Tag Archives: digital transformation

Yes, I’ve been gone for 9 months, because 2020

I find it amusing that my last post, exactly 9 months and 1 day ago, was about burnout. That’s before we knew what would happen just 8 weeks later, when we’d all go into a collective (and very dull) sweat lodge to rediscover ourselves by immersion in the ordinary. Which, as it turns out, also leads to burnout. Who would have guessed.

And not unexpectedly, in that interim, WordPress changed Gutenberg again and the editor is unrecognizable. I wish developers would stop making slick UIs that make it difficult to get tasks done, or that surprise unwitting users with an unplanned for cognitive load, without great up front preparation and expectation setting. (I’ll probably end up loving the new interface. Give me until Saturday.)

What’s been going on all this time? Two main things! First, my newest book came out from ASQ Quality Press: Connected, Intelligent, Automated: The Definitive Guide to Digital Transformation with Quality 4.0. It’s great for anyone who wants to get a really good, deep-in-the-bones feel for what digital transformation really means, along with its pals AI and Machine Learning, and how to make it happen in a way that will benefit the business. (Have a business person who works in tech on your holiday shopping list who throws around a lot of buzzwords? Do you want to cure them? This would make a great gift.)

The second thing is that I joined Ultranauts, an early stage professional services startup that provides quality assurance and quality engineering via functional, manual and accessibility testing; software test automation; and data quality engineering. We’re unique because over 75% of the workforce is autistic or otherwise neurodivergent… and unlike other similar companies or “autism at work” initiatives, we just focus on creating an individualized work environment where everyone can thrive. (Sounds like something that would be great in any company, right? Exactly… that’s what we’re working on.)

I’m still not out of the pandemic fog. In fact, it’s been so thick since maybe July that I haven’t been able to focus on anything but work and related obligations, and sleeping (so apologies to anyone whose messages I’ve missed; I’ve been firing on fumes). Since I started this blog 11 or 12 years ago, I’ve rarely missed a month on the board… posting is enjoyable to me, and a great way to make sure fleeting thoughts don’t completely fleet away. So here’s to the fog lifting, the posts starting to flow again, and a new life pattern emerging.

Preferably one that includes traveling to other countries. And trains.

Value Propositions for Quality 4.0

In previous articles, we introduced Quality 4.0, the pursuit of performance excellence as an integral part of an organization’s digital transformation. It’s one aspect of Industry 4.0 transformation towards intelligent automation: smart, hyperconnected(*) agents deployed in environments where humans and machines cooperate and leverage data to achieve shared goals.

Automation is a spectrum: an operator can specify a process that a computer or intelligent agent executes, the computer can make decisions for an operator to approve or adjust, or the computer can make and execute all decisions. Similarly, machine intelligence is a spectrum: an algorithm can provide advice, take action with approvals or adjustments, or take action on its own. We have to decide what value is generated when we introduce various degrees of intelligence and automation in our organizations.

How can Quality 4.0 help your organization? How can you improve the performance of your people, projects, products, and entire organizations by implementing technologies like artificial intelligence, machine learning, robotic process automation, and blockchain?

A value proposition is a statement that explains what benefits a product or activity will deliver. Quality 4.0 initiatives have these kinds of value propositions:

  1. Augment (or improve upon) human intelligence
  2. Increase the speed and quality of decision-making
  3. Improve transparency, traceability, and auditability
  4. Anticipate changes, reveal biases, and adapt to new circumstances and knowledge
  5. Evolve relationships and organizational boundaries to reveal opportunities for continuous improvement and new business models
  6. Learn how to learn; cultivate self-awareness and other-awareness as a skill

Quality 4.0 initiatives add intelligence to monitoring and managing operations – for example, predictive maintenance can help you anticipate equipment failures and proactively reduce downtime. They can help you assess supply chain risk on an ongoing basis, or help you decide whether to take corrective action. They can also improve help you improve cybersecurity: documenting and benchmarking processes can provide a basis for detecting anomalies, and understanding expected performance can help you detect potential attacks.


(*) Hyperconnected = (nearly) always on, (nearly) always accessible.

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 this theme of technological progress, which is 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.