhere. The best way to mitigate returns is to get the transaction right with the customer at the point of purchase. By providing as much information about the item to them as possible, easy access to customer reviews, etc. will lessen the chance that an item will come back up front. Some retailers are experimenting with virtual dressing rooms and other innovative technology to help minimize the volume of returns.
The cost of returns is truly an astonishing figure; however, as Jim outlines retailers are just not set up to handle the one-off item returns in a cost-effective manner. There are ways to minimize the burden including getting the sale right from the start. Additionally, retailers need to forecast the returns as a part of their planning process and develop more cost-effective measures for handling the merchandise as it comes back. If you are able to better predict the amount of returned merchandise you are likely better equipped to collaborate with your suppliers and partners to mitigate the cost to you while still delighting your customers.
About the Author
Karin Bursa, Executive Vice President, Logility
With more than 25 years of experience in the development, support and marketing of enterprise software solutions, Karin is able to provide The Voyager Blog several provoking perspectives including market-shaping events, end-user perspectives and technical reviews. She is a widely quoted source on the evolution of the supply chain, frequent author to many leading publications, and can be found speaking at many of the industry’s leading conferences.
It seems like the phrase “digital transformation” is everywhere these days. There are as many definitions for digital transformation and articles on the subject. I like the definition provided in i-scoop’s online guide to digital transformation.
“Digital transformation is the profound transformation of business and organisational activities, processes, competencies and models to fully leverage the changes and opportunities of a mix of digital technologies and their accelerating impact across society in a strategic and prioritised way, with present and future shifts in mind.”
The digitisation of a supply chain involves creating a detailed data model that mirrors the intricacies of an actual end-to-end supply chain network. (Learn more in Technology Evaluation Center’s report, The Impact of Digital Transformation on the Supply Chain.) Done right, a digital twin will have enough detail to model the information, money, and product flow from acquisition of components, through production, distribution and fulfilment to the customer. Model element include forecasts, capacities, inventory positions, lead-times, resource availability, costs, revenues, and profits. Finally, the model needs constant updates of customer, production, purchase, and distribution order status to ensure analysis and resulting actions reflect what is currently happening in the physical supply chain.
The benefits of digital transformation are plentiful. Below are three tangible benefits of digitally transforming your supply chain:
A very visible benefit of building a digital twin of your supply chain is the ability to use the information to automate routine process steps and free up resources to work on more value-added activities. Advanced supply chain systems have exception-based workflow and active alerts that when used in conjunction with user-defined limits can automatically process purchase, manufacturing, distribution and customer orders. Human intervention only takes place when plans, transactions, orders, etc. fall outside of defined limits.
Continuous Planning & Optimal Response:
Digitization of the supply chain unleashes the full capabilities of today’s powerful supply chain solutions leading to game changing competitive breakthroughs in customer service and value creation. One such capability is the application of algorithmic optimization in the areas of demand, inventory, supply, manufacturing, and transportation planning. The rich supply chain data available through a digital twin provides the foundation and inputs required for effective algorithmic optimization.
Another advanced supply chain capability is continuous planning. A supply chain digital twin contains up-to-date information on capacities and transactions. As new events take place (for example a new customer order, or a delayed replenishment) a planner can quickly determine an optimal response. Continuous planning and optimal response capabilities often lead to reduction in costs (manufacturing, inventory, transportation) and improvements in customer service (fill-rates, cycle-times).
Often the largest benefits from digitizing the supply chain come from new insights gained from the ability to conduct in-depth end-to-end analysis. The ability to analyze expected demand versus capacitated supply and determine financial impacts of multiple “what-if” scenarios provides the information needed to head off potential risks and fully embrace opportunities. A digital twin of the supply chain provides the information needed to make smart decisions on when to enter new markets, where to introduce new products, when and where to increase production capacity, and how to effectively compete. A digital twin provides a rich environment for running “what-if” scenarios of likely disruptions to determine the appropriate response before they happen. When the disruption does take place, a pre-established plan can be executed beating competitors to market.
How might a digital supply chain transformation change your daily life?
- You have real-time, accurate information, eliminating the need for data manipulation
- Collaboration on actual supply chain activities is online and in real-time
- “What-If” scenarios and simulations are automatic, intelligent and include sufficient data to make informed decisions
- Supply chain decisions move from calendar driven to continuous optimal response
A digital transformation of your supply chain can help you harness visibility, velocity and value and allow you to compete and win in today’s competitive marketplace.
To learn more about digital transformation, read Technology Evaluation Center’s report, The Impact of Digital Transformation on the Supply Chain.
About the author
Henry Canitz is The Product Marketing & Business Development Director at Logility. To read more of Henry’s insights visit www.logility.com/blog.
Last week, even the Colonel couldn’t help KFC restaurants in the United Kingdom. Approximately 800 of the 900 KFCs in the U.K. temporarily closed because of a chicken shortage, according to CNN Money.
The supply problem was pinpointed to issues with the restaurant chain’s new distribution partner, DHL. A KFC spokesperson described the issue as “teething problems” related to the transition that happened just a week before. DHL leaders reported that many of its deliveries were incomplete or delayed because of operational issues.
Although the exact details of this disruption management plan were not outlined in the article, KFC’s explanation to its customers was quick. The restaurant chain first alerted consumers via social media with a post that read, “Some chickens have now crossed the road, the rest are waiting at the Pelican Crossing.” KFC also set up a landing page on its website to report store operations.
