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Market Education Series- A Path Towards Internet of Things Enabled Service Management

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Supply Chain Matters kicks-off the first of a new market education series- A Path Towards Internet of Things Enabled Service Management, in collaboration with supply chain planning and service parts technology provider ToolsGroup.

This supply chain industry analyst is not alone in communicating the long-term implications and benefits of Internet of Things (IoT) technologies applied to multi-industry supply chain business processes.

When I speak to audiences on the future of industry supply chain capabilities, I often context that in over my 30 years of experiences and observations, what I always considered to be the “holy-grail” of our profession was the ability to connect the physical and digital components of various supply chain business processes. That vision is becoming much more of a reality as supply chain teams begin to leverage IoT data and information into planning and customer fulfillment decision-making. From my view, that reality is not the far away.  Planning 3 shutterstock 394279114 300x184 Market Education Series  A Path Towards Internet of Things Enabled Service Management

One of the most promising line-of-business areas that will benefit from IoT enabled technologies applied to supply chain will be equipment services management, especially service and spare parts management. Consider the possibilities when physical objects such as engines, motor vehicles, capital, and other forms of equipment, proactively communicate needs for required maintenance services, replenishment, or repair parts.

Consider the possibilities of far more knowledgeable insights into item-level service or spare parts product demand, more efficient and less costly multi-tier service echelon inventory management, and a more responsive services management process for your customers. A longstanding challenge in service or replenishment parts planning and management has always been the ability to forecast item-level demand when such demand is sporadic or sudden.  Now consider the opportunities to have demand-driven or predictive failure data and information emanating directly from the physical equipment.

Three to five years from today, equipment manufacturers will be communicating to investors about many of these new top-line revenue business growth areas where physical and digital interact in a more predictive service management business capability. Such capabilities insure maximum uptime for customers, supported with a super-efficient supply chain planning and resource management capability connects the physical with the digital.

This is all very possible. However, with any solid business model, there are requirements for foundational process and decision-making capabilities.  If your business or enterprise is considering such business models, now is the time to consider investments in fundamental decision-making support capabilities that can best take advantage of the implications of physical and digital coming together.

We submit one of the most fundamental investments to consider is that of a robust service parts planning and fulfillment process that leverages today’s more advanced capabilities of in-memory computing, machine learning and analytics to support automated decision-making and resource balancing. IoT married to machine learning and more predictive analytics pays near-term dividends for current service management processes as well as future, more robust business models.

In our four-part Supply Chain Matters market education series, A Path Towards Internet of Things Enabled Service Management, in collaboration with supply chain planning and service parts technology provider ToolsGroup, we will help readers to understand and be able to articulate the following:

  • The current state of service and spare parts planning processes and why tailored service parts planning capabilities so different than other forms of supply chain planning? Why is it increasingly becoming fundamental to any service management process and why are so many equipment manufacturers currently investing in this capability?
  • How does a robust service parts planning capability play a foundational role in an Internet of Things (IoT) enabled environment? How does such capabilities, augmented by new advanced technologies, enhancing the effectiveness of an overall IoT integrated process?
  • What are the overall benefits for customers and to the business, and what are some current-day examples? How is this best articulated to the C-Suite? Why equipment manufacturers and services providers are already on this path?

Join us over the coming weeks as we dive deeper into each of these topical areas reflecting on how to build the foundations for both a robust, more efficient, and less costly service parts planning capability as well as laying the critical foundation for new IoT enabled service management business models.

Bob Ferrari

© Copyright 2017. The Ferrari Consulting and Research Group and the Supply Chain Matters® blog. All rights reserved.

 


Autonomous Driving Technologies for Trucks Takes on Added Interest

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Supply Chain Matters continues to highlight exponential developments in advanced technologies that will eventually impact various industry supply chains with an update on increased investments in autonomous driving technologies for trucks.

In November of 2016, Supply Chain Matters observed why increasingly high-tech and semiconductor technology providers wanted to position themselves in automotive value-chains. There have been quite several significant merger, acquisition and strategic product development announcements involving automotive supply chains and the stakes involve which company will ultimately control and benefit from the movement of more advanced technology being embedded into value-chains of automobiles and transportation. As we noted last year, a lot of M&A and investment monies are being plowed into the automotive and transportation sector to take advantage of the various movements towards on-demand, autonomous and highly intelligent motor vehicles. This movement presents a competitive dynamic among traditional OEM’s who control brands and markets with those of technology companies that know about software and digital transformation.

