SEO Keywords: SMRP 33, industrial reliability conference, asset management trends, maintenance best practices, reliability professionals
Meta Description: Discover why SMRP 33 is the must-attend event for reliability and maintenance professionals. Learn about the industry renaissance and why 2026 should be on your calendar.

The Society for Maintenance & Reliability Professionals (SMRP) conference has always been a cornerstone for industrial leaders, but this year’s 33rd edition in Fort Worth, Texas marked a turning point. Attendance surged, vendors jumped from 130 to 220, and the energy was palpable.

Kevin Clark of Nanoprecise summed it up perfectly: “This is a step change from last year. More vendors, more practitioners, and more people looking for real solutions.”

The Rise of RCM and Technology Integration

SEO Keywords: Reliability-Centered Maintenance, RCM benefits, maintenance technology, predictive maintenance, industrial IoT
Meta Description: Explore how Reliability-Centered Maintenance (RCM) is evolving with AI and IoT, making it a powerful strategy for modern industrial operations.

Reliability-Centered Maintenance (RCM) isn’t new—it dates back to the 1960s—but it’s experiencing a revival. Why? Because modern technology makes RCM smarter, faster, and more actionable.

Industry legends like Nancy Reagan are breathing new life into RCM, proving it’s not an outdated methodology but a dynamic framework that thrives when paired with automation and data analytics.

Data – The New Industrial Gold

SEO Keywords: industrial data analytics, edge computing, CMMS integration, predictive maintenance data, AI in reliability
Meta Description: Learn why data is the new gold in industrial reliability and how edge computing and AI are transforming maintenance strategies.

Data has always been valuable, but in today’s industrial landscape, it’s platinum. Yet, there’s a catch: most legacy data was designed for humans, not machines. That creates clutter and inefficiency when feeding AI systems.

Edge computing is accelerating this shift by processing data closer to the source, reducing noise, and delivering contextual insights. The result? Less data, but better data.

AI, Trust, and Cultural Shifts

SEO Keywords: AI in maintenance, industrial AI adoption, CMMS automation, cultural shift in reliability, AI trust issues
Meta Description: Discover how AI is reshaping maintenance and reliability, and why trust and cultural change are critical for successful adoption.

Artificial Intelligence is transforming maintenance—but trust remains the biggest hurdle. False positives can flood CMMS systems with unnecessary work orders, damaging credibility overnight.

Kevin warned: “Cultural shift is sensitive. A few AI mistakes can undo years of progress.”

Looking Ahead – Quantum Computing and Cybersecurity

SEO Keywords: quantum computing cybersecurity, industrial cybersecurity, future of maintenance technology, reliability trends 2026
Meta Description: Explore the future of industrial cybersecurity in the age of quantum computing and why proactive strategies are essential.

The conversation didn’t stop at AI. Kevin and Scott explored the looming impact of quantum computing on cybersecurity. While quantum tech isn’t mainstream yet, its arrival could upend encryption and expose vulnerabilities across industrial networks.

The post The Future of Industrial Reliability: Insights from SMRP 33 with Kevin Clark appeared first on Industrial Talk.

Email marketing has been around for decades, and for many industrial businesses, it feels like a box to check rather than a strategy to embrace. You create campaigns, hit “send,” and hope for engagement—but often, the result is silence. Why? Because inboxes are flooded with generic messages that lack relevance and personality.

Yet, email marketing still matters. Unlike social media platforms, where algorithms dictate visibility, your email list is your asset. You own it. You control the message. And when social platforms go down—as they have before—your email list remains a direct line to your audience.

Takeaway: Email marketing isn’t dead. It’s just misunderstood. The challenge is making it human, helpful, and worth opening.

The Human Touch vs. AI

AI tools promise speed and efficiency, but there’s a hidden cost: authenticity. When every email sounds like it came from the same algorithm, your brand loses its voice. Subscribers notice. They crave connection, not jargon.

The same goes for visuals. AI-generated images often look too polished, too perfect—especially in industrial contexts. Real people want real stories, not stock-like perfection.

Your competitive edge? Your tone, your quirks, your perspective. Use AI as a productivity tool, not a personality replacement. Let your emails reflect the human side of your business—the challenges, the wins, and even the imperfections.

Takeaway: Authenticity beats automation. Keep your voice. Keep it real.

Practical Tips for Better Email Campaigns

If you want your emails to stand out, start with these actionable steps:

• Structure matters: Use bullet points and short sentences. Avoid long paragraphs that overwhelm readers.
• Timing counts: Test different days and times. For some audiences, weekends work; for others, midweek mornings are best.
• Learn from retail giants: Why do you open Amazon’s emails? Because they’re simple, relevant, and actionable. Apply those principles to your industrial campaigns.
• Limit outbound links: Too many links feel like a trap. Keep it focused—one clear call to action per email.
• Stay consistent: Develop a cadence your audience can anticipate. Predictability builds trust.

Takeaway: Small tweaks—structure, timing, tone—can transform your email performance.

Building Trust and Long-Term Relationships

Email marketing isn’t about quick wins; it’s about trust. Shift your mindset from “How do I get clicks?” to “How do I help?” When subscribers feel valued—not used—they engage more.

Mix your content:

• Value-driven emails: Share insights, tips, or industry news without asking for anything in return.
• Action-oriented emails: Include links and CTAs, but only after you’ve built credibility.

Think of your email list as a community, not a data set. Relationships take time, but the payoff is loyalty—and yes, revenue follows.

Takeaway: Help first. Sell second. Trust is the ultimate conversion tool.

Your Next Step (Call to Action)

Ready to rethink your email strategy? Start here:

1. Audit your inbox: Which emails do you open? Which do you delete? Why?
2. Write like you talk: Draft your next email as if you’re writing to one person you know.
3. Flex your creativity: Avoid AI-generated language and images. Your tone is your secret weapon.
4. Commit to consistency: Pick a schedule and stick to it.

👉 Join the conversation!
Subscribe to our newsletter for more insights, or sign up for our upcoming webinar:
“Industrial Marketing Reimagined: Email, Social, and Beyond.”
Click here to register and start building campaigns that connect, not just convert.

Final Thought: Email marketing isn’t about sending messages—it’s about starting conversations. Make yours worth having.

The post Email Marketing in Industrial Business: Why It Still Matters and How to Do It Right appeared first on Industrial Talk.

Why Storytelling Matters in Manufacturing

Headline: Manufacturing Has a Story—Are You Telling It?

Manufacturing isn’t just machines and processes—it’s innovation, resilience, and purpose. Yet, the industry faces a branding challenge. Too often, people think “dirty, grimy, outdated.” The truth? Manufacturing is cutting-edge, tech-driven, and vital to solving global challenges.

Danny Gonzales of Industrial Sage nailed it: “We have a marketing problem, and the answer is great storytelling.” Your work impacts lives thousands of times a day. But if you don’t share that story, who will? Storytelling isn’t fluff—it’s the bridge to talent, customers, and future leaders.

Key Takeaway: If you want to attract the next generation and inspire your workforce, you must communicate your purpose boldly and consistently.

The Human Side of Digital Transformation

Headline: Tech Alone Won’t Transform Your Business—People Will.

Automation, robotics, AI—these tools are powerful, but they don’t replace human connection. In fact, as technology accelerates, human-to-human interaction becomes even more critical. Leaders must step out of their comfort zones, communicate openly, and show up on the shop floor.

Danny shared a powerful insight: “Talk is cheap. Actions matter.” Employees need to feel heard and valued. When frontline workers are part of the process, retention improves, innovation thrives, and culture strengthens.

Pro Tip: Pair your digital strategy with a communication strategy. Inspire your team with purpose-driven storytelling and involve them in decision-making. That’s how you build resilience.

Your Call to Action

Headline: Be Bold. Tell Your Story. Transform Your Industry.

Manufacturing is cool. It’s meaningful. It changes lives. But the world won’t know unless you share it. Stop overthinking. Start communicating—with urgency, energy, and authenticity.

Here’s how you can take action today:

• Connect with Industrial Sage at https://industrialsage.com for expert video storytelling.
• Join the Industrial Talk community at https://industrialtalk.com to amplify your voice.
• Start small: Record a short video about why your work matters. Post it. Repeat.

The future of manufacturing depends on leaders who dare greatly. Be that leader. Tell your story. Inspire the next generation. The time is now—are you ready?

The post Why Storytelling is the Secret Weapon for Manufacturing Success appeared first on Industrial Talk.

In today’s rapidly evolving industrial landscape, the need for skilled labor is more urgent than ever. At the SMRP Conference in Fort Worth, Texas, Scott MacKenzie sat down with Ashley Donahue and Darin Gray of Multi-Skill Training Services to discuss how their organization is tackling this challenge head-on.

With over 30 years in the business, Multi-Skill Training Services has built a reputation for customized, plant-specific training that meets the unique needs of each client. Whether it’s electrical systems, PLC troubleshooting, or world-class maintenance foundations, their approach is hands-on, data-driven, and deeply rooted in real-world application.

“We start with a job task analysis,” Ashley explains. “We identify exactly what skills technicians need, then tailor the training to those needs.”

This isn’t one-size-fits-all. It’s precision training designed to close the skills gap and boost ROI for industrial operations across the U.S.

Training That Travels – Flexibility and Expertise in Action

Multi-Skill Training Services doesn’t just offer training—they bring it to you. Based in Kentucky, their team travels nationwide, delivering on-site instruction or shipping equipment and flying in instructors when needed.

