Avoiding innovation errors through jobs-to-be-done analysis

The lean startup movement was developed to address an issue that bedeviled many entrepreneurs: how to introduce something new without blowing all your capital and time on the wrong offering. The premise is that someone has a vision for a new thing, and needs to iteratively test that vision (“fail fast”) to find product-market fit. It’s been a success as an innovation theory, and has penetrated the corporate world as well.

In a recent post, Mike Boysen takes issue with the fail fast approach. He argues that better understanding of customers’ jobs-to-be-done (i.e. what someone is trying to get done, regardless of solutions are used) at the front-end is superior to guessing continuously about whether something will be adopted by the market. To quote:

How many hypotheses does it take until you get it right? Is there any guarantee that you started in the right Universe? Can you quantify the value of your idea?

How many times does it take to win the lottery?

Mike advocates for organizations to invest more time at the front end understanding their customers’ jobs-to-be-done rather than iteratively guessing. I agree with him in principle. However, in my work with enterprises, I know that such an approach is a long way off as a standard course of action. There’s the Ideal vs. the Reality:

JTBD analysis - innovation ideal vs reality

 

The top process – Ideal – shows the right point to understand your target market’s jobs-to-be-done. It’s similar to what Strategyn’s Tony Ulwick outlines for outcome-driven innovation. In the Ideal flow, proper analysis has uncovered opportunities for underserved jobs-to-be-done. You then ideate ways to address the underserved outcomes. Finally, a develop-test-learn approach is valuable for identifying an optimal way to deliver the product or service.

However, here’s the Reality: most companies aren’t doing that. They don’t invest time in ongoing research to understand the jobs-to-be-done. Instead, ideas are generated in multiple ways. The bottom flow marked Reality highlights a process with more structure than most organizations actually have. Whether an organization follows all processes or not, the key is this: ideas are being generated continuously from a number of courses divorced from deep knowledge of jobs-to-be-done.

Inside-out analysis

In my experience working with large organizations, I’ve noticed that ideas tend to go through what I call “inside-out” analysis. Ideas are evaluated first on criteria that reflect the company’s own internal concerns. What’s important to us inside these four walls? Examples of such criteria:

  • Fits current plans?
  • Feasible with current assets?
  • Addresses key company goal?
  • Financials pencil out?
  • Leverages core competencies?

For operational, low level ideas inside-out analysis can work. Most of the decision parameters are knowable and the impact of a poor decision can be reversed. But as the scope of the idea increases, it’s insufficient to rely on inside-out analysis.

False positives, false negatives

Starting with the organization’s own needs first leads to two types of errors:

  • False positive: the idea matches the internal needs of the organization, with flying colors. That creates a too-quick mindset of ‘yes’ without understanding the customer perspective. This opens the door for bad ideas to be greenlighted.
  • False negative: the idea falls short on the internal criteria, or even more likely, on someone’s personal agenda. It never gets a fair hearing in terms of whether the market would value it. The idea is rejected prematurely.

In both cases, the lack of perspective about the idea’s intended beneficiaries leads to innovation errors. False positives are part of a generally rosy view about innovation. It’s good to try things out, it’s how we find our way forward. But it isn’t necessarily an objective of companies to spend money in such a pursuit. Mitigating the risk of investing limited resources in the wrong ideas is important.

In the realm of corporate innovation, false negatives are the bigger sin. They are the missed opportunities. The cases where someone actually had a bead on the future, but was snuffed out by entrenched executives, schlerotic processes or heavy-handed evaluations. Kodak, a legendary company sunk by the digital revolution, actually invented the digital camera in the 1970s. As the inventor, Steven Sasson, related to the New York Times:

“My prototype was big as a toaster, but the technical people loved it,” Mr. Sasson said. “But it was filmless photography, so management’s reaction was, ‘that’s cute — but don’t tell anyone about it.’ ”

It’s debatable whether the world was ready for digital photography at the time, as there was not yet much in the way of supporting infrastructure. But Kodak’s inside-out analysis focused on its effect on their core film business. And thus a promising idea was killed.

Start with outside-in analysis

Thus organizations find themselves with a gap in the innovation process. In the ideal world, rigor is brought to understanding the jobs-to-be-done opportunities at the front-end. In reality, much of innovation is generated without analysis of customers’ jobs beforehand. People will always continue to propose and to try out ideas on their own. Unfortunately, the easiest, most available basis of understanding the idea’s potential starts with an inside-out analysis. The gap falls between those few companies that invest in understanding customers’ jobs-to-be-done, and the majority who go right to inside-out analysis.

What’s needed is a way to bring the customers’ perspective into the process much earlier. Get that outside-in look quickly.

Three jobs-to-be-done tests

In my work with large organizations, I have been advising a switch in the process of evaluating ideas. The initial assessment of an idea should be outside-in focused. Specifically, there are three tests that any idea beyond the internal incremental level should pass:

jobs-to-be-done three tests

 

Each of the tests examines a critical part of the decision chain for customers.

