How to Know You Have a Well Defined Minimum Viable Product

Conceptually, the idea of a minimum viable product (MVP) is easy to grasp. Early in a project, it’s a deliverable that reflects some semblance to the final product such that it’s barely able to stand on it’s own without lots of hand-holding and explanation for the customer’s benefit. In short, it’s terrible, buggy, and unstable. By design, MVPs lack features that may eventually prove to be essential to the final product. And we deliberately show the MVP to the customer!

We do this because the MVP is the engine that turns the build-measure-learn feedback loop. The key here is the “learn” phase. The essential features to the final product are often unclear or even unknown early in a project. Furthermore, they are largely undefinable or unknowable without multiple iterations through the build-measure-learn feedback cycle with the customer early in the process.

So early MVPs aren’t very good. They’re also not very expensive. This, too, is by design because an MVP’s very raison d’être is to test the assumptions we make early on in a project. They are low budget experiments that follow from a simple strategy:

  1. State the good faith assumptions about what the customer wants and needs.
  2. Describe the tests the MVP will satisfy that are capable of measuring the MVP’s impact on the stated assumptions.
  3. Build an MVP that tests the assumptions.
  4. Evaluate the results.

If the assumptions are not stated and the tests are vague, the MVP will fail to achieve it’s purpose and will likely result in wasted effort.

The “product” in “minimum viable product” can be almost anything: a partial or early design flow, a wireframe, a collection of simulated email exchanges, the outline to a user guide, a static screen mock-up, a shell of screen panels with placeholder text that can nonetheless be navigated – anything that can be placed in front of a customer for feedback qualifies as an MVP. In other words, a sprint can contain multiple MVPs depending on the functional groups involved with the sprint and the maturity of the project. As the project progresses, the individual functional group MVPs will begin to integrate and converge on larger and more refined MVPs, each gaining in stability and quality.

MVPs are not an end unto themselves. They are tangible evidence of the development process in action. The practice of iteratively developing MVPs helps develop to skill of rapid evaluation and learning among product owners and agile delivery team members. A buggy, unstable, ugly, bloated, or poorly worded MVP is only a problem if it’s put forward as the final product. The driving goal behind iterative MVPs is not perfection, rather it is to support the process of learning what needs to be developed for the optimal solution that solves the customer’s problems.

“Unlike a prototype or concept test, an MVP is designed not just to answer product design or technical questions. Its goal is to test fundamental business hypotheses.” – Eric Ries, The Lean Startup

So how might product owners and Agile teams begin to get a handle on defining an MVP? There are several questions the product owner and team can ask of themselves, in light of the product backlog, that may help guide their focus and decisions. (Use of the following term “stakeholders” can mean company executives or external customers.)

  • Identify the likely set of stakeholders who will be attending the sprint review. What will these stakeholders need to see so that they can offer valuable feedback? What does the team need to show in order to spark the most valuable feedback from the stakeholders?
  • What expectations have been set for the stakeholders?
  • Is the distinction clear between what the stakeholders want vs what they need?
  • Is the distinction clear between high and low value? Is the design cart before the value horse?
  • What are the top two features or functions the stakeholders  will be expecting to see? What value – to the stakeholders – will these features or functions deliver?
  • Will the identified features or functions provide long term value or do they risk generating significant rework down the road?
  • Are the identified features or functions leveraging code, content, or UI/UX reuse?

Recognizing an MVP – Less is More

Since an MVP can be almost anything,  it is perhaps easier to begin any conversation about MVPs by touching on the elements missing from an MVP.

An MVP is not a quality product. Using any generally accepted definition of “quality” in the marketplace, an MVP will fail on all accounts. Well, on most accounts. The key is to consider relative quality. At the beginning of a sprint, the standards of quality for an MVP are framed by the sprint goals and objectives. If it meets those goals, the team has successfully created a quality MVP. If measured against the external marketplace or the quality expectations of the customer, the MVP will almost assuredly fail inspection.