Their instructors are seasoned professionals—retired engineers and maintenance managers with decades of experience. Each new trainer undergoes a rigorous onboarding process, including “Train the Trainer” shadowing and hands-on teaching before going solo.

“We’re constantly evolving,” says Darin. “Our curriculum, our equipment, our delivery—it all changes to meet the needs of the industry.”

They also offer online assessments and skill confirmations, empowering supervisors to validate learning outcomes on the plant floor. And yes, refresher courses are part of the package—because if you don’t use it, you lose it.

Inspiring the Next Generation – A Human-Centered Approach to Industrial Growth

As automation and technology reshape manufacturing, the human element remains critical. Multi-Skill Training Services is committed to building a roadmap for the next generation of industrial professionals.

“We give companies a way to take someone with little knowledge and build them up,” Ashley says. “From maintenance fundamentals to advanced controls and hydraulics.”

Founded by a vocational school instructor frustrated with outdated curricula, the company is a living response to the limitations of traditional education. Their model is agile, responsive, and built for the real world.

Call to Action

If you're an industrial leader facing a skills gap, don’t wait. Connect with Multi-Skill Training Services today and start building a workforce that’s ready for tomorrow.

🔗 Visit https://industrialmaintenancetraining.com
📧 Reach out to Ashley Donohoo or Darin Greifenkamp on LinkedIn
📍 Put SMRP 2026 on your calendar – and meet the team in person!

The post Bridging the Industrial Skills Gap appeared first on Industrial Talk.

Quantum Computing and Cybersecurity: Are You Ready for the Next Big Disruption?

The industrial world thrives on innovation, but with every breakthrough comes new challenges. Quantum computing is one of those breakthroughs—a technology that promises to revolutionize industries, accelerate research, and unlock unprecedented computational power. But here’s the catch: it also threatens the very foundation of cybersecurity as we know it.

Why Quantum Computing Changes Everything

Quantum computers aren’t just faster—they’re fundamentally different. Their ability to process complex calculations at unimaginable speeds means that today’s public key cryptography—the backbone of secure communication—could be rendered obsolete. Digital signatures, encrypted transactions, and trust mechanisms that underpin our digital world are all at risk.

Sandy Carielli of Forrester Research explains it best: “If a quantum computer existed that was powerful enough, it would break today’s public key cryptography.” That means emails, contracts, financial transactions, and even healthcare data could be compromised.

The Urgency: Harvest Now, Decrypt Later

Here’s the scary part: attackers don’t need a quantum computer today to start causing problems. They can intercept encrypted data now and store it, waiting for the day quantum computing makes decryption trivial. Sensitive information—like health records—will still matter 10 years from now. If you’re not planning for this, you’re already behind.

What’s Being Done?

The good news: industry leaders and government agencies saw this coming. Over a decade ago, initiatives began to develop post-quantum cryptographic algorithms. NIST (National Institute of Standards and Technology) has already approved new algorithms designed to withstand quantum attacks. Regulatory bodies worldwide are mandating migration to these algorithms by 2035—or sooner.

Financial institutions and government agencies are leading the charge, piloting quantum-safe solutions and conducting cryptographic discovery to identify vulnerabilities. But for most organizations, the clock is ticking.

What Should You Do Today?

1. Start the Conversation
   Bring together stakeholders—security, development, infrastructure, procurement, and risk teams. This isn’t just an IT problem; it’s an organizational priority.
2. Conduct Cryptographic Discovery
   Inventory your systems. Know what algorithms you’re using and where they’re deployed. You can’t protect what you don’t understand.
3. Engage Your Vendors
   Update RFPs and SLAs to ensure vendors are preparing for quantum readiness. Don’t assume—they need to prove it.
4. Prioritize High-Value Data
   Identify information that will still matter in 10 years. Healthcare records, intellectual property, and sensitive contracts should be first in line for quantum-safe protection.

The Bottom Line

Quantum computing isn’t science fiction—it’s coming faster than most expect. Experts predict less than 10 years before quantum computers can break today’s encryption. Some say even sooner. The organizations that act now will protect their data, maintain trust, and stay compliant.

Your Call to Action

Don’t wait for Q-Day. Start preparing today.

• Connect with Sandy Carielli on LinkedIn and explore her insights at https://www.forrester.com.
• Visit https://industrialtalk.com for resources, interviews, and strategies to future-proof your business.
• Lead the conversation in your organization. Quantum security isn’t optional—it’s essential.

Be bold. Be proactive. The future is quantum—make sure you’re ready.

The post Quantum Computing and Cybersecurity appeared first on Industrial Talk.

Why SMRP Is More Than a Conference—It’s a Community Driving Industry Forward

When you walk into the SMRP (Society for Maintenance & Reliability Professionals) annual event, you’re not just attending another industry conference—you’re stepping into a vibrant community of professionals who are passionate about keeping the world moving. This year’s gathering in Fort Worth, Texas, was a powerful reminder of why SMRP stands out: collaboration, education, and innovation are at its core.

The Power of Connection

Dan Anderson, newly elected Chairman of the SMRP Board, summed it up perfectly: “It’s a reconnection of family.” After last year’s cancellation due to Hurricane Milton, this year’s event felt like a homecoming. LinkedIn buzzed with excitement as professionals confirmed their attendance, and the energy on the floor was electric. SMRP isn’t just about networking—it’s about building relationships that last and sharing knowledge that elevates the entire industry.

Inspiring the Next Generation

One of the most pressing conversations at SMRP was about workforce development. How do we attract and inspire the next generation of maintenance and reliability professionals? Dan emphasized that it’s not an “old guys’ game” anymore. The industry must make learning fresh, fun, and accessible. SMRP is leading the charge with initiatives like micro-learning modules and revamping its Body of Knowledge to deliver bite-sized, actionable insights instead of overwhelming PDFs.

Technology and Fundamentals—Finding the Balance

From AI to augmented reality, technology is transforming maintenance and reliability. But Dan reminded us that fundamentals still matter: “You’ve got to be able to throw the ball, run the bases, hit the ball.” Technology is a tool, not a replacement for human judgment. AI can process massive data sets and flag anomalies, but decisions still require human expertise. As Reese Witherspoon famously said, “AI won’t take your job—the person who learns AI will.”

Breaking Down Silos

One challenge Dan highlighted is the fragmentation of industry knowledge. With so many organizations and solutions, it’s easy for professionals to feel lost. SMRP’s mission is to bring people together, foster collaboration, and create a unified vision for success. When we share knowledge and work collectively, the entire industry wins.

Your Call to Action

If you’re in maintenance, reliability, asset management, or industrial technology, SMRP is where you need to be. This isn’t just an event—it’s an opportunity to connect with passionate professionals like Dan Anderson, gain insights that will transform your career, and join a movement dedicated to inspiring the next generation.

Here’s what you need to do:

1. Mark your calendar for SMRP 2026. Budget for it now—you won’t regret it.
2. Connect with Dan Anderson on LinkedIn and follow Reliability X for cutting-edge insights.
3. Visit https://industrialtalk.com to keep the conversation going and access resources that help you stay bold, brave, and innovative.

The future of industry depends on collaboration, education, and innovation—and it starts with you. Be part of the change. Join SMRP. Inspire the next generation. Lead the way.

The post Why SMRP Is More Than a Conference appeared first on Industrial Talk.

While these consumer-facing AI applications have greatly enhanced convenience and personalization, Industrial AI, the unique application of AI in industrial domains, holds the potential to revolutionize many industries, such as manufacturing, energy, mining, and logistics, to make a more profound impact on our society and at a larger scale.

In this blog, the first in a three-part series, we will outline the challenges and best practices that we have overcome ourselves, as well as continue to witness as we guide hundreds of our customers globally conquer and successfully implement.

It’s estimated that the potential value at stake from AI in industries is about 10 to 15 trillion dollars, with more than 1/3 of that, or 3.5 trillion dollars coming from AI models and applications deployed in supply chain management and manufacturing operations. By integrating and adopting AI-based solutions (combining data science, machine learning and related technologies), industrial organizations can harness the power of data-driven informed decision-making to achieve streamlined and optimized operations, enhanced safety, increased sustainability, efficiency, productivity, profitability, and many more.  With these promises, Industrial AI is regarded as the cognitive engine and key enabler of the fourth industrial revolution.

We see the following as a few areas of impact of Industrial AI, including:

• Manufacturing organizations seek to “do more with fewer resources”, and commonly look to digital technology as a solution as part of continuous improvement programs.
• Most manufacturers have teams dedicated to Industry 4.0 (“I4.0”) or “manufacturing digitization”; many have executive leaders responsible for this and many have formalized “product owners”.
• IT organizations are frequently focused on building efficient and scalable platforms to support Industrial AI, rather than experimenting with proof of concepts.
• The enabling technology capabilities and technology eco-system is approaching ubiquitous: Many software firms provide IIoT platforms, the major cloud hyper-scalers have dedicated efforts around Industrial AI and thousands of “.ai” boutique firms offer analytical expertise.
• Manufacturing engineers are exiting academia more technology-savvy and statistics-capable than ever before, ready and able to apply digital tools such as Industrial AI.

While the potential value of Industrial AI is tremendous, value realization is still very low; about 50 to 60 percent of companies have deployed AI but have not scaled it.  According to various surveys, many industrial organizations continue to face many business and technical challenges.  We highlight the three crucial challenges here:

Challenge #1. Lack of a compelling, business-aligned transformation roadmap

Often, digital initiatives are aligned by “digital maturity”, or a linear progression such as

• from Descriptive to Predictive to Prescriptive,
• or from Connect to Visualize to Insight to Recommendation to Automated.

