Tuesday, September 20, 2016

The Minimum Viable Product Balancing Act

This post was first published on LinkedIn.

One of the trickiest concepts from the Lean Startup Methodology is the Minimum Viable Product. In our experience training and coaching teams, we’ve seen lots of confusion. Part of the challenge is that the moniker “Minimum Viable Product” seems to convey diametrically opposite goals. “Minimum” indicating build as little as possible so you don’t waste time or effort. “Viable” indicating that you need to build enough to make the experiment realistic enough that customers will believe they are responding to an authentic product experience. Furthermore, “Product” indicates a level of completeness or refinement in what is presented to customers.

Eric Ries’ shorthand guidance for MVPs is to start off with what you believe is needed in the MVP. Then eliminate half the features. Then eliminate half the features again. His point is that we all tend to design in much more functionality than what is actually needed.

The guidance we give teams is to think of the MVP as the experiment vehicle. You’re building just enough to run a good experiment from which you will validate (or invalidate) your hypotheses. In most cases, you will not need a complete end-to-end product experience if your experiment only requires a partial experience to collect your customer-validated learning. It’s worth noting that the experiment itself may require several iterations before you feel you have designed the appropriate experience to test your hypotheses. Often it's while we are running the experiment that we become aware with problems in the experiment design or the MVP itself.

The other guidance we give teams is that for well-designed MVPs, customers should not have a clue that they are participating in an experiment. Once your customers are “on to you”, then your experiment results cannot be trusted because customers were no longer giving you “real” responses.

A simple landing page that asks customers to sign up for a “coming soon” product can be a valid MVP for measuring customer interest especially if that landing page is being displayed in the same channel you envision your product will eventually be sold.

On the other hand, surveys do not quality as MVPs because at best they ask customers hypothetical questions like “Would you be interested in a product with feature X?”. Answers to hypothetical questions cannot be trusted as predictive of real behavior. This is especially true for breakthrough products. As Henry Ford has been quoted to have said, “If I’d have asked my customers what they wanted, they would have told me ‘A faster horse.’”

There are tricky situations where a product will be distributed by viral propagation (like a social media app). In these cases, the MVP needs to have enough functionality to deliver enough of the value proposition such that customers will share the MVP with their friends. Even then, your MVP can consist of a very thin slice of your ultimate vision for your product as long as that thin slice supports your hypothesis. We can learn a lot from about the effectiveness of a minimal approach from the first versions of Facebook and eBay.

The first version of “The Facebook” that Mark Zuckerberg released at Harvard in 2004 only contained a single profile page for each user, a way to search for people you know, make friend requests, and send messages. There were no news feeds, no groups, no events, or even like buttons! With such a minimal feature set, Zuckerberg was able to build the service in just a few weeks.

The first version of “Auction Web” (which eventually became eBay) Pierre Omidyar released in 1995 was a simple page on his personal website that let sellers list items for auction. The code for that page only took Omidyar a weekend to write.

These minimal first versions are a far cry from the sophisticated services we use today. But their minimal approach allowed both Omidyar and Zuckerberg to quickly get their products into customers’ hands and provided the validation that they were onto something big.

Another important consideration when designing your MVP is making sure you are able to measure results. You can certainly ask your customers what they thought about the experience but when it comes to measuring behavior, nothing beats having analytics built into the MVP. Teams often will spend a lot of time thinking about features and not enough time thinking about measurement, which is essential for running an effective experiment.

Finally, some people have redefined the MVP acronym to mean “Minimum Valuable Product.” In this case, the MVP is referring to a more complete product that can support a pilot release with hundreds of customers. Minimum Valuable Products can be a valid experiment vehicle in the Lean Startup Methodology but we encourage teams not to wait for the weeks and months to achieve that threshold before they start experimenting. For most product ideas, we’ve found lean experiments can start on day one if your mindset for MVP is experiment vehicle.

In summary, the Minimum Viable Product balancing act requires you to:
  1. Minimize effort - only build what’s important
  2. Maximize learning - don’t forget to think through how you will measure results
  3. Ensure viability - your customers shouldn’t be able to tell it’s an MVP!

Jeff Zias and I are writing the book Grassroots Innovation in the Enterprise to be published early 2017.  Do you have stories to share about how you’ve used MVPs in your company?  We’d love to hear from you and share some of the best stories we gather in our book.

Friday, July 22, 2016

Experimentation Baby Steps

This post was first published on LinkedIn.

In an earlier article, we made the case that Experimentation Gives You Innovation Superpowers and that companies with a culture of experimentation empower employees to innovate. Our example was Google who has maintained their search engine dominance by continuously raising the bar on search. Google has built infrastructure and tools to make it easy to run experiments that keep making their search engine better.

