Dual Track Development is not Duel Track

tl;dr:

If you’ve heard the term “dual-track development” before, this article explains where it comes from, and what it means. Here are the key points:

  • Development work focuses on predictability and quality
  • Discovery work focuses on fast learning and validation
  • Discovery and development are visualized in two tracks because it’s two kinds of work, and two kinds of thinking
  • Discovery is a necessary part of product development. Practice it with the same agile and lean principles in mind.
  • If we’re doing discovery right, we substantially change and kill lots of ideas.
  • While a product manager, designer, and senior engineer may lead and orchestrate discovery, they must involve the whole team in discovery tasks wherever possible. Keep discovery work and progress visible to the whole team.
  • Keep measuring and learning even after you ship.

Now, if anyone asks you what the article is about, you can answer them without reading the next 1,500 words.


No one really named it dual-track

Years ago, I was teaching a class with my friend Marty Cagan. It was really just my stuff and his stuff mashed together in a 3-day class. But, during my part I put up a model that I normally show when talking about how Agile thinking and product thinking work together in the same process. The model looked a little like this:

I’d hand-drawn my own version of the model, so it did’t look exactly like this. But, Marty asked me where this model came from. I opened the original paper from Desiree Sy (pronounced See) called Adapting Usability Investigations for Agile User-centered Design.

This is Desiree. You’d like her. She’s very smart.

Her 2007 article describes a common pattern which lots of people doing rigorous design and validation work in Agile development had already arrived at. Because, it’s really the only way this stuff can work. At the time, Desiree was working with Alias, now an Autodesk company, and she and her colleagues there had this working pretty smoothly. They were doing what most people at the time considered somewhere between super-hard and impossible. But, for them it seemed natural. Not easy, but it worked.

Marty asked me “what’s this model called?”

“It doesn’t really have a name” I said. “It’s just the way it’s done.”

“What does she call it?” Marty asked.

We scanned the paper and found this paragraph:

If I extract the important bit, it says

“… we work with developers very closely through design and development. Although the dual tracks depicted seem separate, in reality, designers need to communicate every day with developers.”

And that was it. Marty began using this term in his teaching to product managers. And since I often teach to the same people I began using that term. And gradually others began using that term.

Now I need to tell you I hate the term, and here’s why.

It’s Dual Track, not Duel Track

People just don’t read. It’s a miracle you’ve read this far yourself. Congratulations.

But people do look at pictures. And that picture of dual track seems to suggest different jobs for different people – like product managers and designers figuring out what to build, and developers building it. And in the worst of cases, you may interpret it as developers needing to wait weeks for product managers and designers to get their sh*t done.  It’s not supposed to be that way. If the whole team is responsible for product success, not just getting things built, then the whole team understands and contributes to both kinds of work.

I’d love a different term, and a different picture. But, I don’t have a better term or picture right now. Although I’ll try to draw a few more pictures to supplement this one.

There are two kinds of work, and there’s no way around it

Development work

If you’ve worked in Agile development before, you know teams will talk a lot about velocity. But the velocity they’re talking about is development velocity. Teams hand-wring about their predictability. At the beginning of a sprint, they’ll estimate velocity, and at the end they’ll measure it. Ideally their prediction was accurate.

When you’re delivering production quality stuff, quality is super important. If we’re putting software into production, quality, scalability, performance, localization, and lots of other concerns are important. So, finished development work should be built, tested, and reviewed by others to look after all these concerns. Agile teams will talk a lot about “potentially shippable software” which really means that they may not have built enough of it to ship yet, but once they do, the quality is high enough that they could ship it confidently.

Development work focuses on predictability and quality

Discovery work

One of the tragedies in software development, and all product development for that matter, is that much of what we build doesn’t succeed. It doesn’t deliver the benefit we’d hoped. So, that’s a problem. But, even before that, it takes a bit of time to learn enough about the problems we’re solving to make good decisions about what we should build. We use discovery work to do all that. To answer questions, to test ideas, and to avoid – as much as possible – wasting time over-investing in quality stuff we shouldn’t have built in the first place.

We want to learn as quickly, cheaply, and safely as we can. So velocity is important during discovery too – but this is learning velocity.