This maturity is often driven by technology enabled and/or technical support capability.  This IT capability model, however, is misaligned with business or operational problem-solving needs.  “We aren’t there yet” is an unfortunate reply when presenting a moderately complicated Industrial AI solution to address a critical business or operational issue.

Also, IT-Operations communication channels and tools must be improved:  Operations must recognize IT constraints and assure to build this into the feasibility side of Industrial AI project definitions.  Meanwhile, IT must appreciate and fully understand the operational value proposition of the Industrial AI solution in order to appropriately prioritize.

Challenge #2:  Requirement of multi-disciplinary technical expertise

Applying AI to solve industrial challenges and drive tangible business impact is hard!  It requires multi-disciplinary skills, working in-concert:  domain expertise/operational technology (OT), AI, and digital infrastructure.

Further, industrial AI applications often encounter a variety of technical challenges because of its intricate nature and stringent requirements for worker safety, reliability, data privacy and system robustness.

In addition, the data generated in industrial settings usually exhibit high heterogeneity and complexity, including both structured and unstructured formats, complicating data management activities.

Challenge #3. Complexity of mapping business need to technical capabilities

Industrial processes are usually complex and consists of interconnected subprocesses. Many times, different working conditions and scenarios may be involved and there are lots of inherent uncertainties in many real-world business environments. For example:

• Customer demand is highly variable.
• Equipment fails unexpectedly.
• Environmental conditions are constantly changing.

Even well-defined business needs and objectives have nuances that need to be well understood and factored into solution development.

Meanwhile, the portfolio of technologies and solutions available to the Industrial AI practitioner is vast, often novel or unproven, and rarely well-catalogued.

Aligning complex requirements to complex solutions, often under the watchful eye of a return-on-investment expectation, requires considerable leadership and proficiency.

What Can We Do?

We believe that the onus on business architects to connect dots between what’s been done before and problems the manufacturer faces is the Industrial AI adoption bottleneck.

We call on industry groups and industrial digital transformation leaders to think broader and deeper about industry-specific Industry AI taxonomies.  A structured taxonomy for Industrial AI will accelerate solution realization and increase value delivered.  It provides:

• A clearly articulated business value statement supports tying Industrial AI initiatives to outcomes.
• A common definition of use-cases and solutions supports collaboration across factories or industries.
• A structured categorization scheme that helps ease matching AI solutions with the operational needs.
• A common language allows for operations and AI experts to better work together.

In the past decade, Hitachi have leveraged our deep expertise in both OT and IT and accumulated extensive experience helping our industrial customers overcome the challenges on their digital transformation journeys.  In particular, to help our customers identify the pain points and lay out the AI transformation roadmap, we have developed a systematic industrial AI taxonomy that covers an essential set of business problems faced by customers from various industries where AI can drive better business outcomes.

The Hitachi Industrial AI taxonomy (described in the Figure 1) proposes a structured and linear method of identifying, describing and defining Industrial AI problems:  business outcome to operational problem to analytical approach.  The framework enforces classification of problems and solutions to encourage reuse and reapplication.  The framework is also a tool to help communication between business, operations, and technologists.  The general use of the framework is described below.

Figure 1:  Hitachi Industrial AI Taxonomy Framework

 1. Organize by Operational Domain: The broadest categorization of problem-sets, intentionally aligned to typical operational organizations

2.  Define Operational Problem: A clear and concise problem statement is critical to align all parties. Identification of desired operational outcome (KPI) and articulation of what is going to change for this outcome to be achieved is critical and often omitted.  This includes:

• • KPI sought to improve
  • Decision we are looking to make
  • What lever can be pulled based on the result
  • Timeliness of the decision-making: seconds, hours, days, months

3. Define Analytical Problem: A definition of how the problem should be solved and key mathematical principles.

• • Analytical Problem Type:
  • Analytical (mathematical) Approach

4. Select from a bank of Implementation Solutions: Products, Accelerators and Examples available to address the Industrial AI solution.

Beyond our Industrial AI cataloguing work, our extensive experiences have proven that our diverse and deep AI expertise can be leveraged to develop advanced solutions to cope with some of the technical challenges.  Solving real-world complex industrial problems often requires innovations created by drawing advancements from multiple AI sub-fields such as traditional machine learning, deep learning, reinforcement learning, statistics, operations research, and optimization. We will showcase our AI technology innovations in following posts.

In the second part of this blog, we will get into some specific areas of Industrial AI: Dynamic Scheduling and Asset Management. Stay tuned!

Authors:

David McKnight, Director of Digital Manufacturing Solutions, Hitachi Digital Services

The post Triumphing with Industrial AI appeared first on Industrial Talk.

By: Keith Walsh, OT Security and Operations Director at Armis

Leaders of Industry: 5 essential steps to secure and sustain digital cities, campuses, and buildings

Leaders of Industry is a series of conversations between operational technology, critical infrastructure (CI), and security experts from Armis and other leading companies and institutions. The series explores critical considerations for protecting the OT and CI assets that keep our manufacturing operations, public and private institutions, and cities humming.

This conversation on securing digital cities, campuses, and buildings features the following experts:

• Thomas A. Rodgers, Director of Operational Technology, Penn State University 
• Mirel Sehic, General Manager, Cybersecurity, Honeywell Building Technologies (HBT)
• Keith Walsh, Director, OT Strategy and Operations, Armis

In section 1, Keith Walsh and Thomas Rodgers discuss how Penn State has addressed security challenges related to connected assets across its facilities. In section 2, Keith chats with Mirel Sehic From HBT about managing the expanding attack surface in buildings, campuses, and municipalities and how to address them. And in section 3, we outline 5 essential steps for securing digital buildings, campuses, and cities.

Welcome to the conversation.

Section 1: What does ‘good’ look like in CI security and how do we get there?

Our buildings, campuses, and cities have been growing up fast for the better part of two decades. Today, cities and towns are blanketed with radio frequencies (RF)  to enable our utilities to remotely read gas, water, and electric meters; our highways and bi-ways are covered with smart lighting, cameras, traffic sensors, and speed monitors; and the buildings we work in are networked with devices to ensure safety and comfort to all those who enter.

Just last month, in my not-so-sleepy-anymore-beach-town, I witnessed the construction of 5G poles every 200 meters. With 10x the speed of LTE and significantly lower latencies, we now have a technology that will further accelerate the deployment of industrial IoT devices.

When it comes to finding a dynamic environment illustrating a diverse mix of OT and IoT devices, sensors, and controllers communicating across an ecosystem, one would be hard pressed to find a better example than Penn State University.  With  nearly 2000  buildings hosting 90,000+ in-person and online students Penn State arguably looks more like a smart city than a college campus.

That’s why I was excited to have the opportunity to sit down with Thomas Rodgers, Director of Operational Technology at Penn State to learn more about how he approaches his task of ensuring campuses and buildings maintain their resiliency, safety, and uptime.

Keith: Good morning, Thomas. Can you share with the readers the breadth of the Penn State campus and the challenges you face in the BMS/BAS/smart campus space?

Thomas: Sure. Our BAS systems can be found in many buildings across the Commonwealth of Pennsylvania. Those campuses make up the Facility Automation Systems (FAS). Included in the FAS network are the utility plants for steam/electric generation, wastewater treatment and water treatment facilities, as well as academic buildings, research facilities, museums, dining spaces, and much more. Basically, we are a smart city where most of the building automation systems (BAS) are controlled by the FAS/BAS teams. A big security challenge in the BAS space is visibility into the network and devices. We have many devices on our networks that do not run a traditional operating system where software agents could be installed for endpoint device security posture assessment. In addition, the traditional network scanning vulnerability assessment tools can have a negative effect on OT devices with fragile network stacks.

Another challenge is the scalability and the varying needs of a large and diverse customer base. We are tasked with supporting everything from multimillion dollar research efforts to the simple comfort of heating and cooling. And supporting hundreds of buildings across multiple geographic locations that can be hundreds of miles away provides a unique challenge.  Keeping offsite networks secure and operational at various locations can be difficult. Helping them understand security and the fact that outdated systems need to be updated and replaced at regular intervals is not an easy task and requires us to be constant champions for the cause.

Keith: With such a diverse device ecosystem, how do you wrap your arms around the product life cycle, including patching and updating your various campus support systems?

Thomas: While there are many challenges, applying traditional IT practices to an OT environment isn’t always feasible. The Confidentiality, Integrity, and Availability (CIA) triad in IT gets flipped in OT which presents new priorities in the security space. Performing operating system updates on a server may “break” the building automation software, directly affecting availability. Rigorous testing is required before rolling patches out to your production systems. Also, replacing unsupported operating systems can be challenging because there are multiple parties involved, such as the mechanical systems they are controlling. The building automation software may only be certified to work with a specific operating system and patch level. The endpoint devices may also need to be upgraded or replaced to support the new version of building automation software, which can cost millions of dollars and is not always from the OT budget. Many of these challenges are due to the longevity of our buildings and the extended lifecycle planning of building systems.

Keith: When or how did you realize improvements needed to be made? Or, put another way, what led you to go to market to solve what problems?

