Category Archives: competitiveness

Quality 4.0 and Digital Transformation

The fourth industrial revolution is characterized by intelligence: smart, hyperconnected agents deployed in environments where humans and machines cooperate to achieved shared goals — and using data to generate value. Quality 4.0 is the name we give to the pursuit of performance excellence in the midst of technological progress, which are sometimes referred to as digital transformation.

The characteristics of Quality 4.0 were first described in the 2015 American Society for Quality (ASQ) Future of Quality Report. This study aimed to uncover the key issues related to quality that could be expected to evolve over the next 5 to 10 years. In general, the analysts expected that the new reality would focus not so much on individual interests, but on the health and viability of the entire industrial ecosystem.

Some of the insights from the 2015 ASQ Future of Quality Report were:

  • A shifting emphasis from efficiency and effectiveness, to continuous learning and adaptability
  • Shifting seams and transitions (boundaries within and between organizations, and how information is shared between the different areas)
  • Supply chain omniscience (being able to assess the status of any element of a global supply chain in real time)
  • Managing data over the lifetime of the data rather than the organization collecting it

The World Economic Forum (WEF) has also been keenly interested in these changes for the past decade. In 2015, they launched a Digital Transformation Initiative (DTI) to coordinate research to help anticipate the impacts of these changes on business and society. They recognize that we’ve been actively experiencing digital transformation since the emergence of digital computing in the 1950’s:

 

Because the cost of enabling technologies has decreased so much over the past decade, it’s now possible for organizations to begin making them part of their digital strategy. In general, digital transformation reveals that the nature of “organization” is changing, and the nature of “customer” is changing as well. Organizations will no longer be defined solely by their employees and business partners, but also by the customers who participate – without even explicitly being aware of their integral involvement — in ongoing dialogues that shape the evolution of product lines and new services.

New business models will not necessarily rely on ownership, consumption, or centralized production of products or provision of services. The value-based approach will accentuate the importance of trust, transparency, and security, and new technologies (like blockchain) will help us implement and deploy systems to support those changes.

 

Innovation Tips for Strategic Planning

Image Credit: Doug Buckley of http://hyperactive.to

Image Credit: Doug Buckley of http://hyperactive.to

Over the past 15 years, I’ve helped several organizations with continuous improvement initiatives at the strategic, executive level. There are a lot of themes that keep appearing and reappearing, so the purpose of this post is to call out just a few and provide some insights in how to deal with them! 

These come up when you are engaged in strategic planning and when you are planning operations (to ensure that processes and procedures ultimately satisfy strategic goals), and are especially prominent when you’re trying to develop or use Key Performance Indicators (KPIs) and other metrics or analytics.

 

1) How do you measure innovation? Before you pick metrics, recognize that the answer to this question depends on how you articulate the strategic goals for your innovation outcomes. Do you want to:

  • Keep up with changing technology?
  • Develop a new product/technology?
  • Lead your industry in developing best practices?
  • Pioneer new business models?
  • Improve quality of life for a particular group of people?

All of these will be measured in different ways! And it’s OK to not strategically innovate in one area or another… for example, you might not want to innovate your business model if technology development is your forte. Innovation is one of those things where you really don’t want to be everything to everyone… by design.

 

2) Do you distinguish between improving productivity and generating impact?

Improving quality (the ability to satisfy stated and implied needs) is good. Improving productivity (that is, what you can produce given the resources that you use) is also good. Reducing defects, reducing waste, and reducing variation (sometimes) are all very good things to do, and to report on. 

But who really cares about any improvements at all unless they have impact? It’s always necessary to tie your KPIs, which are often measures of outcomes, to metrics or analytics that can tell the story about why a particular improvement was useful — in the short term, and (hopefully also) in the long term.

