If you had the chance to read my first story about Family Voraus X, you would have read the uncertainty they and everyone of us live nowadays. Their story will inspire business executives to use uncertainty as a driver for opportunity and build a resilient enterprise, a set of lessons and topics which will be covered in the next parts of this story series.

Today, Family Voraus X decided to visit a retail shop in Munich, Germany, imagine you did the same, a cashmere shirt catches your eye. The fabric would ship from suppliers in China or Mongolia. Chinese or Mongolian suppliers will supply threads from Vietnam or Poland. This thread is made from cashmere grown in Indian farms. This is just a simple example, imagine complex products like semiconductors with multi-tier suppliers across the globe, and companies now find it almost impossible to track all these suppliers. When the pandemic started, many companies were caught in surprise when they discovered that one of their products relies on a supplier in Wuhan. This is just merely one example of why we are facing a supply chain crisis.

Germany is one of the countries affected by the current supply chain disruptions. Indeed, German industrial output has been dropping in the past 3 months, according to VDMA, while 81% of mechanical engineering companies in Germany are facing disruptions in the supply chain and facing transport and logistics issues. Production in June was 6.8 percent lower than the pre-pandemic levels and automotive manufacturing has been facing a shortage in semiconductors thus dragging its output.

The semiconductor shortage hit Germany’s automotive industry and placed more than 10,000 Audi employees on short-time work time. A shortage that is not limited to semiconductors but also spans products like metal paper, wood, and plastics. 74.4 percent of building materials dealers in Germany reported bottlenecks in wood supply. Bundesbank, Germany’s central bank, predicted that with the continued uncertainty in supply, economic growth will be 3.7% less than the forecast in June. 3000 surveyed German companies believe that supply chain issues will continue to last at least until next year. It might be even a long-term issue though while the effects are currently throttling durable enterprises like Siemens, Daimer, and BMW.

Semiconductors became a cornerstone to many industries and it comprises a highly specialized, capital intensive concentrated value chain. The semiconductor production process is characterized by 3 steps: Design, Fabrication, and Assembly. Market entry strategies towards fabrication where countries like Taiwan and South Korea have almost 79% of market share are often faced by deadlocks including but not limited to the high levels of expertise needed for Fabrication and the billions needed in capital expenditures.

Innovation in semiconductors is now focused on miniaturization, and back in October 2019, in K-19 Plastics Exhibition in Dusseldorf, I delivered a keynote and discussed Tokyo Institute of Technology Research’s work in single-molecule electronic devices. Indeed, polymers will play a key role in single-molecule electronic devices and will stage for Miniaturized AI. The consistent efforts of miniaturization put pressure on upgrading an already sophisticated machinery, making it costly to start an new fabrication plant in terms of bringing investing in new technologies and attracting skilled workforce. Given the latter, it might be a good option for countries trying to capture the semiconductors value chain to focus on research and development in chip design and software instead of fabrication.

The US President, Joe Biden, met semiconductor producers last September to pitch a program that urges companies to submit information about their supply chains. Earlier in the year, he also placed a $50 billion fund for the US semiconductor industry.

It is not of less importance for Germany and the EU Commission. European Commission President Ursula von der Leyen announced a “European Semiconductor Act” to create a high-class European chip ecosystem that includes production which is expressed as “securing technological sovereignty”.

Furthermore,  semiconductors clearly play a key role in the future of cars. As Şahin Albayrak, Head of AI Lab at the Technical University of Berlin likes to frame it: The car of the future is basically a tablet on wheels with a very large battery. So, algorithms and electronics will cost not less than half of the car value in the next couple of years. Semiconductors will be the key to prolonging the battery life of these vehicles. And the heart of these cars will be algorithms and not mechanical engines anymore. We are talking here about 100 million lines of software code in comparison to 8 million lines of code for a 787 Boeing super-jumbo.

We have already seen the alliances between automotive companies and data companies, for example, Volkswagen is connecting data from all machines, plants, and systems across 124 factory sites gathered from sensors on the shop floor–and AWS Outposts. In addition, BMW’s car as a sensor or Carasso brings a big number of sensor data that is sent to AWS cloud in order to deliver more accurate speed limits in a cap map, improved road geometries , fewer map errors, and smarter route guidance. Since batteries are dangerous to transport, microfactories will play a key role in bringing car manufacturing close to battery production sites. 