Thomas: The most important thing is to understand where you are and create a baseline. In completing our security assessment, in an environment this complex we needed to have a better inventory of authorized/unauthorized devices on the network. The most room for improvement was the visibility of all the software, or devices running on our network. We also lacked a good vulnerability assessment and tracking program, which is key to understanding where you have risk. All of those are key to having a good foundation of cybersecurity in an OT environment. We have a saying on our team, “You don’t know what you don’t know,” and that’s why visibility is key to securing an OT network.

Keith: We couldn’t agree more about needing to know what you don’t know. What might the ideal end state at PSU look like in a perfect world?

Thomas: In the end, an ideal FAS network would have visibility into all aspects of the network and devices. When a new device is attached, a report or alert would go out to the security and network teams letting us know something was connected and needs to be assessed. Routine vulnerability assessments need to be performed by a tool passively scanning the network.

Segmenting the network to separate things like utilities, metering and automation systems is important. Having everything on the same network permits adversaries the ability to pivot from vulnerable systems to other devices.

We all know there is no “perfect world” and there will never be systems without issues or problems, but having a system that is built, secured, and equipped to deal quickly and effectively with the inevitable problems that arise is key to success! We’re well on our way to making that goal a reality.

Keith: That baseline of device discovery you speak of is truly the holy grail because it allows for the successful pursuit of all other use cases, and passive real-time monitoring is certainly the way to go in such a dynamic environment.

Thanks Thomas, we are certainly looking forward to what your journey holds as you progress towards gaining complete visibility of your devices, and your quest to ‘know what you don’t know’.

Thomas: Thanks.

Section 2: Insights on managing the expanding attack surface

Today, virtually every building, campus, and municipality is bursting with newer and older connected devices. And based on Penn State University, we know the reach can encompass hundreds or potentially thousands of buildings across significant distances. Given how smart devices include communications modules that allow them to connect to any network, including the Internet, we now have an entirely new attack surface to manage.

In fact, it’s arguable that the front line of this new attack surface resides within the assets that we place on our networks. Since these devices often allow ingress into our networks, device manufacturers certainly bear some responsibility for device security.. But even with effective built-in security, staying ahead of our adversaries is not an easy task. We must be right 100% of the time, whereas our adversaries only need to be right once.

To discuss managing this cyber-attack surface and ensuring the lifecycle of these devices is properly managed, I spoke with  Mirel Sehic, General Manager, Cybersecurity for Honeywell Building Technologies (HBT). Honeywell is a Fortune 100 company that delivers industry specific solutions that include aerospace products and services, control technologies for buildings and industry, and performance materials globally.

Keith: Welcome Mirel.

Mirel: Hello Keith, great to speak again.

Keith: Mirel, when we think about the transformation of our buildings, campuses, cities and grids over just the last ten years or so, what stands out the most in your eyes? What’s been the driver for the reinventing of our ‘spaces’? Is it industry standards? Has there been an inflection point?

Mirel: Great question Keith. I think the biggest standout is the way we are utilizing our buildings, campuses, and cities—as individuals we are expecting more from these facilities and want increased visibility to know that the buildings we use are safe and rely on technology that keeps our well-being in mind. With these new expectations, buildings need to make changes from a standard operating model to a ‘smart’ and ‘connected’ model, meaning a greater emphasis on technology that intersects both laterally (devices in-building expanding to other devices in-building and ultimately to the edge) as well as interconnectivity with the cloud. As you would expect, taking these historically low cyber-hygiene environments and stacking this new technology can lead to a potentially larger cyber threat footprint.

Keith: Let’s talk about this new attack surface management and this new ‘cyber threat footprint’. Gartner has in fact coined a name for it, CAASM, or Cyber Asset Attack Surface Management. We are now having to manage this new digital footprint found within our enterprises, including BMS/BAS, IoT, and OT devices, alongside the more traditional IT, virtual, and cloud-based assets. How can we get our arms around a cyber footprint that now seems 10x what it was 5 years ago, and will likely be 10x in 5 years, if not sooner?

Mirel: It’s always a good idea to start with the basics. Build a program from the ground up. Prior to any new or substantial change to a building’s operating environment, we must ensure that a cyber assessment has been conducted; this is our starting point. Once we have assessed our environment, we can come to an understanding of what remediation actions need to be taken, be they hardening, network architecture review; endpoint protection, OT monitoring and assessment management, or incident response. Although it may seem simple, this assessment is what provides the blueprint for comfortably expanding the environment’s footprint and doing so securely.

Keith: Mirel, when you talk about the ‘basics’ of getting started, it sounds like you’re speaking about the fundamental understanding of communicating assets in the environment, their software and their interdependencies to determine the risks they pose. And with the explosion of devices, which brings a much larger software footprint, it’s not surprising 2021 was the year of the vulnerability. As we continually add new devices, we introduce even more software, which brings even more vulnerabilities, risks, and threats to our environments. Is vulnerability management a zero-sum game? Are we chasing the dragon? Is there a better way to protect our assets?

Mirel: Good cyber-hygiene is something that must be practiced. We strongly believe in the prevention-first approach to OT cybersecurity—meaning understanding a client’s risk appetite, and then through this understanding of the risk appetite, plan for an effective, in-depth defense strategy. The simple truth is that you plan for what you can afford to lose, and, if you are in a critical infrastructure industry, you need to plan effectively to reduce risk as far as reasonably practicable. Establishing a more robust OT cybersecurity posture often means, as you mentioned, correcting common vulnerabilities, like operating on outdated or unpatched software, or addressing a lack of stringent security measures around communication protocols.

Keith: It sounds like when we talk about good cyber-hygiene, our starting place is identifying and prioritizing the assets in our ‘protect-surface’, as not all devices and processes are created equal, which is understandable. On a campus or in a building, we may for example, deem fire suppression as our number one protect-surface. Flushing out the genetics of these interconnected devices, including the associated vulnerabilities and communication dependencies is a great place to start. It is certainly more manageable to address vulnerabilities in a subset of devices that affect the most critical processes than to become overwhelmed by the endless supply of vulnerabilities.

Lastly, does Thomas share some of the same challenges at Penn State University as you see across varying municipalities, buildings, and campuses?

Mirel: The challenges Thomas sees are very real and consistent across the OT domain. Today, conversations about cybersecurity still primarily focus on information technology (IT) systems and safeguarding data and assets. OT systems in facilities are often overlooked, but they are just as critical to a company’s security, processes, data, reputation and even employee safety.

Keith: Thanks, Mirel. When we talk about OT systems at times being overlooked, we can probably agree that with the interconnected nature of BMS/BAS, OT, IT, and the internet, “securing by obscuring” devices is no longer a fail-safe solution, especially when safety is on the line.

Mirel: Agreed. Thanks, Keith.

Section 3: 5 essential steps to secure and sustain digital cities, campuses, and buildings

There are a lot of steps that should be taken to improve the risk posture of our OT and CI environments. In an ideal world, OEM vendors would dedicate more energy and resources to hardening devices throughout their life cycles. And as always, our network teams need to build proper borders and boundaries, our IT staff to ensure device compliance, and our security operations teams to monitor for intrusion. But, as evidenced by the conversations above, there are plenty of other steps that can be taken to improve the overall risk posture of our OT environments, including the following:

1. Identify your ‘protect-surface’. A real-time, full device inventory, inclusive of hardware, software, and associated vulnerabilities that enables you to know what you don’t know is the foundation for a strong security posture.
2. Segment properly. Typically, you should group devices in subsystems according to their functions. Connections across subsystems should be monitored closely, including connections to the Internet. Anything less allows for pivots to higher profile targets.
3. Never rely on default device and system credentials as publicly available user guides oftentimes include this information.
4. Be a constant champion. Train your staff on what is an acceptable security posture of connected assets and continually reinforce it.
5. Patch. Work closely with your vendors to ensure assets are up to date in a timely manner.

In addition to taking the 5 proactive steps above to improve your security posture, I would suggest one final step—working together. Tear down the walls that exist between IT and OT; plan, execute, and plan again together; invest in platforms that share information because it takes a village to be right 100% of the time.

Download Solution Brief

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Abstract

Guided by factory needs, the LDF network provides direction & solutions for the digitalization journey of DI plants since 2016. By using own HW/SW products & solutions LDF has so far increased their productivity by low three digit MEUR and as recently shown even their resilience in times of a pandemic. While plants from different industries had to close, the output of DI plants was affected by only ~10% and back to normal quickly.

Supported by jointly created road maps, an alliance of >200 experts are working together to leverage new technologies. To guide employees in the digital transformation, even a dedicated learning channel was set up.

Winning several industrial awards, LDF supported to position Siemens as digital thought leader in the market and provided the blueprint for the Siemens-wide Factory Digitalization program with the mission to generate additional business with external customers.

Lean Digital Factory – A core program for the factories of Siemens Digital Industries

As complexity increases and business models change, traditional improvement methods must be augmented with digitalization, which is key for efficiency, flexibility, and speed. Successfully mastering digitalization is complex and requires high efforts. Sharing the burden by bundling expertise of the world-wide DI manufacturing network and our own solution providers while using our own solutions & products, LDF took thought leadership in 4th Industrial Revolution (4IR) technologies.

Our core program Lean Digital Factory is embedded in our framework of core programs „production and logistics excellence, in which we address all aspects of a role model factory from lean philosophy, employee engagement, plant network design, supply chain design and supplier collaboration.

The major benefits we have already achieved beside significant productivity increases are synergies, balanced workforce and capacity, speed learning and a reliable supplier base even before covid19 shocked the world.