Targets real job of enough people

The first test is actually two tests:

  1. Do people actually have the job-to-be-done that the idea intends to address?
  2. Are there enough of these people?

This is the simplest, most basic test. Most ideas should pass this, but not all. As written here previously, the Color app was developed to allow anyone – strangers, friends – within a short range to share pictures taken at a location. While a novel application of the Social Local Mobile (SoLoMo) trends, Color actually didn’t address a job-to-be-done of enough people.

A lot better than current solution

Assuming a real job-to-be-done, consideration must next be given to the incumbent solution used by the target customers. On what points does the proposed idea better satisfy the job-to-be-done than what is being done today? This should be a clear analysis. The improvement doesn’t have to be purely functional. It may better satisfy emotional needs. The key is that there is a clear understanding of how the proposed idea is better.

And not just a little better. It needs to be materially better to overcome people’s natural conservatism. Nobel Laureate Daniel Kahneman discusses two factors that drive this conservatism in his book, Thinking, Fast and Slow:

  • Endowment effect: We overvalue something we have currently over something we could get. Think of that old saying, “a bird in the hand is worth two in the bush”.
  • Uncertainty effect: Our bias shifts toward loss aversion when we consider how certain the touted benefits of something new are. The chance that something doesn’t live up to its potential looms larger in our psyche, and our aversion to loss causes to overweight the probability that something won’t live up to its potential.

In innovation, the rule-of-thumb that something needs to be ten times better than what it would replace reflects our inherent conservatism. I’ve argued that the problem with bitcoin is that it fails to substantially improve our current solutions to payments: government-issued currency.

Value exceeds cost to beneficiary

The final test is the most challenging. It requires you to walk in the shoes of your intended beneficiaries (e.g. customers). It’s an analysis of marginal benefits and costs:

Value of improvement over current solution > Incremental costs of adopting your new idea

Not the costs of the company to provide the idea, but those that are borne by the customer. These costs include monetary, learning processes, connections to other solutions, loss of existing data, etc. It’s a holistic look at tangible and intangible costs. Which admittedly, is the hardest analysis to do.

An example where the incremental costs didn’t cover the improvements is of a tire that Michelin introduced in the 1990s. The tire had a sensor and could run for 125 miles after being punctured. A sensor in the car would let the driver know about the issue. But for drivers, a daunting issue emerged: how do you get those tires fixed/replaced? They required special equipment that garages didn’t have and weren’t going to purchase. The costs of these superior tires did not outweigh the costs of not being able to get them fixed/replaced.

Recognize your points of uncertainty

While I present the three jobs-to-be-done tests as a sequential flow of yes/no decisions, in reality they are better utilized as measures of uncertainty. Think of them as gauges:

JTBD tests - certainty meters

Treat innovation as a learning activity. Develop an understanding for what’s needed to get to ‘yes’ for each of the tests. This approach is consistent with the lean startup philosophy. It provides guidance to the development of a promising idea.

Mike Boysen makes the fundamental point about understanding customers’ jobs-to-be-done to drive innovation. Use these three tests for those times when you cannot invest the time/resources at the front end to understand the opportunities.

I’m @bhc3 on Twitter.

Consumer adoption of Bitcoin | A jobs-to-be-done analysis

Venture capitalist Marc Andreessen recently did one of his tweetstorms on the topic of Bitcoin, a technology he avidly supports. In 25 tweets, he talked about criticisms people have of Bitcoin. Including this one (#18) about “use cases”:

Let’s acknowledge this: When you’re talking currency and payment systems, the use cases and relevant users are enormous. The
whole planet, really, and all manner of transactions. Lots of places where Bitcoin could theoretically make an impact. In this post, I wanted to think through the consumer payment market, one of the bigger targets there is. According to the Federal Reserve, a U.S. consumer makes around 69 payments per month (pdf). Fertile ground for exploiting underserved jobs-to-be-done.

A powerful way to analyze any idea is to apply jobs-to-be-done analysis. Specifically, apply three jobs-to-be-done tests:

  1. Does the idea target an actual job-to-be-done that enough people have?
  2. Is the idea a meaningful improvement over the current way people fulfill their job-to-be-done?
  3. Does the value of the idea to customers exceed the cost of the idea to them?

In the above linked post about the three tests, I note that the output of the tests are really degrees of certainty about an idea. You can think of it as meters:

JTBD degrees of certainty

The more uncertain you are, the higher the adoption risk of the idea by your intended beneficiaries.

For this analysis, we’ll target a specific set of possible beneficiaries:

Bitcoin will become a frequently used currency for U.S. and European consumers, displacing dollars, euros and pounds.

Ok, on to the adoption analysis. Each test includes an assessment of its certainty.

#1: Targets and actual job-to-be-done of enough people

We long ago left barter behind as a primary basis for goods and services exchange. Currency offered many advantages: a way to exchange with you now, even if I don’t have a good you want; store of value of that outlasts many goods; ability to build up a supply of currency for larger purchases; immediate trust because the currency is known, as opposed to the risk of a receiving a deficient product in trade.

