Ways of Working: How We Got Here
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ways of working how we got here

In order to understand how to change, it is critical that we first understand how we got here. How we came to have the traditional ways of working that are in place in most large organizations today. 

 

 

Previous Ways of Working Were Optimized for Repetitive Labor

One of the leaders of the Efficiency Movement, Frederick Winslow Taylor, did much to improve industrial processes. Working first as a machinist and then as a consultant in the 1890s, Taylor applied a scientific approach to work by using a stopwatch to analyze repetitive work, such as shoveling iron ore or inspecting ball bearings. The result, Taylorism, was a top-down, us-and-them, command-and-control management system. Workers were told when to start and stop working, managers set quotas instead of workers setting the pace of work, and tasks were increasingly specialized. Managers would watch the workers, measure their performance, and order changes. Managers planned and workers worked. Employees did what they were told. As Taylor put it in Principles of Scientific Management:

 

“The work of every workman is fully planned out by the management at least one day in advance, and each man receives in most cases complete written instructions, describing in detail the task which he is to accomplish, as well as the means to be used in doing the work. This task specifies not only what is to be done but how it is to be done and the exact time allowed for doing it.”

While Taylor’s methods increased productivity, they did little to increase happiness or satisfaction in the workplace. Indeed, it is clear that Taylor looked down on workers, as this quote from Principles of Scientific Management illustrates : “A man who is fit to handle pig iron  .  .  .  shall be so stupid  .  .  .  that he more nearly resembles in his mental makeup the ox than any other type.”

 

Henry Gantt, the creator of Gantt charts, worked with Taylor in the early 1900s. According to Wallace Clark in The Gantt Chart: A Working Tool of Management (written in 1923), what we call a Gantt chart used to be called the Man Record Chart. The horizontal lines represented a worker’s actual output versus what the manager (not the worker) viewed to be a reasonable quota. If you moved enough crude iron today, you could go home. If not, you had to keep working. As represented in The Gantt Chart by Wallace Clark, “Long line men” were promoted and “short line men [were] very apt to do everything possible to distract the attention of others from their inferiority.”

 

The premise of the Man Record Chart was to watch over workers and follow up on perceived idleness—a continuation of the command-and-control culture of Taylorism, with managers telling workers exactly what to do. While the result was greater efficiency, it also drove a strong “us and them, managers versus workers” culture and unrest from unions.

The time study approach that Taylor championed was then built upon and improved by others, leading to the specialized production lines of Ford’s Model T and eventually the pull-based, just-in-time supply methods pioneered by Toyota that now power modern automotive factories.

 

While Taylorism turned workers into subservient machines, advances in technology led to machines that could do the work better. The automatic loom replaced handweavers. The internal combustion engine revolutionized travel and delivery times. Telegrams and telephones increased the speed at which information could flow. The forklift and automation replaced the muscles of Taylor’s steelworkers. Eventually, with the invention of the microprocessor and the arrival of the Age of Digital, labor’s comparative advantage switched from following orders and moving lumps of iron to the ability to create unique products and services that deliver outcomes for customers. The means of production changed from brawn to brain.

 

From Repetitive Manufacturing to Unique Product Development

In Taylor’s time, work was repetitive and performed by hand. Today, more and more of human endeavor is done with the head and is never the same twice, with automation taking on repetitive tasks. Today’s most dynamic industrial workplaces are no longer steel mills and fields of discarded iron. They’re more likely to resemble hipster cafés with espresso machines and shared tables. In many cities, the warehouses that used to store physical goods are now trendy, bare-brick hotbeds of information technology innovation. Work has moved away from hand-making the same thing repeatedly—effort that’s deterministic and has known-unknowns—to unique, knowledge-based work that is emergent and full of unknown-unknowns.

 

In the same way that going from the Stone Age to the Bronze Age meant not just better tools but also an entirely new society with new ways of living, organizing, and working, so the shift into today’s Digital Age has produced equally large social and economic effects.

In 2011, Marc Andreessen, coauthor of the first widely used web browser (Mosaic) and cofounder of the venture capital firm Andreessen Horowitz, told The Wall Street Journal:

 

“Software is eating the world. Six decades into the computer revolution, four decades since the invention of the microprocessor, and two decades into the rise of the modern Internet, all of the technology required to transform industries through software finally works and can be widely delivered at global scale.”

Organizations that have applied ways of working that suit the domain of work have not just survived, they’ve thrived to a degree rarely seen before. Alphabet, Amazon, Apple, and Microsoft have all been valued at over $1 trillion. Apple was the first publicly traded company to hit this landmark in August 2018, with the other three firms surpassing this valuation within eighteen months. Alphabet (Google) and Amazon went from zero to a $1 trillion valuation in just over twenty years. It is interesting to look back in time and see how for each landmark valuation there is a new normal and organizations with new ways of working that are suited to the technology revolution and type of work. The first $100 billion company was IBM in 1987, in the Age of Digital. General Motors was the first $10 billion company in 1955, in the Age of Oil & Mass Production. US Steel was the first $1 billion company in 1901, in the Age of Electricity & Engineering (and was removed from the S&P 500 Index in 2014).

 

That doesn’t mean that businesses must adopt new ways of working in this new Digital Age. Firms can choose to not adapt. A quote often attributed to W. Edwards Deming states: “It is not necessary to change. Survival is not mandatory.”

 

For example, in the retail apocalypse that started in 2010, approximately 10,000 stores closed in the US and 16,000 in the UK in 2019 alone prior to the COVID-19 pandemic. That’s five hundred stores closing every single week. The main factor cited was the shift to ecommerce. Thomas Cook, HMV, Debenhams, Bonmarche, Mothercare, Clintons, Karen Millen, Jack Wills, Bathstore, Sears, Borders, Topshop US, and Barneys are just some examples of retailers who have shut up shop or have needed to be rescued in the past few. The pandemic is accelerating the trend with as many 25,000 stores predicted to close in the US alone in 2020. Meanwhile, digital natives are set to open 850 stores by 2023 in “clicks to bricks” expansion plans. There are plenty of vacant stores for them to choose from.

 

What Are You Optimizing For?

This is an important question to ask. Within your organization, what are you optimizing for? Are you optimizing for the fast flow of safe value with high levels of customer advocacy and colleague engagement? Or for role-based silos, where work is passed over the wall to the next role-based silo with little notion of end-to-end ownership? Are you optimizing for value and time to value, or for pushing a “promise for a future solution” through endless gates and committees for years? Are you optimizing for fast learning and pivoting in order to maximize outcomes in the shortest possible time and with the least effort and least risk? Or for following a predetermined project plan with learning and risks back-loaded to the end with a large impact radius, big-bang implementation? Are you optimizing for everyone using their brains to run safe-to-learn experiments to continuously improve or for following orders?

 

As we’ve seen, organizations that have optimized their ways of working to suit the type of work have thrived. This results in higher customer expectations, raising the bar. There is a new normal, further fueled by the COVID-19 pandemic, accelerating the Age of Digital.

 

 

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