This was possible because all plants are sharing one mission, to be the role model for excellence in production and logistics to provide proven value add for our customers, based on the methods of a digital enterprise and lean industrial engineering to master the challenges we face in manufacturing: to shorten our time to market, to increase our flexibility, to continuously improve our quality and to boost efficiency by increased security and sustainable operations.

We started this journey 2016 and since then, our factories are known internationally as digital lighthouse and received several recognitions. The factory in Chengdu, China and our factory in Amberg, Germany are rewarded as WEF Lighthouse factories and both facing challenges like serving 60.000 customers, producing 1 product per second with almost 6 sigma quality by having already reached full vertical and horizontal data integration.

In the year before the pandemic breakout, some DI factories pulled almost 10000 visitors per year, and therefore we were building a state-of-the-art digitalization center in Amberg which opened their doors for our customers in May 2021.

Figure 1: Motivation of Lean Digital Factory

Our core program “Lean Digital Factory” (LDF) was initiated to strengthen the focus further on automation and digitalization and shop floor productivity from data and analytics based on lean production philosophy.

The journey to become a lean digital factory always begins with becoming a lean factory first and can be characterized by several lean rules stated 1999 by Spear and Bowen.

One rule is known as that all work and process steps, shall be highly specified as to content, sequence, timing, and outcome. With other words, processes must be described without any waste, but in difference to the past, artificial intelligence and machine learning can be used to make them even more efficient.

Another lean rule states, that every customer-supplier connection must be direct, and there must be an unambiguous yes or no to send requests and receive responses. This can be realized very efficiently with defined digital supplier interfaces with standard communication protocols for tracking and tracing.

From the plant development point of view, the third and most important rule states, that any improvement must be made in accordance with the scientific method and at the lowest possible level in the organization.

From the very beginning, the empowerment of our people to drive and own data driven projects was key. So, our people started by using data to measure, track and optimize our quality for example down to a 5sigma level already with 9-11 dpm. This means, in our DI factories we are working with data to continuously optimize our processes. But one should be aware that one cannot introduce technologies on higher frequency than up- and re-skilling of the people who are going to use this technology.

Due to the reason that we are doing continuous improvement projects since a long time, the amount of shop floor productivity projects increased dramatically over the years to maintain the level of productivity we needed to stay competitive. To focus further on flexible automation with light weight robots and to address automation tasks was one focus. The next level of productivity, which we are reaching right now, is with further digitalization, which automates also administrative and engineering topics and due to shop floor IoT like augmented and connected workers and artificial intelligence (see also figure 1).

Our digitalization approach, which addresses more than 30 factories worldwide was started with an ideation phase, of course we had to define a certain program organization to assure best-practice and solution transfers as well as scalability. The main topic was to define which technologies we want to focus on and which not and how to prioritize. Therefor several technological workshops, expert interviews, visits and so on as well internally as externally have been conducted.

With so called technology radars, technologies have been evaluated economically. In parallel, we defined reference processes, as north star processes which have been released for orientation. Interesting could be, that we never expected that all plants will reach the reference processes at the same time. The focus was that all plants have an orientation for technology, software, and IT investments.

The overall elaborated “Digitalization Roadmap” finally consists out of five work streams flanked by an IT roadmap, solution link analysis and technology stack architecture for state-of-the-art connectivity and data mining.

The realization phase, in which we are now for almost three years can be described as an agile working mode with sprints and backlists. The implementation of solutions by itself are done via three major milestones “Proof of Concepts”, “Pilots” and “Scale Up Phases”. Nowadays, ~25% of our productivity measures are coming from LDF and the tendency is increasing, pushing our LDF plants to a level of up to 7% shop floor productivity per year and the recipe for our success can be seen in the generation of ready to scale up solutions by bundling the power of our manufacturing network to jointly develop and share solutions and to learn from each other by copying with pride.

The five workstreams, who are forming the overall roadmap also serve our digital factory vision, which contains out of the digital twin, which by itself can be divided in a digital twin of product, of production and performance.

What are now the five workstreams. The three workstreams “new ways of working”, “robotics” and “big data & analytics” can be seen as enablers while the workstream “digital twin” and “processes” serve the vertical and horizontal data integration with its respective reference processes.

Figure 2 shortly explains, what a roadmap on the highest level contain.

Figure 2: Generic digital roadmap

In figure above you see a roadmap on high level for a generic workstream with a timeline. Each workstream line addresses a defined target state and a trend, which is helpful for communication reasons. The boxes describing an evaluation state, which should be reached, the numbers are pointing to projects, with a defined timeline and project lead and group as well as a budget. Sometimes the project is a cluster of several single projects, who belong together.

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I was struck by the thought of how different this kid’s childhood is compared to mine. What should have been a joyful, carefree break for this little boy came with the responsibility to consider the carbon budget still left to us, trying to make his contribution to a livable planet.

While this child’s mindset is admirable, he is basically powerless. In the larger scale of things, his actions only have a narrow impact. But the thing is, mine don’t.

As someone who is in charge of a large international organization, backed by a powerful brand, I have far more opportunity and resources to make a much larger and more meaningful contribution to the effort to mitigate climate change. At Siemens, we have the privilege of working with thousands of utilities worldwide, indeed with many of the largest energy companies in the world. And not only that, we work with equally strong partners across the industry, building a true ecosystem. Such an ecosystem has the potential to truly change the dynamics of an entire industry.

My takeaway from this small encounter was the reinforcement of my belief that power comes with an obligation to do everything within one’s power. This is especially true when we look at the magnitude of the threat we are facing today from the climate crisis – and, more recently, from geostrategic upheavals and their incalculable knock-on effects, including in the energy sphere.

Putting power and resources to good use

How can our ecosystem of customers and partners in the energy sector make a difference with the power and resources that we have?

–       We can make sure that grids do not become a bottleneck for the ongoing exponential growth of renewables.

–       We can build and manage grids that can cope with a doubling or even tripling of demand due to the electrification of almost everything, from mobility to heat.

–       We can ensure that grids remain stable in the net-zero world.

–       We can manage the energy transition in an economically viable way.

Our goal – and also our obligation – is to drive a new dynamic and create momentum across the industry. We do that by radically opening up and joining forces with technology partners in order to generate even more speed and a shared momentum.

Yes, we will have to cope with a huge influx of new renewables and a swiftly growing number of distributed energy resources (DER). A large share of these DERs is installed in the medium- and low-voltage grids, which means the distribution grid will be decisive for the success of the energy transition. With the loss of inertia due to the large amount of inverter-based infeed, solutions for active monitoring and control combined with new forms of prosumer relationship management are crucial to ensuring grid stability.

Rethinking grid management (and grid software)

For groundbreaking transformations and disruptions to become reality, grid operators and solutions providers cannot rely only on traditional tools, existing hardware, or proven processes. Change must happen as fast as possible. We’re not talking about decades, but about the next eight years.

Of course, we need to improve and expand the existing grid infrastructure with more copper and grid automation. But this won’t be enough. It’s too slow and too expensive. Familiar tools and methods used in the high-voltage grid won’t be enough, either. They are limited by the available resources and space and are insufficient for managing millions of DERs in low voltage.

This is why I’m convinced that the decisive success factor will be game-changing and interoperable software that is modular, open, and flexible, mirroring the collaborative and transparent approach we all must take in advancing toward the net-zero goal. Based on these design principles, a secure and resilient suite of software solutions can empower us to interact seamlessly, make infrastructures more flexible in dealing with the exponential growth in complexity, and enable us to manage grids closer to their full capacity.

Only software can help us to reach the agility and speed needed during such a transformation. This includes vastly accelerating grid simulations and nearly doubling the efficiency of grid management tasks by changing the user experience, to name just two. All these improvements will lead the way in creating an holistic digital twin in the planning, simulation, and real-time operations and maintenance of power grids. Appropriately enough, most of these solutions were and will be co-innovated and developed in collaboration with our customers.

We at Siemens Grid Software are putting all our determination to work in the service of providing a software suite that enables grid operators and utilities to succeed. We want to work with these companies to take grid planning, operation, and optimization to the next level.

The best time for change is always now.

We tend to repeat the fact that we have to build a sustainable and secure energy future because the challenge is now even more pressing than ever before. Worryingly, this is true again today as I write about grid software as an enabler of decarbonization.

The latest assessment of the IPCC concludes that nothing less than a revolution is required to avert the climate catastrophe. The outbreak of war in Eastern Europe has brought energy supply back to the geopolitical agenda. And in face of extreme weather events, the societal pressures are rising.

Unlike the seven-year-old boy fretting about his chocolate bar’s carbon footprint, we are in a position to bring about large-scale change. We must do everything in our power to save the climate, transform the energy system, and make the world a better place for our children and generations to come. As long as we’re not fulfilling our obligation, the pressure will only continue to mount. With the power of the ecosystem and of modern software, however, we have everything it takes at our disposal.

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Much of the urgency to create a high-resolution map of the world’s ocean floor is based on the potential benefits: helping to manage fishing resources, improving marine navigation and guiding infrastructure construction, as well as better defining the impacts of the impending seabed mining boom.

This pressing need to map the seafloor led to the creation of the Nippon Foundation-GEBCO Seabed 2030 Project, an unprecedented international project to facilitate the complete mapping of the seafloor by 2030. Seabed 2030 is a major contribution to the UN Decade of Ocean Science for Sustainable Development (2021-2030).

But what stands between success and failure in the next 10 years is energy to operate more diverse and robust sensors without the expense and limitations of support from ships as well as energy to sustainably and economically scale to many thousands of sensors needed to cover the vastness of the ocean, and enable persistent ocean data collection.

