CSCMP's Supply Chain Quarterly
January 17, 2020

T = MIC<sup>2</sup>: Game-changing trends and supply chain's "new normal"

Five technology trends are shaping a future where mobility, integration, complexity, and competition will be the defining characteristics of successful supply chain strategy.

Supply chain managers continue to be challenged by exogenous forces that influence consumer behavior and business practices. To achieve long-term, sustainable success, managers will have to identify potentially "game-changing" forces and analyze their implications. That, in turn, will allow them to proactively respond to the opportunities and threats posed by these external factors.

Based on our research, which was supported by the Center for Supply Chain Research (CSCR) at The Pennsylvania State University's Smeal College of Business, we concluded that technology has become—and will remain for the foreseeable future—the major "game changer" for the global marketplace as well as the impetus for improvement of business practices. While the influence of technology is not new, the underlying trends may be more difficult to discern and therefore merit exploration and discussion.

Article Figures
[Figure 1] The pathway to the
[Figure 1] The pathway to the "new normal" Enlarge this image

In this article, we point out some of the important dimensions of technological change that will influence supply chains and supply chain management. Our conclusions are based upon a review of the literature, reports from key organizations, and discussions at two events sponsored by CSCR: a Supply Chain Leaders Forum (SCLF) in March 2014 and a research breakout session at a CSCR Corporate Sponsor meeting in April 2014. The two CSCR programs brought together more than 80 academicians and top supply chain professionals from a variety of companies and industries to discuss technology and related trends in supply chain management.

As a result of our research, we identified five game-changing technologies and related emerging trends for supply chains. The five game-changing technologies are mobile communication, deep learning, cloud computing, intelligent robotics, and manufacturing digitization. In investigating these trends, we articulate a "new normal" for characteristics of supply chains, which we call MIC2Mobility,Integration, Complexity, and Competition—that will shape areas of strategic focus for the foreseeable future. What follows is a discussion of each of these trends and its potential impact in the context of MIC2.

Mobile communication technologies (mobile telephones and devices, mobile connectivity standards, mobile platforms, and mobile applications) have advanced remarkably in recent years. The mobile phone system in North America, for example, was primarily analog throughout the 1980s, but is now digitized with 4G standard networks. Mobile phones and devices have advanced with the development of mobile connectivity standards and a variety of different proprietary platforms or operating systems for smartphones, such as Windows Mobile, RIM Blackberry OS, Apple iPhone iOS, and Google's Android. Advanced mobile platforms, in turn, are significantly enhancing mobile applications development. "App stores," which allow users to purchase and download new applications for their devices, have now become quite common. Some familiar names include Google Android Market (now Google Play), Windows Phone Marketplace, Blackberry App World, and Apple App Store.1

Together these developments have completely revolutionized the capabilities of mobile phones and devices. Notable trends in the supply chain context include mobile technologies used in conjunction with bar-code scanning, digital imaging, and real-time mapping and global positioning system (GPS). All of these are designed to capture up-to-date information and extend visibility and control over a wider array of functionalities in supply chains. Trending areas of applications and some examples include:

  • Outside-the-office data access: access to enterprise applications such as enterprise resource planning (ERP) or transportation management systems (TMS);
  • Freight and carrier management: obtain freight rate quotes, find and share loads, track shipment status, and receive shipment notifications;
  • Transportation operations: real-time routing directions and traffic reports, real-time automated route operations, dynamic driver dispatching, and driver hours-of-service calculation;
  • Asset and inventory management: real-time automated vehicle and equipment locating, and inventory location and accountability for each participant, such as loading-dock workers, delivery drivers, and receivables clerks;
  • Customer service: order and delivery status visibility, and truck arrival notification;
  • Paperwork and documentation: scanning and signature capture for proof of delivery, and documentation of damage and usage conditions for warranty claims.

