Gartner Hype Cycle Guide – BMC Software | Blogs

The Peak of Inflated Expectations: On the Edge

Jonathan Johnson — Fri, 22 May 2020 00:00:56 +0000

When any two people meet and begin a relationship, both parties come together with an ability to dream. They both make contributions to a dream, and the possibilities can be endless. Dreams are expectations. In an undisciplined practice, dreams get to be fantastic, ungrounded expectations. This period of ideation is the honeymoon period—the relationship, the idea thrives on excitement alone.

Words and minds enable dreams. Investments even pour in. Together, the parties form an idea for what the product should be. It is the task of the dreamer to go big—as big as possible. It is up to others to tether them to reality. In product development, engineers and accountants are counterparts to the dreamers. They tell the dreamers what is possible and what is not. Then, between the dreamers and the engineers, the dreamers’ expectations face the hard truth of reality, and a product can really take its shape. The Statue of David finally sheds its rocky shell.

When expectations go beyond what is possible, people flock to the concept. As if in awe by magic, or to witness the impossible, or to be a part of something new and fashionable, people gather to see whether the expectations are accurate—whether there will be innovation.

This moment is the peak of inflated expectations—let’s take a look.

What is the peak of inflated expectations?

In in the Gartner Hype Cycle, the peak of inflated expectations is the second of five phases in product development hype. It is important to see where value meets expectations. Hype is important to the discoverability of a product. Hype creates attraction, and attraction admits existence.

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The ideal situation is to discern between the hype and the value—this is the aim of the hype cycle. The bad case occurs when a product relies on hype alone. The good case is when a product’s hype is deserved, and it rests sturdily on a growing foundation of research. In any given moment, it is not an easy task to make the distinction. Only in hindsight can the distinction become obvious.

On the one hand, if people are gathering to see something incredible, nobody wants to miss it for fear of missing out. But on the other, if it is not really that incredible, dollars, time, and attention is spent on something that never deserved the attention in the first place—in this case, you get false prophets.

This phase of inflated expectations may be characterized by:

Excitement
More buzz than proof
Research bearing out (or not) the viability of the initial idea
An exploration of alternative options

When hype fails to create value

Theranos had a dream. It needed to build hype for that dream in order to create its product. As more and more people bought into their dream, Theranos received more resources to realize the dream it sold. After a while, Theranos could not create the product they said they would provide, and a pivotal moment occurred.

The expectations Theranos created were incredible, but the value they promised was unattainable. Their inability to engineer the expectations made them face a decision:

Let down everyone’s expectations of the product and tell the truth about the poor progress on their dream product.
Continue with the dream and find a way to cheat.

Of course, we know that Theranos chose to cheat.

The expectations they sold successfully built an incredible dream many supported. They attracted big name investors and were given loads of money. Theranos promised to positively change people’s lives forever. With so much attraction, and the desire for their success, failure actually became more costly than being discovered as a fraud. In Theranos’ best-case scenario, they could engineer the product and deliver the dream. In the worst-case scenario, at least in the eyes of its founders, Theranos fails to deliver the dream product they sold.

Theranos made an error in its ability to tell its narrative. Its founders could only navigate one possible narrative: either success or failure. They had an inability to adapt their narrative to the reality of the situation, and so the founders followed its initial track to its tragic conclusion. If it had been able to adapt, perhaps it would have found alternate solutions. It could fail to deliver on its initial expectations but find new possibilities and set new expectations. Instead, Theranos, eventually, could not make good on its promise, and ended as a failed Disneyland: everyone who’d bought admission got to stand disappointed in a tumbleweed-filled wasteland.

Theranos couldn’t grow past its inflated expectations. It was caught in its expectations and failed to find enough fuel to continue its propulsion forward. If it were to have found and created a product, the company would have had something substantial to speak for itself—Theranos would no longer need to rely on creating a stream of inflated expectations.

Where value meet expectations

Many stories are not tragic. Products and services provided by the government are provided largely because of hype. A government might provide products that people expect, but nobody has yet to be able to create on their own. This is the definition of a public good.

