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Multiple award-winning CTO, researcher, and bestselling author Gene Kim hosts enterprise technology and business leaders.
In the first part of this two-part episode of The Idealcast, Gene Kim speaks with Dr. Ron Westrum, Emeritus Professor of Sociology at Eastern Michigan University.
In the first episode of Season 2 of The Idealcast, Gene Kim speaks with Admiral John Richardson, who served as Chief of Naval Operations for four years.
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Is slowify a real word?
Could right fit help talent discover more meaning and satisfaction at work and help companies find lost productivity?
The values and philosophies that frame the processes, procedures, and practices of DevOps.
This post presents the four key metrics to measure software delivery performance.
October 22, 2020
The world changed on June 26, 2018. It happened quietly. Few people even noticed. But that was the day that, after more than a century, General Electric, the last original member of the Dow Jones Industrial Average, was removed from the index.
GE was one of just a dozen firms that Charles Dow included in his list in 1896. The company appeared alongside giants such as American Tobacco, American Sugar Refining Company, and Tennessee Coal and Iron, companies that dominated what Carlota Perez, an expert on the effect of technology on socioeconomic development, calls the Age of Electricity and Engineering in her book Technology Revolutions and Financial Capital.
As the previous age gave way to the Age of Oil and Mass Production, sugar refining lost its monopoly. Health concerns put out tobacco. General Electric, however, just kept going. It rode the change, feeding electricity into America’s growing economy and transforming from an industrial conglomerate into a financial colossus. In 2004, GE was the largest firm in the world by market capitalization with a value of $382 billion.
In 2016, it was one of the world’s ten largest companies, a symbol of how big and stable a company can become with expertise that suits the age. Just two years later, it was not. With a market value of $61 billion, only 15% of its peak value, and with its share price contributing less than half a percent to the Dow Jones’s value, GE found itself relegated from industry’s top league. Something had changed.
The reasons for GE’s decline are numerous (bad bets in oil, junk mortgages, and the size of GE Capital’s short-term borrowing leading up to the 2008 credit crisis had much to do with it); however, it’s not the only large, venerable company to find it was no longer leading the pack.
The rate of creative destruction is now faster than ever. In 1964, a firm listed on the S&P 500 Index could expect to remain on the index for thirty-three years. By 2016, that tenure had fallen to twenty-four years. By 2027, companies can expect to spend no more than twelve years on the index before they’re replaced. At the current churn rate, between 2018 and 2028, about half the index will have changed. With companies growing and shrinking faster than ever before, there is a need to be on the right side of change in order to survive and thrive.
A look at the current set of companies listed on the Dow Jones provides one clue to the source of the dramatic turnover on the S&P 500. Alongside stalwarts such as ExxonMobil and Procter & Gamble are Verizon, Cisco, IBM, and Intel, as well as Microsoft and Apple, two of the world’s largest firms by market capitalization. Currently, seven of the world’s ten largest firms by market capitalization are information technology companies, including (in addition to Microsoft and Apple) Google’s parent company Alphabet, Facebook, Amazon, and China’s Tencent and Alibaba. An economy that used to be dominated by oil and repetitive mass production has given way to one dominated by a continuous stream of information technology innovation and unique product development.
It’s not just what the technology companies are making. What characterizes today’s most highly valued organizations is how they make what they make. Their behavioral norms and system of work are different from anything that’s come before. They are applying better approaches to work by evolving their ways of working to deliver value in a way that suits the nature of their work. We are in the Age of Digital.
In this new age, every company is an information technology company, whether they know it yet or not. Today, nearly all change and nearly all product development in organizations (such as a new mortgage, a new vaccine, or a new model of car) includes information technology. For example, by 2030 it is forecasted that software will account for half of the total cost of a new car. The organizations that are thriving are the ones that are leveraging information technology and treating software not as a cost center but rather as central to generating new business value.