You also have to balance productivity and impact. For example, maybe you run an ultra-efficient 24/7 Help Desk. Your effectiveness is exemplary… when someone submits a request, it’s always satisfied within 8 hours. But you discover that no tickets come in between Friday at 5pm and Monday at 8am. So all that time you spend staffing that Help Desk on the weekend? It’s non-value-added time, and could be eliminated to improve your productivity… but won’t influence your impact at all.

We just worked on a project where we had to consciously had to think about how all the following interact… and you should too:

  • Organizational Productivity: did your improvement help increase the capacity or capability for part of your organization? If so, then it could contribute to technical productivity or business productivity.
  • Technical Productivity: did the improvement remove a technical barrier to getting work done, or make it faster or less error-prone?
  • Business Productivity: did the improvement help you get the needs of the business satisfied faster or better?
  • Business Impact: Did the improvements that yielded organizational productivity benefits, technical productivity benefits, or business productivity benefits make a difference at the strategic level? (This answers the “so what” question. So you improved your throughput by 83%… so what? Who really cares, and why does this matter to them? Long-term, why does this awesome thing you did really matter?)
  • Educational/Workforce Development Impact: Were the lessons learned captured, fed back into the organization’s processes to close the loop on learning, or maybe even used to educate people who may become part of your workforce pipeline?

All of the categories above are interrelated. I don’t think you can have a comprehensive, innovation-focused analytics approach unless you address all of these.

 

3) Do you distinguish between participation and engagement?

Participation means you showed up. Engagement means you got involved, you stayed involved, your mission was advanced, or maybe you used this experience to help society. Too often, I see organizations that want to improve engagement, and all the metrics they select are really good at characterizing participation.

I’m writing a paper on this topic right now, but in the meantime (if you want to get a REALLY good sense of the difference between participation and engagement), read The Participatory Museum by Nina Simon. Yes, it is “about museums” — and yes, I know you’re in business or industry — and YES, this book really will provide you with amazing management insights. So read it!

Where is Quality Management Headed?

Image Credit: Doug Buckley of http://hyperactive.to

Image Credit: Doug Buckley of http://hyperactive.to

[This post is in response to ASQ’s February topic for the Influential Voices group, which asks: Where do you plan to take your career in 2016? What’s your view of careers in quality today—what challenges is this field facing? How can someone starting out in quality succeed?]

We are about to experience a paradigm shift in production, operations, and service: a shift that will have direct consequences on the principles and practice of design, development, and quality management. This “fourth industrial revolution” of cyber-physical systems will require more people in the workforce to understand quality principles associated with co-creation of value, and to develop novel business models. New technical skills will become critical for a greater segment of workers, including embedded software, artificial intelligence, data science, analytics, Big Data (and data quality), and even systems integration. 

Over the past 20 years, we moved many aspects of our work and our lives online. And in the next 20 years, the boundaries between the physical world and the online world will blur — to a point where the distinction may become unnecessary.

Here is a vignette to illustrate the kinds of changes we can anticipate. Imagine the next generation FitBit, the personalized exercise assistant that keeps track of the number of steps you walk each day. As early as 2020, this device will not only automatically track your exercise patterns, but will also automatically integrate that information with your personal health records. Because diet strategies have recently been shown to be predominantly unfounded, and now researchers like Kevin Hall, Eran Elinav, and Eran Siegal know that the only truly effective diets are the ones that are customized to your body’s nutritional preferences [1], your FitBit and your health records will be able to talk to your food manager application to design the perfect diet for you (given your targets and objectives). Furthermore, to make it easy for you, your applications will also autonomously communicate with your refrigerator and pantry (to monitor how much food you have available), your local grocery store, and your calendar app so that food deliveries will show up when and only when you need to be restocked. You’re amazed that you’re spending less on food, less of it is going to waste, and you never have to wonder what you’re going to make for dinner. Your local grocery store is also greatly rewarded, not only for your loyalty, but because it can anticipate the demand from you and everyone else in your community – and create specials, promotions, and service strategies that are targeted to your needs (rather than just what the store guesses you need).