Now your reaction might be - “But that’s Google! They have tons of money so of course they can afford a culture of experimentation and all the technology investments required to sustain it.” Well, your company may not be as big as Google but you probably can’t afford to not have a culture of experimentation. Making product decisions that rely on gut and opinions is not a recipe for long-term success. The good news is that any company without much more than a curious mindset can start experimenting today.

In Eric Ries’ The Lean Startup, he describes how by running customer experiments we maximize our chances of success by removing uncertainties on whether our product will succeed or fail. Every experiment that yields customer-validated learning gives us greater confidence in our idea or provides us new insights on how to improve our idea (or if appropriate, abandon the idea). Running these experiments can be done more cheaply and efficiently versus investing the time and effort to build out the full product, while crossing our fingers that it will succeed when launched.

So let’s say you have an idea for a product you believe millions of customers around the world will love. Here are a few baby steps you can take to start acquiring customer-validated learning:

Recruit a unit-of-one customer

Can you recruit just one customer to sign up to be an early user of your product based on its description? This may seem like a ridiculously low bar but you’ll be surprised how many ideas fail this simple test (if you’re having a hard time finding one customer, maybe your idea isn’t so great after all). We call this customer a “unit-of-one” customer and encourage all teams to find their unit-of-ones before they start developing their product.

Your unit-of-one customer will often provide you invaluable early feedback. When teams are debating how to approach a feature, a unit-of-one customer can be a tiebreaker and provide real world use cases. The unit-of-one customer can eventually be a helpful reference to other customers and help you understand what the real market for your product is.

A team at Intuit had an idea for a mobile-based cash register for mom-and-pop shops in India they called ShopOwner. The product would replace hand-written receipts which are prevalent in small shops. Engineer Mithun Shenoy recruited his mother who ran a beauty salon to be their unit-of-one customer. One of the surprising insights she provided the team was one of the most important benefits of ShopOwner is that it made the business look much more professional (colloquially described as “Hi-Fi”) which reduced customer bargaining.

Dry Market Tests

A dry market test gauges interest in a product concept before the product is ready by presenting marketing material to potential customers and measuring how many demonstrate an interest in purchasing. A customer can demonstrate interest by a range of commitments including clicking on a “Buy Now” link, signing up for a waiting list, or paying an actual deposit.

Dry market tests are one of the leanest experimentation techniques given the only effort required is to develop marketing copy and finding customers to run the experiment on. Companies from just about any industry can use this type of experimentation. Even non-technical employees can quickly assemble web landing pages using a service like Unbounce and run an ad campaign using Google or Facebook. Services like Nielsen’s BASES can provide more sophisticated forecasting for product concepts.

A company can enable the running of dozens of dry market tests by setting aside a modest budget to use some of the services mentioned. Having a dry market specialist in the organization to coach teams on the best approach can ensure consistency in results and maximize learning.

Concierge MVP

In a concierge minimum viable product, employees deliver the value proposition manually. By manually performing the tasks that constitute what the product will eventually offer in an automated way, employees can test how much the value proposition matters to customers and the best way to deliver that value. Also, it’s much easier to run several iterations of experiments given no product development is required to make design changes.

An Intuit team was tasked with improving a call center’s Voice Response Unit (the automated telephone answering system to route customers to the right agent). They found out that it took several weeks to reprogram the system which would be way too long to experiment with different approaches. They came up with the idea to have real people replace the VRU. When customers heard “Press 1 for billing questions”, they had no idea they were hearing a live person who would route the call manually. Using this approach, the team was able to quickly test several permutations - no programming required!

These experimentation baby steps will get your company started on your journey to developing an experimentation culture. Developing a mindset of data over opinions is the biggest shift. After that, the organization will be bought in to start making investments in developing experimentation infrastructure that make experiments more rigorous and easier to run. Google didn’t generate their awesome infrastructure overnight - that took years of continuous investment. If you want to develop this innovation superpower, start with these baby steps today!

Jeff Zias and I are writing the book Grassroots Innovation in the Enterprise to be published this fall.  Do you have stories to share about how you’ve used experimentation in your company?  We’d love to hear from you and share some of the best stories we gather in our book.

Friday, July 1, 2016

How Innovators and the Legal Team Became BFFs

The following post was first published on LinkedIn.

In a typical big company, the employees pushing the envelope on innovation could have an adversarial relationship with the legal department. Some innovators will even try to fly under the radar fearing the lawyers will put a kibosh on their project as soon as they get wind of it. When they ultimately have to get legal sign off, they anticipate a contentious meeting which will likely result in long delays making them wish they were working in a startup.

