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How one man’s innovation provided the missing link for a 20th century agricultural revolution
GUEST POST from John Bessant
There’s a lot of good stuff which comes out of Ireland. Leaving aside the wonderful music, the amazing countryside (complete with its ‘soft’ rain) and some excellent food and drink (including a drop or two of the black stuff to which I am occasionally partial). But it’s also a country which punches well above its weight in terms of ideas — it’s got a reputation for being a smart economy basing its progress on putting knowledge to work. Creating value from those ideas — innovation.
That’s something which you’ll find not only in the universities and hi-tech companies dotted across the landscape but also down on the farm. Farming’s a tough business — anyone who watches the series ‘Clarkson’s Farm,’ will recognize the multiple challenges farmers face, battling all that Nature can throw at them when she’s in a bad mood plus rising costs, increasing regulation and volatile markets. It’s a field (ouch) where innovation is not just a nice to have, it’s essential.
And in Dromara, County Down there’s a statue erected to honor a man to whom many farmers, not just in Ireland but around the world, have cause to be grateful. Harry Ferguson.
Of course farming innovation isn’t new; it’s been at the heart of our progress towards being able to feed ourselves and so move beyond subsistence to doing something constructive with our newly-found spare time. Like building cities and societies. Think back to your school days and you’ll recognize many of the key innovations which enabled the ‘agricultural revolution’, increasing productivity to help feed a growing population. The early days were all about ingenious implements — Jethro Tull’s seed drill, (1701), Cyril McCormick’s reaper (1840), John Deere’s steel plow (1847) — all these and hundreds of other innovations helped move the needle on farming practices.
But better implements still faced the limitations of power — and that aspect of innovation remained unchanged for centuries. We’d moved on from back-breaking manual labor but for centuries we relied on animals, primarily horses, to pull or occasionally push our implements. Power was the agricultural equivalent of the ‘philosophers stone’ for alchemists, the secret which would turn base metals into gold (or farms into more productive units). So with the advent of steam power in the early 1800s it looked like it had been discovered; as factories, mines and even early railways were showing, a steam engine could harness the power of many horses.
But (in an early example of the hype cycle) the promise of steam power failed to deliver — largely for technical reasons. Steam engines were big and heavy which meant they had to stay in one place with their power distributed to where it was needed by elaborate systems of pulleys, belts and wheels. They were unreliable and dangerous with an unpleasant tendency to explode unpredictably. For certain tasks they held out promise — they could plow a simple flat field ten times as fast as a team of horses— but their inflexibility limited their application.
Traction engines provided a partial solution since these machines could carry out basic tasks drilling and plowing. Though they were often too heavy to work directly on muddy fields they had the advantage of power which could quickly be moved to where they were needed. Set them up on the side of a field, hook them up to relevant implements like plows and put them to work. When the job was finished, uncouple everything and move on to the next field (as long as it was fairly flat and big).
(Interestingly it was the traction engine which inspired Henry Ford to work on transportation. Reflecting on his first encounter with a traction engine on the family farm he said ‘I remember that engine, as though I had seen it only yesterday, for it was the only vehicle other than horse-drawn I had ever seen….it was that engine that took me into automotive transportation’).
So steam power wasn’t really going to change the farming world. But another innovation was — the internal combustion engine. Engineers around the world had seized on the possibilities of this technology and were working to try and come up with a ‘horseless carriage’, something which Karl Benz managed to do with his Motorwagen in 1885 in Germany. It didn’t take a big leap of imagination to see another location where replacing horses could have an advantage — and John Froelich, an engineer from Iowa duly developed the first gasoline-powered tractor, mounting an engine on a traction engine chassis in 1892.
Unfortunately he wasn’t able to make the machine in volume, producing only four tractors before closing down the business. But others were more successful; for example in 1905 the International Harvester company produced its first tractor, and in 1906 Henry Ford invested over $600,000 in research for tractors, building on his growing experience with cars. An early outcome was the ‘Automobile plow’, a cross-over concept using the Model T as the base.
Pretty soon, just as in the personal transportation marketplace, hundreds of entrepreneurs began working on tractor innovation; a classic example of what Joseph Schumpeter (the godfather of innovation economics) would call ‘swarming’ behavior. By 1910 there were over a thousand tractor designs on offer from 150 different companies.
A key part of Schumpeter’s theory of how innovation works is that many of the early entrepreneurs active in a new field will fail, whether for technical or business reasons, and there will be convergence along key dimensions — setting up a technological trajectory along which future developments will tend to run.