Currency won out over barter for many reasons. And to that end, Bitcoin addresses an actual job-to-be-done: a measure of value that can be exchanged for goods and services.

The level of certainty for this test:

Targets actual job-to-be-done
of enough people
Certainty meter- targets real JTBD enough people

 #2: Better than current solution

Any new thing has to provide better outcomes than the incumbent solution. And not just a little better. Studies show people will undervalue the benefits of a new offering, and overvalue the benefits of an existing solution. This reflects the varying degrees of the Possibility Effect and the Uncertainty Effect people have. Providing a strong improvement in outcomes is needed to overcome the inertia of the Early and Late Majorities.

Put yourself into the shoes of a typical consumer:

  • I need to pay for groceries
  • I need to pay for my Amazon purchases
  • I need to pay for school tuition
  • I need to pay for gas
  • I need to pay for rent

All these activities happen today with dollars, euros, pounds and so on. In what way does paying by Bitcoin provide better outcomes for my payment needs than the currency I use today? Among the Bitcoin improvements I’ve seen described:

Payment cannot be repudiated: The blockchain technology locks in the transmittal of the payment. There’s a full record of payment offered, payment accepted. Which is great as a record for the transaction. Except repudiation isn’t a material issue for consumers for today. They by and large don’t feel pain from it.

No centralized government control over the currency: Bitcoin is a distributed currency, with no central authority overseeing and manipulating it. The implied value is that issues like devaluation, inflation and governments tracking your spending are finally put to rest.

But stop and think about that. Who cares about these issues? Go find 10 neighbors. Ask them their level of concern that the money in their wallet is managed by a central authority. Find out what they think about the traceability of their spending. Many payment services companies actually offer traceability as a feature, not a bug (e.g. Mint, Yodlee, American Express, etc.). I haven’t heard much outcry about payment traceability among the general public.

Reduced identity theft fraud: Credit card numbers can be stolen and used by thieves. Marc Andreessen asserts that Bitcoin greatly reduces this risk. And I suspect he’s right, as far as we understand the risks today. But already, creative thieves are figuring out ways to steal Bitcoins. Innovation at its finest.

But getting better about reducing identity theft is a clear opportunity for better outcomes. Credit card companies have become quite advanced with this via big data algorithms, which spot out-of-norm transactions and flag them. Companies are also good at covering the losses resulting from payment identity theft.

Because Bitcoin is still experiencing losses due to fraud, it’s not clear in consumers’ minds that it’s less risky than current currency and payment methods.

The level of certainty for this test:

Meaningful improvement over
the current way people fulfill
the job-to-be-done
Certainty meter- meaningful improvement over current

#3: Value to consumers exceeds costs of new idea

In this test, you’re asked to look holistically at the costs of a new idea. Monetary costs, yes. But also other costs, such as:

  • Connecting the new solution to existing infrastructure
  • Loss of features you enjoy in current solution
  • Giving up the uncertainty of the current solution
  • New unwanted behaviors

Given the low (non-existent?) value of Bitcoin over current currencies, pretty much any cost will cause a high level of uncertainty for this test.

And Bitcoin has costs. Its current volatility makes it tough to rely on a consistent store of value. You receive $10,000 worth of Bitcoin today, what will that be worth in a month? There’s a learning curve for usage. You need to know how to operate a Bitcoin account, and retrain yourself to think in terms of Bitcoin values (like when you travel abroad and have to mentally calculate the local currency price into your home currency to understand what something really costs).

To the extent that economic cycles will inevitably continue, you need to get used to no central authority intervening to help stabilize things. It’s not clear what a Bitcoin-dominated world would look like in terms of economic stability. Likely, though, this uncertainty doesn’t weigh into consumers’ calculus of costs.

The level of certainty for this test:

Value to consumers exceeds
the cost of the new solution
Certainty meter- value exceeds costs

Wrapping up

It’s hard to see how Bitcoin becomes a regular currency used by consumers. It doesn’t offer sufficient improvement over incumbent currencies and the cost is hard to overcome with any potential value. One possibility: if the lower fraud rates associated with Bitcoin are reliable, perhaps merchants will offer discounts for use of them. That could spur some people to switch to Bitcoins.

The bigger story of Bitcoin is actually the blockchain technology. The ability to ascertain easily, without an intermediary, that a transaction (e.g. document signing, receipt of something, etc.) has occurred seems to offer tangible value over current solutions. That may be Bitcoin’s true legacy.

I’m @bhc3 on Twitter, and I’m a Senior Consultant with HYPE Innovation.

Bring customers into the idea review process

Say you’ve got some internal ideas at your company. Who takes a look at them? Assesses them to determine next steps for each idea? Figures out the value and difference the ideas can make?

How about your own customers?