Government subsidizes many goods that people expect to exist—expect to have—in an effort to fuel the hype around those products and bring them into existence. Government subsidizes things like education, renewable energies, crop purchases, and healthcare. In some cases, it even ventures out to create these services itself. In a way, government is an early investor into many, many goods.

Some big companies that rose seemingly overnight in the early 2010s grew where value and hype met half-way. The new landscape of technology allowed for a new breed of company; one that emerges quickly and dominates the field just as quickly. Thanks to computers and the internet, people can communicate in various ways. New technologies could be adopted in just a few years rather than 10-20 years.

Facebook and Uber had a lot of hype and provided a lot of immediate value. These company cultures, then, got to ride out the full wave of their expectations and see the hype curve to its end.

More than a decade ago, Facebook promised that it would create a connected world. None of us really knew what this meant. Facebook said that it would allow friends to connect with each other, send each other updates, see how other people were dating, see what everyone was buying.

Some expectations were fulfilled. People who joined Facebook got to connect with friends. They could see what their friends were doing, they could share photos.
Some expectations couldn’t be met. The company promised to advertisers that when an individual would buy something, it would show to their friend group that someone bought that item. This makes a very desirable, word-of-mouth type of advertising available to advertisers. As the feature rolled out, users expressed privacy concerns (some users did not want their friends to see what they bought on Amazon), and Facebook had to redefine how to get a good service to its paying advertisers.

Facebook navigated its expectations by allowing the expectations of their products and product features to be A-B tested. Their promise was not on any single feature, but on their mission to create a more connected world. They would do this in whatever way they could—whatever way worked.

In the ideal world, where a new product succeeds, both engineering and dreams grow together in tandem: The peak of inflated expectations never rises too high. The fall into depression and disillusionment isn’t too great. All participants ride on a steady line of enlightenment.

The Gartner Hype Cycle

Explore every phase of hype:

Additional resources

For more on product development and innovation, check out these resources:

The Slope of Enlightenment: On Greased Wheels

Jonathan Johnson — Fri, 22 May 2020 00:00:53 +0000

We’ve now reached the Slope of Enlightenment. A product has been ideated. It has been taken to the extremes of imagination. It has been tried and tested in R&D phases. All fantasies about the social impact and the possibilities of the product have been rooted in what is possible and what is not. This is a beautiful stage for any product.

Here, we’ve reached a period of Renaissance. Let’s see what it looks like.

What is the slope of enlightenment?

The Gartner Hype Cycle identifies five key phases during a new technology’s development. During the Slope of Enlightenment, the fourth phase, a product gets to do all the things any product strives to accomplish: exist. It has passed the durability tests, venturing out into the woods to live with the wolves, and returns home accepted in the community as “one of them”.

This phase is characterized by:

A team who is confident in their work
High levels of productivity
More people who want to get involved
An easier time making progress

(Source)

Contrast the slope of enlightenment to the previous three phases. The beginning phases for any new product are chaotic; there exists lots of uncertainty. Previous phases have taken an idea and shaped it into something that is possible. As soon as a reality sets in, even new ideas have a much higher rate of contributing to the product’s end goal.

But here, in the enlightenment, the chaos rate falls. The team calms, the error rate decreases. The project’s direction is a lot clearer, more certain. It is easier to communicate where the project is headed.

Confidence

Now, team members can wear fewer hats. Before a product reached enlightenment, team members had to adapt quickly. The project direction was unclear, testing was dynamic, resource needs changed daily. Projects early in the hype cycle consist of only a few people with a lot of multi-disciplinary know-how and an ability to adapt.

When the product enters a moment of enlightenment, team members can now focus on just one task or area. There is less uncertainty to where a project is headed. Goals are created and stay in place, so it is easier to hire team members who have specialized skills.

Specialization allows management to assign a task and know that it will be executed with quality. This contributes to a culture of confidence, from everyone, that adds to the overall value of the product.

Here’s an example of this confidence: A skillfully written Dockerfile is not as valuable in a product’s initial testing—the entire container design might get scrapped in just a few iterations. But in an environment with increased certainty, the well-written Dockerfile, authored by a someone who has written thousands, suddenly becomes much more valuable. It serves a purpose for a much longer period of time. When the Dockerfile does need to change, the range in variation will be much smaller and easier to execute.