Also, last week, I was invited by AWS  to Munich for the Analyst and Press only Digital Builders Showroom as part of AWS Re:Invent summit, however, due to uncertainty and the new variant, it went virtual at the end and from my cocoon, here’s an interesting outlook presented by Martin Schleicher of Contintenal as he showcased the growing value of software in vehicles of the future:

If the innovation cycles for software are six months, compared to up to five years for cars according to Holger Seidel from the Fraunhofer Institute for Factory Research IFF in Magdeburg, then how do you think automotive companies would keep up?

Some questions we are often seeing in news headlines include: Why is there a shortage in semiconductors? How long will Semiconductor shortage last? Is there still a shortage of semiconductors?

However, the above facts are reassuring the need for executives more than ever before to manage uncertainty and change the way they used to plan for their businesses instead of just figuring out why did it all started!

Stay tuned for next part in this series as family Voraus X take us into possible solutions executives can take to become resilient under uncertainty.

Family Voraus X, living in the 21st century, is made of two business executives, two sons and daughter. They begin their day taking kids to school, commuting to work by the riverside, arriving at their desks and doing business as usual.

Who would have thought that a “black swan” event would change that routine and give rise to questions Voraus X family didn’t expect would come through…

Uncertainty started at home, in pandemic times, as they tried to approach a question from kids: Mom, Dad, when will our schools reopen? An uncertainty that continues to their commute as we get the news that lorry drivers are not providing petrol to fuel stations. 

And even if they manage to arrive at their office new challenges are coming to the table: How long will the container ship take to arrive and how much is the number of products in it? Is it because of the Covid-19 pandemic, shortage in containers, or lorry driver shortage causing UK’s petrol stations closures and stockpiling? Why is there a supply chain crisis? Is supply chain affected by COVID-19? All these questions are legitimate in the current supply chain crisis for any business executive, not only Voraus X. 

Indeed, we have been living in globalization and lean manufacturing that resulted in complex, global multi-tier, and fragmented supply networks and reduced (optimized) inventory levels. However, for any business executive, it is one thing that matters now: managing uncertainty i.e. How can we predict the shortage in supply?

However, predicting shortage is not even enough, it is how you use that prediction to gain advantage over your competitors. Harvard Business Review describes this as:  “organizational resilience, the ability of an organization to successfully confront the unforeseen, has always been a core element of success. Supply chain resilience no longer implies merely the ability to manage risk. It now assumes that the ability to manage risk means being better positioned than competitors to deal with—and even gain advantage from—disruptions”.

However, before starting to develop your strategy to become a resilient enterprise and manage uncertainty, you first need to define it and see how to translate it into behavior in your business. And, once it becomes part of your organization’s behavior and social learning culture, you can then start utilizing your predictions to gain advantage from disruptions. 

Defining Uncertainty:

One of the best definitions I came across comes from the Austrian philosopher, Ludwig Wittgenstein who likes to put it: “Wer an allem zweifeln wollte, der würde auch nicht bis zum Zweifel kommen. Das Spiel des Zweifelns selbst setzt schon die Gewißheit voraus”. If you tried to doubt everything you would not get as far as doubting anything. The game of doubting itself presupposes certainty. One cannot begin to doubt without being certain, without first believing a set of propositions to be true.  

Take Voraus X kids’ question as an example, they learn by believing us at first, doubt would come after their belief. There should be a foundation for uncertainty as it is not universal. It needs a tolerable measure of certainty. This certainty will be the base that businesses can rely upon to face any similar future crisis.

How to translate uncertainty into behavior in your business?

The whole point of doubting and uncertainty is to use it as a vehicle for behavioral change, to reach certainty.  In order for certainty to become a behavior, it should be accompanied by affection and not only cognition. 

The anthropological perspective bolsters the above thought.  Ethnography is seen as a technology for an anthropologist’s imagination, and anthropologists also think of uncertainty as a “technology of the imagination”, disruption, surrender, and moving beyond. Thus, enabling us not just to imagine but also to improvise, change, and intervene. In a nutshell, it enables us to respond creatively to the world.