Although parts of this example may seem futuristic, the technologies are already in place. What is missing is our ability to link the technologies together using development processes that are effective and efficient – and in particular, coordinating and engaging the people  who will help make it happen. This is a job for quality managers and others who study production and operations management

As the Internet of Things (IoT) and pervasive information become commonplace, the fundamental nature and character of how quality management principles are applied in practice will be forced to change. As Eric Schmidt, former Chairman of Google, explains:  “the new age of artificial intelligence is beginning, and it’s a big deal.” [2] Here are some ways that this shift will impact researchers and practitioners interested in quality:

  • Strategic deployment of IoT technologies will help us simultaneously improve our use of enterprise assets, reduce waste, promote sustainability, and coordinate people and machines to more effectively meet strategic goals and operational targets.
  • Smart materials, embedded in our production and service ecosystems, will change our views of objects from inert and passive to embedded and engaged. For example, MIT has developed a “smart band-aid” that communicates with a wound, provides visual indicators of the healing process, and delivers medication as needed. [3] Software developers will need to know how to make this communication seamless and reliable in a variety of operations contexts.
  • Our technologies will be able to proactively anticipate the Voice of the Customer, enabling us to meet not only their stated and implied needs, but also their emergent needs and hard-to-express desires. Similarly, will the nature of customer satisfaction change as IoT becomes more pervasive?
  • Cloud and IoT-driven Analytics will make more information available for powerful decision-making (e.g. real-time weather analytics), but comes with its own set of challenges: how to find the data, how to assess data quality, and how to select and store data with likely future value to decision makers. This will be particularly challenging since analytics has not been a historical focus among quality managers. [4]
  • Smart, demand-driven supply chains (and supply networks) will leverage Big Data, and engage in automated planning, automatic adjustment to changing conditions or supply chain disruptions like war or extreme weather events, and self-regulation.
  • Smart manufacturing systems will implement real time communication between people, machines, materials, factories and warehouses, supply chain partners, and logistics partners using cloud computing. Production systems will adapt to demand as well as environmental factors, like the availability of resources and components. Sustainability will be a required core capability of all organizations that produce goods.
  • Cognitive manufacturing will implement manufacturing and service systems capable of perception, judgment, and improving quality autonomously – without the delays associated with human decision-making or the detection of issues.
  • Cybersecurity will be recognized as a critical component of all of the above. For most (if not all) of these next generation products and production systems, quality will not be possible without addressing information security.
  • The nature of quality assurance will also change, since products will continue to learn (and not necessarily meet their own quality requirements) after purchase or acquisition, until the consumer has used them for a while. In a December 2015 article I wrote for Software Quality Professional, I ask “How long is the learning process for this technology, and have [product engineers] designed test cases to accommodate that process after the product has been released? The testing process cannot find closure until the end of the ‘burn-in’ period when systems have fully learned about their surroundings.” [5]
  • We will need new theories for software quality practice in an era where embedded artificial intelligence and technological panpsychism (autonomous objects with awareness, perception, and judgment) are the norm.

How do we design quality into a broad, adaptive, dynamically evolving ecosystem of people, materials, objects, and processes? This is the extraordinarily complex and multifaceted question that we, as a community of academics and practitioners, must together address.

Just starting out in quality? My advice is to get a technical degree (science, math, or engineering) which will provide you with a solid foundation for understanding the new modes of production that are on the horizon. Industrial engineering, operations research, industrial design, and mechanical engineering are great fits for someone who wants a career in quality, as are statistics, data science, manufacturing engineering, and telecommunications. Cybersecurity and intelligence will become increasingly more central to quality management, so these are also good directions to take. Or, consider applying for an interdisciplinary program like JMU’s Integrated Science and Technology where I teach. We’re developing a new 21-credit sector right now where you can study EVERYTHING in the list above! Also, certifications are a plus, but in addition to completing training programs be sure to get formally certified by a professional organization to make sure that your credentials are widely recognized (e.g. through ASQ and ATMAE).