Your MVPs will probably be ugly, especially at first. They will be missing features. They will be unstable. Build them anyway. Put them in front of the customer for feedback. Learn. And move on to the next MVP. Progressively, they will begin to converge on the final product that is of high quality in the eyes of the customer. MVPs are the stepping stones that get you across the development stream and to the other side where all is sunny, beautiful, and stable. (For more information on avoiding the trap of presupposing what a customer means by quality and value, see “The Value of ‘Good Enough’“)

An MVP is not permanent. Agile teams should expect to throw away several, maybe even many, MVPs on their way to the final product. If they aren’t, then it is probable they are not learning what they need to about what the customer actually wants. In this respect, waste can be a good, even important thing. The driving purpose of the MVP is to rapidly develop the team’s understanding of what the customer needs, the problems they are expecting to have solved, and the level of quality necessary to satisfy each of these goals.

MVPs are not the truth. They are experiments meant to get the team to the truth. By virtue of their low-quality, low-cost nature, MVPs quickly shake out the attributes to the solution the customer cares about and wants. The solid empirical foundation they provide is orders of magnitude more valuable to the Agile team than any amount of speculative strategy planning or theoretical posturing.

(This article cross-posted on LinkedIn.)

The Value of “Good Enough”

Any company interested in being successful, whether offering a product or service, promises quality to its customers. Those that don’t deliver, die away. Those that do, survive. Those that deliver quality consistently, thrive. Seems like easy math. But then, 1 + 1 = 2 seems like easy math until you struggle through the 350+ pages Whitehead and Russell1 spent on setting up the proof for this very equation. Add the subjective filters for evaluating “quality” and one is left with a measure that can be a challenge to define in any practical way.

Math aside, when it comes to quality, everyone “knows it when they see it,” usually in counterpoint to a decidedly non-quality experience with a product or service. The nature of quality is indeed chameleonic – durability, materials, style, engineering, timeliness, customer service, utility, aesthetics – the list of measures is nearly endless. Reading customer reviews can reveal a surprising array of criteria used to evaluate the quality for a single product.

The view from within the company, however, is even less clear. Businesses often believe they know quality when they see it. Yet that belief is often predicate on how the organization defines quality, not how their customers define quality. It is a definition that is frequently biased in ways that accentuate what the organization values, not necessarily what the customer values.

Organization leaders may define quality too high, such that their product or service can’t be priced competitively or delivered to the market in a timely manner. If the high quality niche is there, the business might succeed. If not, the business loses out to lower priced competitors that deliver products sooner and satisfy the customer’s criteria for quality (see Figure 1).

Figure 1. Quality Mismatch I
Figure 1. Quality Mismatch I

Certainly, there is a case that can be made for providing the highest quality possible and developing the business around that niche. For startups and new product development, this may not be be best place to start.

On the other end of the spectrum, businesses that fall short of customer expectations for quality suffer incremental, or in some cases catastrophic, reputation erosion. Repairing or rebuilding a reputation for quality in a competitive market is difficult, maybe even impossible (see Figure 2).

Figure 2. Quality Mismatch II
Figure 2. Quality Mismatch II

The process for defining quality on the company side of the equation, while difficult, is more or less deliberate. Not so on the customer side. Customers often don’t know what they mean by “quality” until they have an experience that fails to meet their unstated, or even unknown, expectations. Quality savvy companies, therefore, invest in understanding what their customers mean by “quality” and plan accordingly. Less guess work, more effort toward actual understanding.

Furthermore, looking to what the competition is doing may not be the best strategy. They may be guessing as well. It may very well be that the successful quality strategy isn’t down the path of adding more bells and whistles that market research and focus groups suggest customers want. Rather, it may be that improvements in existing features and services are more desirable.

Focus on being clear about whether or not potential customers value the offered solution and how they define value. When following an Agile approach to product development, leveraging minimum viable product definitions can help bring clarity to the effort. With customer-centric benchmarks for quality in hand, companies are better served by first defining quality in terms of “good enough” in the eyes of their customers and then setting the internal goal a little higher. This will maximize internal resources (usually time and money) and deliver a product or service that satisfies the customer’s idea of “quality.”