Crucially, unlike in the age of repetitive mass production—where, for example, 1,500 cars are produced by one factory every day, one car a minute, twenty-four hours a day—in the Digital Age, you don’t write the same software thousands of times. Software is written once, rewritten a few times to improve it, and then runs thousands of times. Every software binary coming off the virtual assembly line is unique. People don’t know what they want and you don’t know how you’re going to write the software until you’ve written it. Only once it’s in the hands of people do they know what they don’t want and do you realize how you should have written the code. Rather than the domain of work being repetitive, knowable, and deterministic with known-unknowns (you know how to fix it if something goes wrong), unique product development is unknowable and emergent with unknown-unknowns instead. For something that has not been done before, you don’t know what you don’t know until you do something and get feedback.
Over time, as compute power has increased, as we went from punch cards and valve-based computing with slow feedback loops (such as an overnight run) to microprocessors and the ability to have near-immediate feedback loops, an increasing number of software engineers realized that the then-conventional “heavyweight,” sequential, stage-gate processes for software development were not optimal for the complex and emergent domain of digital knowledge work.
Practitioners felt and saw the pain. With inspiration from articles such as “The New New Product Development Game,” software engineers in the late 1980s and early 1990s saw the benefits of better ways of working that were taking place in manufacturing firms like Toyota, Honda, and Xerox, with small empowered multidisciplinary teams and frequent small iterations, rather than the previous way of working with sequential, big-batch, stage-gate work passing by job role. This was in the context of product development and was heavily influenced by the legendary W. Edwards Deming, the godfather of Agile and Lean. With experimentation and experience, “lightweight” processes for software development became increasingly popular, being more suited to the emergent nature of digital work. In 2001, the values and principles of these lightweight processes were codified in the Agile Manifesto.
People doing product development found that these Agile principles helped them deliver value early and often with empowered teams. This led to better outcomes. These agile ways of working—suited to unique, emergent, product development—altered everything because they correctly optimize the approach to the work to the type of work. This way of working leads to the delivery of Better Value Sooner Safer Happier.
Increasingly old, traditional companies—the horses rather than the unicorns—are feeling the need to exhibit agility across the whole organization in order to keep up with the “born agile” disrupters who are not held back by legacy ways of working. Organized human endeavor in the Digital Age has increasingly shifted from repetitive production to unique product development. In addition, fueled by the same technological revolution, the pace of change has become faster.
To succeed, organizations are recognizing the importance of being proficient in ways of working suited to and leveraging the increasingly emergent nature of work and the continuous pace of change. Organizations are recognizing a need to exhibit business agility. These ways of working are not specific to IT, nor to any sector. They are essential to survive and thrive in the Age of Digital.
In order to understand the macro picture, it is helpful to look at the work of Professor Carlota Perez. In 2002, Perez wrote Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages, an analysis of the relationship between financial bubbles and technological change. In it, Perez demonstrates how, since the first industrial revolution, approximately every forty to sixty years there is a new technology-led revolution that gives rise to a paradigm shift and a new economy with societal impact. There is a recurrence of financial bubbles bursting in the middle of each technology-led revolution, caused by over investment in the hype, leading to a recession and then a new golden age. Each recession is a tipping point from a previous normal to a new normal. Since the beginning of the dot com crash in 2000, we’ve been living through the tipping point in the Age of Digital.
In each age, the ways of working evolve, suited to its context. Each advances on organized human endeavor, increasing productivity. We went from factory systems to subcontracting to Taylorism and Fordism and subsequently Lean in the Age of Oil & Mass Production. Now, we are emerging into business agility in the Age of Digital.
Project management and Gantt charts come from two technological revolutions ago, optimized for the primary context at the time, which was repetitive, knowable, deterministic, and generally physical activity. The evolution in ways of working, with time studies, reinforced the notion of managers versus workers, with a command-and-control, order-giver, order-taker, behavioral norm. Productivity improved, however, at a human cost, with workers treated as cogs in a machine.
Unfortunately, today, some organizations are still misapplying this way of working from more than a century ago to unique, unknowable, emergent, behavioral knowledge work: a type of activity that benefits from a wholly different approach, if there is a desire to deliver Better Value Sooner Safer Happier.
This book is here to help you on your unique journey to better ways of working in the Age of Digital in order to lead to better outcomes. It is a collection of antipatterns and patterns grouped into eight chapters, each chapter being a key learning.