The technology called "deep learning" has its roots in the artificial neural networks (also known as neural nets) that are patterned to mimic the arrangement of neurons in the brain, and the connections (or synapses) between the neurons. The development of neural nets began in the late 1950s, and the technology has advanced from single-layer, supervised learning to multilayer, unsupervised applications. The improved algorithms, aided by modern computational power, have led to rapid improvements in the speed and accuracy of various applications (for example, speech, text, image, and pattern recognition) now known as "deep learning."2

Deep learning has been put to use extensively, and there are many examples. Using speech recognition, Google Now and Apple's Siri both function as a voice-activated virtual personal assistant, while Microsoft's Speech Recognition allows users to voice-operate Windows and programs. Facial recognition is used in Apple's iPhoto, Google's Picasa, and Facebook's automatic face identification and name tagging of uploaded pictures. Pattern recognition enables Netflix's and Amazon's personalized recommendations, and Facebook's analysis of posts for better ad targeting and news feeds. Text recognition is used in Adobe's optical character recognition function, and computer vision is used in Google's Street View.3 In a supply chain environment, deep learning applications emphasize autonomous learning that has become a "smart computing" aspect of data analytics and software applications, especially in the areas of "big data" mining and pre-screening; self-adapting planning and performance management; and predictive analytics (demand forecasting and risk management).

Metaphoric for clouds' incorporeal and universal nature, cloud computing is a practice of offering access to a shared pool of computing resources (such as servers, storage systems, applications, and networks) over the Internet. The cloud computing market has grown rapidly and is on its way to generating revenues of US $100 billion a year.4 A notable trend in cloud computing is the emergence of service-oriented architecture (SOA) that comes in four broad variations:5

  • Software-as-a-Service (SaaS) can be described as a software distribution service. Examples of SaaS cloud solutions are customer relationship management (CRM) tools (such as, workflow management tools (for example NetSuite's SuiteCloud Developer Tools), and electronic data interchange (such as
  • Platform-as-a-Service (PaaS) is a platform for the creation of software (as opposed to the delivery of software in SaaS). Examples of PaaS are Google Application Engine, Microsoft Azure Services, and
  • Infrastructure-as-a-Service (IaaS) is a cloud computing infrastructure-resource service for operating systems, storage, servers, networking components, and data-center space. IaaS enables the storing and accessing of data and programs, as well as a range of solutions such as managed servers, managed hosting (website hosting, business application hosting, and cloud media hosting) over the Internet instead of on a computer's hard drive. Examples of IaaS providers are Google Cloud, Rackspace Cloud, and Amazon Web Service.
  • Business-Process-as-a-Service (BPaaS) is business process outsourcing (BPO) services that are delivered and accessible over the Internet. Common areas of cloud-based BPO services are employee benefits management, business travel procurement, business process management (such as IBM Blueworks Live), and industry-specific processes (for example, Google Adsense for advertising services).

SaaS is the most mature market and the most widely used cloud computing service. It has become an accepted deployment model for many software categories, with CRM leading the global SaaS market.6 In the past few years, interest in SaaS-based supply chain solutions (as opposed to the traditional purchase-and-install format) is growing. Adoption rates are particularly strong in collaborative sourcing and procurement, transportation management systems (TMS), and global trade management (GTM) markets.7

Industrial robots have been around for over 50 years. However, it is only recently that a new generation of less expensive, more sophisticated, easily trained, artificially intelligent robots has emerged. In the supply chain area, the integration of intelligent robotics into operations is becoming more prominent in manufacturing and warehousing.

In manufacturing, advances in assembly-line robots have enabled new "cooperative working" models and the technique of "guiding and teaching by example." Cooperative working features will change today's manufacturing plants, which are configured with a clear division of labor between humans and robots, to ones that will host humans and robots working side by side, allowing the skills of human workers to be combined with the precision and force that robots can provide. Additionally, "guiding and teaching by example"—rather than the typical inflexible and uneconomic programming—makes it feasible to use intelligent robots for the small-batch assembly that is common in many small and medium-size organizations.8