Case in point: Several months back, I was assembling several bar clamps and needed a set of cutting tools used to put the thread on the end of metal pipes – a somewhat exotic tool for a woodworker’s shop. Shopping around, I could easily drop $300 for a five star “professional” set or $35 for a set that was rated to be somewhat mediocre. I’ve gone high end on many of the tools in my shop, but in this case the $35 set was the best solution for my needs. Most of the negative reviews revolved around issues with durability after repeated use. My need was extremely limited and the “valuable and good enough” threshold was crossed at $35. The tool set performed perfectly and more than paid for itself when compared with the alternatives, whether that be a more expensive tool or my time to find a local shop to thread the pipes for me. This would not have been the case for a pipefitter or someone working in a machine shop.

By understanding where the “good enough and valuable” line is, project and organization leaders are in a better position to evaluate the benefits of incremental improvements to core products and services that don’t break the bank or burn out the people tasked with delivering the goods. Of course, determining what is “good enough” depends on the end goal. Sending a rover to Mars, “good enough” had better be as near to perfection as possible. Threading a dozen pipes for bar clamps used in a wood shop can be completed quite successful with low quality tools that are “good enough” to get the job done.

References

1Volume 1 of Principia Mathematica by Alfred North Whitehead and Bertrand Russell (Cambridge University Press, page 379). The proof was actually not completed until Volume 2.

(This article cross-posted at LinkedIn.)

Relative Team Expertise and Story Sizing

In Parkinson’s Law of Triviality and Story Sizing, I touched on the issue of relative expertise among team members during collaborative efforts to size story cards. I’d like to expand on that idea by considering several types of team compositions.

Team 1 is a tight knit band of four software developers represented in Figure 1.

Figure 1 - Team 1
Figure 1 – Team 1

Their preferred domain and depth of experience is represented by the color and area of their respective circles. While they each have their own area of expertise, there is a significant overlap in common knowledge. All four of them understand the underlying architecture, common coding practices, and fundamental coding principles. Furthermore, there is a robust amount of inter-domain expertise. When needed, the HTML5/CSS developer can probably help out with JavaScript issues, for example. The probability of this team successfully working together to size the stories in the product backlog is high.

Team 1 represents a near-ideal team composition for a typical software related project. However, the real world isn’t so generous in it’s allocation of near-ideal, let alone ideal, teams. A typical team for a software related project is more likely to resemble Team 2, as represented in Figure 2.

Figure 2 - Team 2
Figure 2 – Team 2

In Team 2, the JavaScript developer is fresh out of college,  new to the company and new to the business. His real-world experience is limited so his circle of expertise is smaller relative to his teammates. The HTML5/CSS developer has been working for the company for 10 years and knows the business like the back of her hand. So she has a much wider view of how her work impacts the company and product development. As a team, there is much less overlap and options for helping each other through a sprint is diminished.  As for collaborative story sizing efforts, the HTML5/CSS and C# developers are likely to dominate the conversation while the JavaScript developer agrees with just about anything not JavaScript related.

As Agile practices become more ubiquitous in the business world, team composition beings to resemble Team 3, as shown in Figure 3.

Figure 3 - Team 3
Figure 3 – Team 3

The mix now includes non-technical people – content developers and editors, strategists, and designers. Even assuming an equal level of experience in their respective domains, the company, and the business environment, there is very little overlap. Arriving at a consensus during a story sizing exercise now becomes a significant challenge. But again, the real world isn’t even so kind as this. We are increasingly more likely to encounter teams that resemble Team 4 as shown in Figure 4.

Figure 4 - Team 4
Figure 4 – Team 4

As before, the relative circle of expertise among team members can vary quite a bit. When a team resembles the composition of Team 4, the software developers (HTML5/CSS and C#) will have trouble understanding what the Learning Strategist is asking for while the Learning Strategist may not understand why what he wants the software developers to deliver isn’t possible.