I talk a lot about jobs-to-be-done here, and getting a firm grip on those to understand where innovation and product enhancement opportunities lie. But sometimes that’s not realistic. Ideas come from many sources, and more likely than not, fail to reflect hard analysis of jobs-to-be-done. But customer feedback is valuable. Any idea which can touch on customers’ experience – products, services, support, pricing, deliver, knowledge – can benefit from their perspectives.

The concept sounds right, yes? But it’s also something that’s somewhat scary. I know this because I asked innovation executives for a number of large companies what they thought of it. There was hesitancy to the concept of bringing customers into what is generally an internal – and often murky at best – process of evaluating ideas.

In my post, What if customers evaluated your company’s ideas?, five areas are examined to de-scarify this idea:

  • Differentiating from focus groups
  • Profile of right customers to involve
  • Type of ideas
  • Ways to engage customers in the evaluation process
  • What criteria make sense?

Give it a read, and see if this is something you’d consider.

I’m @bhc3 on Twitter, and I’m a Senior Consultant with HYPE Innovation.

Gmail offers surprising innovation lessons for the Fortune 500

If you’re familiar with the story of Gmail, you know – for a fact – that it was a 20% time employee project by Paul Buchheit. A little bottom-up experimentation that grew into something big.

Surprise! That story is wrong.

It was a desire by Google, the company, to offer its own email. From Harry McCracken’s great piece How Gmail Happened: The Inside Story of its Launch 10 Years Ago:

Gmail is often given as a shining example of the fruits of Google’s 20 percent time, its legendary policy of allowing engineers to divvy off part of their work hours for personal projects. Paul Buchheit, Gmail’s creator, disabused me of this notion. From the very beginning, “it was an official charge,” he says. “I was supposed to build an email thing.”

Gmail’s creation has more in common with innovation inside large enterprises than it does with the start-up world. Read on if you recognize these:

  1. Job-to-be-done thinking
  2. Reports of the death of company innovation are greatly exaggerated
  3. Corporate antibodies are everywhere
  4. Senior executive support
  5. Big Innovation takes time

Job-to-be-done thinking

Yahoo email screenshot

Image via Variable GHZ, “Why Yahoo Mail is Still an Epic Catastrophe

Anyone remember life before Gmail? We had low storage limits. ‘OK’ search. Poor spam control. Yahoo, one of the dominant players at the time, pursued the freemium strategy that required paying for more storage and better controls. Which isn’t unheard of, mind you.

It’s just…

Think of the core job-to-be-done: When I want to update others, I want to send and receive communications. Some key job tasks that define that job include:

  • Easily send pictures to others
  • Read emails from real people and organizations that I care about
  • Find old emails when I need them
  • Expand my usage of email economically

Yahoo, Hotmail, AOL were fine as far as they went, but they each were challenged on these key job tasks. Back when I had a Yahoo email, I remember the spam being awful and it seemed impossible to control.

Google looked at the offerings in the market, and recognized an opportunity to better satisfy people’s expectations for these important job tasks. Larger size limits, stellar spam control, excellent search and ongoing improvements through Gmail Labs.

Lesson: ABI (Always Be Improving) on the customers’ jobs-to-be-done. Think of the entire job flow and determine which areas are ripe for a better service and experience. Big companies can too easily focus on executing what they have rather than thinking about customers need. 

Reports of the death of company innovation are greatly exaggerated

Image via Family Life Resources

Somewhere along the line, a narrative has emerged that pretty much every big company cannot innovate its way out of a bag. Admittedly, the increasingly rapid turnover of the S&P 500 and the fast rise and decline of companies fuels this narrative. But it’s glib to say companies just don’t do it.

Google’s 20% time is espoused as the antidote to this issue. Middle management stifling innovation? Let everyone experiment on their own. But Gmail wasn’t a 20% time project. It was actually something planned and resourced for development for the organization at large.

This is an important point. If companies set their mind to innovate in an area, people will contribute and provide fantastic ways to get there. Tony Vengrove advised on a key element for success here:  “A compelling vision statement describes what the company wants to become in the future. It not only needs to inspire but ideally it should inform the innovation agenda.”

Lesson: Innovation is not dead inside companies. It does require leadership to set a vision that employees can focus on.  

Corporate antibodies are everywhere

Google is rightly perceived as one of the most innovative companies on the planet. Given that, one might assume that the innovation wheels are well greased there. But I was struck by these quotes from McCracken’s story about the birth of Gmail:

“A lot of people thought it was a very bad idea, from both a product and a strategic standpoint,” says Buchheit of his email project. “The concern was this didn’t have anything to do with web search. Some were also concerned that this would cause other companies such as Microsoft to kill us.”

Within Google, Gmail was also regarded as a huge, improbable deal. It was in the works for nearly three years before it reached consumers; during that time, skeptical Googlers ripped into the concept on multiple grounds, from the technical to the philosophical. It’s not hard to envision an alternate universe in which the effort fell apart along the way, or at least resulted in something a whole lot less interesting.

Inquisitor vs. Corporate AntibodyIn those two quotes, you see critiques that aren’t really about specific elements of Gmail, the concept.