It is now becoming ever more obvious that value-chains of short and long-haul trucks are another, perhaps more promising area of long-term strategic interest. The reasons are likely obvious to our readership audience. The increased savings in efficiencies, driver productivity, and overall safety make a case for more near-term investment. There is also the other elephant in the room, namely the continual shortage or turnover of qualified long-distance truck drivers. In September of last year, consulting firm McKinsey indicated in a research report- Delivering Change, the transition of commercial transport by 2025, that by this timeframe, at least one in three new heavy duty trucks will contain higher levels of onboard automation technology, including Level 4 autonomous technologies, that will buffer the need for full-time driving.

Another open question is obviously the receptivity of regulators to various forms of autonomous driving technologies applied to trucking and transport. There are some perceptions that European regulators have been more open to considerations of advanced technology, and have become directly involved in ongoing industry demonstrations of various forms of autonomous driving technology. US federal regulators, on the other hand, seem to be taking a more wait and see perspective. In either case, the receptivity by safety regulators will obviously be an important determinant in timing.

Latest Announcements

Semiconductor technology provider Nvidia whom originally developed of the Graphical Processing Unit (GPU) chip in 1999, and that ultimately sparked the growth of the PC gaming market. The company has moved on to redefine modern computer graphics and gaming platforms and has made advancements in parallel computing. More recently, GPU deep learning ignited modern artificial intelligence married with digital visualization— which Nvidia describes the next era of computing, has led to the development of autonomous vehicle technologies.

Thus far, Nvidia has been collaborating with what the company describes as a wide range of automotive partners, including Tesla, Mercedes Benz, Audi, and others. A recent presentation at an investor conference indicates 80+ companies are currently leveraging the company’s self-driving platform and that every Tesla Motors vehicle now comes equipped with DRIVE PX 2 for full self-driving capabilities

In a company blog posting in March, Nvidia announced that it’s working with PACCAR, maker of Kenworth, Peterbilt and DAF truck brands, on developing technology for autonomous vehicles. The same blog posting further announced a partnership with Tier One automotive parts and systems component producer Bosch, for self-driving car technology.

PACCAR has developed a proof-of-concept self-driving truck with SAE Level 4 (full self-driving) capability built on the DRIVE PX 2 technology. It includes elements of adaptive cruise control, the identification of digital objects along with lane-keeping technology to make trucks safer in long-distance hauling.

Convoy Approach

Wall Street is increasingly paying closer attention to autonomous driving technology applied to trucks and truck fleets. Earlier this month, Silicon Valley based software firm Peloton Technology raised $60 million in a second-round of funding for expanding its development and market presence in automating commercial truck fleets.

As its name implies in the field of competitive cycling, Peloton Technology supports the ability of trucks to travel in a convoy with a driver in the lead vehicle controlling various following truck (s). While the value proposition is predicated on higher safety and fuel savings, some in the industry are a bit skeptical on the notions and regulatory approval of an automated convoy of multiple trucks controlled by software. Instead, the software provider is initially focusing on supporting a convoy of two trucks, with the lead driver in full control of both vehicles. Peloton is planning development and deployment of its software for 2018.

Current investors in Peloton include Intel Corporation, Omnitracs LLC, Magna International, United Parcel Service and Volvo AB, all various value-chain players in trucking, transportation, autonomous driving and truck component technology.

Future Technology Leaders

If our readers have been scanning various other business and technology media, you have likely read that the trucking industry has struggled of-late because of the compelling need of fleet owners to want to invest in new, more fuel efficient and technology-laden trucks. The likely solution rests both in hybrid powered technologies and in increased levels of safety, driver productivity and automation.

Thus, over the coming months, a number of both established players and high-tech startups will all be vying to be the future technology innovators and leaders. Startups will bring the usual speed, agility, and advanced technology knowledge – all prerequisites for the majority of new business models. To counter new entrants, OEMs must demonstrate agility to both build their own digital capabilities and enter collaborative efforts with partners around the product value chain.

Established names such as Daimler, PACCAR, Scania, and Volvo will be contrasted with those of Otto (recently acquired by Uber), Nicola Motor Company, others and yes, even Tesla Motors.

Exponential technology developments will eventually impact many industry supply chains, the product value-chains they support, and the tools and technologies utilized to move physical goods. As in all things exponential, the question is timing, and the cycles of that timing are accelerating.