That was certainly the case with tractors; key pieces of the puzzle were coming into place like an ability to deal with difficult terrain by using all-wheel drive (offered by John Deere in 1914) and the trend towards smaller (and more affordable) machines, pioneered by the Bull Company. Agricultural shows began to feature tractor demonstrations which allowed farmers to see first-hand the relative benefits of different machines and an early front runner in the move towards widespread market acceptance was International Harvester with their light and affordable Titan 10/20 model.
This was a growing market; by 1916 over 20,000 tractors had been sold in the USA. As with many innovations once the ‘dominant design’ has emerged for the basic product configuration emphasis shifts to the ways in which they can be made — process innovation. Those players — like Henry Ford — with experience in mass production had a significant potential advantage. His Fordson brand became the benchmark in terms of pricing and other manufacturers often struggled to compete unless they were large, like the John Deere company which offered its Model D in 1923 for around $1000. Ford had priced aggressively to try and capture the market, originally offering the Fordson for $200 in pre-sales advertising , but eventually selling the tractor in 1917 for $750 ( a price at which he was actually making a loss).
Ford understood the principle; he’d used it to open up the automobile market by offering ‘…to build a car for the great multitude’ at a price that multitude could afford. But things were a little more complex down on the farm. At first sight tractors seemed a great idea not least because of their running cost advantages. Animals, while a flexible source of power, were also a big cost since they needed food, shelter and veterinary services, plus there was an opportunity cost in terms of land needed to grow their feed which could otherwise be sued for more profitable crops. It took around 6 acres per horse over the farming year. Tractors ran on kerosene, becoming widely available and at low cost; and they only burned this fuel when they were working.
Ford’s strategy appeared to pay off; by 1923 he had over 75% of the US market . Yet only five years later things had deteriorated so much that the company exited the business. What led to this dramatic shift was a series of challenges to which cost advantages based on process innovation weren’t the answer. Product innovation once again became a key differentiator. This time the issue wasn’t around simply replacing the animal power unit with a mechanical one; it had everything to do with what you connected that power up to.
Early tractors solved the connection problem with a simple drawbar, essentially a metal stick to which you could attach different implements. Which worked fine when the going was flat, the surface dry, the field large and simple. Unfortunately most farming also involves uneven ground, plenty of mud and rain-filled potholes, trees and other obstacles and small fields with uneven boundaries. To cope with all of that you need a utility tractor — not for nothing was the IH Farmall a runaway success in the 1920s — the name says it all. Having spent a significant amount (for a small farmer) on buying your lightweight utility tractor you want it to carry out much more than just row crop duties — helping out with a wide range of construction and maintenance operations down on the farm,.
In particular one innovation which helped endear International Harvester to many a farmer’s heart was the ‘power take off’ device — essentially making power available to be hooked up to a variety of different implements. Introduced in 1922 this opened up the market by massively increasing the versatility of tractor. All manner of attachments — seed drills, rotary cutters, posthole diggers, snow throwers — all could be run off the core PTO. We could draw an analogy to today’s IT world; buying a tractor without the ability to attach tools to it would be like buying a computer without software.
Which brings us back to Harry Ferguson (in case you thought we’d lost the Irish connection). Because connecting farm implements to tractors became his passion — and the basis for a highly successful business. In doing so he provided the platform on which so much could happen, much as Steve Jobs with the smart-phone enabled users to find and deploy the apps they wanted . And along the way he was able to help Henry Ford re-enter and revive his tractor business.
Ferguson was born 1884 in County Down, Ulster and grew up in a farming family — though he wasn’t particularly taken with the life. Nor was he that keen on school either, dropping out at the age of 14. What saved him was a love of reading and a fascination with all things mechanical — which in the early 20th century was a good interest to have. His brother helpfully opened a repair shop to cater to the emerging motor trade and Harry joined him, kindling enough focused motivation to study at Belfast Technical College. Arguably, though, his skill set was less around the mechanical detail than in the front office — sales and PR. He persuaded his brother to sponsor him and he proved adept at motor car and cycle racing — even persuading his brother to fund the development of Ireland’s first airplane which Harry then learned to fly!
Eventually he set up his own automobile business, May Street Motors, in Belfast in 1911 and one of his first appointments (a 21 year old mechanic, Willy Sands) proved to be crucial in his subsequent success. Sands was a gifted engineer; he remained with Ferguson for nearly fifty years, working in the backroom and helping develop the technologies which built business success.
