Category Archives: Industry 4.0

Agile vs. Lean: Explained by Cats

Over the past few years, Agile has gained popularity. This methodology emerged as a solution to manage projects with a number of unknown elements and to counter the typical waterfall method. Quality practitioners have observed the numerous similarities between this new framework and Lean. Some have speculated that Agile is simply the next generation’s version of Lean. These observations have posed the question: Is Agile the new Lean?  

ASQ Influential Voices Roundtable for December 2019

The short answer to this question is: NO.

The longer answer is one I’m going to have to hold back some emotions to answer. Why? I have two reasons.

Reason #1: There is No Magic Bullet

First, many managers are on a quest for the silver bullet — a methodology or a tool that they can implement on Monday, and reap benefits no later than Friday. Neither lean nor agile can make this happen. But it’s not uncommon to see organizations try this approach. A workgroup will set up a Kanban board or start doing daily stand-up meetings, and then talk about how they’re “doing agile.” Now that agile is in place, these teams have no reason to go any further.

Reason #2: There is Nothing New Under the Sun

Neither approach is “new” and neither is going away. Lean principles have been around since Toyota pioneered its production system in the 1960s and 1970s. The methods prioritized value and flow, with attention to reducing all types of waste everywhere in the organization. Agile emerged in the 1990s for software development, as a response to waterfall methods that couldn’t respond effectively to changes in customer requirements.

Agile modeling uses some lean principles: for example, why spend hours documenting flow charts in Visio, when you can just write one on a whiteboard, take a photo, and paste it into your documentation? Agile doesn’t have to be perfectly lean, though. It’s acceptable to introduce elements that might seem like waste into processes, as long as you maintain your ability to quickly respond to new information and changes required by customers. (For example, maybe you need to touch base with your customers several times a week. This extra time and effort is OK in agile if it helps you achieve your customer-facing goals.)

Both lean and agile are practices. They require discipline, time, and monitoring. Teams must continually hone their practice, and learn about each other as they learn together. There are no magic bullets.

Information plays a key role. Effective flow of information from strategy to action is important for lean because confusion (or incomplete communication) and forms of waste. Agile also emphasizes high-value information flows, but for slightly different purposes — that include promoting:

  • Rapid understanding
  • Rapid response
  • Rapid, targeted, and effective action

The difference is easier to understand if you watch a couple cat videos.

This Cat is A G I L E

From Parkour Cats: https://www.youtube.com/watch?v=iCEL-DmxaAQ

This cat is continuously scanning for information about its environment. It’s young and in shape, and it navigates its environment like a pro, whizzing from floor to ceiling. If it’s about to fall off something? No problem! This cat is A G I L E and can quickly adjust. It can easily achieve its goal of scaling any of the cat towers in this video. Agile is also about trying new things to quickly assess whether they will work. You’ll see this cat attempt to climb the wall with an open mind, and upon learning the ineffectiveness of the approach, abandoning that experiment.

This Cat is L E A N

From “How Lazy Cats Drink Water”: https://www.youtube.com/watch?v=FlVo3yUNI6E

This cat is using as LITTLE energy as possible to achieve its goal of hydration. Although this cat might be considered lazy, it is actually very intelligent, dynamically figuring out how to remove non-value-adding activity from its process at every moment. This cat is working smarter, not harder. This cat is L E A N.

Hope this has been helpful. Business posts definitely need more cat videos.

The Connected, Intelligent, Automated Industry 4.0 Supply Chain

ASQ’s March Influential Voices Roundtable asks this question: “Investopedia defines end-to-end supply chain (or ‘digital supply chain’) as a process that refers to the practice of including and analyzing each and every point in a company’s supply chain – from sourcing and ordering raw materials to the point where the good reaches the end consumer. Implementing this practice can increase process speed, reduce waste, and decrease costs.

In your experience, what are some best practices for planning and implementing this style of supply chain to ensure success?

Supply chains are the lifeblood of any business, impacting everything from the quality, delivery, and costs of a business’s products and services to customer service and satisfaction to ultimately profitability and return on assets.

Stank, T., Scott, S. & Hazen, B. (2018, April). A SAVVY GUIDE TO THE DIGITAL SUPPLY CHAIN: HOW TO EVALUATE AND LEVERAGE TECHNOLOGY TO BUILD A SUPPLY CHAIN FOR THE DIGITAL AGE. Whitepaper, Haslam School of Business, University of Tennessee.

Industry 4.0 enabling technologies like affordable sensors, more ubiquitous internet connectivity and 5G networks, and reliable software packages for developing intelligent systems have started fueling a profound digital transformation of supply chains. Although the transformation will be a gradual evolution, spanning years (and perhaps decades), the changes will reduce or eliminate key pain points:

  • Connected: Lack of visibility keeps 84% of Chief Supply Chain Officers up at night. More sources of data and enhanced connectedness to information will alleviate this issue.
  • Intelligent: 87% of Chief Supply Chain Officers say that managing supply chain disruptions proactively is a huge challenge. Intelligent algorithms and prescriptive analytics can make this more actionable.
  • Automated: 80% of all data that could enable supply chain visibility and traceability is “dark” or siloed. Automated discovery, aggregation, and processing will ensure that knowledge can be formed from data and information.

