Earlier this month, Clarkson University’s Global Supply Chain Management (GSCM) program presented its 17th annual Executive Seminar, delivering state-of-the-art education to corporate professionals.
“We are pleased that our executive seminar continues to attract supply chain professionals from several highly respected global companies,” said Professor Farzad Mahmoodi, the Joel Goldschein ’57 Endowed Chair in Global Supply Chain Management and director of the program. “It’s a strong endorsement of the quality of our faculty and the relevance of our curriculum.”
The annual, four-day, on-campus program attracted participants from Amazon, Toyota, Stanley Black & Decker, Xerox, Lockheed Martin, Verizon, Corning, Raymond Corporation, Entegris, Par Technology and Indium.
The participants came to Clarkson from 12 states: California, Colorado, Connecticut, Illinois, Indiana, Maryland, Massachusetts, Michigan, Minnesota, New Jersey, New York and Ohio.
In addition to lectures by faculty experts, the seminar utilized a highly interactive format that employs team and hands-on activities, including simulations and negotiations exercises. Participants also benefited from networking opportunities with industry professionals and Clarkson faculty.
The market for supply chain management (SCM) software, maintenance and services continued its growth in 2016, generating more than $11.1 billion, a 9% increase over 2015 revenues, according to the research firm Gartner.
That total includes applications for supply chain execution (SCE), supply chain planning (SCP) and procurement software. Since the market’s 2% decline in 2009, the market has posted double-digit growth in four of the past six years, according to Gartner. The SCM market is expected to exceed $13 billion in total software revenue by the end of 2017 and exceed $19 billion by 2021, Gartner forecasts, with software as a service (SaaS) enabling new growth opportunities.
“It continues to be a good year for the supply chain overall,” says Chad Eschinger, managing vice president of Gartner. “The Cloud-based segment grew 20%, which is consistent with what we’ve seen in recent years.”
The push for Cloud capabilities also fueled some of the acquisition activity over the last year. Eschinger cites examples such as Infor’s acquisition of GT Nexus, Kewill’s acquisition of LeanLogistics, Oracle’s acquisitions of LogFire and NetSuite, and E2open’s acquisitions of Terra Technology and, more recently, Steelwedge.
“Broadly speaking, we’re seeing cyclical consolidation,” Eschinger says. “For some companies it’s a land grab, for others it’s an effort to add functional and technical underpinnings to go to the Cloud or provide a fuller complement of Cloud capabilities.”
Suite vendors are increasingly inclined to offer end-to-end solutions, Eschinger says, tying in customer relationship management capabilities, replenishment, network design, clienteling and more. In addition to supply chain efficiency, these solutions are also aimed at improving and standardizing the consumer’s experience.
“The Amazon effect continues to wreak havoc in retail and for manufacturers selling direct-to-consumer,” Eschinger says. “Everyone wants real-time visibility into inventory, so data and the associated analytics continue to be front and center for most organizations.”
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Plex Systems, a developer of cloud ERP for manufacturing, has introduced two new analytic applications designed to provide manufacturers insight into supply chain performance and their workforce.
The new Supply Chain and Human Capital analytic applications build on the library of applications in the IntelliPlex Analytic Application Suite, a broad suite of cloud analytics for manufacturing organizations.
The Plex Manufacturing Cloud is designed to connect people, processes, systems and products in manufacturing enterprises. The goal is not only to streamline and automates operations, but also enable greater access to companywide data. The IntelliPlex suite of analytic applications aims to turn that data into configurable, role-based decision support dashboards–with deep drill-down and drill-across capabilities. The IntelliPlex Analytic Application Suite includes analytics for sales, order management, procurement, production and finance professionals.
IntelliPlex Supply Chain Analytic Application
The new IntelliPlex Supply Chain Analytic application provides a dashboard for managing strategic programs, such as enterprise supplier performance, inventory and materials management and customer success. Metrics include:
- On-time delivery and return rates by supplier, part, material, etc.
- Production backlog by part group, product time, etc.