The large-scale efforts currently underway are aspirational, but the ocean is big, and so far, we’ve mapped only 20% – which leaves an area twice the size of Mars yet unmapped. The simple truth is that seafloor mapping needs more sensors, along with innovative and cost-effective ways to deploy and power them if interested parties hope to win the race to understand and protect the ocean.

While ships are required for seafloor mapping in certain regions of the ocean, ships alone are not practical to map the vastness of the seafloor in a reasonable time frame – especially given the relatively small number available and the cost of operating them. Autonomous underwater vehicles (AUVs) have been increasingly used to extend the footprint covered by ships. However, AUVs have a relatively short life, mostly due to the finite battery capacity to power propulsion; the faster an AUV travels, the shorter the AUV mission life. Furthermore, AUVs need to be recovered periodically by ships for battery replacement or recharging.

Future ocean datasets will be gathered by comprehensive networks of low-cost ocean robots. There has been a rapid growth of autonomous surface vehicles powered by renewable energy from solar, wind and wave. There is an opportunity to add underwater vehicles such as profiling floats to further reduce dependence on ships and enable large numbers to cover the entire ocean. One successful example is the international Argo network with a global array of 4,000 profiling floats to measure environmental conditions like temperature and salinity down to 2,000 meters.

A recently announced $53 million expansion of funding from the National Science Foundation (NSF) will pay for an additional 500 biogeochemical (BGC) floats to expand data collection, including oxygen, nitrates, pH, and chlorophyll, in order to estimate the carbon in the ocean.

Such data are critical to understanding how human activity contributes to trends like sea-level rise, ocean warming, carbon dioxide increase, oxygen loss, ocean acidification, and algae blooms. However, more and more powerful sensors (e.g., echo sounders for seafloor mapping) require more energy from batteries, therefore increasing cost and reducing the float’s mission life. With today’s battery technology, 20% (or 800) of the Argo floats must be replaced each year. In addition to the environmental impact of these dead floats – though small compared to many larger pollution sources – it’s costly to deploy so many floats annually. It will also become increasingly expensive as more sophisticated sensors are added to these platforms.

It’s a reality that weighs on those working to understand the ocean, as shown by a survey at the OceanObs’19 conference that named energy as the single biggest challenge for sustained ocean observing systems.

How To Accelerate Efforts

The U.S. Department of Energy’s Powering the Blue Economy is a government initiative designed to accelerate new technologies that power coastal and maritime industries. Some technologies are showing promise, but governments aren’t the only ones working on solutions.

A privately-owned company called Saildrone recently launched Surveyor, a 72-foot autonomous drone powered by a combination of solar and wind power that’s designed for mapping the seafloor.

My company Seatrec is powering profiling floats using the ocean’s natural temperature difference. We are forging a public-private partnership to complement existing profiling float efforts by increasing their life span and the amount of data that can be collected. A global fleet of profiling floats powered by the ocean’s thermal energy has the potential to carry echo sounders to map the gaps of the global seafloor.

The simple truth is that multiple approaches are needed to accelerate seafloor mapping and build a network of complementary sensors to continually monitor the ocean’s water column in a cost-effective way.

A Win For The Ocean And Commerce

Winning the race to map the seafloor and better understand the ocean in time to regenerate the marine environment and derive socioeconomic benefit from it requires unique partnerships between governments, academic institutions and private companies. But the effort will also open the door to a robust “blue economy” with the potential to provide for environmentally sustainable, equitable and profitable use of the ocean.

Google Earth, for example, was originally envisioned as a way to serve noble causes such as rainforest preservation and international diplomacy but it also unlocked massive commercial applications that helped make Google one of the largest companies in the world. Real-time data from the ocean covering 71% of the planet holds even greater potential.

The Argo network shows how a large number of floats – once equipped with more powerful sensors and a renewable energy source – can provide a cost-effective, efficiency multiplier for quickly mapping the seafloor and providing long-term, continuous, real-time ocean data.

To me, it’s an investment that’s well worth it. Not only to keep the ocean healthy, but the technologies developed in the effort will form the backbone of a robust blue economy potentially worth trillions of dollars per year. Leveraging new energy technologies to power floats that are more durable, sustainable and scalable is key.

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Gen Zers were brought up alongside our phones, growing, and adapting with every new advancement in technology. Phones are our lifeline; it is how we communicate, learn, and understand almost everything.

Zers perform best by having an interaction with technology that engage and motivate us to keep working. Taking something we see as our core competency…working with automation, builds our self-esteem through validation, inspiring us to work harder and find enjoyment.

Automation In Academia Transfers To The Gen Zers' Workplace

Integrating technology and learning is not something new, especially since the COVID-19 pandemic. As Boomers and Millennials had to make the difficult adjustment of putting their entire lives online, this adjustment however was quite easy Gen Zers.

Pine Crest School in Ft. Lauderdale, Florida, which I attended for 14 years prior to starting my higher education at Boston University last year, started integrating technology and automating their learning program since Lower School. Whether it was utilizing the iLab to make our science projects, learning how to use the 3D printer for art class, or even taking out our phones during class to play interactive games to help us understand the course material, we were always using technology to further our education. Teachers were beginning to understand that students show quantifiable success when utilizing technology in the learning process, particularly given our comfort with learning programs to further our studies. At Boston University the integration of learning and technology was included in the automated orientation.

Students are required to take a drug and alcohol seminar as well as a sexual assault seminar. The program was fully online with interactive videos and quizzes to keep the students focused on the material. Since many Zers are used to using electronics throughout their educational careers, the transition to a working environment makes automation an extremely critical process for young workers.

Gen Zers Want New and Innovative Automation Technology

As shown above, our role in the workforce is growing significantly and we will be the majority by 2040 according to the U.S. Census Bureau. Outdated business practices hackneyed, and dull training will be reasons for my generation to quit a job. According to Dell Technologies, 80% of Generation Z hopes to work with cutting-edge technologies and around 91% cite technology as the most important factor when choosing a job.

For Gen Zers: Automation = Technology

Gen Zers are excited about technology and use the language of automation synonymously. Since issues like quality assurance, quality control regulatory compliance, occupational health and safety, ISO certification are constantly changing, Zers will simply access these data on their phones and proceed as
immediately debriefed workers.

Deploying Automation For Zers

Zers want to hear about fun and sexy automation tools, processes, and techniques. From Lean Six Sigma to Automated Guided Vehicles, this can all be presented to Zers as dynamic and intriguing (all via phone).

No longer are the outdated methodologies such as in-person seminars and training instruction acceptable. When manufacturers, now looking to hire millions of new workers, package and communicate in a manner appealing to Gen Zers, success is inevitable. To the C-Suite…check out TikTok; it can be your automation friend. Your children, nieces, and nephews will appreciate that you are savvy and aware of the trends that guide their lives.

Start Small In The Gen Z Realm

As manufacturers start implementing new technologies that engage Gen Z employees, simple advancements such as having employees clock-in via scanning a QR code or allowing them to take training through an interactive video presentation are simple ways to make a big impact.

Rachel Snyder as a Generation Z individual herself, Snyder has a unique understanding of the role of social media among her peers; her analysis examines how it impacts the lives, decisions, and actions of fellow Gen Z thinkers. Instagram, Snapchat, and TikTok are more than resources but rather the answer to reaching her generation. These insights are vital for businesses to inspire, motivate, and engage Gen Z job applicants and employees. Traditional PR, messaging, tradeshows, job boards will simply be ignored by Gen Z thinkers according to Snyder.

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At Industrial Talk, we view these individuals and companies as elite industrial athletes who possess laser-like focus on positively changing the world…exactly what industry is meant to do!

Our purpose is to be THE platform to educate, collaborate and innovate, the ESPN of Industry delivering entertaining, engaging & inspiring content. It’s what humans want!

Industrial Talk will never stop growing or evolving because industry is constantly changing and innovating. The doors of Industrial Talk are always open for companies and individuals who long to collaborate because their passion is changing the world by solving challenging problems the industrial world faces today. We must have a spirit of collaboration and an unquenchable desire to move industry forward.

What is the ultimate goal of Industrial Talk?  Through this website and the Industrial Academy we desire to plant dreams, instill hope and create miracles for a future that is being positively transformed through industrial innovation.  Industrial education delivered by industrial leaders committed to changing the world must be the priority, and it absolutely is at Industrial Talk. We are committed!

Please ask us how you can participate in changing the world through industry and this one-of-a-kind platform.

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SACRIFICE: The surrender or destruction of something prized or desirable for the sake of something considered as having a higher or more pressing claim.

PERSEVERANCE: Steady persistence in a course of action, a purpose or state, especially in spite of difficulties, obstacles or discouragement.

SUCCESSFUL ARE THE SACRIFICIAL. THEY DEVELOP PERSEVERANCE. Really…Sacrifice and Perseverance? They don’t even coexist in the same universe. Sacrifice is a bummer, a major burnout factor because it’s painful, while perseverance invites images of grit and determination, toughness. Sacrifice presents as a necessary evil to be grudgingly endured while perseverance looks like the trophy at the end: “YES, I PERSEVERED! LOVE ME!” It’s like this: We know that giving up something desirable is necessary to achieve a certain end. EXAMPLE: Studying for a test instead of watching Netflix is seen as a sacrifice at the time. We take the test and the sacrifice either pays off with the desired result, an A, or a C, based on perspective. For a short moment sacrifice and perseverance can peacefully coexist, with sacrifice as the means to an immediate end.