Ferguson was quick to spot an opportunity in the emerging tractor market and managed to obtain a franchise for sales and service of the John Deere Overtime tractor which was being built in the UK. That gave Ferguson and Sands extensive experience in the way the tractor was put together, the repairs it needed and the context into which it was being applied.
The miseries of the Great War on the home front included food shortages and problems with imports so the British government were urgently seeking anything which could help out with farm productivity — including subsidizing investment in tractors. Harry played a part in this when he was given a contract for the Irish Board of Agriculture in 1917 to oversee government-owned tractor maintenance and production records. The duo traveled the country to advise farmers, help set up equipment like plows and understanding the problems farmers faced in deploying the tractor. For example soil compaction, caused by the heavy weight of tractors and plows of the time, was a common complaint.
All of this honed their skills at repairs and improvements to the current stock of tractors in Ireland; their next break came when conversion kits for the Model T car began to appear to create a car/tractor. Ferguson took a franchise for the Eros, a kit which involved putting larger rear wheels on the car, together with a chain transmission to them and installing a bigger radiator to cope with the engine load. His experience with farmers paid off; he realized that this lighter weight car/tractor could solve the soil compaction problem and so got Sands to design a lightweight plow for the Eros.
This — the ‘Belfast plow’ — was launched in 1917 and was the first farm implement bearing Ferguson’s name; it was half the weight of a standard plow and crucially used a clever idea for the hitch connecting the tractor to the plow. This meant that the load from pulling the plow was shared equally by all four wheels instead of just the rear ones; this made it easier to steer and drive.
But Henry Ford was not about to let the tractor opportunity market fall into the hands of conversion kits for Model Ts; instead he commissioned design and manufacture of his own tractor with a large slow turning engine. He persuaded the British Ministry of Munitions to purchase 6000 units in return for his setting up a factory in Ireland. The Fordson tractor (as it was called) arrived in 1917 but quickly ran into problems as farmers began to use it. In particular it had a worrying tendency to flip over on its back if it hit an obstacle; its powerful engine and the relative lack of weight on the front end meant it could be pulled over by an obstacle or an unexpected drag while plowing. Nonetheless its arrival spelt the end of conversion kits — and dealt a blow to Harry Ferguson’s dream.
He was nothing if not resilient; in true entrepreneurial style he turned the arrival in force of Fordsons to an opportunity, adapting his lightweight plow for use with the tractor. In particular they worked on their hitch system so that it helped overcome the tendency for the front wheels to rear up; their design included a clever depth control device — a floating skid — which stopped the problem happening when the plow dug too deep and pulled the tractor over.
This worked well with the plow but for other implements they realized depth control could be enabled by the use of a hydraulic lever which adapted to the terrain. Putting all of this together led them to a system which worked on a variety of implements including disc harrows and cultivators. In 1925 Ferguson was granted a patent for this three point hitch — and it became the basis on which he built his future success. It was the key to unlocking the puzzle of how to connect power to implements and became the dominant design, one which is still widely used today.
The significance of this design should not be underestimated, and it’s something explored in depth in an excellent review by Scott Marshaus at the University of Wisconsin. Even though other factors helped contribute to the major increase in agricultural productivity like fertilizers, better seed strains and environmental management of pests the importance of completing the mechanization cycle is central. Yes, you can replace horses and mules with machine power but you can’t plant the seeds or distribute the chemicals unless you have the means to connect power with application. Which was the problem that Ferguson did so much to solve.
Just when all looked promising the market weather changed once again, another shift triggered by the business strategy of Ford. After years of making a loss the company decided to exit the tractor market in 1927, choosing instead to concentrate resources on their new Model A automobile. Which left Ferguson with no market for his Fordson-fitting plow.
So he (and Sands, as ever working away diligently in the backroom) developed their own lightweight tractor based on the Fordson design. They included their 3 point hitch and the prototype ‘Black Tractor’ appeared in 1933. Ferguson then went into partnership with the David Brown company to manufacture what became known as the Ferguson Brown Model A; production started in 1936. Disagreements quickly followed with Brown wanting to make a bigger tractor so Ferguson pulled out of the venture.
Instead he took one of the production Model A tractors into Henry Ford’s back garden — literally. In 1938 he showed it off and tested it against the Fordson and another tractor from Allis-Chalmers at Ford’s Fair Lane country estate. It performed so well that Ford wanted to make a deal on the spot and after brief discussion the two men shook hands. This handshake deal put a version of the tractor, called the Ford-Ferguson Model 9N into production in 1939 and it sold over 10,000 in its first year. By 1940 the factory was churning out 150 per day.