Since the transformation is just getting started, best practices are few and far between — but recommendations do exist. Stank et al. (2018) created a digital supply chain maturity rubric, with highest levels that reflect what they consider recommended practices. I like these suggestions because they span technical systems and management systems:

  • Gather structured and unstructured data from customers, suppliers, and the market using sensors and crowdsourcing (presumably including social media)
  • Use AI & ML to “enable descriptive, predictive, and prescriptive insights simultaneously” and support continuous learning
  • Digitize all systems that touch the supply chain: strategy, planning, sourcing, manufacturing, distribution, collaboration, and customer service
  • Add value by improving efficiency, visibility, security, trust, authenticity, accessibility, customization, customer satisfaction, and financial performance
  • Use just-in-time training to build new capabilities for developing the smart supply chain

One drawback of these suggestions is that they provide general (rather than targeted) guidance.

A second recommendation is to plan initiatives that align with your level of digital supply chain maturity. Soosay & Kannusamy (2018) studied 360 firms in the Australian food industry and found four different stages. They are:

  • Stage 1 – Computerization and connectivity. Sharing data across they supply chain ecosystem requires that it be stored in locations that are accessible by partners. Cloud-based systems are one option. Make sure authentication and verification are carefully implemented.
  • Stage 2 – Visibility and transparency. Adding new sensors and making that data accessible provides new visibility into the supply chain. Key enabling technologies include GPS, time-temperature integrators and data loggers.
  • Stage 3 – Predictive capability. Access to real-time data from supply chain partners will increase the reliability and resilience of the entire network. Enterprise Resource Planning (ERP), Manufacturing Execution Systems (MES), and radio frequency (RFID) tagging are enablers at this stage.
  • Stage 4 – Adaptability and self-learning. At this stage, partners plan and execute the supply chain collaboratively. Through Vendor Managed Inventory (VMI), responsibility for replenishment can even be directly assumed by the supplier.

Traceability is also gaining prominence as a key issue, and permissioned blockchains provide one way to make this happen with sensor data and transaction data. Recently, the IBM Food Trust has demonstrated the practical value provided by the Hyperledger blockchain infrastructure for this purpose. Their prototypes have helped to identify supply chain bottlenecks that might not otherwise have been detected.

What should you do in your organization? Any way to enhance information sharing between members of the supply chain ecosystem — or more effectively synthesize and interpret it — should help your organization shift towards the end-to-end vision. Look for opportunities in both categories.


References for Connected, Intelligent, Automated stats:
  1. IBM. (2018, February). Global Chief Supply Chain Officer Study. Available from this URL
  2. Geriant, J. (2015, October). The Changing Face of Supply Chain Risk Management. SCM World.
  3. IBM & IDC. (2017, March). The Thinking Supply Chain. Available from this URL

Designing Experiences for Authentic Engagement: The Design for STEAM Canvas

As Industry 4.0 and Digital Transformation efforts bear their first fruits, capabilities, business models, and the organizations that embody them are transforming. A century ago, we thought of organizations as machines to be rigidly designed and controlled. In the latter part of the 20th century, organizations were thought of as knowledge to be cultivated, shared, and expanded. But “as intelligent systems gain traction, we are once again at a crossroads – where organizations must create complete and meaningful experiences” for their customers, stakeholders, and employees.

Read our new paper in the STEAM Journal

How do you design those complete, meaningful, and radically engaging experiences? To provide a starting point, check out “Design for Steam: Creating Participatory Art with Purpose” by my former student Nick Kamienski and me. It was just published today by the STEAM Journal.

“Participatory Art” doesn’t just mean creating things that are pretty to look at in your office lobby or tradeshow booth. It means finding ways to connect with your audience in ways that help them find meaning, purpose, and self-awareness – the ultimate ingredient for authentic engagement.

Designing experiences to make this happen is challenging, but totally within reach. Learn more in today’s new article!

Happy World Quality Day 2018!

Each year, the second Thursday of November day is set aside to reflect on the way quality management can contribute to our work and our lives. Led by the Chartered Quality Institute (CQI) in the United Kingdom, World Quality Day provides a forum to reflect on how we implement more effective processes and systems that positively impact KPIs and business results — and celebrate outcomes and new insights.

This year’s theme is “Quality: A Question of Trust”.

We usually think of quality as an operations function. The quality system (whether we have quality management software implemented or not) helps us keep track of the health and effectiveness of our manufacturing, production, or service processes. Often, we do this to obtain ISO 9001:2015 certification, or achieve outcomes that are essential to how the public perceives us, like reducing scrap, rework, and customer complaints.