These are lessons learned the hard way, and they are presented here to help you avoid potential potholes. Where work is emergent there is no such thing as best practice. There is no one size fits all. Your context is unique. These antipatterns and patterns are approaches that have been experienced by the authors and observed across hundreds of organizations to—more often than not—act as a headwind (antipattern) or a tailwind (pattern) to improving outcomes. This book, and the patterns and antipatterns within it, is shared learning. As your context is unique, your mileage may vary. No other organization has the same impediments, history, and culture as your organization. There is a need to apply an emergent mindset to this emergent domain of work. Take these learnings and optimize for fast learning. Amplify experiments that work and dampen experiments that don’t.
The focus of this book is on outcomes, not on Agile for Agile’s sake, or Lean for Lean’s sake. These outcomes are expressed as Better Value Sooner Safer Happier (or BVSSH for short).
Better is quality. Quality is built in rather than inspected in later. With smaller slices of value and multidisciplinary teams, changes are within a team’s cognitive load (that is, complexity that fits in your head) and there is a limited “impact radius.” There are fewer incidents and outages. There is less rework, less failure demand. More time is spent proactively rather than reactively.
Value is unique; it’s why you are doing what you are doing. It is of value to someone. It could be financial; it could be maintaining public safety; it could be charitable.
Sooner is time to market, time to learning, to pivoting, to de-risking, to avoiding a “sunk cost fallacy,” to locking in progress and value early and often.
Safer is Governance, Risk, and Compliance (GRC), information security, data privacy, regulatory compliance and resilience in chaos, be that a cyber-attack or a global pandemic. It is customers trusting your organization. It is agile rather than fragile. It is speed and control, not one or the other. It is cultural, keeping the conversation on risk alive. The better the brakes, the faster you can go.
Happier covers customers, colleagues, citizens, and climate, as it is not about “more for less” at any human or climatic cost. It is high levels of customer advocacy and colleague engagement with a positive impact to society and the one planet we live on. It is a more humane way of working.
Each of these elements balances the other. You can’t force Sooner, as there will be a downward trend in Better and Happier. Improving on BVSSH is not prescriptive. Measures are vector metrics (trends) rather than absolutes so that improvement over time can be compared. No one is exempt from improving. Within guardrails, teams are empowered and supported to build a muscle memory of continuous improvement in line with BVSSH. Sometimes it’s more agile and lean; sometimes it’s smaller waterfalls due to history, a command and control culture of fear, and lack of psychological safety. It depends on your unique culture, history, and context.
A key theme in this book that is worth highlighting is “Go Slower to Go Faster.” This is explored in particular in Chapters 2 and 7. There will be quick wins, and it is a fallacy to try to do too much too soon. People have a limited velocity to unlearn and relearn. You cannot force the pace of change in the same way that King Canute could not hold back the tide. Forcing the pace of change will likely lead to real, lasting change either not happening at all (with new labels on the same old behavior) or taking longer and with more risk. Lasting behavioral change takes as long as it takes, based on actions taken to nurture it, ignore it, force it, or sabotage it. It can be given a tailwind or a headwind. The intent is that this book gives you a tailwind.
What this book does not attempt to do is to touch on each body of knowledge. This is such a rich, deep, fascinating topic that it could fill a library. And if you are holding a physical copy, you are probably grateful that it doesn’t weigh more! While in particular agile, lean, and DevOps are spoken of, there is no explicit attempt to cover in depth topics such as systems thinking, design thinking, user experience (UX) design, Eli Goldratt’s Theory of Constraints, W. Edwards Deming’s System of Profound Knowledge, and so on. It is a beautiful, never-ending learning journey, which you too can contribute to, should you wish to.
The intent is that this book will give you a tailwind for improved ways of working. This book is not just about agile. Or just about lean. It is about ways of working for better outcomes in the Age of Digital.
In my next post, I’ll set the historical context for how we got where we are, which is critical to understand before we can hope to change.
This post is excerpted from Sooner Safer Happier by Jonathan Smart, with Zsolt Berend, Myles Ogilvie, and Simon Rohrer.
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