So, it might come as a surprise that at the 2013 Lean Startup Conference, Intuit’s CEO Brad Smith, General Counsel Laura Fennell, and myself (at the time VP of Innovation) were on stage talking about how we collaborated on innovation. How was it possible that the people you expected to be frenemies would be BFFs (best friends forever)?

It starts with Intuit’s approach to innovation. Instead of consigning the job of innovating to a few geniuses, at Intuit innovation is everybody’s job. Every employee is responsible for helping the company grow whether it means finding new ways to serve customers or run the business more efficiently.

A lawyer working for a company might believe that their main job is to reduce the company’s legal exposure. We live in a litigious society and so they must make sure we avoid missteps. Taken to an extreme, the most effective way to reduce exposure is to say no to everything. With that attitude, it’s no wonder employees start to see the lawyer as a barrier to innovation.

Here’s what Laura said about corporate lawyers:
“The shocking reality for a lawyer is when you go to a company, nobody cares about what you do. Your job is not to be the best lawyer out there. Your job is to help the company move fast and innovate.”
If a corporate lawyer instead sees her main job as helping innovation, she can become a huge asset to innovation. When new ideas are brought to the table, she can work alongside the innovators to find ways to bring the ideas forward that are prudent and don’t create untenable legal exposure. Instead of just saying no to a particular approach, the lawyer helps by suggesting other ways of getting to the same outcome. Laura calls this “getting to yes”.

Here’s an example of lawyers partnering with innovators: At Intuit, every month we held an Incubation Week where teams of employees would sign up to turn their ideas into Minimum Viable Products (MVPs). Each team’s goal was to release their MVP to customers by the end of the week. Our legal department helped teams get ready for release by providing a checklist for staying within guidelines. Legal’s help didn’t end there. In the middle of the week, a group from the department would visit the teams and review what each had developed. If they saw any problems (for example, the team had chosen a name that infringed on another company’s trademark), they would sit with the team and help come up with a solution (like brainstorming new names).

Here's what Intuit Assistant General Counsel Arien Ferrell says about Intuit's legal team:
Intuit’s legal team owns innovation and product launch just as passionately as any developer, designer, or innovator – this is the key to our success…we’re not 'legal', separate and distinct from the businesses, we’re members of the same team who own and dance to the same music.  We don’t seek to minimize legal exposure…our goal is to get to the right risk level for the opportunity presented.
It’s not just the legal department that can end up being a barrier to innovation. Other functions like Human Resources and IT may inadvertently create barriers if they don’t take on this partnership mindset.

Here’s what Brad said about getting to yes:
“Our job is not to put barriers up and tell you why you can’t. The job of all functions is to find a way to get to yes and to do it with speed as the currency.”
Jeff Zias and I are writing the book Grassroots Innovation in the Enterprise for which we’ve developed a Grassroots Innovation Model for empowering employees in a company to drive growth. One of the components of that model is Funding & Support. One critical aspect of how a company supports employee-driven innovation is by having every function be an innovator’s BFF and get to yes.

Do you have stories to share about how functions in your company are supporting innovation? We’d love to hear from you.

Thursday, June 16, 2016

How Amazon Bridged the Insight-Decision Divide

This post was first published on LinkedIn.

At Amazon, all senior leaders are required to take two days of customer service training every other year. Amazon CEO Jeff Bezos in this fireside chat describes one experience he had while being trained. Bezos was taking calls from customers and had an experienced customer service agent listening in and available to jump in if he needed help.

On one particular call, as soon as the customer’s order appeared on the screen, the experienced agent leaned over to Bezos and whispered “She’s going to want to return that table”, pointing to one of the previous orders. Sure enough, the customer told Bezos “I want to return the table”. It turned out the top of the table was scratched because it had been packaged poorly. After handling the return and finishing up with the customer, Bezos turned to the agent and asked “How did you know that the customer was going to return the table?”

“Oh that table always gets returned,” replied the agent.

What Bezos had just experienced is what we describe as the Insight-Decision Divide. Frontline employees by virtue of working with customers and products every day are bombarded with insights that can have a significant impact on the company’s bottom line. However, in most companies, these employees don’t have a voice and their ideas become hidden assets.

Bezos was determined to fix Amazon’s Insight-Decision Divide. To that end, he borrowed concepts from the Toyota Production System by instituting Kaizen Days and the Andon Cord.