But the quality system encompasses all the ways we organize our business — ensuring that people, processes, software, and machines are aligned to meet strategic and operational goals. For example, QMS validation (which is a critical for quality management in the pharmaceutical industry), helps ensure that production equipment is continuously qualified to meet performance standards, and trust is not broken. Intelex partner Glemser Technologies explains in more detail in The Definitive Guide to Validating Your QMS in the Cloud. This extends to managing supplier relationships — building trust to cultivate rich partnerships in the business ecosystem out of agreements to work together.

This also extends to building and cultivating trust-based relationships with our colleagues, partners, and customers…

Read more about how Integrated Management Systems and Industry 4.0/ Quality 4.0 are part of this dynamic: https://community.intelex.com/explore/posts/world-quality-day-2018-question-trust

Quality 4.0 in Basic Terms (Interview)

On October 12th I dialed in to Quality Digest Live to chat with Dirk Dusharne, Editor-in-Chief of Quality Digest, about Quality 4.0 and my webinar on the topic which was held yesterday (October 16).

Check out my 13-minute interview here, starting at 14:05! It answers two questions:

  • What is Quality 4.0 – in really basic terms that are easy to remember?
  • How can we use these emerging technologies to support engagement and collaboration?

You can also read more about the topic here on the Intelex Community, or come to ASQ’s Quality 4.0 Summit in Dallas next month where I’ll be sharing more information along with other Quality 4.0 leaders like Jim Duarte of LJDUARTE and Associates and Dan Jacob of LNS Research.

Quality 4.0: Reveal Hidden Insights with Data Sci & Machine Learning (Webinar)

Quality Digest

What’s Quality 4.0, why is it important, and how can you use it to gain competitive advantage? Did you know you can benefit from Quality 4.0 even if you’re not a manufacturing organization? That’s right. I’ll tell you more next week.

Sign up for my 50-minute webinar at 2pm ET on Tuesday, October 16, 2018 — hosted by Dirk Dusharme and Mike Richman at Quality Digest. This won’t be your traditional “futures” talk to let you know about all of the exciting technology on the horizon… I’ve actually been doing and teaching data science, and applying machine learning to practical problems in quality improvement, for over a decade.

Come to this webinar if:

  1. You have a LOT of data and you don’t know where to begin
  2. You’re kind of behind… you still use paper and Excel and you’re hoping you don’t miss the opportunities here
  3. You’re a data scientist and you want to find out about quality and process improvement
  4. You’re a quality professional and you want to find out more about data science
  5. You’re a quality engineer and you want some professional preparation for what’s on the horizon
  6. You want to be sure you get on our Quality 4.0 mailing list to receive valuable information assets for the next couple years to help you identify and capture opportunities

Register Here! See you on Tuesday. If you can’t make it, we’ll also be at the ASQ Quality 4.0 Summit in Dallas next month sharing more information about the convergence of quality and Big Data.

Quality 4.0: Let’s Get Digital

Want to find out what Quality 4.0 really is — and start realizing the benefits for your organization? If so, check out the October 2018 issue of ASQ’s Quality Progress, where my new article (“Let’s Get Digital“) does just that.

Quality 4.0 asks how we can leverage connected, intelligent, automated (C-I-A) technologies to increase efficiency, effectiveness, and satisfaction: “As connected, intelligent and automated systems are more widely adopted, we can once again expect a renaissance in quality tools and methods.” In addition, we’re working to bring this to the forefront of quality management and quality engineering practice at Intelex.

Quality 4.0 Evolution

The progression can be summarized through four themes. We’re in the “quality as discovery” stage today:

  • Quality as inspection: In the early days, quality assurance relied on inspecting bad quality out of items produced. Walter A. Shewhart’s methods for statistical process control (SPC) helped operators determine whether variation was due to random or special causes.
  • Quality as design: Next, more holistic methods emerged for designing quality in to processes. The goal is to prevent quality problems before they occur. These movements were inspired by W. Edwards Deming’s push to cease dependence on inspection, and Juran’s Quality by Design.
  • Quality as empowerment: By the 1990’s, organizations adopting TQM and Six Sigma advocated a holistic approach to quality. Quality is everyone’s responsibility and empowered individuals contribute to continuous improvement.
  • Quality as discovery: Because of emerging technologies, we’re at a new frontier. In an adaptive, intelligent environment, quality depends on how:
    • quickly we can discover and aggregate new data sources,
    • effectively we can discover root causes and
    • how well we can discover new insights about ourselves, our products and our organizations.”

Read more at http://asq.org/quality-progress/2018/10/basic-quality/lets-get-digital.html  or download the PDF (http://asq.org/quality-progress/2018/10/basic-quality/lets-get-digital.pdf)

« Older Entries