 

References

[1] http://www.huffingtonpost.com/entry/no-one-size-fits-all-diet-plan_564d605de4b00b7997f94272
[2] https://www.washingtonpost.com/news/innovations/wp/2015/09/15/what-eric-schmidt-gets-right-and-wrong-about-the-future-of-artificial-intelligence/
[3] http://news.mit.edu/2015/stretchable-hydrogel-electronics-1207
[4] Evans, J. R. (2015). Modern Analytics and the Future of Quality and Performance Excellence. The Quality Management Journal22(4), 6.
[5] Radziwill, N. M., Benton, M. C., Boadu, K., & Perdomo, W., 2015: A Case-Based Look at Integrating Social Context into Software Quality. Software Quality Professional, December.

Free Speech in the Internet of Things (IoT)

Image Credit: from "Reclaim Democracy" at http://reclaimdemocracy.org/who-are-citizens-united/

IF YOUR TOASTER COULD TALK, IT WOULD HAVE THE RIGHT TO FREE SPEECH. Image Credit: from “Reclaim Democracy” at http://reclaimdemocracy.org/who-are-citizens-united/

By the end of 2016, Gartner estimates that over 6.4 BILLION “things” will be connected to one another in the nascent Internet of Things (IoT). As innovation yields new products, services, and capabilities that leverage this ecosystem, we will need new conceptual models to ensure quality and support continuous improvement in this environment.

I wasn’t thinking about quality or IoT this morning… but instead, was trying to understand why so many people on Twitter and Facebook are linking Justice Scalia’s recent death to Citizens United. (I’d heard of Citizens United, but quite frankly, thought it was a soccer team. Embarrassing, I know.) I was surprised to find out that instead, Citizens United is a conservative U.S. political organization best known for its role in the 2010 Supreme Court Case Citizens United v. FEC.

That case removed many restrictions on political spending. With the “super-rich donating more than ever before to individual campaigns plus the ‘enormous’ chasm in wealth has given the super-rich the power to steer the economic and political direction of the United States and undermine its democracy.” Interesting, sure… but what’s more interesting to me is that the Citizens United case, according to this source

  • Strengthened First Amendment protection for corporations, 
  • Affirmed that Money = Speech, and
  • Affirmed that Non-Persons have the right to free speech.

The article goes on to state that “if your underpants could talk, they would be protected by free speech.”

Not too long ago, a statement like this would just be silly. But today, with immersive IoT looming, this isn’t too far-fetched. 

  • What will the world look (and feel) like when everything you interact with has a “voice”?
  • How will the “Voice of the Customer” be heard when all of that customer’s stuff ALSO has a voice?
  • What IS the “Voice of the Customer” in a world like this?

If Japan Can, Why Can’t We? A Retrospective

if-japan-canJune 24, 1980 is kind of like July 4, 1776 for quality management… that’s the pivotal day that NBC News aired its one hour and 16 minute documentary called “If Japan Can, Why Can’t We?” introducing W. Edwards Deming and his methods to the American public. The video has been unavailable for years, but as of just last week, it’s been posted on YouTube. So my sophomore undergrads in Production & Operations Management took a step back in time to get a taste of the environment in the manufacturing industry in the late 1970’s, and watched it during class this week.

The last time I watched it was in 1997, in a graduate industrial engineering class. It didn’t feel quite as dated as it does now, nor did I have the extensive experience in industry as a lens to view the interviews through. But what did surprise me is that the core of the challenges they were facing aren’t that much different than the ones we face today — and the groundbreaking good advice from Deming is still good advice today.