THEN we move on to whatever comes next.  BUT (yes, I know, starting a sentence with ‘but’ isn’t really grammatically correct. Deal with it.) what about sacrifice as the MEANS to another valuable virtue, one that is totally NECESSARY in business? Sacrifice then transforms into that first required rung on the ladder of success. You can’t get to the second one without being ELEVATED by sacrifice. It may still look like a temporary requirement, BUT (notice grammatical correctness.) it is actually the ESSENTIAL/NECESSARY state-of-mind and ATTITUDE that one must develop to continue moving upward.

The cool thing about sacrifice is that it is AUTOMATICALLY BUILT-IN to the business leadership program. No need to buy those “Sacrifice and Love It!” or “Hey, Let’s Suffer Together!” self-help tomes. (Yes, I used the word ‘tome’ instead of ‘book’. Impressed?) From the moment the synapses in the brain are jumped and the decision is made to grow through the business leadership-building process that built-in virtue factory starts grinding out pink unicorns and rainbows…HA! You thought I was going to say “SACRIFICE”! Well, I really was, just thought pink unicorns and rainbows would get your attention. Seriously though, as in the definition, the surrender of something else that is prized or desirable MUST BE forfeited in order to move through this process. Your body, mind and soul just can’t be in two places at once.

Remember, sacrifice is closely linked to discipline. They need each other, a perpetual motion machine of sorts that increases its own production through the give and take reality of practicing discipline. That might mean getting up early or setting a non-negotiable daily schedule; while sacrifice is, “No, I won’t buy the new car now. I’ll wait.” Delayed gratification never hurt anyone. Quite the contrary, it helps. Over time the Sacrifice muscle strengthens to support your newly-incorporated disciplines and even though the  dangling carrot/goal may sometimes move farther away, the discipline to continue reaching for it, based on the BEAUTIFUL ATTITUDE THAT SACRIFICE IS NECESSARY, WILL RESULT IN PERSEVERANCE, which is nothing more that CONSISTENT DISCIPLINE.

CALL TO ACTION: Write down one sacrifice that must be made in order to begin your business-leadership growth-journey. Take note that this is just the beginning. There’s no need to bog yourself down with a long list what will inevitably end up in the trash.

ULTIMATE GOAL: That simple exercise will prime the pump of creative thought and deeper consideration of the long-lasting value of a beautiful attitude in business leadership.

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Warren Buffett, the chairman and CEO of Berkshire Hathaway, turns 91 in August. Remarkably, at an age where most people's cognitive functions have entirely regressed, where many are now at the hands of caretakers, Buffett still captures the world's attention as the fifth richest person on the planet.

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• Manufacturing returned to America
• New sourcing of raw materials and parts in the U.S.
• Expanding operations in America vs. going overseas
• Foreign direct investment in U.S. manufacturing

Statistics on reshoring are suspect

Statistics published with actual numbers of reshored jobs are suspect and unverifiable.  These published statistics are typically directionally correct, but cannot be verified. Some organizations count the number of jobs being returned as they are published in newspapers and press releases – numbers that might never materialize.  Others use import statistics that do not account for expansion projects in the U.S. Both are sketchy approaches with unreliable results.

While there is no official way to track and verify the actual reshoring numbers in terms of jobs returning or revenue increases, we have evidence that the reshoring trend is quite positive. We can also confirm anecdotally, the positive trend by the number of inquiries and consulting projects we get at the Reshoring Institute (www.ReshoringInstitute.org). Our “business activity” test is way up!

One startling number I saw recently was published by Thomasnet. Thomasnet surveyed over 500 industrial buyers – 83% of these buyers said they intended to find and place 10-12% more orders with domestic suppliers this year than last.  Based on Thomasnet’s collected buying data from past years as compared with next year, this simple change – buying 10%-12% more U.S.-made products – could inject $443 Billion into the US economy. WOW!

If these numbers are anywhere near correct, we are in for a wild ride. Thomasnet is a reliable source, and although the numbers are a projection based on a survey, they are likely to be directionally correct. Since we define the new placement of orders in the U.S. as part of reshoring, this number made me sit up and take notice. The trend is indeed positive.

The effect on the U.S. economy

What effect is this likely to have on the American economy? It’s like putting dry kindling onto a roaring fire. The effect is immediate, visible, and significant.  If this much money is put into U.S.- made industrial buying, we will all surely feel the positive effects of a roaring and on-fire economy.

There is also a magnifier effect when new jobs are added in the manufacturing sector. Based on the Bureau of Economic Analysis (BEA) annual input-output tables have calculated that a dollar’s worth of final demand for manufacturers generates $1.48 in other services and production. Other economists put the number higher – as much as $2.00 for every $1.00 spent on manufacturing.

Manufacturing is the backbone of a robust economy.  In the 1960s, manufacturing accounted for about 25% of the U.S. GDP. In recent years it’s dwindled to less than 12% and employs only 9% of the workforce. There is a lot of room for growth in American manufacturing if we can make the economic case for bringing manufacturing back. We must focus on automation, advanced manufacturing techniques, and reduction of labor to reduce overall costs and increase productivity.

China’s robust growth over the past 25 years can be attributed to a manufacturing economy that is nearly 40% of China’s GDB. China makes and sells more manufactured goods than any other country on the planet.  It is time we focus on rebuilding manufacturing in America.

The reasons for returning manufacturing to the U.S.

The pandemic is the primary reason for this uptick in the return of American sourcing and manufacturing. Previous efforts including the tax reduction act of 2017, and the global trade war with China contributed but created only lukewarm results. The pandemic, on the other hand, introduced supply chain risk and exposed America’s vulnerability in supply chains for medical products and supplies.  Now we are experiencing severe semiconductor shortages, steel shortages, and shortages in other industries.

If some of the statistics for reshoring and industrial buying are true, or at least directionally correct, then American manufacturing is poised for rapid rebirth and astonishing results. I am very optimistic that Reshoring will continue to expand in America.

The post Reshoring is Booming! appeared first on Industrial Talk.

1. SUCCESSFUL are the SACRIFICIAL…They develop perseverance.
2. SUCCESSFUL are the HUMBLE…They know who they are, strengths & weaknesses. They ask for help.
3. SUCCESSFUL are the FAILURES…They will rightly value success as the result of falling and getting back up again & again & again.
4. SUCCESSFUL are the CALM…They develop enduring strength.
5. SUCCESSFUL are the SELFLESS…They are motivated to do what’s right for others rather than what’s just expedient.
6. SUCCESSFUL are the FORGIVING…They build connections rather than tear them down.
7. SUCCESSFUL are the GENEROUS…They understand servant leadership.

AND WE BEGIN…

Beautiful Attitudes for business…Why? Why does a deeply held regard for all things beautiful and uplifting have anything at all to do with leadership success in business? Not talking about the occasional good feeling resulting from accomplishment and reward, so go home and pop the cork. It’s celebration time! No, this is the consistent, eternally-abiding sense of bringing good into the world simply because it’s right. BUT IS IT SUSTAINABLE? Is the idea that a beautiful attitude brings business leadership success just a touchy-feely, kumbaya pipe dream? I believe it is definitely NOT. Sustainable regard for the beautiful in our attitudes is actually the pre-requisite for admirable leadership and business success. They are easily seen as a match made in heaven if one simply takes a moment to consider the alternatives…anger, bitterness, revenge…YUCK! (And frankly, no fun at all.)

Business Beatitudes provide structure, the bones necessary for stability and growth. Without the BB, founding principles are MIA, leaving the business leader to flail in the changing winds of trends and market forces, minus the Monday-morning quarterbacking that can be quite helpful in the evaluation re-cap. (You know, the “I’ll never do THAT again” file.) I’ve lived in the changing winds, on the receiving end of market-forces victimization, and if I’m honest with myself, may have been perceived a time or two as the giver as well. (We’ll talk about the Law of Unintended Consequences later.) But I digress…

Where do go with all of this? We take it into the marketplace, putting the Business Beatitudes to the test, a stress-test if you will, of their usefulness in bringing about quantifiable change to the bottom line AND happiness in the workplace. When the Leadership is laser-focused on building sustainable Beautiful Attitudes and EXEMPLIFIES them, the business as a living entity not only grows but THRIVES.

Let’s get started NOW!

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According to the Organization for Economic Cooperation and Development, US Real GDP is projected to grow by 6.9% in 2021. Accordingly, shippers should prepare for this year to be a perpetual peak season across all transport modes.

Full Report

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The transition from internal combustion engines (ICEs) to electric vehicles (EVs) is accelerating worldwide. Significant progress in commercial electrification is being seen, most notably in last mile delivery. Last mile services have always been a part of the end-to-end supply chain, but as we navigated lockdowns during COVID-19, getting a broader range of goods onto consumers' doorsteps has made it a retailer battleground. Expanded corporate fleets and outsourcing contracts for more responsive last mile services have become integral to answering shifting consumer expectations. In parallel, the electrification landscape has evolved rapidly, with barriers to adoption being resolved and the cost benefits of conversion being actualized.