In Four Personality Types that Determine Innovation Success or Failure, a distinction is drawn between Inquisitors, who reflect thoughtfully on issues facing an idea, and Corporate Antibodies, who just want the idea dead. Here are hypothetical responses to Gmail by the two different personality types:

Inquisitor: “Won’t we spook people when they see ads related to the email they’re reading?”

Corporate Antibody: “Email has become a commodity. There are other products we should be building.”

Lesson: Corporate antibodies will always be with us. Recognize legitimate probing for faults versus efforts to undermine the idea in total. Spend time figuring out how to get around Corporate Antibodies, not appeasing them.

Senior Executive Support

Senior executives matter in innovation

In a land of radical transparency and holacracy, the traditional top-level support needed for initiatives is a thing of the past. Alas, we are not in that land. For the 99.9% of people who live with today’s reality, top-down support continues to be the effective way things get done.

It does put pressure on top executives then. They are held accountable by the C-suite, the Board and shareholders. Already in this post, senior executives are called on to ensure innovation moves forward in two different ways.

Set the innovation course: Leadership – be it in business, community, military – has a role in establishing the objectives for people. Indeed, set objectives and get out of the way. In Gmail’s case, Larry Page and Sergey Brin saw a future that extended beyond just search. Paul Buchheit was charged to figure out what a Google email app would look like.

Remove obstacles to innovation: We saw previously that Corporate Antibodies are alive and well. But they didn’t stop Gmail’s progress. From McCracken’s article: “Fortunately, the doubters didn’t include Google’s founders. ‘Larry [Page] and Sergey [Brin] were always supportive,’ Buchheit says. ‘A lot of other people were much less supportive.’ “

Lesson: If senior management isn’t paying attention to innovation, it’s a safe bet no one in the company is either. Employees respond to the agenda set by executives. Organic growth comes from a clear focus that involves executives and employees.

Big Innovation takes time

One of my favorite perspectives on innovation comes from Jeff Bezos. In an interview on Harvard Business Review:

ADI IGNATIUS: Jeff, you’ve said that you like to plant seeds that may take seven years to bear fruit. Doesn’t that mean you’ll lose some battles along the way to companies that have a more conventional two or three-year outlook?

JEFF BEZOS: Well, maybe so, but I think some of the things that we have undertaken I think could not be done in two to three years. And so, basically if we needed to see meaningful financial results in two to three years, some of the most meaningful things we’ve done we would never have even started. Things like Kindle, things like Amazon Web Services, Amazon Prime. The list of such things is long at Amazon.

2014 2019Note that he’s referencing Big Innovation. Concepts that are market changers. There are plenty of opportunities for small-ball innovation (or improvements). But for the really big stuff, executives need to back away from the notion that it can be done in one year.

This was seen with Gmail as well. It was in the works for three years before it was launched to consumers. Continual effort was applied to the product features, the user experience, the business model and the infrastructure to support it. During this time, the project was assailed internally, but as noted previously, senior management supported its ongoing development. Similar to the way Bezos sticks with groundbreaking projects for the long term.

Lesson: Senior management must recognize the magnitude of the innovation it seeks and commit the right time horizon, resources and support to it. This applies for small ball innovation and Big Innovation.

Google, of course is now a HUGE company, on par with the biggest in the world. Its Gmail experience provides valuable lessons for Fortune 500 firms seeking to innovate.

I’m @bhc3 on Twitter, and I’m a Senior Consultant with HYPE Innovation.

Is it innovation or just an improvement? Does it matter?

On the LinkedIn Front End of Innovation group, I saw this post:

Interesting (and heated) discussions @ Unleashing Innovation Summit in Amsterdam earlier in the month: Incremental innovation is NOT innovation – it’s just marketing. REAL innovation is breakthrough/transformational… Agree or not?

I’ve seen this debate before. Attempts to finally, once-and-for-all establish just where improvement ends and innovation begins. People end up with a Maginot Line that fails to defend the sanctity of innovation. Quick: Amazon 1-click purchasing…improvement or innovation?

Does it matter that we define innovation? I once collected a bunch of people’s definitions of innovation to celebrate the multiple ways people think about it. That was a nod to the different ways people think about it. It was divergence, not convergence.

But there are times people want a clearer line between innovation and improvement. Let’s see how some smart folks have articulated the difference.