Bob Ferrari

© Copyright 2017. The Ferrari Consulting and Research Group and the Supply Chain Matters® blog. All rights reserved.


Describing an Exponential Organizational and Supply Chain Capability

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In February, this supply chain industry analyst attended the Oracle Modern Supply Chain Experience Conference held in San Jose California.  Through Supply Chain Matters, I have shared several prior observations and takeaways from this conference. We noted the extraordinary attendance, upwards of 2800 attendees at a supply chain management information technology focused conference. We further highlighted the momentum of Cloud-based technology deployments in the many different business process areas that today come under the umbrella of supply chain management along with the building interest levels surrounding Internet of Things (IoT) technology being applied to future supply chain management processes.

There was one keynote that I initially did not share in prior conference highlights, principally because I needed time to absorb the many compelling messages that were delivered. The title was Exponential Organizations and the presenter was Yuri van Geest, Co-Founder of Singularity University. Yuri Exponential Organizations sized 207x300 Describing an Exponential Organizational and Supply Chain Capabilityhas a background in organizational design and is noted as a keen observer of exponential technologies and trends.  He is a co-author of the book- Exponential Organizations- Why new organizations are ten times better, faster, and cheaper than yours (and what to do about it).

The keynote opened with van Geest recounting the dizzying exponential developments that have occurred in artificial intelligence, alternative energy, biotechnology and medicine, robotics, additive manufacturing, sensors, and drones. His primary message was that most of these exponential technology developments will eventually impact supply chains and the organizations and people that makeup this community. His takeaway message was that the best vision of the future is happening at the peripherals of such technology development.

My initial presumption was that many of the conference attendees would have a difficult time absorbing the stark nature of the messages or would dismiss this talk as that of a technology genius speaking far above an ability to absorb the real implications.  Frankly, the conference organizers should have allowed additional time to accommodate all the content as well as to allow for further audience interaction.

Since the conference, I have had the opportunity to read the book and revisit my notes from the keynote. My goal in this blog is help distill what I perceive to be some other key takeaway messages related to future supply chain management organizational purpose, design, and work activities, at least from my perspective after having time to really absorb the content.

Geest did a suberb job of translating today’s far more exponential technology trends to what he viewed as direct impacts on industry supply chains. As an example, he stated that over the next ten years, the exponential developments in 3D printing capabilities will foster the ability to print nearly everything in materials including molecular assembly. The implication is the ability for products to be produced within primary areas of consumption, with the model of contract manufacturing being one of virtual capabilities to receive electronic design information and print on-demand products. A further implication is a more localized supply chain or regional network.

The notions of machine learning or cognitive acquired deep learning technology capabilities will at some point in the future lead to autonomous supply chain planning and customer fulfillment, where algorithms and physical sensing manage supply chain needs. While on the subject of planning, the book declares traditional five-year planning as obsolete, and that in exponential organizations, there should never be more than a one-year planning cycle supplemented by continuous just-in-time learning and events.

Regarding the physical, Geest further spoke to the compelling impacts that IoT focused developments would have on supply chains.  In the book, there is a passage that is worth sharing:

In the same way that today we can no longer handle the complexities of air traffic control or supply chain management without algorithms, almost all the business insights and decisions of tomorrow will be data-driven.”

Obviously, the messages are profound and perhaps threatening to many. None the less, van Geest’s message is that we cannot ignore compelling events and individually, people need to be trained and prepared with new individual and team-based skills.

To better understand the implications, I turned back to book to ascertain what were described as the key competencies of the future Chief Operating Officer, Chief Human Resources Officer and either Chief Data or Chief Innovation Officers.

Here are just a few excerpts to ponder:

  • Digital based production and the unbundling of production steps will free the company to focus on its core competencies (customer relationships, R&D, design, and marketing)
  • The notion of a recycled materials supply chain where production materials recycled and reused multiple times.
  • Internet of Things sensors used to monitor the entire supply chain.
  • The need for long-distance transport to drop over time due to the rise of localized production and a closed-loop material supply chain.
  • Universal Cloud access to social technologies, data, and services, independent of physical location.
  • Data management systems that use methodologies, processes, architectures, and technologies to transform raw data into meaningful and useful business information, available to all teams.
  • The need for Big Data security practices.
  • The hiring of employees based on overall potential, not just past record of accomplishment, and on the premise of who can ask the right questions.
  • New notions of peer-based and continuous learning.
  • Reputation measured by contributions in communities and work teams.