In this phase, your company’s time, direction, and investment dollar go much farther.

Productivity

With well-defined goals, everything the teams does makes it further and faster—and with less effort! The wheel on the carriage has been ground into a well-rounded circle, the axel’s been greased, and now the system can just…move.

“It happens with less effort!”

Specialization allows quality work to be done on individual tasks. A year can be spent polishing a diamond, rather than rapidly producing coals. Money is used more wisely. Ideation is also more effective: all the bad ideas have been rinsed from the system. Momentum is built, the carriage is already rolling, and it is easier to separate a bad idea from a good one.

In its early phases, Netflix could have explored ideas about building its own consumer hardware, such as Redbox-like vending machines. Now, however, the Netflix question has evolved well past that. They know their product offering, and they can easily say, “That’s not it.” It no longer gets off-base kinds of product ideas. Instead, Netflix benefits from a more refined stream of ideas that make minor, nuanced differences to their product offerings.

More people

As the project’s trajectory is much more certain, people want to get involved in the hype. While team members are busy specializing, you likely need to scale up and add more people to the team.

Thanks to this new-found clarity, new hires have a quicker on-boarding process. They can be shown what to do and become more effective. They have a well-defined set of tasks. Joining the team during the enlightenment phase means new hires have very specific tasks—your team shifted from doing everything to doing something.

Public attention

When people see something that works (the well-refined machine of enlightenment), they are attracted to it. People want to work there. Investors want to put their money there. Imitators follow.

A positive feedback loop exists between people who work at a company and the people who want to work at the company. There is a tango between the audience and the performer, and both feed from the other’s reactions.

Money is used more effectively. In R&D, a company tells investors, “We hope to find something that works.” In enlightenment, the company gets to say, “Your money goes to X product, which makes us Y dollars.” Now, all the risk-hungry, adrenaline-seeking investors during the VC seed and Angel rounds don’t get as excited, but there are fewer of them and it’s an unstable game–we’re past that game. The product can garner more stable attention and acquire, similarly, more stable investment (longer term relationships) with Mezzanine, A- and B- level, investments.

On greased axles, the product has a steady ride forward. The future arises from the mist, and the vision gets shared by founders, team members, and investors. Next, the product would like to see its acceptance by the wider community and live in the hearts of many.

The Gartner Hype Cycle

Explore every phase of hype:

Additional resources

For more on product development and innovation, check out these resources:

The Trough of Disillusionment: Working Hard

Jonathan Johnson — Fri, 22 May 2020 00:00:22 +0000

After a product is ideated and moves through the Peak of Inflated Expectations, the idea has been sold to management or investors, and everyone is on board with pursuing the product. The product now enters the Trough of Disillusionment. During this phase, a viable product really takes its shape, but you’ll likely experience certain challenges—let’s see what they are.

What is the trough of disillusionment?

The third of five phases in the Gartner Hype Cycle, the trough of disillusionment is arguably the most difficult phase. Here, you’ve already explored an original concept and performed some initial fundraising and testing. But your concept has peaked—the idea was over-inflated or a poor fit for the market. Now, you’re back to the drawing board to reframe the concept.

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The trough of disillusionment is the hype phase that makes or breaks a product. Investors need to do their due diligence to avoid amassing many buried products here in the trough.

This phase of disillusionment is characterized by:

Humility. After initial expectations failed, your team is feeling humbler about the concept.
Decreased confidence. Some team members may question the concept’s viability.
An open-minded approach. With initial failures out of the way, team members are more open to new avenues for the concept.
Reassurance. The concept owners reassuring investors, researchers, and the public that everything is fine, that your concept will get off the group.

Teams coping with the trough of disillusionment often experience challenges on three fronts: psychological, experimental, and risk management.

Psychological challenges

Among the concept team, depression sets in and humility is embraced. The development team realizes, “I am not there yet. There is more road to come.” Researchers are a strong breed, willfully positing hypotheses and allowing dreams to get tested against the world. Where some would like to linger in dreams and possibility spaces, researchers allow reality to have its way with the dream. Researchers are great to have aboard during this phase.