All should have been plain sailing but Ferguson’s prickly nature posed problems. He was, in many ways, a classic example of an entrepreneur, seeking opportunity wherever he could find it and adapting setbacks to become new directions for development. However he was also, according to his biographer Colin Fraser,‘someone who combined the extremes of subtlety, naiveté, charm, rudeness, brashness, modesty, largesse and pettiness; and the switch from any one to another could be abrupt and unpredictable. And, he had a penchant for confrontation.”
He had hoped that Ford in the UK would start production after the end of WW2 and he wanted a seat on the board; when this was rejected he threatened to walk away and start production on his own. But his position was weak; what he didn’t know was that Henry Ford 2nd, who took over in 1945, had discovered that the tractor business was still losing money at a desperate rate. He also discovered that the Ford-Ferguson 2N was being sold at a loss to Ferguson for resale to his dealers, an arrangement that cost Ford $25 million. Not surprisingly Ford wanted to stop and Ferguson was advised that 1947 would be the last year of the handshake agreement.
Ferguson fought back, putting his own version of the Ferguson/Ford tractor into production in 1946 in a war-surplus British factory. But competing with Ford was always going to be difficult; in response Ford introduced a new version, the Ford Model 8N in 1947, conspicuously missing the ‘Ferguson’ name from the badge. Ford’s engineers had tried to improve and sidestep Ferguson’s patented ideas but the core 3 point hitch and hydraulic system were retained. Although Ford’s marketing and distribution muscle backed him into a corner Ferguson in turn fought back, suing Ford in 1948 for $251 million for infringement of these patents.
Ferguson eventually won the bitter dispute and used some of the $9.25 damages agreed to continue to make tractors in the UK. But his attempts at working independently in the USA failed and eventually he merged his business with the Massey-Harris company in 1953.He retired from the tractor business but continued to develop ideas for the world of motor sport, including creating the first four wheel-drive system for use on Formula One racing cars.
He died in 1960 as a result of a barbiturate overdose; the inquest was unable to conclude whether this had been accidental or not. A sad end for someone whose passion and drive had helped enable the later stages of the agricultural revolution. But he left a powerful innovation footprint in farming soil all around the world. remembered in the tractor brand which bears his name and in the 3 point hitch design which is still in widespread use.
I get tired of listening to “experts” explain how leaders need to be bolder. Usually what they are advocating for is more disruptive innovation, less business as usual. But this completely ignores the impact of context and ends up patronizing behavior that may actually be well-grounded. It depends on which zone you are operating out of.
In the Performance Zone, the goal is to deliver on the quarterly plan. It is not the time or place for disruptive innovation. Leadership means getting your team to the finish line despite whatever roadblocks may crop up. Grit and resourcefulness, combined with attention to tactics, is what is wanted here.
In the Productivity Zone, the goal is to be there for the long haul. Again, disruptive innovation is not on the docket. Analysis and optimization are the keys here, and leaders must be willing to step back, take a systems view of things, and invest in efforts that will enable the Performance Zone to perform better in the future.
By contrast, the Incubation Zone is all about disruptive innovation, and most pundits champion a leadership style that is a perfect fit for this zone. So, if you are in this zone, by all means embrace hypothesis testing, agility, fast failure and the like. Just remember that what works here does not work well in any of the other three zones.
Finally, the Transformation Zone is where the pundits ought to be focusing because transformation is a bear, and no one can ever really tame it. Business lore celebrates the amazing disrupters here — Jobs, Musk, Bezos, etc. — as well we should. But in so doing we should not ignore the amazing disruptees, the leaders who redirected their enterprises to bring them kicking and screaming into a new age — Gerstner, Nadella, Iger, and company. For my money, their leadership style is the single most important one for any aspiring CEO to master.
That’s what I think. What do you think?
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Happy employees mean more engaged and productive employees. I’ve written many times that what’s happening inside an organization will be felt on the outside by customers. A good employee experience (EX) will positively impact the customer experience (CX). And of course, the opposite is true. A “ripple effect” of employee satisfaction or dissatisfaction will inevitably reach your customers, impacting their overall experience.
As a result of the Covid-19 pandemic, which forced a shutdown, many companies and organizations realized—or at least thought—their employees could work remotely. Many companies walked away from their offices and didn’t renew their leases. This shift in the traditional in-office, five-day-a-week schedule was either eliminated or modified, and many workers discovered they enjoyed working from home. However, it looks as if this “experiment” didn’t work out as planned, and many companies will start requiring RTO (return to office) in a schedule that looks similar to pre-pandemic office hours and attendance requirements.