Let’s follow Family Voraus X family’s journey through these uncertain times, In the next blog, I’ll tell you how a visit to a retail shop in Munich, Germany was followed by tremendous bottlenecks that affected supply chains globally while focusing my lens on the German landscape.  If you keep following Voraus X family series, you’ll be able to broaden your perspective about supply chain crisis solutions, understand the different ways/layers for building a resilient enterprise and managing uncertainty with the help of industry 4.0 and automation, in addition to the, often overlooked, cultural and behavioral change in organizations, and how would this help you and especially my executives audience make use of such disruptions.

When I took this photo back on March 13, 2020, overlooking this busy highway that connects Petaling Jaya with Kuala Lumpur, I didn’t know that I was just a few hours away from the 1st Movement Control Order (MCO)/lockdown in Malaysia. And, and phrases like “new normal”, “supply chain disruptions”, “Semiconductor shortage” are what will top the news in the next months.

If you use a field glass, you will also see the Headquarters of NXP Semiconductors Sdn Bhd in Petaling Jaya.  Ofcourse, a field glass might magnify your view but it won’t be able to predict that in June 2021, NXP Semiconductors Sdn Bhd would operate at 60% of their workforce and can only operate fully once 80 to 100 percent of the workers were vaccinated.

These disruptions are causing Europe to rethink its semiconductor manufacturing strategies by, for example, planning to build edge fabs, especially that according to Bruegel, Europe’s market share of semiconductor production is only 2 percent. 

My quark news for today is coming from the Netherlands with NXP semiconductors.

NXP is powering Electronic Design Automation in the cloud (Powered by AWS) in order to accelerate semiconductor innovation and getting new designs to market faster. Besides, that will enhance the productivity for semiconductor design and verification, and free its engineers to focus on chip innovation. In my point of view, is a bold move to increase their footprint in the right spot of the semiconductor industry, by focusing on innovation in chip design and software instead of shifting the focus to fabrication. 

All this will open up a couple of questions which we will be covering in an upcoming blog piece answering questions such as why there is semiconductor shortage, when did semiconductor shortage start, and how to build supply chain resilience.

To Know More about NXP’s cloud-based EDA, check AWS blog published just now. Stay tuned for our coverage on the semiconductor shortage issue.

This brought to you by our Quark News Edition. 

With the increasing advancement of AI and ML technologies comes the understanding that our current relationship with AI is deeply shaped by our society’s historical experience with technology. In this course, AI engineers and enthusiasts will gain the skills to design human-centered AI experiences using human-focused science. Learn how to deploy techniques from social science to tackle cognitive gaps and fallacies when building effective computing platforms. Through case studies, practical tips and design anthropology exercises, you observe how anthropology and ML can add a new dimension to AI.

When was the first time I saw Facebook’s new smart glasses “Ray-Ban Stories”? A couple of minutes ago? Ha…No, a couple of years ago, and specifically in Leipziger Pl. 9, Berlin, Germany at the Spy’s museum! In the latter glasses, a tiny digital video camera is integrated into the traditional spy glasses and videos saved into an accompanying recorder. In Facebook’s glasses, it is stored in your smart phones though…

Two main talking points about this product:

Privacy and Adoption:

• Privacy?

Obviously in AI, I do believe that German’s Bauhaus Design Philosophy ” Form Follows Function” does not apply to AI. Even if the LED indicator light flickers on when the Facebook’s glasses are recording, notifying people that they are being photographed or filmed, different types of biases, uncertainties and discriminations will come into surface from the usage of the product.

• Adoption? In a world of deepfakes, we might not be surprised to see a shift in human behaviour that is very similar to the peri-personal space behaviour our ancestors had in the stone age while they experienced stone age technologies. Indeed, we might wear these smart glasses to record interactions with our surroundings so that it protect us from baseless allegations in future automated cities. It also comes with the cool Ray-Ban brand

I speak more about these concepts in my newly released UC Berkeley Extension course here.

I am happy to know your thoughts/comments?