When I’ve attempted to facilitate story sizing sessions with teams that resemble Team 4 they either become quite contentious (and therefore time consuming) or team members that don’t have the expertise to understand a particular card simply accept the opinion of the stronger voices. Neither one of these situations is desirable.

To counteract these possibilities, I’ve found it much more effective to have the card assignee determine the card size (points and time estimate) and work to have the other team members ask questions about the work described on the card such that the assignee and the team better understand the context in which the card is positioned. The team members that lack domain expertise, it turns out, are in a good position to help craft good acceptance criteria.

  • Who will consume the work product that results from the card? (dependencies)
  • What cards need to be completed before a particular card can be worked on? (dependencies)
  • Is everything known about what a particular card needs before it can be completed? (dependencies, discovery, exploration)

At the end of a brief conversation where the entire team is working to evaluate the card for anything other than level of effort (time) and complexity (points), it is not uncommon for the assignee to reconsider their sizing, break the card into multiple cards, or determine the card shouldn’t be included in the sprint backlog. In short, it ends up being a much more productive conversation if teammates aren’t haggling over point distinctions or passively accepting what more experienced teammates are advocating. The benefit to the product owner is that they now have additional information that will undoubtedly influence the product backlog prioritization.

Minimum Viable Product – It’s What You Don’t See

Take a moment or two to gaze at the image below. What do you see?

Do you see white dots embedded within the grid connected by diagonal white lines? If you do, try and ignore them. Chances are, your brain won’t let you even though the white circles and diagonal lines don’t exist. Their “thereness” is created by the thin black lines. By carefully drawing a simple repetitive pattern of black lines, your brain has filled in the void and enhanced the image with white dots and diagonal white lines. You cannot not do this. This cognitive process is important to be aware of if you are a product owner because both your agile delivery team members and clients will run this program without fail.

Think of the black lines as the minimum viable product definition for one of your sprints. When shown to your team or your client, they will naturally fill the void for what’s next or what’s missing. Maybe as a statement, most likely as a question. But what if the product owner defined the minimum viable product further and presented, metaphorically, something like this:

By removing the white space from the original image there are fewer possibilities for your team and the client to explore. We’ve reduced their response to our proposed solution to a “yes” or “no” and in doing so have started moving down the path of near endless cycles of the product owner guessing what the client wants and the agile delivery team guessing what the product owner wants. Both the client and the team will grow increasingly frustrated at the lack of progress. Played out too long, the client is likely to doubt our skills and competency at finding a solution.

On the other hand, by strategically limiting the information presented in the minimum viable product (or effort, if you like) we invite the client and the agile delivery team to explore the white space. This will make them co-creators of the solution and more fully invested in its success. Since they co-created the solution, they are much more likely to view the solution as brilliant, perfect, and the shiniest of shiny objects.

I can’t remember where I heard or read this, but in the first image the idea is that the black lines are you talking and the white spaces are you listening.

The Passing of a Master

It has been several months since news of Emily Busch ‘s unexpected death and I still wrestle with the thought I shall never have the privilege of again practicing Aikido with her at Nippon Kan. The blow to Homa Sensei is undoubtedly far greater. I do not know his pain, but I am familiar with it.

Looking at the growing stack of draft posts, I see about a dozen on the subject of mastery. I feel I have a lot to contribute to this subject, particularly in regard to Agile practices. And yet, I hesitate due to a sense that I still have more to learn before I’m in a position to teach on the subject. In no small measure this hesitation is counseled by having met and studied with a great many truly masterful people across a wide variety of human experience.

Emily was one of those masters.

Not only was she a master of Aikido (6th degree black belt and Sensei at Nippon Kan), she was a master jeweler. She designed and made the wedding rings for both my first and second wife along with several beautiful pendants and a set of ear rings for one of my nieces. I never had a personal jeweler before Emily and shall not have another before my time is finished on this earth.