Kaizen is the lean manufacturing practice to achieve continuous improvements in multiple aspects of the manufacturing process. By achieving regular and incremental changes, Kaizen results in major improvements over time. With Amazon’s Kaizen Days, small teams are assembled to experiment with different solutions, measuring impact on a small scale before rolling out solutions to the larger organization.

Andon is the lean manufacturing term where any frontline worker can stop manufacturing production because of a problem. With Amazon’s Andon Cord, a customer service agent who noticed repeated instances of customers complaining about problems with a product, was now empowered to pull that product from the website.

Amazon’s Kaizen Days and Andon Cord exemplify three aspects of our Grassroots Innovation Model. With Kaizen Days, Amazon is applying elements of Experimentation and Funding and Support. With the Andon Cord, Amazon is applying elements of Freedom. Kaizen Days and Andon Cord empower Amazon frontline employees to innovate and help drive growth.

Jeff Zias and I are writing the book Grassroots Innovation in the Enterprise to be published this fall. Thanks to former Amazon Principal Engineer John Rauser for sharing this Amazon story.  Do you have a story to share on how your company has bridged the Insight-Decision Divide?  We’d love to hear from you.

Saturday, June 4, 2016

Fixing #AirbnbWhileBlack

This post was first published on LinkedIn.

There have recently been several incidents reported of black customers of Airbnb being denied lodging.  Particularly disturbing was this story involving a host in Charlotte that was so egregious it elicited a response from Airbnb’s CEO. Sadly, there have been enough of these stories that #AirbnbWhileBlack is now a trending topic.

How much should we hold Airbnb accountable for these problems? Haven’t they strongly condemned racism and published an anti-discriminatory policy which all hosts are supposed to abide by? Shouldn’t we just chalk up these incidents as Airbnb reflecting the sad state of bigotry in our country and that in spite of all our progress, we still have a long way to go?

I propose there is much more that Airbnb can do to address these problems and that we should expect no less. I say this even though I’m a huge fan of the Airbnb story.  The hustle and creativity Brian Chesky and Joe Gebbia exemplified in building their disruptive company is very inspiring and one of the stories we share when teaching Lean Startup methodologies.

To understand what more can be done, we should first recognize an underlying issue - the lack of diversity in the Silicon Valley bubble. While the Valley itself is an amazing melting point of immigrants from all corners of the globe, those of us working in tech firms tend to have very similar backgrounds, education and income. The problem is exacerbated by the even narrower diversity in leadership roles. Airbnb is far from being the only Silicon Valley company with these diversity challenges. (Airbnb has been making positive steps like hiring a director of diversity).

How many Airbnb employees do you think have been denied lodging because of their race? If you think the answer is somewhere between scant and none, is it any wonder then that #AirbnbWhileBlack hasn’t been addressed in the product design? Company statements and anti-discriminatory policies are a start. But there’s much more we can do to make our product experiences better for users who live outside the Silicon Valley bubble.

A friend asked me, “How do you address and prevent racism in product design?” My answer is that we solve it like any other product challenge - through innovation. We just need to make it a priority to solve.

In the spirit of innovation and being solution-oriented, I’d like us to all participate in a brainstorm of how Airbnb can fix #AirbnbWhileBlack. I’ll kick things off with a couple of ideas:

  • Restrict a host from offering lodging to a guest during a timeframe that they’ve said is not available to another guest.
  • On the host profile page, track how many times the host has denied a guest lodging.

The design principle behind these ideas is preserving the host’s right to deny lodging while introducing disincentives and increasing transparency. Are there other principles we should be considering?

I look forward to hearing your ideas. I’d especially love to hear from those of you who are hosts and can speak knowledgeably about that experience.

Friday, June 3, 2016

Bridging the Insight-Decision Divide

Sorry, we don't sell tulips. You're the fifth person to ask today.
Team, what are we going to do about the stagnant revenue from our flower shops?
This post was originally published on LinkedIn.

A very common scenario in corporations is when senior leaders realize the business is facing challenges the company is not on track to overcome.  They decide they need to take a step back and re-examine their strategy.  At this point they will typically hire an expensive consulting firm to help them work through their new strategy.  The consulting firm works for several months gathering data, interviewing employees and customers, and eventually delivering their recommendations.  When the turnaround strategy is unveiled with much fanfare, many employees are unimpressed – “We already knew this and it wouldn’t have cost the company millions of dollars if they had just asked us.”

Because many employees have a front row view of customer and product issues, they are frequently bombarded with insights that spark ideas that could jump-start growth.  But many companies often don’t even ask employees for their ideas.  And if employees voice ideas, they are often not listened to.  But what’s even more pervasive is that employees who are fully subscribed to their “day jobs” won’t have time to explore their insights.  These ideas are destined to become hidden assets.