Today’s factories will need to be able to produce customized products with variable requirements, and this will trigger them to become smart factories, which will leverage emerging technologies like AI and the IoT, or what is being called the Industrial IoT (IIoT). In the data economy, industrial companies will need to act fast, since relying on static scheduling in production will not suffice to cope with changing order information. Also, they will need to be able to distribute the workload among robots and machines dynamically, also taking into account the equipment’s energy consumption, which most traditional factories are just not equipped to do.

The Necessary Edge

Personalizing services through dynamic task distribution, in this context, requires a technology that achieves ultra-low latency at the level of the local machines that distribute the production tasks. Because it is a burden to send this data to a cloud manufacturing platform for analysis, edge computing is the recommended approach for this scenario, as it would be able to support real-time production cycles. For a smart factory engaged in high personalization and a variety of machine tasks, predefined rules would not work unless an intelligent edge node is established that can use its own self-organized coordination abilities to negotiate with other nodes to solve largescale problems in parallel. Machines and robots at a factory are now starting to be equipped with edge nodes that can measure energy consumption. These nodes also have analytics embedded, such as optimization algorithms like swarm intelligence, which can prioritize tasks based on each machine’s individual energy consumption.

In the scenario above, each edge node has intelligence and autonomy, as each one is embedded with reasoning, planning, and machine-to-machine coordination abilities. The role of these edge nodes differs from that of a smart meter, which can only estimate the relationship between the workload of one piece of equipment and the energy it is consuming. In contrast, these edge nodes act as data storage, analytics, and intelligent information interaction nodes.

What Does This Edge Platform Look Like?        

This use case, among many others, including predictive maintenance through real-time altering, is not possible without a proper multi-access edge computing (MEC) platform. A MEC platform working with 5G could make it possible to produce ultra-low-latency-sensitive manufacturing applications. Because of the large volumes of data that will be generated by the machines and robots in a smart factory, applications like this will be required, not only to handle the data volumes but also to deliver the needed processing capability in a local context with location awareness. A MEC platform consists of different tiers that collect data from IIoT machines to perform different tasks across each tier, such as reducing redundancy and errors; decoding and compressing the data, as well performing other raw-data pre-processing operations; and storing the data. To be optimally effective, a MEC platform must also be able to support deep-learning-processing-intensive, low-latency features such as real-time anomaly alerts, to meet stakeholders’ needs for enhanced decision-making insights.

Why Does the MEC Platform Need Data Virtualization?

To be optimally effective, a MEC platform requires access to all data sources across all the different tiers. However, MEC platforms that rely on traditional data integration methods like ETL processes will struggle to connect to these disparate data sources. This is why MEC platforms require an agile data integration technology like data virtualization to be fully effective. Data virtualization can be deployed at any intermediary layer between the edge and data center or the cloud, including organization and region-based layers. It works by abstracting the data sources and creating a unified view of all the information, i.e. maintenance, inventory, parts, and dealers, to optimize processes and enable predictive analysis.

Finding the balance between machines and human creativity in a smart factory could be through the emergence of virtual voice assistants that will be the next interface in a smart factory.

• Bill of Materials (BOM) identifies all product parts and the timeframe and cost of production.
• Big Data store, manage, and track BOM or even schedule required materials that should be available to reduce costs.
• 5G could make ultra low latency sensitive manufacturing applications possible.
• Data Virtualization securely combines data from diverse source systems and create unified views that made it easier to take corrective steps to ensure ideal yield and efficient plants.
• Edge computing orchestrate production and task scheduling.
• Virtual voice assistants will be the interface that resonates and talks with humans to track all bill of material goods, assemblies, subassemblies and tracks finished goods and assets in a factory to alert and communicate to us information about their status and condition. These VAs are becoming more anthropomorphistic embodying humanistic traits from voice tonality to design, convenience, sociability, and experience.

Maximize Yield, Minimize Downtime

To keep up with supply and demand, manufacturers can settle for nothing less than highly optimized systems that maximize yield and minimize business downtime. They need advanced technologies that work together and despite this high level of automation and collaboration among machines and robots in a smart factory, humans will always remain central to the manufacturing operations. They will always be monitoring, controlling, and supervising the manufacturing process to deliver new innovations in today’s data economy.

Smart Factories will play a key role in the post corona world. Stay Tuned for the next posts to know more!

* This post was originally published at Datavirtualizationblog.com