In warehousing, robotic warehousing has gained traction, accelerated by the order fulfillment challenges of e-commerce. The system of smart machine-to-machine integration in robotic warehousing requires sophisticated robotic engineering, vision and sensing technologies, and advanced software and control systems. Modern warehouse robots possess the mechanical capabilities for movement and mobility that are necessary for navigating around the complex environment of a distribution facility. They are also highly autonomous and are capable of sensing and intelligently adjusting to different products and tasks (such as varying alignments, pallet balance, and mixed-pallet arrangements).9 Perhaps the most talked-about case in point is the giant e-tailer Amazon, which currently has about 1,000 robots working in its fulfillment centers and is on its way to increasing that number to at least 10,000 by the end of 2014.10

As business investment in industrial robotics continues to increase, highly automated, human-controlled factories and distribution facilities will continue to emerge. These new facilities are marked by more complex interactions between humans, machines, and processes—a situation that has already changed the skill requirements in some industries. Factory and warehouse workers will have to be trained to work alongside robots and be empowered to program and guide the machines, shifting them from manual labor to skilled, quasi-manual labor.11

The manufacturing of physical products has been advancing in the digital space. Manufacturing digitization—where both the product design and the manufacturing process model (from production layout to step sequencing for a specific product) are carried out digitally—is not a new concept. However, it is the innovation in the additive manufacturing (AM) or industrial three-dimensional (3-D) printing technology that has garnered attention for its revolutionary potential. Even politicians and government officials have high hopes for this technological breakthrough. In his 2013 second-term State of the Union address, U.S. President Obama described 3-D printing as "having the potential to revolutionize the way we make almost everything."12

Initially used most widely in product prototyping, 3-D printing technology is increasingly being adopted for a number of finished products. The technology is being recognized for its numerous advantages: quick turnaround from design to production; cost-effective production of small lots with special-purpose tooling; design flexibility for complex product structures; and ability to enable product customization. Hence, 3-D printing is a particularly advantageous alternative to conventional manufacturing technologies for products that are high in labor cost, increase their value with customization, require complex tooling for new products, and/or are produced in small quantities.

Despite the technology's advantages and promising growth, the high costs of 3-D printing machines, maintenance, and material are inhibiting wider adoption. Machines for 3-D printing and their maintenance costs can range from less than US $1,000 to over $1 million, depending on the process employed. Costs of materials for 3-D printing are also high. Executives at one of the CSCR meetings gave examples of 3-D polymers that can cost 53 to 104 times more than the injection-molding equivalent, and 3-D metal that can be 7 to 15 times more expensive than conventional materials. The price difference is partially due to higher standards of material purity and composition, and to the extra step beyond traditional material processing that is required for 3-D printing. In addition, materials are not standardized, there are multiple competing producers, and demand for 3-D printing materials remains relatively low. Contributing further to the high material prices is the 3-D printer manufacturers' practice of controlling which materials are "certified" for use with their equipment, preventing customers from sourcing materials from the supplier(s) of their choice and creating barriers to entry for third-party material suppliers.

In the near term, participants in the CSCR events view 3-D printing as being advantageous for fit-to-scale prototypes, low-demand parts with long lead times, and inventory management (because digital inventories can be printed on demand locally). They speculate that we will see wider adoption of 3-D printing as the associated technologies improve, machine and material costs decline, and companies better understand where those technologies fit into their supply chain processes.

In the long term, executives believe that 3-D printing technologies could play a key role in open-source collaboration. Until recently, open-source product design has lagged behind open-source software development projects. The latter possess mature, widely used open-sourced design tools and minimal costs for duplication and distribution of the software code. With advances in 3-D printing technologies, more companies are actively exploring open-source collaboration in the physical-product world. In this environment, the digital design or blueprint files for a physical product can be shared within the growing number of "open-source community" companies and individuals. Prototypes can then be rapidly developed using 3-D printers, and any subsequent improvements made to the design can be redistributed.

The "new normal": T = MIC2
The effects of these five technology trends on supply chain management are already in play. Aggregated, they are creating disruptions in established social and commercial relationships within the business world, and they are driving fundamental changes in global supply chains. We connote the "new normal" in supply chains that is being driven by the five game-changing technology trends (T) as MIC2, where M = mobility, I = integration, and C2 = complexity and competition. The pathway to the new normal is depicted in Figure 1. In the following sections, we discuss the impact that the characteristics of mobility, integration, complexity, and competition are likely to have on supply chain decision making in the future.