Perspectives on defining innovation

Scott Berkun: Innovation is significant positive change. This is a high bar, and it should be. What does significant mean? I’d start with the invention of the light bulb, constitutional governments, wireless radio and maybe web browsers. Perhaps you could say significant is a 30% or more improvement in something, like the speed of an engine or the power of a battery. If you know the history of your profession you know the big positive changes people made over the last 50 years, giving you perspective on the scale of brilliance you need to have to be worthy of that word. (#)

Alan Lepofsky: Both innovation and improvement are important concepts, but unfortunately the two terms are often used interchangeably. Innovation reimagines an existing process or market, or creates a brand new one. Improvement enhances an existing process or market, but does not create disruption.  (#)

Chris AndrewsI think your point highlights something important: there’s a pretty fine line between business-as-usual product improvements and real innovation, and it’s important not to confuse the two. (#)

Jon Van Volkinburg: I don’t see innovation as something that merely creates value for a customer and/or for the provider. Expanding or adding a service, feature, or function is not innovation, and these things create value. These things are growth, novelty, and invention. They are great, necessary, and can lead to innovation if the environment and timing is right. If you want, I guess you can call it incremental innovation… but I wouldn’t, to me the term “incremental innovation” is an oxymoron. (#)

What if we actually settled this debate once and for all?

Assume for a moment that we, as a society, agree on what constitutes Innovation. Then what? What is the logical flow of events and decisions that follow such a conclusion?

The reality it that doesn’t matter what something is called ex post facto. It only matters what impact it has on the consumers of the improvation.

Innovation or improvement comic

Before seeking improvation:

  • Understand the problem you’re addressing (no easy task itself)
  • Develop a sense of the magnitude of what’s required (shave a few $1,000? develop a $1 billion market?)
  • Be prepared to follow through on the ideas generated at a level commensurate with their scale

Here, it is important to understand how you define what you’re seeking. And it doesn’t matter whether you call it an improvement or an innovation. Afterwards, after the idea has become real? Again, it doesn’t matter what anyone calls it. It’s about how well it addresses the job-to-be-done. Call it what you want.

You like to-may-to,
And I like to-mah-to…

I’m @bhc3 on Twitter, and I’m a Senior Consultant with HYPE Innovation.

 

Will customers adopt your innovation? Hope, fear and jobs-to-be-done

When will a customer decide your innovative product or service is worth adopting? It’s a question that marketers, strategists and others spend plenty of time thinking about. The factors are myriad and diverse. In this post, let’s examine two primary elements that influence both if an innovation will be adopted, and when it would happen:

  1. Decision weights assigned to probabilities
  2. Probability of job-to-be-done improvement

A quick primer on both factors follows. These factors are then mapped to the innovation adoption curve. Finally, they are used to analyze the adoption of smartwatches and DVRS.

Decision weights assigned to probabilities

Let’s start with decision weights, as that’s probably new for many of us. In his excellent book, Thinking, Fast and Slow, Nobel laureate Daniel Kahneman describes research he and a colleague did that examined the way people think about probabilities. Specifically, given different probabilities for a gain, how do people weight those probabilities?

Why?

Classic economics indicates that an outcome has a 25% probability, then 25% is the weight a rational person should assign to that outcome. If you’ve taken economics or statistics, you may recall being taught something along these lines. However, Kahneman and his colleague had anecdotally seen evidence that people didn’t act that way. So they conducted field experiments to determine how people actually incorporated probabilities into their decision making. The table below summarizes their findings:

Decision weights vs probability

The left side of the table shows that people assign greater weight to low probabilities than they should. Kahneman calls this the possibility effect. The mere fact that something could potentially happen has a disproportionate weight in decision-making. Maybe we should call this the “hope multiplier”. It’s strongest at the low end, with the effect eroding as probabilities increase. When the probability of a given outcome increases to 50% and beyond, we see the emergence of the uncertainty effect. In this case, the fact that something might not happen starts to loom larger in our psyche. This is because we are loss averse. We prefer avoiding losses to acquiring gains.

Because of loss aversion, an outcome that has an 80% probability isn’t weighted that way by people. We look at that 20% possibility that something will not happen (essentially a “loss”), and fear of that looms large. We thus discount the 80% probability to a too-low decision weight of 60.1.

Probability of job-to-be-done improvement

A job-to-be-done is something we want to accomplish. It consists of individual tasks and our expectation for each of those tasks. You rate the fulfillment of the expectations to determine how satisfied you are with a given job-to-be-done. This assessment is a cornerstone of the “job-to-be-done improvement” function:

Job-to-be-done improvement function

Dissatisfaction: How far away from customers’ expectations is the incumbent way that they fulfill a job-to-be-done? The further away, the greater the dissatisfaction. This analysis is really dependent on the relative importance of the individual job tasks.  More important tasks have greater influence on the overall level of satisfaction.

Solution improvement: How does the proposed innovation (product, service) address the entirety of the existing job? It will be replacing at least some, if not all, of the incumbent solution. What are the better ways it fulfills the different job tasks?

Cost: How much does the innovation cost? There’s the out-of-pocket expense. But there are other costs as well. Learning costs. Things you cannot do with the new solution that you currently can. The costs will be balanced against the increased satisfaction the new solution delivers.

These three elements are the basis of determining the fit with a given job-to-be-done. Because of their complexities, determining precise measures for each is challenging. But it is reasonable to assert a probability. In this case, the probability that the proposed solution will provide a superior experience to the incumbent solution.