  • Before 1980, it was common practice to produce a whole bunch of stuff and then check and see which ones were bad, and throw them out. The video provides a clear and consistent story around the need to design quality in to products and processes, which then reduces (or eliminates) the need to inspect bad quality out.
  • It was also common to tamper with a process that was just exhibiting random variation. As one of the line workers in the documentary said, “We didn’t know. If we felt like there might be a problem with the process, we would just go fix it.” Deming’s applications of Shewhart’s methods made it clear that there is no need to tamper with a process that’s exhibiting only random variation.
  • Both workers and managers seemed frustrated with the sheer volume of regulations they had to address, and noted that it served to increase costs, decrease the rate of innovation, and disproportionately hurt small businesses. They noted that there was a great need for government and industry to partner to resolve these issues, and that Japan was a model for making these interactions successful.
  • Narrator Lloyd Dobyns remarked that “the Japanese operate by consensus… we, by competition.” He made the point that one reason Japanese industrial reforms were so powerful and positive was that their culture naturally supported working together towards shared goals. He cautioned managers that they couldn’t just drop in statistical quality control and expect a rosy outcome: improving quality is a cultural commitment, and the methods are not as useful in the absence of buy-in and engagement.

The video also sheds light on ASQ’s November question to the Influential Voices, which is: “What’s the key to talking quality with the C-Suite?” Typical responses include: think at the strategic level; create compelling arguments using the language of money; learn the art of storytelling and connect your case with what it important to the executives.

But I think the answer is much more subtle. In the 1980 video, workers comment on how amazed their managers were when Deming proclaimed that management was responsible for improving productivity. How could that be??!? Many managers at that time were convinced that if a productivity problem existed, it was because the workers didn’t work fast enough, or with enough skill — or maybe they had attitude problems! Certainly not because the managers were not managing well. Implementing simple techniques like improving training programs and establishing quality circles (which demonstrated values like increased transparency, considering all ideas, putting executives on the factory floor so they could learn and appreciate the work being done, increasing worker participation and engagement, encouraging work/life balance, and treating workers with respect and integrity) were already demonstrating benefits in some U.S. companies. But surprisingly, these simple techniques were not widespread, and not common sense.

Just like Deming advocated, quality belongs to everyone. You can’t go to a CEO and suggest that there are quality issues that he or she does not care about. More likely, the CEO believes that he or she is paying a lot of attention to quality. They won’t like it if you accuse them of not caring, or not having the technical background to improve quality. The C-Suite is in a powerful position where they can, through policies and governance, influence not only the actions and operating procedures of the system, but also its values and core competencies — through business model selection and implementation. 

What you can do, as a quality professional, is acknowledge and affirm their commitment to quality. Communicate quickly, clearly, and concisely when you do. Executives have to find the quickest ways to decompose and understand complex problems in rapidly changing external environments, and then make decisions that affect thousands (and sometimes, millions!) of people. Find examples and stories from other organizations who have created huge ripples of impact using quality tools and technologies, and relate them concretely to your company.

Let the C-Suite know that you can help them leverage their organization’s talent to achieve their goals, then continually build their trust.

The key to talking quality with the C-suite is empathy.

 

You may also be interested in “Are Deming’s 14 Points Still Valid?” from Nov 19, 2012.

3 Steps to Creating an Innovative Performance Culture

Image Credit: Doug Buckley of http://hyperactive.to

Image Credit: Doug Buckley of http://hyperactive.to

Want to leapfrog over your competitors by designing an extremely high-performance culture for your organization? If so, I have the secret formula.

It starts here: in his August post to ASQ’s View From the Q blog, guest blogger James Lawther asks:

What are your DOs and DON’Ts of creating a performance culture?