In August, ResumeBuilder surveyed 1,000 corporate decision-makers about their RTO plans. Here are the main results:
90% of companies will return to the office by 2024.
only 2% say their company never plans to require employees to return to work in person.
72% say RTO has improved revenue.
28% will threaten to fire employees who don’t comply with RTO policies.
The Opportunity
Why return to the traditional office environment? The answer is something we already know. Because companies potentially make more money.
The move to return to the office started in 2021, just after the lockdown. That year, 31% of companies required employees to return to their offices, 41% in 2022 and 27% in 2023. Most of the respondents to the survey claimed they saw an improvement in revenue, productivity and worker retention.
And for those companies that plan to demand RTO in 2024, 81% say it will improve revenue, 81% believe it will improve the company culture and 83% say it will improve worker productivity.
These decision-makers aren’t making an arbitrary determination. They recognize the negative impact an RTO policy can have. Many of them (72%) said their company would offer commuter benefits, 57% would help with child-care costs and 64% would provide catered meals. But are the perks enough?
The Danger
There is concern that a shift back to full-time office hours could cause a company to lose good employees in a hiring environment in which candidates are “calling the shots” and working for companies that not only give them a steady paycheck and traditional benefits, but also a work schedule and in-office policy that aligns with their need for work/life balance. Even so, according to the survey, 28% of the decision-makers surveyed claimed they would fire employees for not complying with their RTO policies.
As we navigate the complexities of a post-pandemic working world, companies face a tough choice that will shape and impact both the employee and customer experiences. Suppose a company decides to require a 100% return to the office. It must recognize and weigh the opportunities—primarily, increased productivity and revenue—with the negatives—less-than-enthusiastic employees and the potential (even probable) loss of employees.
In the 1970’s and 80’s, business investment in computer technology were increasing by more than twenty percent per year. Strangely though, productivity growth had decreased during the same period. Economists found this turn of events so strange that they called it the productivity paradox to underline their confusion.
Productivity growth would take off in the late 1990s, but then mysteriously drop again during the mid-aughts. At each juncture, experts would debate whether digital technology produced real value or if it was all merely a mirage. The debate would continue even as industry after industry was disrupted.
Today, that debate is over, but a new one is likely to begin over artificial intelligence. Much like in the early 1970s, we have increasing investment in a new technology, diminished productivity growth and “experts” predicting massive worker displacement . Yet now we have history and experience to guide us and can avoid making the same mistakes.
You Can’t Manage (Or Evaluate) What You Can’t Measure
The productivity paradox dumbfounded economists because it violated a basic principle of how a free market economy is supposed to work. If profit seeking businesses continue to make substantial investments, you expect to see a return. Yet with IT investment in the 70s and 80s, firms continued to increase their investment with negligible measurable benefit.
A paper by researchers at the University of Sheffield sheds some light on what happened. First, productivity measures were largely developed for an industrial economy, not an information economy. Second, the value of those investments, while substantial, were a small portion of total capital investment. Third, the aggregate productivity numbers didn’t reflect differences in management performance.
Consider a widget company in the 1970s that invested in IT to improve service so that it could ship out products in less time. That would improve its competitive position and increase customer satisfaction, but it wouldn’t produce any more widgets. So, from an economic point of view, it wouldn’t be a productive investment. Rival firms might then invest in similar systems to stay competitive but, again, widget production would stay flat.
So firms weren’t investing in IT to increase productivity, but to stay competitive. Perhaps even more importantly, investment in digital technology in the 70s and 80s was focused on supporting existing business models. It wasn’t until the late 90s that we began to see significant new business models being created.
The Greatest Value Comes From New Business Models—Not Cost Savings
Things began to change when firms began to see the possibilities to shift their approach. As Josh Sutton, CEO of Agorai, an AI marketplace, explained to me, “The businesses that won in the digital age weren’t necessarily the ones who implemented systems the best, but those who took a ‘digital first’ mindset to imagine completely new business models.”
He gives the example of the entertainment industry. Sure, digital technology revolutionized distribution, but merely putting your programming online is of limited value. The ones who are winning are reimagining storytelling and optimizing the experience for binge watching. That’s the real paradigm shift.
“One of the things that digital technology did was to focus companies on their customers,” Sutton continues. “When switching costs are greatly reduced, you have to make sure your customers are being really well served. Because so much friction was taken out of the system, value shifted to who could create the best experience.”
So while many companies today are attempting to leverage AI to provide similar service more cheaply, the really smart players are exploring how AI can empower employees to provide a much better service or even to imagine something that never existed before. “AI will make it possible to put powerful intelligence tools in the hands of consumers, so that businesses can become collaborators and trusted advisors, rather than mere service providers,” Sutton says.