Then KFC purchased a full-page ad in British newspapers to apologize to its clientele. The ad featured an empty chicken bucket with the chain’s initials scrambled to read “FCK,” a nod to an expletive that, in this case, means oops or whoops, along with an apology note. The company continues to offer humor-filled updates via social media. Although 95 percent of the restaurants have reopened, some are still operating with limited menus because of the distribution disruptions.
Public relations expert Rupert Younger, director of the Oxford University Centre for Corporate Reputation, applauded KFC’s effort to apologize and explain the issue to the public. “It speaks to a business that understand[s] that mistakes were made and they’re prepared to have fun at their own expense,” he said. He also told CNN Money that he was impressed that KFC’s ad did not outright blame DHL for the issue. Younger expects that KFC will soon face an increased demand because of its open, authentic and humorous apology.
I think we can all learn a lesson from KFC here. Disruptions happen, and supply challenges can be a headache for everyone involved. But, while you’re fixing the problem and planning for the future, transparency and a bit of humor can go a long way with your customers. A positive attitude can foster positive relationships going forward.
Risk and recovery
As KFC recovers from this supply chain challenge, no doubt the restaurant chain will update its disruption management strategy. One potential preventive measure could be to add protective capacity, which the APICS Dictionary defines as, “The resource capacity needed to protect system throughput — ensuring that some capacity above the capacity required to exploit the constraint is available to catch up when disruptions inevitably occur.”
When managing disruptions, it helps to have a risk management plan in place. APICS can equip you with the tools to build a risk management plan to anticipate and recover from disruptions. By participating in APICS Risk Management seminars and elective topic presentations at APICS 2018, you will learn about risk and supply chain management, how to assess and control risk, and more. In addition, earning your APICS Risk Management Education Certificate shows your employer that you are ready to tackle risks for your company. Visit apics.org/risk to learn more.
About the author
Abe Eshkenazi, APICS CEO
While retailers are still celebrating one of the strongest holiday buying seasons in recent years, the secondary retail market is now enjoying its own successful season. Once consumers take their unwanted items back to retailers, resellers and reverse logistics groups acquire those items to turn their own profits, according to an article in The Wall Street Journal.
The National Retail Federation reports that holiday sales totalled nearly $692 billion in the last two months of 2017. Reverse logistics provider Optoro estimates that about 13 percent, or $90 billion, of that merchandise, will be returned by the end of this month. The most commonly returned items include clothing and apparel, electronics, beauty products, and sports and outdoor gear.
About half of this returned merchandise is restocked on the retailers’ shelves and often resold at a discount. Some 5 billion pounds of merchandise is just thrown away because this option is cheaper than restocking and reselling the items. The remainder is picked up and sold by the secondary retail market. Retailers have actually improved their reverse logistics processes in the past few years, with many being able to process hundreds or thousands of items a day, noted Tony Sciarrotta, executive director of the Reverse Logistics Association. Some retailers even add a second logistics shift to help manage the returned items and move them to the next selling point as quickly as possible, he said.
As a result of these return trends, January and February tend to be the busiest months for resellers and the reverse supply chain, explained Howard Rosenberg, chief executive of B-Stock Solutions. B-Stock Solutions manages liquidation sites for Best Buy and Sears, among other major retailers, and auction sites for retailers such as Costco, Macy’s, JCPenney and Lowe’s. “It’s just mayhem during this period,” Rosenberg said.
Resellers acquire the returned items through liquidation sites at a deep discount, enabling them to turn a profit. For example, last week, Best Buy sold 49 returned washing machines and dryers on one online auction site for $13,300 — a 68 percent discount. Similarly, on the same day, Sears resold four pallets of sportswear, intimate apparel and accessories for only $5,825 — a 93 percent discount. Damaged or bulk items usually have the greatest discounts.
Because of the strong holiday selling and returning seasons in the past few years, the resale market is stronger than ever. Post-retail sales of returned and overstocked items totalled $554.2 billion in 2016 — only $137.8 billion less than 2017’s November and December sales — and have been growing at approximately 7.5 percent a year, reported Zac Rogers, an operations and supply chain professor at Colorado State University. Nearly half of those 2016 sales were collected by salvage dealers and online auction houses, the remaining half collected by smaller vendors like dollar stores, factory outlets, pawn shops and flea markets.
The secondary retail market also received a volume surge this year following the rise in online purchases, which are more likely to be returned than items purchased in a physical store.
In conjunction, online liquidators like B-Stock, Liquidation.com and Optoro’s Bulq.com have grown their businesses. Online auction sales have increased 66 percent in the past 10 years, and combined sales through factory outlets, dollar stores and value retailers have more than doubled.
Be a part of the action
These retail trends are fueling the growth of the reverse supply chain, which the APICS Dictionary defines as, “The planning and controlling of the processes of moving goods from the point of consumption back to the point of origin for repair, reclamation, recycling or disposal,” or, in this case, resale. The growing secondary retail market will need resources to collect, manage and move an increasing amount of inventory to the new end users.
APICS offers resources to help you and your company participate in the growing reverse supply chain. Consider earning your APICS Certified in Logistics, Transportation and Distribution (CLTD) designation. The APICS CLTD program covers reverse logistics as well as capacity planning and demand management, order management, inventory and warehouse management, transportation, global logistics, logistics network design, sustainability and other important topics. Learn more at asci.org.au/cltd.
Author – CEO, APICS