Discovery work focuses on fast learning and validation

Because the goal is learning, not working software, a discovery learning loop looks a bit like this:

It starts by describing:

  • What we believe is the problem we’re solving and for whom
  • The solution we’d build to solve it
  • How we’d measure success

That’s our bet, our best guess, our belief, our hypothesis. All of those are uncomfortable words for people who believe they’re building the right thing. But, the truth is, we’re always making a bet that we’ll get value. Embedded in that bet are lots of assumptions, risks, and maybe some questions. To focus our learning, we’ll choose the assumption, risk, or question that scares us the most and identify an experiment or method to learn. Then do it. Then use what we’ve learned to change all those going-in beliefs about problems and solutions.

Sadly, one of the most time consuming and expensive ways to learn is to build potentially shippable software. So we don’t – unless we really can’t come up with any other way to learn, or we’re really confident our bet is good. Remember, we’re not betting we can build it on time. We’re betting that people have the problem we’re solving and will happily try, use, and adopt our solution.

The most expensive way to test your idea is to build production quality software

That’s how a learning loop works. And there’s a few things you should know about it.

We do all this as fast as we can. In hours when possible. Sometimes it may take days. But, we hope it doesn’t take weeks. So, lots of discovery learning loops should fit in a typical 2-week sprint.

Discovery work often results in killing ideas. At the end of every test you’ve got a decision to make: build it, kill it, or keep learning. Yes, what I’m really saying here is discovery work can and should result in killing ideas. Not everything goes forward. This can make some folks really uncomfortable.

We time-box discovery cycles. To keep discovery costs from running away from us, we’ll timebox a test or experiment from a few hours to a few days.

We can’t predict what we’ll need to learn next – not easily. When we learn something really valuable, it tends to really change our going-in beliefs, and really change what our next biggest assumption or question is. This can really suck.

Discovery loops chain together a little like this:

By now it should be clear that both development and discovery work are critical. But the mindset you approach the work with, and your process for doing it, are very different.

OK, it’s really 3 kinds of work…

To actually start building work software, you’ll need to make a lot of tactical design decisions. These may not be the risky decisions that need validation, but they still need to be made. It’s often designers that need to spend time ahead of development to refine and finish design work in preparation for writing code.

If you’ve validated the product is worth building, you’ll likely need to finish some detailed design work before you write code

It’s happening all at once

It would be super-cool if we could all focus on discovery work, get it done, then move our focus to tactical design and development. And that could work if all team members had the same skills. But since some are good at writing code, some are good at user experience design, and others are good at a variety of other things, we’ve got an opportunity to be doing many kinds of work at once. So we do.

Discovery work happens concurrently and continuously with development work.

I draw the conjoined model a little like this these days.

Discovery work uses irregular cycle lengths. It’s “Lean” in that we’re trying to make the discovery cycle as short as possible. Ideas in discovery mutate and very often get abandoned. The best move forward into more deliberate development cycles. I’m not sure how to show all that stuff in a single drawing. But, I’m trying to in the one above.

Discovery and development are shown in two tracks because they’re two kinds of work, and two kinds of thinking

Two tracks, not two teams

But, you shouldn’t think of it as two processes – just two parts of one process. And, I think you’re doing developers and others on the team a disservice not to involve them in discovery work.

There’s usually more than enough discovery work to do and lots of ways to involve the whole team in doing it. If you feel pressure to shorten discovery work to “feed the beast,” it usually means you’re making decisions to build software before learning enough to be confident that you should. In the best case the outcomes are uncertain and usually the outcomes are just bad.

The whole team is responsible for product outcomes, not just on-time delivery

Busting dual-track myths

Let me hit the biggest misconceptions people have with the model again.

Myth: Discovery is a process that precedes agile development. It shouldn’t.

Discovery is a necessary part of product development. Practice it with the same agile and lean principles in mind.

Myth: All work moves from discovery to development. It doesn’t.

If we’re doing discovery right, we substantially change and kill lots of ideas.

Myth: The discovery team is different than the development team. It shouldn’t be.

While a product manager, designer, and senior engineer may lead and orchestrate discovery, they must Involve the whole team in discovery tasks wherever possible. Keep discovery work and progress visible to the whole team.

Myth: Once you move from discovery to development, discovery work done. It’s not.

This misconception is something that really bugs my friend Jeff Gothelf. He sees the production-quality software we build as our last-best experiment.

Keep measuring and learning even after you ship.