The new normal of mobility is characterized by the ease with which the means of consumption and supply chain operations can be mobilized geographically and/or functionally. On the consumption end of the spectrum, an innovative blend of mobile communication, social media, and creative e-commerce and m-commerce (mobile commerce) applications has led to the era of anywhere, anytime consumers, sometimes referred to as omnichannel consumers. Omnichannel consumers digitally research, select, and pay for a product, and then take possession of it either in a store (in-store pickup of goods ordered on mobile devices or computers) or at home (home delivery). They demand a seamless and unified shopping experience in which they can move from one channel to another while accessing the same features, information, and service quality from store personnel, online customer service staff, and delivery persons.

Echoing developments in the consumer space, companies in the business-to-business environment are now striving to achieve geographical and/or functional mobility across core supply chain processes through a creative combination of the game-changing technologies discussed earlier. In manufacturing, digital design for a physical product can now be sent to any machine for production anywhere, whether in a factory or to a 3-D printer in the back of a service van. As one executive who attended a CSCR program explained, replacement parts can now be 3-D printed on demand by field personnel, who no longer have to carry complete spare-parts inventories. In transportation, cloud-enabled transportation "control towers," coupled with enablers such as cloud-based TMS solutions, enhance mobility through dynamic shipment routing and scheduling, multimodal transportation-capacity matching, exception management, and so forth. In warehousing and distribution, companies now must develop mobility of processes and resources to perform not only traditional store fulfillment and direct-to-customer shipping for online orders, but also store-to-store transfers and even store fulfillment (in-store pickup) of goods ordered on computers and mobile devices. And, as another executive pointed out, cross-channel, integrated enterprises that can tap into inventory sources—whether from the supplier, the warehouse, a distributor, or the store shelf—to meet anywhere, anytime business-to-consumer (B2C) and business-to-business (B2B) requirements are growing in importance.

Complexity in global supply chains mirrors the increased mobility in consumption and supply chain activities. For a start, cloud computing, intelligent robotics, and manufacturing digitization technologies have made startups easier for small and medium-size firms, and even individual entrepreneurs, eroding much of the scale advantages often enjoyed by large enterprises. As a result, executives at our meetings projected that supply chain complexities will grow as supply chains become more fragmented, with more specialized parties on the playing field.

Adding to the production network complexities are the dramatically changing requirements of omnichannel consumers. These consumers expect more services and products to be personalized, conveniently available at low prices, and delivered in narrower windows (within set hours) via an expanding number of shipping choices, including same-day, next-day, expedited, premium, and many other configurations. Together, these expectations raise the level of complexity in various aspects of supply chains.

With the growth in e-commerce and m-commerce, companies now must re-examine their supply chain processes and strategies in order to create a unified experience for consumers across channels. They must do this while optimizing the costs associated with an increase in the number of stock-keeping units (SKUs) due to larger product assortments and an expanding number of delivery-service offerings designed to meet individual consumers' fulfillment preferences. There is a consensus among supply chain executives in our program that a deep understanding of consumers, realigned store operations, fulfillment excellence, and integrated information technology (IT) systems are keys to success. Nevertheless, they concede that the complexities driven by omnichannel commerce remain significant. Currently, information sharing is not yet timely across channels, and companies across industries are still experimenting with supply chain network and process design to manage omnichannel commerce.

For anywhere-anytime consumers, value is not just about personalization, it is also about shared beliefs and experiences. This is particularly important to younger consumers who value shared knowledge and experiences and are concerned about ethical and responsible business practices. These consumers increasingly rely on the advice of family, friends, colleagues, and third-party specialists who evaluate and rate products and services. At the same time, they are becoming increasingly critical and vocal through social media sites about their disappointments (for example, poor service or unavailability of products) and against companies that are perceived to be socially irresponsible. As the executives in the CSCR programs emphasized, complexities increase because negative information now travels faster, and therefore companies need to develop "social listening" capability. This capability is imperative not only to detect and prevent any potentially damaging publicity but also to develop a deeper understanding of omnichannel consumer shopping and buying behavior, as well as to gauge demand signals or changes in consumer preferences that can affect product, pricing, and supply chain strategies.