Citing Deming and Drucker, and noting how so many organizations rely on a “carrots and sticks” approach to performance management, he converges on the following recommendation: “The way to create a high performance culture is to seek out poor performance, embrace it and fix it, not punish it.” I think, though, that this is not a new approach… rather than improving upon poor performance, why don’t we seek out truly amazing performance and then just make more of it? These three steps will help you do it:

  • Eliminate power relationships. Power is poison! It creates and cultivates fear (which, according to Deming, we need to drive out). Unfortunately, our educational system and our economy are firmly steeped in power relationships… so we’re not accustomed to truly cooperative relationships. (In fact, being reliant on the income from our jobs shoehorns us into power relationships before we even begin working.) Holacracy is one approach that some organizations are trying out, but there are many possibilities for shifting from organizational structures that are designed around power and control, versus those that are designed to stimulate interest, creativity, and true collaboration.
  • Create systems to help everyone find (and share) their unique skills, talents, and gifts. This is the key to both engagement and high performance — and this isn’t a one-shot deal. These skills, talents, and gifts are extremely dependent on the organizational context, the external environment, and a person’s current interests… and all of these change over time!
  • Create systems to help people become stewards of their own performance. Accenture and Google have both recently given up performance reviews… and Deming has always warned about them! Unless we’re managing our own performance, and the process and outcomes are meaningful to us individually, we’ll just be dragged down by another power relationship.

Quality professionals are great at designing and setting up systems to achieve performance goals! Now, we have an innovation challenge: adopt the new philosophy, design quality systems that substitute community in place of power and control, and use our sophisticated and capable information systems to give people agency over their own performance.

“Creative teamwork utterly depends on true communication and is thus very seriously hindered by the presence of power relationships. The open-source community, effectively free of such power relationships, is teaching us by contrast how dreadfully much they cost in bugs, in lowered productivity, and in lost opportunities.” — E. S. Raymond in The Cathedral and the Bazaar

A Chat with Jaime Casap, Google’s Chief Education Evangelist

jaime-casap-head

“The classroom of the future does not exist!”

That’s the word from Jaime Casap (@jcasap), Google’s Chief Education Evangelist — and a highly anticipated new Business Innovation Factory (BIF) storyteller for 2015.  In advance of the summit which takes place on September 16 and 17, Morgan and I had the opportunity to chat with Jaime about a form of business model innovation that’s close to our hearts – improving education. He’s a native New Yorker, so he’s naturally outspoken and direct. But his caring and considerate tone makes it clear he’s got everyone’s best interests at heart.

At Google, he’s the connector and boundary spanner… the guy the organization trusts to “predict the future” where education is concerned. He makes sure that the channels of communication are open between everyone working on education-related projects. Outside of Google, he advocates smart and innovative applications of technology in education that will open up educational opportunities for everyone.  Most recently, he visited the White House on this mission.

jaime-quote-image

The current system educational system is not broken, he says. It’s doing exactly what it was designed to do: prepare workers for a hierarchical, industrialized production economy. The problem is that the system cannot be high-performing because it’s not doing what we need it to for the upcoming decades, which requires leveraging the skills and capabilities of everyone.

He points out that low-income minorities now have a 9% chance of graduating from college… whereas a couple decades ago, they had a 6% chance. This startling statistic reflects an underlying deficiency in how education is designed and delivered in this country today.

So how do we fix it?

“Technology gives us the ability to question everything,” he says.  As we shift to performance-based assessments, we can create educational experiences that are practical, iterative, and focused on continuous improvement — where we measure iteration, innovation, and sustained incremental progress.

Measuring these, he says, will be a lot more interesting than what we tend to measure now: whether a learner gets something right the first time — or how long it took for a competency to emerge. From this new perspective, we’ll finally be able to answer questions like: What is an excellent school? What does a high-performing educational system look (and feel) like?

Jaime’s opportunity-driven vision for inclusiveness  is an integral part of Google’s future. And you can hear more about his personal story and how it shaped this vision next month at BIF.

If you haven’t made plans already to hear Jaime and the other storytellers at BIF, there may be a few tickets left — but this event always sells out! Check the BIF registration page and share a memorable experience with the BIF community this year: http://www.businessinnovationfactory.com/summit/register

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