 

The book addresses the obvious question regarding the impact on future jobs. The premise is that the democratization of technology will allow individuals and teams to follow their passions and create new economic opportunities and businesses, far different than work being performed today.

These are heady messages, and will cause some pause or skeptics. We applaud Oracle’s supply chain management  conference organizers for hosting such a thought-provoking presentation.

From our lens, there is no denying that the exponential changes occurring in technology and business will eventually impact how supply chains are manifested and managed. The question is in what time frames.

The other obvious question, will teams and individuals be prepared?

We encourage readers to share further thoughts and comments.

Bob Ferrari

© Copyright 2017. The Ferrari Consulting and Research Group and the Supply Chain Matters® blog. All rights reserved.


Apparel and Footwear Supply Chain Meets Industry 4.0 Adoption

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The first notions of what is today ‘s prolific global industry supply chain presence began with the apparel and footwear industry. Now this same industry is moving in the direction of Industry 4.0.

A posting by Digiwaxx Media’s TheBlast  observes that German based apparel and footwear manufacturer Adidas will soon start the marketing of shoes manufactured by robots within Germany.

This posting notes:

More than 20 years after Adidas ceased production activities in Germany and moved then to Asia, Adidas unveiled the group’s new prototype “Speedfactory” in Germany.”

The German footwear provider is also planning to operate similar “Speedfactory” in the United States along with one in Western Europe. Both the German and U.S. automated factories are initially being planned to produce upwards of half a million pair of shoes annually, and according to reports, would be priced similarly as those produced in Asia.  Addidas Futurecraft MFG 300x145 Apparel and Footwear Supply Chain Meets Industry 4.0 Adoption

The basis of the supply chain strategy is to produce closest to the major areas of product demand, thus avoiding added global transportation and inventory carrying costs. What has brought this strategy closer to fruition is the combination of higher direct labor costs in high volume manufacturing areas such as China, meeting the technology convergence of faster, more dexterous, and cheaper robots.

In his book, Thank You for Being Late, An Optimist’s Guide to Thriving in the Age of Accelerations, internationally recognized author Thomas Friedman has an entire chapter devoted to what is described as The Supernova. Noted by Friedman:

With each new (computing and technology) platform, the computing power bandwidth and software capabilities all meld together and change the method, cost, or power and speed in which we do things, or pioneer totally new things we can do that we never imagined- and sometimes all of the above. And these leaps are now coming faster and faster, at shorter and shorter intervals.”

Many publications cite the statistic that it took 50 years for the world to install the first million industrial robots while the next million will take only eight years to reach that milestone. That includes the wide-scale adoption of automated assembly techniques within China itself. Thus is the opportunity being provided to apparel and footwear providers, as well as other industry supply chains that have a high sensitivity to direct labor costs within respective products. Noted is an estimate from German robot producer Kuka indicating that a typical indutrial robot can cost in the area of 5 euros an hour to operate.

Nike was one of the first shoe manufacturers to pioneer the 3D printed Flynit athletic shoes five years ago and now, Adidas is pioneering its application of automated shoe manufacturing.

In the not too distant future, apparel manufacturers will do the same. Industry disruptors focused on “fast fashion” business strategies have been leveraging supply chain near-shoring strategies to provide far more agile responses to the latest and most prominent fashion trends. Their appeal to higher margin, in-demand fast fashion supports higher pricing and thus flexibilities to support near-shoring of fast production. The key to fast fashion has proven to be more agile supply chain sourcing strategies and such strategies will be enhanced further when robotics is applied to the precision cutting and sewing of fabrics.

Of course, there are many social and workforce implications to these trends, all very important to social responsibility practices. That topic deserves a more detailed blog commentary.

Suffice at this point, to close with the takeaway that an industry that was noted as one of the earliest adopters of global based, low-cost manufacturing outsourcing is now on the verge of adopting Industry 4.0 supply chain practices.

Bob Ferrari

© Copyright 2017. The Ferrari Consulting and Research Group and the Supply Chain Matters® blog. All rights reserved.