For all her skill and mastery, she very much understood the importance of service. There was no task that needed attention at the dojo or in preparation for a seminar that was beneath her rank. And I wonder how many patrons to Domo restaurant knew they had their order taken and served by a 6th degree black belt.

Emily had already achieved the rank of black belt by the time I began practicing at Nippon Kan in 1989. My very early memories from practicing with her are of her patience and ability to skillfully instruct a 6’5″ oaf like me in the ways of Aikido – both on and off the mat. I don’t know if Emily even weighed 120 pounds, but that never stopped her from putting my sorry ass on the mat or sending me over her shoulder. Even so, I never matched Emily’s skill, even on my good days.

Those mastery related posts will have to wait a while longer. And in the wider view, my respect for those whom make claim to be masters without having done the work and earned the title have lost a little more of my respect.

Emily Sensei will be missed.

What does Agile documentation look like?

Reading through Dusty Phillips’ second edition of “Python 3 Object-oriented Programming,” this quote caught my attention:

Further, the most important person you will ever have to communicate with is yourself. We all think we can remember the design decisions we’ve made, but there will always be the Why did I do that? moments hiding in our future. If we keep the scraps of papers we did our initial diagramming on when we started a design, we’ll eventually find them a useful reference.

That strikes me as a good benchmark for acceptable documentation in Agile. Whether coder, UI/UX designer, data architect, or whatever, if you are keeping a good record of what you decided and why, you’ll probably be able to recreate the rationale for why things got to be the way they are for anybody who needs to know. Especially if that anybody is you. And there is a good chance that someone following in your footsteps will be able to pick up the same rationale even in your absence. All this without putting an unnecessary burden on project progress for the sake of detailed documentation.

Of course, what qualifies as “good” is the tricky part. A suggested threshold would be to specify only as much information as makes sense or for what is known given the current situation. Documentation should be subject to iterative practices just as much as code.

False Barriers to Implementing Scrum – II

In a previous post, I described several barriers to implementing scrum. Recently, an additional example came to light similar to the mistake of elevating scrum or Agile to a philosophy.

In a conversation with a colleague, we were exploring ways on how we might drive interest for browsing the growing wealth of Agile related information being added to the company wiki.  It’s an impressive collection of experiences of how other teams have solved a wide array of interesting problems using Agile principles and practices. Knowing that we cannot personally attend to every need on every project team, we were talking through various ways to develop the capacity for exploration and self-education. I think I must have used the phrase “the information is out there and readily available” a couple of times to many because my colleague reacted to where I put the bar by comparing learning Agile to surgery.

Using the surgery metaphor, she pressed the comparison that all the information she needs about surgery is “out there and readily available” but even if she knew all that information she likely wouldn’t be a good surgeon. Fair point that experience and practice are important. And if that is the case, then everyone should be taking every opportunity they can to practice good agile rather than regressing to old habits.

More importantly, perhaps, is the misapplied metaphor. Practicing agile isn’t as complicated as surgery or rocket science or any other such endeavor that requires years of deep study and practice. Comparing it to something like that places the prospects of doing well in a short amount of time mentally beyond the reach of any potential practitioners.

Perhaps a better metaphor is the opening of a new rail line in the city. A good measure of effort needs to be expended to educate the public on the line’s availability, the schedules, how to purchase fares, where the connections are, what are the safety features, etc. Having done that, having “put the information out there where it is generally available,” it is a reasonable expectation that the public will make the effort to find it when they need it. It is unreasonable, and unscaleable, to build such a system and then expect that every passenger will be personally escorted from their front door to their seat on the train.

It is also interesting to consider what this does to the “empathy scale” when such an overextended metaphor is applied to efforts such as learning to practice Agile. If we frame learning Agile as similar to surgery then as people work to implement Agile are we more inclined to have an excessive amount of empathy for their struggles and be more accepting or accommodating of their short comings?

“Not to worry that you still don’t have a well formed product backlog. This is like surgery, after all.”