During this time, concept managers face a different scenario. A manager makes a promise to deliver a product and takes responsibility for that promise. Your reputation, and your team’s, rests on this promise. In this phase, managers require a bit of a performance while they approach bumpy waters and tell everybody—researchers, investors, customers—that their team is doing what they can to make the product happen. Managers must:

Speak strongly for a product or idea
Give others the confidence to support the idea
Walk through product-testing keeping face no matter the results

For everyone involved, humility is a must. After all the excitement around imagining a new product, talk does not make a product. If a product were to live on talk alone, it would exist buzzing only on the peak of inflated expectations. If a product is to be actualized, it must go through this phase of disillusionment. Hard work and repeated trials and errors create a product. All hype must get tested against actual tests. Humility accepts A as A.

Experimental challenges

An idea really gets to see what it is worth when it is ground beneath the mill.

Traditionally, R&D is the place for testing. For example, a machine learning project receives one million dollars in funding. A few qualified engineers are brought together. After four months of trials and tribulations, the project falls flat and must be abandoned because it did not have the datasets required to create the feature that was promised.

The idea may have been a good one, but the data to support creating the feature did not exist. This product feature fails or is delayed—this might be one iteration in the disillusionment trough. Now the team must reassess if it is possible to get the data necessary to create the feature, make the data to create the feature, or redesign the feature to suit the data they do have. If it’s none of these, it might be time to shelve the project and start another.

In experimentation, especially in its beginning stages, expectations tend to be totally, completely shattered. A team’s confidence to reach the goal can fall from 100% to 0% and the goal disappears, impossible to reach. More mature projects, both in time, resources, and experience, won’t see such sways in the team’s confidence, and confidence levels can oscillate at a steady rate.

The feeling here is not unlike the big swings seen in recent college grads. Many have only had schooling that builds and builds inflated expectations, then they go to a company and they themselves enter the trough of disillusionment.

The confidence levels of teams are affected during this period, but it does not necessarily reflect the actual success of the product itself. It is possible that confidence levels fall flat, but the product is making good progress and forming into something usable. It is possible confidence levels are incredibly high, but the team is totally ignorant of what is happening (that’d be a bad team) and the product fails. It is possible that confidence transcends, and confidence is placed in the ability to do research itself. This kind of confidence is the kind that can make good of any situation. Here, no product fails, the goals transform.

Risk management challenges

That wonderful dance between ideation and testing is where investment is needed, and investment gets burned. Reputations are made or lost. If the team loses a battle, trust is lost and an L goes on the track record.

In the era of coding, the depths at which the trough goes can be decreased if there is code already written to prove the concept.

“Code wins arguments.”

The gap between people who know code and people who don’t know code invites an area of dishonesty. To the non-coder, the code looks like magic, and it is all the same. To the coders of the world, there is good code, and bad code. There is code that is novel and research-based, like producing a unique Machine Learning model, and there is code that gets a job done, like having all the elements of a functioning iOS or Android app.

Potential for enlightenment

Lots can be dreamed. Lots can be promised. Someone can say they will rid the world of hunger and poverty. If that is all the project has to go on—hope—the disillusionment trough starts to look a little bigger. If there is code, if there is data, the trough decreases. If the claim is that wild, the project should never reach the trough in the first place. The disillusionment trough grows in proportion to the size of the claim.

Hard work with real, data-driven results might prove your concept enough. If you make it beyond the disillusionment, you will begin to be rewarded in the Slope of Enlightenment.

The Gartner Hype Cycle

Explore every phase of hype:

Additional resources

For more on product development and innovation, check out these resources:

The Plateau of Productivity: All Aboard

Jonathan Johnson — Fri, 22 May 2020 00:00:05 +0000

Here is a product. We call it Dylan. Dylan started playing music in cafes. Small audiences chipped the edges off our Dylan. Many songs were written. Minor tweaks were made to lines of stanzas. After lots of R&D, and a first couple years of barely breaking even on an album, Dylan started to get widely adopted. It became a national sensation. Suddenly, there are several Dylan knockoffs. There are imitators, both good and bad, identified by their saying, “I was inspired by Dylan.”