With the new normal of mobility and complexity comes a new basis of competition, in which "big data" (defined as large pools of data that can be captured, communicated, aggregated, stored, and analyzed) holds unforeseen power and impact. Executives in our sessions concurred that **bold italic{data-driven strategies} are becoming an essential ingredient of competitive strategies. To capitalize on this potential new source of competitive advantage, successful data-driven strategies leverage big data by exploiting a combination of mobile communication and social media; increased data access facilitated by the cloud; and smarter analytics aided by deep learning.

Investments in analytic capabilities that are designed to cultivate data-driven competitive advantages are growing. In this respect, the executives described a host of possible analytic applications of varying breadth and depth. In terms of depth, these can range from relatively basic descriptive analytics (connect with reality, a "single source of the truth"), to predictive analytics (understand the most likely future scenario and its business implications), prescriptive analytics (recommend the best alternative), and cognitive analytics (highly automated optimization solutions that get "smarter" over time). As for the breadth of applications, the analytics employed can range from single or multiple functions within the enterprise to the connection of trading partners in single or multiple functions (make, source, and deliver). However, executives cautioned that having the right talent on staff, particularly data-savvy managers and analysts, is also important in developing data-driven competitive strategies to their fullest potential.

The game-changing technologies discussed in this article bring forth markedly different ways companies can better integrate and enhance collaboration with customers, supply chain partners, and employees. Technology-driven changes in this respect predominantly evolve in three distinctive contexts, including machine-to-machine integration, cross-channel integration, and social integration.

Machines, which previously operated largely as separate assets, have undergone a transformation such that they have become more integrated parts of certain business processes. Machine-to-machine (M2M) integration (also known as the "Internet of Things" [IoT]), is becoming more common in supply chain management. M2M integration enables networked devices (such as surveillance cameras, in-vehicle systems, smart meters, and tracking devices) to exchange information without the manual assistance of humans. Here, sensor devices—for example, radio frequency identification (RFID) and wireless sensor-networking technologies—capture an event (such as inventory level or truck location) and relay the information through a wireless, wired, or hybrid communication network. "Smart" middleware then translates the captured event into meaningful information; for instance, that items need restocking or trucks need rerouting.

Smart M2M has now become an important aspect of both automated manufacturing systems and automated warehouse management. Other common applications include offsite diagnostics and maintenance, fleet management, and remote and/or condition-based monitoring. One example the executives discussed is the use of M2M to enable vehicle and cargo-container tracking, including monitoring driving speeds, fuel consumption, temperature and humidity, and delivery progress. They also mentioned remote shelf monitoring as an example of M2M in a retail setting, and noted its advantages of providing real-time visibility into their inventory and enabling efficient automatic replenishments.

In the increasingly complex omnichannel commerce environment, cross-channel integration requires both intra-organizational and inter-organizational reconfigurations. Intra-organizationally, as speed of information becomes a key capability, the IT department is becoming a front-line resource that must be integrated with all aspects of business functions. Store operations need to be realigned to perform the dual functions of both retail store and warehouse in order to optimize service quality and fulfillment cost. With their roles becoming more strategically elevated within organizations, supply chain functions like merchandising, distribution, and logistics must be integrated with critical enablers such as IT and store operations. Meanwhile, inter-organizational integration with logistics service providers grows in importance, particularly given the rise of specialist logistics companies that focus on e-commerce or multichannel fulfillment. These specialists have built into their distribution centers more types of material handling equipment and value-added capabilities (for instance, packaging, kitting, and final assembly) that handle the typically small and highly variable e-commerce and m-commerce orders.