Part 1: Trends and Drivers for Converting Last Mile Fleets

Sustainability Commitments

Many companies prioritize environmental, social, and governance (ESG) strategies with a clear trend toward corporate fleet electrification. Some of the leading brands in online retail and transportation have established roadmaps to green the last mile. For instance, Amazon has tasked its sustainability scientists with analyzing and measuring its carbon footprint and has determined that online shopping is greener than in-store. They report that a single delivery van trip can eliminate an average of 100 shopper roundtrips by car.[1] This dove tails with Amazon’s Climate Pledge to have half of its shipments net-zero carbon by 2030.[2]

Delivery powerhouse FedEx has developed its fleet electrification plan. As part of its broader $2B investment in three core sustainability areas – vehicle electrification, sustainable energy, and carbon sequestration – FedEx has committed to having its entire fleet of parcel pick-up and delivery vehicles electrified by 2040.[3] Many others are following the same path toward electrification.

Regulations

Various state legislatures are assessing green transportation regulations; California is the most aggressive. By 2035, the state will require 55 percent of delivery trucks and vans, 75 percent of box trucks, and 40 percent of tractor-trailers to be electric. By 2050, all commercial truck sales in California must be electric.[4] Most states are enforcing federal standards rather than establishing their own, as that would create a patchwork of varying regulations that would complicate compliance. California is serious about the transition to commercial EVs to make a permanent dent in greenhouse gases.

Federal and State Incentives

Federal tax incentives are another way the public sector promotes the transition to EVs, making the change to electricity more cost-effective and appealing for businesses. The current $7,500 federal tax credit on EVs applies to OEMs that have produced fewer than 200,000 cars, essentially excluding EV purchases from Tesla, Nissan, and GM. Lawmakers are considering removing the 200,000-vehicle cap and sweetening the deal by increasing the tax credit to $10,000 for EVs made in the United States and adding another $2,500 for EVs assembled by workers represented in a union.[5]

Incentives go beyond the EV to include offsets to the cost of charging infrastructure installation. For example, the Alternative Fuel Vehicle Refueling Property Tax Credit eases the financial burden for businesses through a federal tax credit of 30 percent of the cost, up to $30,000, for commercial installations.[6] Some states such as California, Colorado, and New York also provide business incentives to install electric charging infrastructure.

Total Cost of Ownership

Perhaps the most significant factor driving the commercial EV transition is the total cost of ownership (TCO). This is a CAPEX plus OPEX calculation that includes the price of the vehicle plus the cost of its maintenance plus the cost of fuel over the vehicle’s entire lifetime. Because of government incentives, low electricity costs, and minimal maintenance relative to an ICE vehicle, EVs deliver a lower TCO than commercial ICE vehicles. Add to that the recent escalation in gas prices and EVs become an even more effective business decision.

With EVs becoming increasingly affordable and with the side benefits of achieving ESG goals through the electrification of transportation, we can expect to see a steady rise in commercial vehicles transitioning to electric.

What is Up Next?

In part two of this three-part series, I will discuss how the challenges that previously slowed fleet electrification are being resolved and spotlight the companies driving the transition for last mile delivery services.

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When I published my first book “Big Data” in September, 2013, I referred to the fourth stage of the “Big Data Business Model Maturity Index as the “Data Monetization” phase.  However, it wasn't until my latest book “The Economics of Data, Analytics, and Digital Transformation” that I published the end of last year, that I finally got the concept right.  For most organizations, it shouldn't be “Data Monetization.”  Instead, “Insights Monetization” – customer, product, and operational insights or predicted propensities – is more appropriate (Figure 1).

The “Insights Monetization” phase of the Data & Analytics Business Maturity Index is described as such:

That doesn't mean to preclude data monetization – or the direct selling of one's data – as an option, but data monetization has a very different context than insights monetization.  Let me explain.

What is Data Monetization?

The problem with the term “Data Monetization” is that for many organizations, this implies the direct selling of the organization's data.  And there are certainly companies out there that do sell data.  Nielsen, Acxiom, Experian, Equifax and CoreLogic are companies whose business model is the acquisition, aggregation, and selling of third-party data.  For example, Figure 2 shows the personal data that one can buy from Acxiom.  Yea, sort of scary.

Figure 2:  Source: “Here are the data brokers quietly buying and selling your personal …“

Selling data requires a significant organization to acquire, cleanse, align, package, market, sell, support, and manage the data for external consumption.  And there is a myriad of growing legal and privacy concerns to navigate, so a pretty decent legal team will be required as well.

For other organizations, data monetization amounts to creating data services that facilitate the exchange of an organization's data in exchange for something of value from another organization. Walmart's Retail Link® is an example of this sort of “data monetization.”

Walmart's Retail Link® gives Walmart suppliers – think Consumer Packaged Goods (CPG) companies like Procter & Gamble, PepsiCo, and Unilever – access to Walmart's “point of sale” (POS) data. Retail Link provides suppliers access to the supplier's product sell-through (sales) data by SKU, by hour, by store. Suppliers can also get on-hand inventory by SKU, as well as gross margin achieved, inventory turns, in-stock percentages, and Gross Margin Return on Inventory Investment (Figure 3).

This is a great example of Data Monetization. Unfortunately, not all organizations have the clout and financial and technology resources of a Walmart to dictate this sort of relationship.  Walmart invests a significant amount of time, money and people resources to on-board, support, maintain, and upgrade Retail Link.  In that aspect, Walmart looks and behaves like an enterprise software vendor.

But for organizations that lack the clout, finances, and technology expertise of a Walmart, there are other “monetization” options.

Keys to Insights Monetization

Insights Monetization is about leveraging the customer, product, and operational insights (predicted propensities) buried in your data sources to optimize and/or reengineer key business and operational processes, mitigate (compliance, regulatory, and business) risks, create new revenue opportunities (such new products, services, audiences, channels, markets, partnerships, consumption models, etc.), and construct a more compelling, differentiated customer experience.

To drive “Insights Monetization” requires some key concepts and techniques.

(1) Nanoeconomics.  Nanoeconomics is the economics of individualized human and/or device predicted propensities.  Nanoeconomics helps organizations transition from overly generalized decisions based upon averages to precision decisions based upon the predicted propensities, patterns, and trends of individual humans or devices (Figure 4).

Remember, making decisions based on averages at best yield average results.  We can do better than average by leveraging nanoeconomics to make precision policy and operational decisions.

(2) Analytic Profiles provide a model for capturing and codifying the organization's customer, product, and operational analytic insights (predicted propensities) in a way that facilities the sharing and refinement of those analytic insights across multiple use cases (Figure 5).

An Analytic Profile capture of metrics, predictive indicators, segments, scores, and business rules that codify the behaviors, preferences, propensities, inclinations, tendencies, interests, associations and affiliations for the organization's key business entities such as customers, patients, students, athletes, jet engines, cars, locomotives, CAT scanners, and wind turbines.

(3) Use Cases are clusters of Decisions around a common Key Performance Indicator (KPI) where Decisions are a conclusion or resolution reached after analysis that leads to an informed action.  Sample use cases include reduce customer attrition, improve operational uptime, and optimize asset utilization. And the application of the Analytic Profiles can be used to help optimize or address the organization's top priority use cases (Figure 6).

The power of use cases are:

• Readily identifiable by the business stakeholders (because they live them every day)
• Resolution or optimization is a source of quantifiable business and operational value (improving, reducing, or optimizing the use cases can have material business and operational value)
• Encourages tight collaboration between business stakeholders and the data & analytics teams to properly define the objectives, benefits, value statements, and potential impediments of the use case, identify the metrics and KPIs against which use case progress and success will be measured, and codify the associated costs of use case False Positives and False Negatives (see “The Art of Thinking Like a Data Scientist” methodology).
• Provides the basis for a use case-by-use case development and implementation approach – driven by Return on Investment (ROI) – to building the organization's data and analytic assets (see the “Schmarzo Economic Digital Asset Valuation Theorem“).

Organizations tend to fail because they peanut butter their precious data and analytics resources across too many poorly defined use cases, and don't get the prerequisite business stakeholder buy-in to actually deploy or use the resulting analytics.  Focus baby, focus!

The post Monetization of Data appeared first on Industrial Talk.

To determine how knowledgeable and ingenious threat actors could be in compromising a manufacturing facility, we conducted a research in 2019 that essentially had us simulating a factory of our own. Using our most realistic honeypot to date, we created an environment that could lure cybercriminals into carrying out attacks and at the same time give us an all but unimpeded look at their actions.

We designed our pure-production honeypot to mimic a real system, including programmable logic controllers, a human-machine interface (HMI), and other components of an industrial control system (ICS). We then created a cover company for this faux factory: a rapid prototyping consultancy firm with ostensibly real human employees, working contact channels, and a client base composed of large anonymous organizations from critical industries. This ruse proved effective, as shown by the different types of attacks our honeypot attracted.

Our research paper, “Caught in the Act: Running a Realistic Factory Honeypot to Capture Real Threats,” contains the full details of our honeypot, from its conceptualization to the description of noteworthy attacks we encountered on it. Here we recount some of the highlights of our honeypot’s monthslong run.

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Achieving media coverage is a good way to build a manufacturer’s profile, increase a well-earned reputation, and communicate messaging to target audience customers. Posting a single published feature article is not enough; it must provoke the implementation of cross-promotional PR strategies which exponentially increase the reach of the media coverage. PR is the protein shake to augment a good marketing campaign.

Manufacturers as thought leaders

Research has shown thought leadership in manufacturing marketing makes a difference for B2B brands. Nearly two-thirds of decision-makers said that thought leadership is one of the top ways to gauge the caliber of thinking that a company can provide. This approach permits creativity, authentic voice of the manufacturer, and advances all other elements in manufacturing marketing.

Read the Full Article Here!

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