From Jeff Gothelf’s perspective, it’s all discovery and we learn from everything we make; be it a paper prototype, or the next feature in your production software. I agree with him.

There’s lots more to this story

I’ve talked conceptually about what discovery and development work is, and why you combine them in the same process. But, I’ve said very little about how you do this in practice. You should be feeling a little unsatisfied. Sorry about that.

But, this is the first article in a series I’m writing. Next articles will cover:

  • How to keep discovery visible in a typical Agile process like Scrum
  • How to adjust typical Agile planning, standup, and review meetings so they focus on both discovery and development
  • How to think through your next best experiment and scale discovery investment along with confidence

What questions are you left with? What’s your biggest challenge doing any of this stuff? Please let me know what I should be talking about that I haven’t mentioned above.

Shameless plug

I teach classes in Scrum Product Ownership. But, they’re really classes about product management and design in an Agile context. Because, do you really need yet another class on Scrum? I’ve got upcoming classes scheduled with my friend Jeff Gothelf, author of Lean UX and Sense & Respond. The two of us tackle product thinking, discovery work, and this sticky dual-track stuff head-on. You should consider coming. Or tell someone in your organization that needs to understand this stuff about the workshop.

Opportunity Canvas

An Opportunity Canvas is a simple one-pager I like to use to facilitate a discussion about a new feature or capability. It’s put together in the spirit of the Business Model Canvas or Lean Canvas which are fabulous tools for discussing new products. But, unlike those canvases, the Opp Canvas assumes you’ve got a product already out there so you won’t need to reconsider the operational or revenue model – which is what those other canvases ask you to deal with.

filling-out-an-opp-canvas  2-opportunity_canvas

Because we’ve got so many good ideas for features we could add, we should consider the specific user’s problems we’re solving, and how we think they would use your solution to solve them. And, since it’s not only about users, you should discuss how users being challenged hurts your business, and how helping them helps your business. This all helps to figure out how we’ll measure success. The Opp Canvas helps drive that discussion.

If you just want to give the thing a try, go ahead and download a pdf here.

If you want to tailor it to fit your needs, here’s the original document. It’s laid out in PowerPoint, so it’s nothing fancy.

Stay tuned

I’ll write a more full featured article on this later. For now, I needed to get the files in a more obvious place to download.

 

 

Common Agile Practice Isn’t for Startups

Why common Agile processes like Scrum and Extreme Programming can cause startups to focus on the wrong thing

When working with startups individually or coaching in an accelerator, I often get asked to do a basic Agile tutorial. And, every time I’m asked, I get this sinking feeling. What most people believe Agile development is today isn’t at all what you need if you’re a startup. In fact, trying too hard to get Agile “right” is a good way to slow down the stuff that should really be happening.

Common Agile Practice is for Delivery

When most people think of common Agile practice today, they think of this Scrum/Extreme Programming hybrid – or XcrumP as I like to call it. It goes a little like this.

  1. A product owner builds a backlog of user stories that describes your Minimum Viable Product – the smallest product you think will succeed in the market (stories came from XP, backlogs from Scrum).
  2. Prioritize the backlog highest priority first, (which is hard because we need it all, at least we’re pretty sure we do).
  3. Use a Sprint Planning Session to plan the details for 2 weeks worth of work (but we’re hopelessly optimistic so we often over-commit to 3 weeks or more).
  4. Start a 2-week Sprint (Scrum’s name for a time-boxed development cycle, and they could be as short as one week, or as long as a four).
  5. Every day hold a standup meeting (which actually feels like a status report to the people who are stressed because development isn’t moving fast enough).
  6. Every day move sticky notes around a task board (which looks more like a Kanban board).
  7. Try using some sort of tracking tool to track the backlog and progress (and show burndown charts which for some reason people really hate to create by hand).
  8. Use engineering rigor like test-driven development, automated acceptance tests, and continuous integration (but throw it out when it looks like we’re not going to get everything done in time).
  9. As stories are finished coding, the tester thoroughly tests them, and the product owner reviews them (but usually we hand off a pile of finished stories to the tester the last day of the Sprint and tell them to test it all, then watch the tester melt down).
  10. At the end of 2-weeks, stop and do a Sprint Review where we briefly show what we got done, and reflect on how we could improve (but we spend a lot of time arguing about whether things are really “done-done” because we want a high velocity, and then we make excuses for why we couldn’t get 3 weeks of work done in 2 weeks).
  11. Repeat steps 2-10 till done or out of cash, whichever comes first.