Are we as an organization and each of our employees better served by the application of a more appropriate metaphor, one that matches the skill and expectations of the task?

“We’ve provided instruction as to what a product backlog is and how to create one. We’ve guided you as you’ve practiced refining a product backlog. You know where to find suggestions for improving your skills for product backlog stewardship (wiki, books, colleagues, etc). Now role up your sleeves and do the work.”

Successful coaching for developing the ability in team members for actively seeking answers requires skillfully letting them struggle and fail in recoverable ways. It is possible to hold their hand too long. To use another metaphor, provide whatever guidance and instruction you need to so they know how to fish, then let them alone to practice casting their own line.


Photo credit: langll

How to know when Agile is working

On a recent flight into Houston, my plane was diverted to Austin due to weather. Before we could land at Austin, we were re-diverted back to Houston. I’ve no idea why the gears aligned this way, but this meant we were out-of-sequence with the baggage handling system and our luggage didn’t arrive at the claim carousel for close to an hour and a half. Leading up to the luggage arrival was an unfortunate display from an increasingly agitated young couple. They were loudly communicating their frustration to an airport employee with unknown authority. Their frustration was understandable in light of the fact that flights were undoubtedly going to be missed.

At one point, the woman exclaimed, “This isn’t how this is supposed to work!”

I matched this with a similar comment from one of the developers on one of my project teams. Stressed with the workload he had committed to, he declared there are too many meetings and therefore “the agile process is not working!” When explored, it turned out some version of this sentiment was common among the software development staff.

In both cases, the process was working. It just wasn’t working as desired or expected based on past experience. In both cases, present events were immune to expectations. The fact that our luggage almost always shows up on time and that agile frequently goes smoothly belies how susceptible the two processes actually are to unknown variables that can disrupt the usual flow of events.

There is a difference with agile, however. When practiced well, it adapts to the vagaries of human experience. We expect the unexpected, even if we don’t know what form that may take.

There is an assumption being made by the developers in that “working agile” makes work easy and stress free. I’ve never found that. And I don’t know anyone who has. It stresses teams differently than waterfall. I’ve experienced high stress developing code under both agile and waterfall. With agile, however, teams have a better shot at deciding for themselves the stress they want to take on. But there will be stress. Unstressed coders deliver code of questionable value and quality, if they deliver at all.

The more accurate assessment to make here is that the developers aren’t practicing agile as well as they could. That’s fundamentally different from “agile isn’t working.” In particular, the developers didn’t understand what they had committed to. Every single sprint planning session I’ve run (and the way I coach them to be run) begins with challenging the team members to think about things that may impact the work they will commit to in the next sprint – vacations, family obligations, doctor visits, other projects, stubbed toes, alien abductions – anything that may limit the effort they can commit to. What occurred with the developers was a failure to take responsibility for their actions and decisions, a measure of dishonesty (albeit unintended) to themselves and their team mates by saying “yes” to work and later wishing “no.”

Underlying this insight into developer workload may be something much more unsettling. If anyone on your team has committed to more than they can complete and has done so for a number of sprints, your project may be at risk. The safe assumption would be that the project has a hidden fragility that will surprise you when it breaks. Project time lines, deliverables, and quality will suffer not solely because there are too many meetings, but because the team does not have a good understanding of what they need to complete and what they can commit to. What is the potential impact on other projects (internal and client) knowing that one or more of the team members is over committing? What delays, quality issues, or major pivots are looming out there ready to cause significant disruptions?

The resolution to this issue requires time and the following actions:

  • Coaching for creating and refining story cards
  • Coaching for understanding how to estimate work efforts (points and/or time)
  • Develop skills in the development staff for recognizing card dependencies
  • Develop skills for time management
  • Find ways to modify the work environment such that it is easier for developers to focus on work for extended periods of time
  • Evaluate the meeting load to determine if there are extraneous meetings
  • Based on metrics, specifically limit each developer’s work commitment for several sprints such that it falls within their ability to complete

Image credit: Prawny

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