- Spend by supplier and type, including unapproved spend
- Inventory turns and aging based on type, location, etc.
- Materials management accuracy, adjustments and trends by type, location, etc.
- On-time fill rate, customer lead time, average days to ship, fulfillment by location
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Speaking to a full house at the BROWZ Client Summit 2016 Sundance Resort, V.P. of Product Development, Aaron Rudd stated “BROWZ OneView is a significant development in the evolution of supply chain management software that will not only meet our clients needs today, but will meet their supply chain needs as they expand in the future.”
BROWZ OneView is an entirely new interface and user experience for BROWZ clients.
“Our goal was to enhance the way our clients interact with our solutions and their supply chain. From conducting a simple supplier search to in-depth analysis across a global supply chain. BROWZ is empowering our clients with the new OneView platform,” Rudd said.
“The software provides meaningful insight into the entire supply chain using key performance indicators which also provides the flexibility to analyze the performance of individual locations or specified risk level with the click of a button.”
Having an effective supply chain has always been key to retail success. Whether you call it micro-merchandising or the customer-centric supply chain, the challenge has traditionally been to quickly identify trends or activity in a store that is outperforming the norm, and rapidly roll this out to all stores with similar attributes and customer behaviours. Indeed, much of the ‘flair’ that separated well- from poorly performing retail operators was down to the ability of some key individuals to spot trends, clusters and patterns that drove better understanding of customer behaviour, and act upon these insights to deliver to customers’ demands.
This macro-level insight is, however, no longer good enough. Today, retailers need to be able to understand not only how items are performing across the entire retail estate as well as within individual stores and spot trends and patterns accordingly; they also need to be able to marry this micro-level performance to geographic and demographic information to reflect the demand from a particular store’s customers. And, they need to be able to forecast how those same items will be performing in weeks and months to come.
This is the capability that is required to truly deliver today’s customer-centric supply chain. But it demands a level of detail simply too difficult for humans to manage. Software solutions are designed to raise the average performance level by helping the poor or below average operators benefit from the expertise of the higher performers and placing this supporting technology in the hands of those key individuals who would act as district or regional manager.
But the needs of today’s customer-centric supply chain have outpaced even the majority of these solutions.
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Of all the disruptive technologies we track, big data analytics is the biggest. It’s also among the haziest in terms of what it really means to supply chain. In fact, its importance seems more to reflect the assumed convergence of trends for massively increasing amounts of data and ever faster analytical methods for crunching that data. In other words, the 81percent of all supply chain executives surveyed who say big data analytics is ‘disruptive and important’ are likely just assuming it’s big rather than knowing first-hand.
Does this mean we’re all being fooled? Not at all. In fact, the analogy of eating an elephant is probably fair since there are at least two things we can count on: we can’t swallow it all in one bite, and no matter where we start, we’ll be eating for a long time.
So, dig in!
Getting better at everything
Searching SCM World’s content library for ‘big data analytics’ turns up more than 1,200 citations. The first screen alone includes examples for spend analytics, customer service performance, manufacturing variability, logistics optimisation, consumer demand forecasting and supply chain risk management.
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Companies that want to effectively manage their supply chain must invest in business intelligence (BI) software, according to a recent Aberdeen Group survey of supply chain professionals. Survey respondents reported the main issues that drive BI initiatives include increased global operations complexity; lack of visibility into the supply chain; a need to improve top-line revenue; and increased exposure to risk in the supply chain. Fluctuating fuel costs, import/export restrictions and challenges, and thin profit margins are driving the need for businesses to clearly understand all the factors that affect their bottom line.
Business Intelligence essentially means converting the sea of data into knowledge for effective business use. Organizations have huge operational data that can be used for trend analysis and business strategies. To operate more efficiently, increase revenues, and foster collaboration among trading partners companies should implement BI software that illuminates the meaning behind the data.
There is a vast amount of data to collect and track within a supply chain, such as transportation costs, repair costs, key performance indicators on suppliers and carriers, and maintenance trends. Being able to drill down into this information to perform analysis and observe historical trends gives companies the game-changing information they need to transform their business.