Mapping decision weights across the innovation adoption curve

The decision weights described earlier are an average across a population. There is variance in those. The decision weights for each probability of gain in job-to-be-done will differ by adoption segment, as shown below:

Decision weights across innovation adoption curve

The green and red bars along the bottom of each segment indicate the different weights assigned to the same probabilities for each segment. For Innovators and Early Adopters, any possibility of an improvement in job-to-be-done satisfaction is overweighted significantly. At the right end, Laggards are hard-pressed to assign sufficient decision weights to anything but an absolutely certain probability of increased satisfaction.

Studies have shown that our preferences for risk-aversion and risk-seeking are at least somewhat genetically driven. My own experience also says that there can be variance in when you’re risk averse or not. It depends on the arena and your own experience in it. I believe each of us has a baseline of risk tolerance, and we vary from that baseline depending on circumstances.

Two cases in point: smartwatches and DVRs

The two factors – decision weights and probability of improved job-to-be-done satisfaction – work in tandem to determine how far the reach of a new innovation will go. Generally,

  • If the probability of job-to-be-done improvement is low, you’re playing primarily to the eternal optimists, Innovators and Early Adopters.
  • If the probability of improvement is high, reach will be farther but steps are needed to get later segments aware of the benefits, and to even alter their decision weights.

Let’s look at two innovations in the context of these factors.

Smartwatches

SmartwatchSmartwatches have a cool factor. If you think of a long-term trend of progressively smaller computing devices – mainframes, minicomputers,  desktops, laptops, mobile devices – then the emergence of smartwatches is the logical next wave. Finally, it’s Dick Tracy time.

The challenge for the current generation of smartwatches is distinguishing themselves from the incumbent solution for people, smartphones. Not regular time wristwatches. But smartphones.  How much do smartwatches improve the jobs-to-be-done currently fulfilled by smartphones?

Some key jobs-to-be-done by smartphones today:

  • Email
  • Texting
  • Calls
  • Social apps (Facebook, Twitter, etc.)
  • Navigation
  • Games
  • Many, many more

When you consider current smartphone functionality, what job tasks are under-satisfied? In a Twitter discussion about smartwatches, the most compelling proposition was that the watch makes it easier to see updates as soon as they happen. Eliminate the pain of taking your phone out of your pocket or purse. Better satisfaction of the task of knowing when, who and what for emails, texts, social updates, etc.

But improvement in this task comes at a cost. David Breger wrote that he had to stop wearing his smartwatch. Why? The updates pulled his eyes to his watch. Constantly. To the point where his conversational companions noticed, affecting their interactions. What had been an improvement came with its own cost. There are, of course, those people who bury their faces in their phones wherever they are. The smartwatch is a win for them.

If I were to ballpark the probability that a smartwatch will deliver improvement in its targeted jobs-to-be-done, I’d say it’s 20%. Still, that’s good enough for the Innovators segment. I imagine their decision weights look something like this:

Decision weights - Innovators

The mere possibility of improvement drives these early tryers-of-new-things. It explains who was behind Pebble’s successful Kickstarter campaign. But the low probability of improving the targeted jobs-to-be-done dooms the smartwatch, as currently conceived, to the left side of the adoption curve.

DVRs

DVRDigital video recorders make television viewing easier. Much easier. Back when TiVo was the primary game in town, early adopters passionately described how incredible the DVR was. It was life-changing. I recall hearing the praise back then, and I admit I rolled my eyes at these loons.

Not so these days.

DVRs have become more commonplace. With good reason. They offer a number of features which improve  various aspects of the television viewing job-to-be-done:

  • Pause a live program
  • Rewind to watch something again (your own instant replay for sports)
  • Set it and forget it scheduling
  • Easy playback of recorded shows
  • Easy recording without needing to handle separate media (VCR tape, DVD)

But there are costs. If you’ve got a big investment in VCR tapes or DVDs, you want to play those. It does cost money to purchase a DVR plan. The storage of the DVR has a ceiling. You have to learn how to set up and work with a DVR. It becomes part of the room decor. What happens if the storage drive crashes?

My estimate is that the DVR has an 80% probability of being better than incumbent solutions. Indeed, this has been recognized in the market. A recent survey estimates U.S. household adoption of DVRs at 44%. Basically, knocking on the door of the Late Majority. I imagine their decision weights look like this:

Decision weights - Late Majority

On the probability side of the ledger, they will need to experience DVRs themselves to understand its potential. For the Late Majority, this happens through experiencing an innovation through their Early Majority friends. They become aware of how much an innovation can improve their satisfaction.

On the decision weight, vendors must do the work of addressing the uncertainty that comes with the innovation. This means understanding the forces – allegiance to the incumbent solution, anxiety about the proposed solution – that must be overcome.

Two influential factors

As you consider your product or service innovation, pay attention to these two factors. The first – jobs-to-be-done – is central to getting adoption of any thing. without the proper spade work there, you will be flying blind into the market. The second factor is our human psyche, and how we harbor hope (possibility) and fear (uncertainty). Because people are geared differently, you’ll need to construct strategies (communication channels, messaging, product enhancements) that pull people toward your idea, overcoming their natural risk aversion.