It Takes An Ecosystem To Drive Impact
Another aspect of digital technology in the 1970s and 80s was that it was largely made up of standalone systems. You could buy, say, a mainframe from IBM to automate back office systems or, later, Macintoshes or a PCs with some basic software to sit on employees desks, but that did little more than automate basic clerical tasks.
However, value creation began to explode in the mid-90s when the industry shifted from systems to ecosystems. Open source software, such as Apache and Linux, helped democratize development. Application developers began offering industry and process specific software and a whole cadre of systems integrators arose to design integrated systems for their customers.
We can see a similar process unfolding today in AI, as the industry shifts from one-size-fits-all systems like IBM’s Watson to a modular ecosystem of firms that provide data, hardware, software and applications. As the quality and specificity of the tools continues to increase, we can expect the impact of AI to increase as well.
In 1987, Robert Solow quipped that, “ You can see the computer age everywhere but in the productivity statistics,” and we’re at a similar point today. AI permeates our phones, smart speakers in our homes and, increasingly, the systems we use at work. However, we’ve yet to see a measurable economic impact from the technology. Much like in the 70s and 80s, productivity growth remains depressed. But the technology is still in its infancy.
We’re Just Getting Started
One of the most salient, but least discussed aspects of artificial intelligence is that it’s not an inherently digital technology. Applications like voice recognition and machine vision are, in fact, inherently analog. The fact that we use digital technology to execute machine learning algorithms is actually often a bottleneck.
Yet we can expect that to change over the next decade as new computing architectures, such as quantum computers and neuromorphic chips, rise to the fore. As these more powerful technologies replace silicon chips computing in ones and zeroes, value will shift from bits to atoms and artificial intelligence will be applied to the physical world.
“The digital technology revolutionized business processes, so it shouldn’t be a surprise that cognitive technologies are starting from the same place, but that’s not where they will end up. The real potential is driving processes that we can’t manage well today, such as in synthetic biology, materials science and other things in the physical world,” Agorai’s Sutton told me.
In 1987, when Solow made his famous quip, there was no consumer Internet, no World Wide Web and no social media. Artificial intelligence was largely science fiction. We’re at a similar point today, at the beginning of a new era. There’s still so much we don’t yet see, for the simple reason that so much has yet to happen.
When there’s disagreement between words and behavior, believe the behavior. This is especially true when the words deny the behavior.
When there’s disagreement between the data and the decision, the data is innocent.
When there’s agreement that there’s insufficient data but a decision must be made, there should be no disagreement that the decision is judgment-based.
When there’s disagreement on the fact that there’s no data to support the decision, that’s a problem.
When there’s disagreement on the path forward, it’s helpful to have agreement on the process to decide.
When there’s disagreement among professionals, there is no place for argument.
When there’s disagreement, there is respect for the individual and a healthy disrespect for the ideas.
When there’s disagreement, the decisions are better.
When there’s disagreement, there’s independent thinking.
When there’s disagreement, there is learning.
When there’s disagreement, there is vulnerability.
When there’s disagreement, there is courage.
When there’s disagreement, there is trust.
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My most recent book, Zone to Win, lays out a game plan for digital transformation based on organizing your enterprise around four zones. They are the:
Performance Zone, where you make, sell, and deliver the products and services that constitute your core business.
Productivity Zone, where you host all the cost centers that support the Performance Zone, functions like finance, HR, IT, marketing, legal, customer support, and the like.
Incubation Zone, where you experiment with next-generation technologies to see if and how they might play a role in your future.
Transformation Zone, which you bring into existence on a temporary basis for the sole purpose of driving a digital transformation to completion.
The book uses these four zones to help you understand your own company’s dynamics. In this blog, however, we are going to use them to help you understand your customer’s company dynamics.
Here is the key insight. Customers buy your product to create value in one, and normally only one, zone. Depending on which zone they are seeking to improve, their expectations of you will vary dramatically. So, if you really want to get your customers to hate you, you have to know what zone they are targeting with your product or service.
To start with, if your customer is buying your product for their Productivity Zone, they want it to make them more efficient. Typically, that means taking cost out of their existing operations by automating one or more manual tasks, thereby reducing labor, improving quality, and speeding up cycle time. So, if you want to make this customer hate you, load up your overall offer with lots of extras that require additional training, have features that can confuse or distract end users, and generally just gum up the works. Your product will still do what you said it would do, but with any luck, they won’t save a nickel.