Technology Addressing the Convergence of Internet of Things and Smart Manufacturing Deployments

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As a follow-up to Supply Chain Matters recent attendance and coverage of this year’s Oracle Modern Supply Chain Experience Conference, we wanted to specifically follow-up on some sessions that addressed Internet of Things (IoT) enablement of future smart manufacturing, supply chain and service management business processes.  Oracle MSCE banner Technology Addressing the Convergence of Internet of Things and Smart Manufacturing Deployments

Noted in many of our prior blog commentaries related to IoT deployment strategies, many businesses are starting to connect the dots relative to the existing wave of new advanced technologies that can literally allow connecting physical things with digitally focused applications, processes, and new business services. Included are the notions of what is commonly described as Industry 4.0, or the fourth industrial revolution, enabled by more sophisticated sensors, additive manufacturing, new iterations of analytics and data management. The common objective is convergence- a convergence of operational technologies along with data management, business applications software and decision-support technologies working together in an integrated real-time manner.

When this author presents or speaks with supply chain management focused audiences, I often describe the objective as what I once termed as the “holy grail” of supply chain management, our ability to connect the physical and the digital, now coming much closer to reality.

In Oracle’s approach to supporting customer IoT transformation, multiple speakers emphasized the importance of the overall IT architecture strategies required in addressing the different needs at the physical layer (the machines), and the digital applications layer of applications and information needs. We cannot stress how important these strategies and approaches have been addressed in multiple conferences and discussions we have been involved in. The obvious most important consideration is the management of data at each level.

At the physical layer, data is purely operational in nature. We are talking about sensor readings, alarms, state conditions, fault detection and all sorts of other operational data. As emphasized in prior highlights of a recent MIT IoT focused conference, engineers are fully aware that much of this data can be spurious, perhaps upwards of 60 percent. On the other hand, the remaining data can point to important and insightful information when placed in context with other data. The Oracle presentations cited sample classes of questions related to the era of “Smart Manufacturing”:

Are there patterns of events that tend to cause or lead to actual equipment failures?

Is there a correlation between product failures in the field and the manufacturing process originally used to manufacture that product?

Can we predict the likelihood of a product defect and avoid costly downtime?

Many developers on the front lines of current IoT initiatives will readily tell you that the challenges related to filtering and capturing the correct physical data, whether structured, unstructured or time-series in-nature are hard, but not insurmountable. A current reality is that most physical or operational assets currently reside behind a data-protected firewall, for valid reasons. As we have noted in prior commentaries, developers cite consistent and secure data management standards as well as combinations of encryption technologies as the means to unlock data discovery across various layers. Oracle emphasizes the need for a robust and scalable technology foundation supported by an open standard, in-memory, Hadoop data lake approach that supports three distinct data types in a secure manner.

A further critical aspect often includes distinct data aggregation at both the physical and digital application layers, each aggregation providing added contextualization to overall intelligence and required decision-making. Managing all this data needs to further include a more cost effective approach, and that is where the advantages of Cloud-based deployment and storage strategies play an important consideration.

Some of our functional or IT readers who experienced prior IT data warehouse approaches can well relate to the frustrations for the ability of various functional users to mine or discover data on their own without the direct assistance of IT. We were pleased to observe that Oracle’s approach is anchored to presenting of data to differing personas or business roles, ranging from that of occasional or frequent business user or domain expert, to an actual data scientist.

The Oracle presenters cited a jam or jelly manufacturing process as an example of the goal of actionable manufacturing intelligence that was developed for a pilot customer:

What most everyone has today is an operational report of what has occurred, namely descriptive analytics. For example, 68 percent of batches of strawberry jam made in July, incurred a production yield of between 78-82 percent.

The goal is actionable intelligence supported by more prescriptive or predictive data and analytics. In the same example, the 68 percent of batches of 78-82 percent production yield:

  • Occurred during the second shift and involved a common operator
  • The sugar utilized came from specific identified lots from a specific supplier(s)
  • The mixer speed variation was in a certain range and ambient humidity reading but did encounter some discernable variations.

This added context of the data provides the intelligence as well as determinants to manage higher manufacturing yields or identify potential production issues in a timelier manner.  These are the notions of mining the data, that can be applied to many other supply chain related business processes or business model support needs, many of which can save substantial amounts and open many new opportunities for equipment services.

A final observation relates to current IoT approaches and pilot efforts perhaps being investigated. In the many technology and industry perspectives we have reviewed or encountered, it is important to stress that teams evaluate prospective IoT technology vendors not only on the specific technology approaches and capabilities they provide, but also on the partner ecosystem they recruit and support, along with actions to adapt and support an open standards approach for data security as well as data maintenance.

Bob Ferrari

© Copyright 2017. The Ferrari Consulting and Research Group and the Supply Chain Matters® blog. All rights reserved.

 


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