I’m @bhc3 on Twitter, and I’m a Senior Consultant with HYPE Innovation.

When customers want a product roadmap, do this instead

Product roadmaps suck.Roadmap

There, I said it. <exhales>

OK, let’s explain that. Roadmaps that are real, living documents representing what you will deliver…are awesome. But that may not be the case for you; it wasn’t for me. Instead, a product roadmap was at its core a sales document for a prospect call. A lot of effort, with various people weighing in on what should show up there. Ginning up dates over the next 24-36 months for when features will be delivered. A visually lickable timeline.

And it’s defunct as soon as it’s published. Poor roadmap, it never had a chance. If anyone actually remembers what was in the roadmap months later, you’re left explaining that, “um…yeah…things changed”.

To be fair, this happens more in industries where the level of uncertainty is high. You’re assembling the future, learning as you go along and making adjustments. Industries with stability can put a roadmap out there and stick to it. But if your industry has a lot of fluctuation in its future, roadmaps are an  exercise in futility.

Given this, what’s the point of creating them? For me, a better way to handle the inevitable roadmap requests was needed. Internally for client-facing peers; and with sales prospects and current clients. I took the view that the customer’s roadmap request was essentially about these three questions:

  1. Where will your development resources be focused over the 12-36 months?
  2. Does your view of what’s needed for successful outcomes matches mine?
  3. What are the core values of your platform philosophy?

In other words, knowing that X feature would be rolled out in 12 months wasn’t really what influenced the customer. It wasn’t as if they said, “Oh, that feature will be there in a year? I’ll pay $X for your platform today and begin to use it once that feature is ready.”

I wanted to find a better way. Answer the questions the customer has while avoiding unrealistic commitments and schedules.  So I developed a different approach to requests for a roadmap. It focuses on two core elements:

  • Product themes
  • How we’ll work with the client

Themes are the future the customer is buying. Work with the client describes the ongoing interactions around product design. Both are part of the decision calculus of the customer. Should I go forward with this company or not?

Product themes

Product themes are the core areas that are the means to the outcomes customers seek. When I worked at Spigit, I developed five core themes (conceptualized in below graphic):

Themes

Themes are the broad areas in which the platform needs to excel. They are selected because they are key to satisfying high-level jobs-to-be-done. They will vary by product. An accounting app might have themes around ‘accuracy’, ‘sync with GAAP’ and ‘integration with other apps’. A supplier of chemicals might need to concern itself with ‘potency of compounds’ and ‘safety’.

Themes are where an analytical approach meets a flair for artistry. Internally, they are great for organizing future release efforts. I would actually grade the platform on the themes, using the A to F scale, to help prioritize future effort.

For customers, themes provide a peek into what makes your platform special. You’re communicating a promise for what future releases will address. Customers develop a sense of the platform today, and the platform of the future.

Past + possible features = proof

For the themes, plan on doing more than stating them. Bring them to life by talking features. Yes, this sounds like the roadmap rat-hole. But it’s a different way to do that:

Theme + features

Past features are proof that you are focused on the themes, and they illustrate how you have approached enhancing the themes for clients thus far. They connect the experience of your product today to the themes.

Possible features are a source of excitement, and proof that you’re focused on the themes in future development. They’re not supposed to be a committed list of features over the next 3 years. Rather, they provide a sense for how you’re approaching fulfillment of customers’ jobs-to-be-done. This gives you the chance to talk about some of the ideas floating around in your organization while avoiding the farce of putting dates on when (and if) they’ll be delivered. When asked, I put it to them straight: “These are several ideas we currently have for this theme. What are your thoughts on them?”

Which leads nicely into the other major point to cover…

How we’ll work with the client

In the B2B market, customers want to have direct input into the product design process. Not so much in the consumer market, where we simply stop buying something if it doesn’t satisfy us. But the dollars and reputation that can be on the line in the corporate market translate into greater interest in where the product is going.

To address this desire, communicate how you will work with your customer in the product design process. I would talk about three areas:

Customer insight in product design

Jobs-to-be-done: Ongoing learning about the different things customers seek to accomplish, what they rank as most important and their level of satisfaction with achieving those goals. This is a deeper dive into motivations, how outcomes will be measured and current pain points.

Ideas: As the most active users of your product (often more than you), customers will see opportunities for improvement.  Maintain a site for ongoing suggestions as they occur, and run targeted ideation campaigns for specific areas of development.

Design feedback: Prior to committing to production of a product, run several designs by them. The designs will emphasize different functions and looks, and customers give an early read on how they will be received.

The combination of themes and the ways you’ll work with customers answers the key questions they have. It actually goes way beyond the normal roadmap, providing philosophical underpinnings for your product.  And for the product manager, it’s something you can discuss with integrity and enjoyment.

I’m @bhc3 on Twitter.

Follow

Get every new post delivered to your Inbox.

Join 749 other followers