Now, if instead they are buying your product to experiment with in their Incubation Zone, they are looking to do some kind of proof of concept project. Of course, real salespeople never sell proofs of concepts, so continue to insist that they go all in for the full Monty. That way, when they find out they can’t actually do what they were hoping to, you will have still scored a good commission, and they will really hate you.
Moving up in the world, perhaps your customer has bought from you to upgrade their Performance Zone by making their operations more customer-focused. This is serious stuff because you are messing with their core business. What an opportunity! All you have to do is over-promise just a little bit, then put in a few bits that are not quite fully baked, turn the whole implementation over to a partner, and then, if the stars align, you can bring down their whole operation and blame it entirely on someone else. That really does get their dander up.
But if you really want to extract the maximum amount of customer vitriol, the best place to engage is in their Transformation Zone. Here the CEO has gone on record that the company will transform its core business to better compete in the digital era. This is the mother lode. Budget is no object, so soak it to the max. Every bell, whistle, doo-dad, service, product—you name it, load it into the cart. Guarantee a transformational trip to the moon and back. Just make sure that the timeline for the project is two years. That way you will be able to collect and cash your commission check before you have to find other employment.
Of course, if for some reason you actually wanted your customer to like you, I suppose you could reverse these recommendations. But where’s the fun in that?
That’s what I think. What do you think?
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One of the most often repeated episodes in the history of technology is when Steve Jobs was recruiting John Sculley from his lofty position as CEO at Pepsi to come to Apple. “Do you want to sell sugar water for the rest of your life,”Jobs asked, “or do you want to come with me and change the world?”
It’s a strange conceit of digital denizens that their businesses are something nobler than other industries. While it is true that technology can do some wonderful things, if the aim of Silicon Valley entrepreneurs was truly to change the world, why wouldn’t they apply their formidable talents to something like curing cancer or feeding the hungry?
The reality, as economist Robert Gordon explains in the The Rise and Fall of American Growth, is that the measurable impact has been relatively meager. According to the IMF, except for a relatively short burst in growth between 1996 and 2004, productivity has been depressed since the 1970s. We need to rethink how technology impacts our world.
The Old Productivity Paradox
In the 1970s and 80s, business investment in computer technology was increasing by more than 20% per year. Strangely though, productivity growth had decreased during the same period. Economists found this turn of events so strange that they called it the productivity paradox to underline their confusion.
The productivity paradox dumbfounded economists because it violated a basic principle of how a free market economy is supposed to work. If profit seeking businesses continue to make substantial investments, you expect to see a return. Yet with IT investment in the 70s and 80s, firms continued to increase their investment with negligible measurable benefit.
A paper by researchers at the University of Sheffield sheds some light on what happened. First, productivity measures were largely developed for an industrial economy, not an information economy. Second, the value of those investments, while substantial, were a small portion of total capital investment. Third, businesses weren’t necessarily investing to improve productivity, but to survive in a more demanding marketplace.
Yet by the late 1990s, increased computing power combined with the Internet to create a new productivity boom. Many economists hailed the digital age as a “new economy” of increasing returns, in which the old rules no longer applied and a small initial advantage would lead to market dominance. The mystery of the productivity paradox, it seemed, had been solved. We just needed to wait for the technology to hit critical mass.
The New Productivity Paradox
By 2004, the law of increasing returns was there for everyone to see. Google already dominated search, Amazon ruled e-commerce, Apple would go on to dominate mobile computing and Facebook would rule social media. Yet as the dominance of the tech giants grew, productivity would once again fall to depressed levels.
Yet today, more than a decade later, we’re in the midst of a second productivity paradox, just as mysterious as the first one. New technologies like mobile computing and artificial intelligence are there for everyone to see, but they have done little, if anything, to boost productivity.
At the same time the power of digital technology is diminishing. Moore’s law, the decades old paradigm of continuous doubling in the power of computer processing is slowing down and soon will end completely. Without advancement in the underlying technology, it is hard to see how digital technology will ever power another productivity boom.
Considering the optimistic predictions of digital entrepreneurs like Steve Jobs, this is incredibly disappointing. Compare the meager eight years of elevated productivity that digital technology produced with the 50-year boom in productivity created in the wake of electricity and internal combustion and it’s clear that digital technology simply doesn’t measure up.
The Baumol Effect, The Clothesline Paradox and Other Headwinds
Much like the first productivity paradox, it’s hard to determine exactly why the technological advancement over the last 15 years has amounted to so little. Most likely, it is not one factor in particular, but the confluence of a number of them. Increasing productivity growth in an advanced economy is no simple thing.