Imitators are everywhere. They’re knock-off brands, not so much of Dylan, but of an idea, freedom and humanism. If someone wished not to be an imitator, they’d need to redefine Humanist ideals. Bob Dylan hit the Plateau of Productivity in the late 1960s, and now we see participants in the humanist aesthetic, practicing in the tradition for 60 years.

What is the plateau of productivity?

The Gartner Hype Cycle identifies five key phases during a new technology’s development. When a product reaches The Plateau of Productivity, the fifth and final phase, the product:

Starts to go mainstream, seeing widespread adoption
Has a clear value proposition
Begins to reap its rewards

(Source)

A viable product garners attention. By now, our product has been ideated, it’s gone through its honeymoon phase, it has been tried and tested, and it has even been adopted by early users, has a steady team of workers, investors, and has grown into its own. Now, the product gets to mature.

Mainstream, widespread adoption

In 2020, Facebook and Uber have reached this phase of the hype cycle. Before, however, they both spend years in a race to a finish line with all-night hack-a-thons and unorthodox business moves.

Since the early 2010s, Uber has been discounting fares, fighting to establish market dominance against other ride-share start-ups. Uber continues to challenge industry norms. Facebook’s slogan famously called for workers to move fast and break things. More recently, Zuckerberg has repeatedly faced U.S. and European authorities, where both parties had their hands in the air, trying to figure out what the role of Facebook has been and what it should be going forward.

It was all very new.

Today, both services have been adopted globally, and have earned their spot in the marketplace. They’re no longer rebels. Their role is no longer to break things. They are supposed to be responsible members of the community.

Capital gains indicate value

A company who has made it this far should start to see their hard work pay off. (If it’s not, you’re likely still in the Trough of Disillusionment or the Slope of Enlightenment.)

The fruits of their efforts should be measured in:

Market viability. When the company makes the statement, “I offer this value,” and the public says, “Yes you do. I will pay for it.” There is viability. If the public denies it, there is likely more work to do.
Mainstream adoption. The value in mainstream adoption comes in the form of the Network Effect.
Employee retention. Employees stick around longer.
Company ratings. Approval ratings should be increasing.
Income. Accountants should be happy, seeing their faithful, guiding star return positive numbers. The company’s bottom-line should indicate that the product has reached maturity.

Challenges on the plateau of productivity

Of course, all this productivity is not without its challenges. Around this time, companies often see two significant challenges.

Changes in management

Achieving the plateau of productivity often sees changes in management. A mature company can’t go swinging fists with a 19-year-old’s mindset. The baton gets passed from a serial entrepreneur to a seasoned CEO. Steve Jobs was ousted at an early age so Apple could mature under a new CEO: the former president of PepsiCo.

Travis Kalanick, founder of Uber, resigned as CEO after years of more-or-less careless behavior. Facebook founder, Zuckerberg couldn’t face the public with sincerity in his first years of Facebook, appearing somewhat disillusioned. (Also, he was only 20 years old.) But today he faces public attention with greater maturity. As the company matured, so did Mark Zuckerberg.

This period invites revisioning the company’s role. Whether management actually changes is almost beside the point: this period marks a switch in behaviors from the rebellious outsider to the respected community member.

Scaling the product

A mainstream product needs to scale. When a service goes from 10,000 users to 1,000,000 users, logistics can get in the way.

Fortunately, scaling computational resources isn’t too difficult these days. The same team that could provision the resources for thousands of users can usually handle provisioning the resources for a million users. Even 10 million users isn’t too far-fetched: advancements in cloud computing providers and Kubernetes technology allows people to scale automatically.

Instead, the real challenge in scaling lies in creating greater nuance in the offered product. One million people is a lot more than ten thousand people, and like Mr. Lydgate said:

“You can please some of the people all of the time, you can please all of the people some of the time, but you can’t please all of the people all of the time”.

The product might appear simple to the user, perhaps keeping options to five menu items. But those five items are going to be different. McDonald’s is still McDonald’s (of course!), but when its patrons’ tastes change across the world. There’s a spam burger in Hawaii, and there’s a mashed potato burger in China.

When the new product goes mainstream, suddenly, everyone has an appetite. You can’t please all the people all the time…but you can try.