Another element of the integration new normal is social integration, which encompasses social brand and social business aspects. According to executives who attended the CSCR meetings, social brand integration requires companies to use social media as part of their marketing strategy, while social business integration requires the integration of IT systems, processes, and planning with social media. They observed that companies are exploring and experimenting with various enterprise social technologies, which differ from consumer-grade tools like Facebook and Twitter. These business-grade tools are available from leading vendors and include such products as Cisco Systems' Quad, IBM's Connections, Microsoft's SharePoint Workspace, Oracle's WebCenter, SAP's StreamWork, and Yammer Inc.'s Yammer.

With advances in functionality and designs that are more integrated with existing business processes, applications, and data, enterprise social technologies are shaping the environment in which companies promote collaboration and knowledge sharing among their employees as well as with customers and supply chain partners. Some of the features the executives discussed include: wikis used for knowledge sharing; shared "whiteboards" used for managing projects; employee social networks used to provide access to information and specialized expertise across business units; and social communities used to engage customers and derive insights about their preferences and to experiment with new offerings.

An important force for change
Over the course of the last several decades, exogenous factors have shaped and developed the supply chains of many companies as well as their approach to achieving efficiency and effectiveness. Deregulation of transportation was a disruptive force during the 1980s that transformed not only the transportation service providers but also the scale and competitiveness of many of their customers. In the 1990s the emergence of large-scale, economically powerful retailers changed the dynamics in many supply chains. These retailers demanded and received more customized service from suppliers and manufacturers in order to improve their own efficiency and be able to offer lower consumer prices. The 2000s brought increased globalization, a major force that changed industry dynamics and competitive landscapes on a worldwide basis. In this environment, supply chain management emerged as a critical ingredient of the financial success of many companies.

Now, in the 2010s and for the foreseeable future, technology has become the most important force for organizational change. In this paper, we identified and described five game-changing technology trends that we believe will transform supply chains. These technology trends are creating a global supply chain of the future that will operate in an economic arena of highly mobilized production and consumption, and will allow small but global players to be more competitive. Success in this new, more complex landscape will require an emphasis on unified, cross-channel services and on the leveraging of data-driven insights through investment in analytic tools and knowledgeable people as the foundation for integration and competitive advantages.

We have tried to point out some of the important dimensions of technological change, but we have merely scratched the surface. The best and worst is yet to come—so be vigilant. Our best advice: "Look out" to identify disruptive exogenous forces, "look around" to gauge the competitive climate, and "look in" to assess your resources and capabilities.

1. SwitchPay, "The History of Mobile Technology in Business" (infographic) 2013.
2. Robert D. Hof, "10 Breakthrough Technologies 2013: Deep Learning," MIT Technology Review, April 23, 2013.
3. Colin Lewis, "The Economic Impact of the Robotic Revolution," Robohub, February 19, 2014.
4. Eric Griffith, "What Is Cloud Computing?" PC Magazine, March 13, 2013.
5. Louis Columbus, "Forecasting Public Cloud Adoption in the Enterprise,", July 2, 2012; Griffith, "What Is Cloud Computing?"
6. Louis Columbus, "Gartner Predicts CRM Will Be a $36B Market by 2017,", June 18, 2013.
7. Bridget McCrea, "Supply Chain Technology: 2014 State of TMS—Cost Reductions and ROI Continue to Soar," Logistics Management, February 2014.
8. International Electrotechnical Commission (IEC), "Robots: Reshaping Manufacturing," E-tech, January/February 2013.
9. David Cardinal, "Warehouse Robots Come of Age," Extreme Tech, March 28, 2012.
10. Katie Lobosco, "Army of Robots to Invade Amazon Warehouses," CNN Money, May 22, 2014.
11. Rodney Brooks, "Robots at Work: Toward a Smarter Factory," The Futurist 47, no. 3 (2013).
12. Doug Gross, "Obama's Speech Highlights Rise of 3-D Printing,", February 13, 2013.

John J. Coyle is Professor Emeritus of Logistics and Supply Chain Management at Smeal College of Business, Pennsylvania State University. Kusumal Ruamsook is a research associate at The Center for Supply Chain Research, and instructor in supply chain management at the Smeal College of Business, at The Pennsylvania State University.

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