One possibility for the lack of progress is the Baumol effect, the principle that some sectors of the economy are resistant to productivity growth. For example, despite the incredible efficiency that Jeff Bezos has produced at Amazon, his barber still only cuts one head of hair at a time. In a similar way, sectors like healthcare and education, which require a large amount of labor inputs that resist automation, will act as a drag on productivity growth.
Another factor is the Clothesline paradox, which gets its name from the fact that when you dry your clothes in a machine, it figures into GDP data, but when you hang them on a clothesline, no measurable output is produced. In much the same way, when you use a smartphone to take pictures or to give you directions, there is considerable benefit that doesn’t result in any financial transactions. In fact, because you use less gas and don’t develop film, GDP decreases somewhat.
Additionally, the economist Robert Gordon, mentioned above, notes six headwinds to economic growth, including aging populations, limits to increasing education, income inequality, outsourcing, environmental costs due to climate change and rising household and government debt. It’s hard to see how digital technology will make a dent in any of these problems.
Technology is Never Enough to Change the World
Perhaps the biggest reason that the digital revolution has been such a big disappointment is because we expected the technology to largely do the work for us. While there is no doubt that computers are powerful tools, we still need to put them to good use and we have clearly missed opportunities in that regard.
Think about what life was like in 1900, when the typical American family didn’t have access to running water, electricity or gas powered machines such as tractors or automobiles. Even something simply like cooking a meal took hours of backbreaking labor. Yet investments in infrastructure and education combined with technology to produce prosperity.
Today, however, there is no comparable effort to invest in education and healthcare for those who cannot afford it, to limit the effects of climate change, to reduce debt or to do anything of anything of significance to mitigate the headwinds we face. We are awash in nifty gadgets, but in many ways we are no better off than we were 30 years ago.
None of this was inevitable, but the somewhat the results of choices that we have made. We can, if we really want to, make different choices in the days and years ahead. What I hope we have learned from our digital disappointments is that technology itself is never enough. We are truly the masters of our fate, for better or worse.
Digital transformation is hardly new. Advances in computing create more powerful infrastructure which in turn enables more productive operating models which in turn can enable wholly new business models. From mainframes to minicomputers to PCs to the Internet to the Worldwide Web to cloud computing to mobile apps to social media to generative AI, the hits just keep on coming, and every IT organization is asked to both keep the current systems running and to enable the enterprise to catch the next wave. And that’s a problem.
The dynamics of productivity involve a yin and yang exchange between systems that improve efficiency and programs that improve effectiveness. Systems, in this model, are intended to maintain state, with as little friction as possible. Programs, in this model, are intended to change state, with maximum impact within minimal time. Each has its own governance model, and the two must not be blended.
It is a rare IT organization that does not know how to maintain its own systems. That’s Job 1, and the decision rights belong to the org itself. But many IT organizations lose their way when it comes to programs—specifically, the digital transformation initiatives that are re-engineering business processes across every sector of the global economy. They do not lose their way with respect to the technology of the systems. They are missing the boat on the management of the programs.
Specifically, when the CEO champions the next big thing, and IT gets a big chunk of funding, the IT leader commits to making it all happen. This is a mistake. Digital transformation entails re-engineering one or more operating models. These models are executed by organizations outside of IT. For the transformation to occur, the people in these organizations need to change their behavior, often drastically. IT cannot—indeed, must not—commit to this outcome. Change management is the responsibility of the consuming organization, not the delivery organization. In other words, programs must be pulled. They cannot be pushed. IT in its enthusiasm may believe it can evangelize the new operating model because people will just love it. Let me assure you—they won’t. Everybody endorses change as long as other people have to be the ones to do it. No one likes to move their own cheese.
Given all that, here’s the playbook to follow:
If it is a program, the head of the operating unit that must change its behavior has to sponsor the change and pull the program in. Absent this commitment, the program simply must not be initiated.
To govern the program, the Program Management Office needs a team of four, consisting of the consuming executive, the IT executive, the IT project manager, and the consuming organization’s program manager. The program manager, not the IT manager, is responsible for change management.
The program is defined by a performance contract that uses a current state/future state contrast to establish the criteria for program completion. Until the future state is achieved, the program is not completed.
Once the future state is achieved, then the IT manager is responsible for securing the system that will maintain state going forward.
Delivering programs that do not change state is the biggest source of waste in the Productivity Zone. There is an easy fix for this. Just say No.
That’s what I think. What do you think?
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