In most companies, decisions on what ideas to explore are made by senior leaders. But these senior leaders don’t have the same proximity to insights because they spend most of their working day meeting with other senior leaders. We call this the Insight-Decision Divide.

In our upcoming book, Grassroots Innovation in the Enterprise, Jeff Zias and I will describe how companies can bridge this divide. The most foundational facets of our Grassroots Innovation Model are providing time and freedom for employees to spend time on their ideas. With time and freedom, employees have the “air cover” to follow up on insights without having to worry that they’ll get chewed out by their manager for spending time on something she may not consider a priority.

When we describe the Insight-Decision Divide to companies we advise, the concept always resonates with our audience. But this is often accompanied by sentiments of resignation such as “implementing a time and freedom program at our company will be too hard”, “we’re too busy”, or “it will be too difficult to sell to other leaders”.

The good news is that you can start bridging the divide with baby steps. With the momentum you hopefully start to build up, you can eventually develop a full-fledged innovation program that incorporates all facets of the Grassroots Innovation Model.

Here are a few ideas for baby steps:

  • Organize a hackathon: Maybe you can’t get the company to commit to giving every employee time to work on the ideas but you can probably get leaders to agree to a one day hackathon. In the hackathon, employees will be invited to bring their ideas and work on storyboards and prototypes to be shared at the end of the day. The hackathon will be tangible evidence to employees that leaders are interested in what they think.  (Please read Jeff’s list on how to not screw up a hackathon).
  • Install an idea collaboration tool: Even if employees don’t have time to work on their ideas, you can start by asking them to write their ideas down. An innovation management system like BrightIdea or Spigit will allow employees to see their colleagues’ ideas and provide feedback. Senior leaders can use these ideas as input into their resource allocation process.
  • Appoint innovation rotations: Put together a small team of some of your most entrepreneurial employees and challenge them to solve one of the company’s most gnarly problems. Give the team decision-making autonomy but time box their assignment to what you think the company can reasonably afford (could be as short as a few days or a week but probably no longer than three months).

Keep in mind that these baby steps are not meant to constitute a sustainable program. For reasons we outline in our book, without a fully formed Grassroots Innovation Model, your early momentum will eventually peter out when the novelty is gone. But the baby steps at least provide you a way to get started in the face of institutional impedance.

Have you tried any of these baby steps or other ideas on how to get an innovation program started at your company? We’d love to hear from you and share some of your stories in our book.

Saturday, May 7, 2016

Update to the Innovation Programs Assessment Model

This post was first published on LinkedIn.

Jeff Zias and I are writing the book Grassroots Innovation in the Enterprise to be published this fall. In March, we published a blog post where we introduced a draft of a model to help assess innovation programs in the enterprise.

To review, the model included these four facets:
  • Freedom – Employees are given autonomy to explore ideas they are passionate about.
  • Time – Employees are given self-directed time, carved out from their day jobs, to work on their own projects.
  • Collaborative Culture and Tools – Employees can easily find out what other employees are working on in their self-directed projects, provide feedback, and form teams across organizational and geographic boundaries.
  • Funding and Support – Employees are given resources, tools, training, and senior leadership mentoring to develop their self-directed projects.  A formal process is in place allowing projects to “graduate” to officially funded initiatives.
We published a Grassroots Innovation Program Assessment Poll using the previous draft of the model. Thanks to those of you who participated in the poll. So far, all respondents have indicated that their companies are implementing some parts of the grassroots innovation model. However, everyone has room to improve since no company so far is firing on all cylinders.

We were pleased to receive positive responses and several suggestions on how to refine the model. Thanks so much for your helpful feedback!

Since March, we’ve also published a post on how a culture of experimentation gives companies innovation superpowers. That post describes how Google has maintained its search engine leadership by developing a highly evolved practice of experimentation supported by infrastructure and tools.  Other companies like Amazon and Facebook have also developed a highly refined practice around experimentation.

It’s clear to us then that Experimentation should be a fifth facet in our innovation model. A culture of experimentation synergistically supports the other facets because ideas from frontline employee can be tested alongside ideas from senior leaders.  When a meritocracy of ideas is achieved, the company is more likely to benefit from giving employees time, freedom, tools, and funding to spend on their own ideas.

We’ve created a new Assessment Poll to include the Experimentation facet.  We look forward to receiving more of your responses. Please continue to send us feedback on the model.  Also, we’d love to hear about what’s working well for you and what challenges you’re experiencing running innovation programs at your company.