More features are added. More services are created. Services are created to cater to each individual’s needs. Companies can harness machine learning for this: when the user meets a set of parameters, X, a specific service, y, can be provided. (If this were an orchestral composition, we’d call a machine learning service, Variations on Y.)

When a company fails to cater to a particular taste, imitations arrive. Other founders see an opportunity to pounce on an idea that has already gone through the R&D phase and hasn’t saturated the market. They develop the niche feature and serve it to the audience. They capitalize on the trend.

How companies respond to these challenges can further cement their position on the productivity plateau. All those wheels that were once spinning in place have found their grip. Whether it is a founder, early investors, researchers, marketers, or early adopters, everyone at this stage should feel some sort of accomplishment. They’ve let go of their child’s hand and watch it take its own shape in the world. Finally, the product is no longer becoming, it has become.

The Gartner Hype Cycle

Explore every phase of hype:

Additional resources

For more on product development and innovation, check out these resources:

The Innovation Trigger: An Idea Begins

Jonathan Johnson — Fri, 22 May 2020 00:00:01 +0000

And it begins. A spark. A possibility like no other. Only in pieces. Fragments. Like watching the neurons of your brain fire, illuminate, connect. You collect all the things you think you’ve ever known. You predict what can be based on what is, what isn’t, and what was.

It’s time to build.

This is the innovation trigger—the idea that could propel a new product, a new approach. Let’s take a look at this phase of product development.

What is the innovation trigger?

The innovation trigger is the first of five phases that comprise the Gartner Hype Cycle. A leading IT analyst and research group, Gartner tracks and visualizes the perceived value of a new technology innovation or trend, helping companies determine whether (and when) to embrace or bypass a given product.

(Source)

As the first stage in the development of any technology, the innovation trigger is a period with a lot of shoulds: a widget that should be, a service that should help, an idea that should exist. It is a period with not a lot more to go on than people’s dreams. The technology often lacks a product or market viability.

This phase is characterized by:

An idea
Lack of product or market viability
Explanations about how great the product could be
Excitement
Creativity

The innovator’s tale

Ideas are easy to come by. They pop into the mind as a response to reading a news article, sitting in a classroom, conversing with another human being. There exists an idea every time one speaks. They think, “I have an idea how to respond to that statement.”

Good ideas, however, are hard to come by—and even harder to speak and bring to life. The intention of speaking is often to be understood, and good ideas are not often simple to understand. Good ideas can require a lot more explanation than any normal statement. “It is a beautiful day outside” is a much simpler idea than “People are all designers of language”. If the intention is to be understood, then the speaker will find more success with the first statement than the second.

If the intention was to be understood, no one would become an innovator.

Innovators, who wish to have good ideas and who wish to be understood, suffer. They have options to make the process easier, but they still face a dilemma. If they wish to be understood, they can surround themselves with people who already understand. But, nothing would be innovated if everyone already understood. The innovator is demoted to a parrot.

To the innovator, speaking to a room full of people who understand is no different than existing only in his own mind. Thus, there’s a degree to understanding. They can speak to people who understand 90% and the innovator will take them the rest of the 10%. They can speak to people who understand 30% and try to get the person the other 70%. Adjustments to direct communication or symbolic communication are made when speaking to each crowd.

To help be understood, the innovator can utilize the age-old art of rhetoric and argumentation. The innovator needs to build a case to support his idea. He can gather evidence. Evidence helps the innovator have other things speak for him. Suddenly, the innovator appeals to logic, and logic allows for new ideas to be good, right, ideas.

Eventually, after battle-testing the idea long enough against research and a bewildered audience, an innovator can learn what tactics to employ to communicate their idea.

“It’s not a joke until an audience laughs.” – Dave Attell

In its first stages, a product cannot exist on its own. It needs people behind it, who want to make it and who want to use it. Innovating is a difficult job. Few embrace its challenges. The marketplace of ideas is vast and plenty. There are few pockets worth anything.

Building an innovation team

A new technology must have a good team. New ideas need to propagate. And, with no product or market viability, the technology only exists through a public consciousness via word-of-mouth.