Read more at Why Supply Chains Need Business Intelligence
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While many public companies focus their attention on embellishing their quarterly results, Amazon has always taken the long view.
The online retailer leader has invested heavily in infrastructure including a nationwide network of warehouses, robots which help ship orders, and even predictive technology that helps the company know what a customer plans to buy before he or she orders it.
Amazon even has a pioneering deal with the United States Postal Service which allows for Sunday delivery in some markets.
All of this has not come cheap, and it has hurt Amazon’s short-term profitability in some quarters, but it has helped the company build a strong competitive advantage over its chief rivals Wal-Mart and Target.
Those two physical retailers are struggling to change their supply chains to meet the needs of individual digital customers rather than stores. That’s a radical switch that requires major changes to how both brick-and-mortar chains operate.
But if either Wal-Mart or Target can hope to compete with Amazon, they have to recreate the digital leader’s ability to ship millions of products in a two-day window efficiently. Both companies seem to at least understand the problem and are taking steps to catch up.
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DHL, the world’s leading logistics company, today launched its latest white paper highlighting the untapped power of data-driven insight for the supply chain. The white paper has revealed that most companies are sitting upon a goldmine of untapped supply chain data that has the ability to give organizations a competitive edge. While this wealth of supply chain data already runs the day-to-day flow of goods around the world, the white paper has revealed a small group of trailblazing companies are utilizing this data as a predictive tool for accurate forecasting.
“The predictive enterprise: Where data science meets supply chain” is a white paper by Lisa Harrington, President of the lharrington group LLC that was commissioned by DHL to identify the opportunities available to companies to anticipate and even predict the future. It encourages companies to get ahead of their business and direct their global operations accordingly.
Data mining, pattern recognition, business analytics, business intelligence and other tools are coalescing into an emerging field of supply chain data science. These new intelligent analytic capabilities are changing supply chains – from reactive operations, to proactive and ultimately predictive operating models. The implications extend far beyond just reinventing the supply chain. They will help map the blueprint for the next-generation global company – the insight-driven enterprise.
Jesse Laver, Vice President, Global Sector Development, Technology, DHL Supply Chain, said, “At DHL, we’re helping our customers get ahead of the competition by working with them to harness the wealth of data information from across their businesses, allowing us to develop smarter supply chain solutions that factor in their wider business operations. For our technology customers, we use data analytics to predict what’s going on in the supply chain, such as what products are in high demand, so we can tailor our solutions accordingly.”
While supply chain analytics technologies and tools have come a long way in the last few years, integrating them into the enterprise is still far from easy. Companies typically progress through several stages of maturity as they adopt these technologies. The descriptive supply chain stage uses information and analytics systems to capture and present data in a way that helps managers understand what is happening.
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At its heart, supply chain management requires a balancing of operational efficiency, customer satisfaction and quality. Managing the true cost to serve for each and every order is the aspiration to allow better negotiation and value creation across the supply chain. Customer- and consumer-centricity helps anticipate product and service requirements. Supply chains are becoming more extended and complex with a consequent increase in risk and the need for resilience. There are multiple data sources making it difficult to manage and measure end-to-end processes and metrics. Aligning priorities through integrated planning remains pivotal, but there is an explosion of data available that needs to be incorporated and the value extracted to understand how supply and demand issues impact profit and revenue targets.
New technology provides greater supply chain transparency. Strategic supplier engagement continues to be important as a way of reducing costs and mitigating risk. Effective supply chain management can be either a compelling competitive differentiator or, conversely, a source of risk, cost and poor customer service.
Organizations are looking to enable better and more consistent decision-making across complex processes with diverse systems and data. Many are leveraging business intelligence (BI) platforms to give them the capability to make decisions across the organization, including environments in which mobility and access to decision-critical information on the go is crucial. Putting the information in the hands of the people on the front line—those managing supply chain processes—is key to enabling decision-making at the point of decision. But this requires synchronizing an enormous amount of data that comes from many systems and sources in a way that it can be easily consumed by people who need to act on the insights.
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