In Bluebeard, Kurt Vonnegut said people generally do not like new ideas, and a special team of three is needed. He said:

Most people cannot open their minds to new ideas unless a mind-opening team with a peculiar membership goes to work on them. The team must consist of three sorts of specialists, otherwise, the revolution, whether in politics or the arts or the sciences or whatever, is sure to fail:

The rarest of these specialists is an authentic genius.

The second sort of specialist is a lot easier to find: a highly intelligent citizen in good standing in his or her community, who understands and admires fresh ideas of the genius, and testifies that the genius is far from mad.

The third sort of specialist is a person who can explain anything, no matter how complicated, to the satisfaction of most people.

New technologies go about gathering these innovation teams.

The genius is someone, or several people, who diligently puts all the pieces together. Part of what makes them a genius is their mystery, so I do little for him with explanation.

The intelligent citizens, now, are the members of the community who have built-in reputation. They are often older and have a reputation among peers for the work they have done, or their outstanding contributions to the community. These people are your businessmen, community leaders, religious council, scholars. There exist people with reputations everywhere.

Finally, the third member of the team is the one who makes the complicated simple—a translator of sorts. This is largely the role of a marketing or advertising company, who can take a large, genius idea and boil it down to a three-word slogan or tagline: Just do it. Think different. Or we can look at company mission statements:

“Uber’s mission is to bring transportation—for everyone, everywhere.”
“SpaceX designs, manufactures and launches advanced rockets and spacecraft.”

Product viability

Products in this stage are unrefined. They look like wireframes. They are short, code mock-ups in a Jupyter notebook. They might even get to have a simple product set up.

The good technologies are usually promoted by individuals just as unrefined. If the promoter is refined, with nice shoes, smile, and a handshake, then there’s reason to be skeptical about why there is so much patina, and so little product.

This phase has promoters pointing at pieces of paper saying, “Once people use it, it should work like this.” They can create business plans that say, “The business should look like this.” They can make financial statements that say, “The numbers should look like this.”

Products in the phase of the Innovation Trigger exist on shoulds. If there are enough people behind this should, perhaps it can grow beyond its infancy and graduate into adolescence. The product has a long way to go before it stands tall amongst the crowd as its own. The idea’s next stop, if it can make it? The Peak of Inflated Expectations.

The Gartner Hype Cycle

Explore every phase of hype:

Additional resources

For more on product development and innovation, browse our many articles or check out these resources:

Introduction to the Gartner Hype Cycle

Muhammad Raza — Tue, 05 May 2020 09:51:46 +0000

The Gartner Hype Cycle is a graphical representation of the perceived value of a technology trend or innovation—and its relative market promotion. The cycle can help you understand how the perceived value of a given technology evolves over the course of its maturity lifecycle.

The maturity lifecycle accounts for several phrases: the initial (over-)enthusiasm of the industry when the technology is introduced, followed by a phase of mass adoption when we begin to evaluate the promised value, and, later, a maturity phase when the technology is improved. Over the course of this lifecycle, the Gartner Hype Cycle speculates on the potential growth trajectory and value that can be obtained by exploiting the technology in its current and next maturity phase.

This snapshot helps organizations answer a key question every time a new technology innovation presents value or disillusionment: should you invest in the technology? In this article, we’ll discuss how the Gartner Hype Cycle works and how to interpret the value of a technology innovation with this graphical representation:

Source

How do hype cycles work?

According to Gartner’s research methodology, a technology innovation goes through five phases of its maturity cycle. Gartner uses several market indicators to establish a true representation of the expected value and maturity phase of a technology innovation. These phases include:

Innovation Trigger

This is the initial phase of a technology breakthrough. It may be a product, process, concept, trend, or idea that attracts media attention and is considered as a legitimate breakthrough. Early adopters investigate the technology, which is characterized by its novelty, high price, and expectation to undergo high customization over the course of its maturity lifecycle. The technology is accessible only to limited entities such as research labs and startup firms.

Media attention and popularity of the technology breakthrough cause a steep rise in its expected value until a peak is reached. Lack of mass adoption means that the technology’s commercial viability is unproven but also not yet contested against the rising expectations.

Examples of the Innovation Trigger:

Flying autonomous vehicles
Biotechnology such as artificial tissue
4D printing

Peak of Inflated Expectations

At this phase, the technology is widely publicized. Vendors use it as a buzzword in marketing campaigns and investors and customers see it as a hotspot. This phase often sees a surge of vendors, flooding the market with complementary and competing products.

Many organizations pioneer adoption in pursuit of the early mover advantage, while some practice caution over the limited failure stories gradually surfacing in the industry. Early adopters typically risk the challenges associated with the technology that may take years to reach the desired maturity level. At the height of this peak, some startups pioneering the technology breakthrough may see high-profile acquisitions by large enterprises.

Examples of the Peak of Inflated Expectations:

Deep neural networks
Digital twin
Carbon nanotube

Trough of Disillusionment

Soon after a technology innovation reaches the Peak of Inflated Expectations, we see activity beyond early adopters. Frequently, some negative press surfaces. Organizations are now looking for meaningful value beyond initial success stories and industry hype.

As the technology fails to live up to high expectations, the growth in adoption is slowed or delayed. Vendors consolidate their offerings as experimentations fail and variations fail to gain sufficient market traction. Successful vendors reach Series B or C funding rounds with improvements validated by early adopters. The technology evolves into its next generation with only a small percentage (up to 5%) of the audience adopting it.

Toward the end of this phase, the industry questions the transformational potential of the technology. Media outlets frequently highlight the challenges, failure, and backlash facing early suppliers and adopters of the technology.

Examples of the Trough of Disillusionment:

Blockchain
Smart Fabrics
Augmented Reality
Computer Vision

Slope of Enlightenment

The technology innovation has now undergone enough success and failure stories, updates, and improvements for the industry to understand an optimal path of growth trajectory. Accordingly, second and third generations of the innovation emerge, presenting proven solutions to specific problems and industrial use cases. As a result, adoption rises closer to 20% of the audience as the technology reaches its next maturity phase.

Consulting companies are able to provide methodologies and frameworks to assist new adopters. The resulting case studies and adoption statistics are reliable, and the perceived value is now closer to reality. Toward the end of this phase, most conservative adopters and industry laggards are yet to incorporate the technology innovation to their adoption agenda in the near future.

Examples of the Slope of Enlightenment:

Predictive analytics
IT Risk Management solutions
Cloud services for government

Plateau of Productivity

This is the phase of mainstream adoption (30% or more of the audience). Media outlets and technology experts regularly publish relevant news, best practices, and insights on future updates. The technology is readily produced and available as an off-the-shelf solution. A growing community builds around the technology and an ecosystem of relevant products and services emerges. Successful adoption stories across a variety of industry verticals are observed. Successful vendors reach closer to acquisitions and IPOs.

Examples of the Plateau of Productivity:

Cloud office suites
GPU acceleration
Speech recognition

Different technology, different expectations change

In the Gartner Hype Cycle, each phase represents a specific magnitude of expectations. These maturity phases progress differently for every technology innovation:

Some technologies stay at one phase longer than others, which contributes to their expected value in the industry accordingly.
Some technology innovations follow through the maturity lifecycle faster than others, eventually reaching the final state of Plateau of Productivity. This is where the industry has adopted the said technology at scale and the perceived value translates into its real value.
Not all technology trends follow the entire maturity lifecycle. Some fail to live up to their hype, disappearing from the hype cycle altogether. This behavior suggests that the real value was evaluated early during their maturity lifecycle and the promised rewards were deemed unrealistic or unfeasible.
Certain innovations tend to transition back and forth between the maturity phases. Reasons include the evolution of the technology itself, where it presents new value promises as it evolves.
The scope of evaluation changes over time. As the technology industry evolves, its appetite for risk and circumstances change. The values are perceived accordingly, and technology innovations don’t maintain a consistent magnitude of expected value over prolonged time periods.

Steering towards the Plateau of Productivity

In addition to the opportunities and risks, every technology breakthrough is accompanied by a myriad of hype. At every phase of the hype cycle, certain decisions can help effectively adopt the technology when the time is right for your specific use case and business requirements. The following policies can help better advance the adoption efforts in the right direction:

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Additional resources

To learn more from Gartner, the technology research group, see our Complete Guide to 2020 Gartner Events.