That’s the basic flow. And my snarky comments in parens are what I see usually go wrong. And sadly, they may sound way too familiar to some of you.

I remind people often that:

process isn’t skill

Understanding a process isn’t the same thing as doing it well. And, it takes a while to build the skill and discipline necessary to predictably deliver at high quality. But happily with a common Agile process like Scrum, you’ll get to stop and reflect on where you’re really sucking every couple weeks, and you’ll see that get better over time.

Common Agile practice today uses time-boxed development cycles to put just enough structure around the process of planning work, doing work, and then stopping to evaluate and course correct. This simple execution loop uses velocity, or the rate we’re delivering software as its most visible metric. And that makes sense considering of the key Agile principles (mentioned in the Agile Manifesto) is: “+Working software is the primary measure of progress.”

If you’re going to execute well, you’ll need to build these basic Agile muscles.

If you want a more thorough drawing, look at my Agile & Scrum Quick Reference Guide.

But all that emphasis on delivery velocity leads people to believe that that’s all Agile processes are about. And when you want more stuff faster, which we all do, that can be a pretty seductive draw.

Agile in the Startup – the Anti-pattern

A few guys in a garage programming day and night stopping only to eat pizza and play Call of Duty.

Is that the mental model you have for a startup? This is the sort of startup where the founders believe their idea is fantastic, so fantastic that their biggest problem is getting their big idea built faster so they can release it to much fanfare at a big launch party. A startup thinking this way might adopt an Agile development approach with the hopes of building faster, or to at least get a bit of visibility into how fast the team is actually going.

Imagine a Silicon Valley startup adopting Scrum so they can go faster.  Actually, don’t imagine it.  Watch this short excerpt from the HBO series Silicon Valley – but watch out, because there’s lots of “adult language.”  (If you offend easily – go back to just imagining it.)

Thanks to my friend Aaron for first showing me this. If you’re in a startup, start watching Silicon Valley for a good “scared straight” experience.

As silly as this video makes Scrum look, the video points out a few of the key benefits of an Agile process like Scrum, benefits like making a plan, and keeping work visible. In the video Dinesh says: “You see what he’s doing right? He’s trying to get us to compete so we work faster…” And, in spite of being mad about being manipulated, the programmers code faster so they won’t be outdone by each other.

OK, all that’s great. But for some of you, you already know that building more faster isn’t really your biggest risk. At least not to start with.

Most Startups are About Discovery

These days, thanks to Lean Startup thinking and Customer Development, we now know our biggest risk isn’t getting the software built, but validating that there are customers out there that want our product, and can use it. I’m going to call that stuff product discovery.

Now I suspect if you’re reading this, you’re familiar with Lean Startup’s build-measure-learn loop, but I’ll explain it anyway – from my perspective.

lean startup model

  1. Describe our big product idea (but recognize that it’s a hypothesis, we can’t assume people want it)
  2. Identify the riskiest assumptions hidden in our product idea (assumptions about who our customers are, and their needs, as well as assumptions about how they’d value and use our product)
  3. Separate out the few biggest assumptions (those that would sink your product if they weren’t correct)
  4. Identify an approach to validating those assumptions – your Minimum Viable Product Test (customers you could talk to, and potentially prototypes or examples they could engage with to validate your assumptions)
  5. Build your simple prototype (and write a few notes about how you’ll engage with customers to test your assumptions)
  6. Engage with customers to test your assumptions (pay attention to what you’ve learned as you do)
  7. Make sense of what you’ve learned, and rethink your big product idea
  8. Repeat steps 2-7 until you’re confident you’ve identified the smallest product you really need to build, or until you’re out of cash

There’s something very different about this process loop: the primary measure of progress during discovery isn’t delivery velocity, it’s learning velocity. And sadly, we can’t measure its features or stories completed. And, even worse, we can’t plan two weeks of it in detail because what we learn today can and should change what we do tomorrow.

When you’re doing discovery right, it could look a little like this team at the Nordstrom Innovation Lab.

Notice the Nordstrom Lab still uses time-boxes, 1 week in this case. But, they didn’t start the time-box by predicting how much they’d deliver, but with learning goals in mind. Then they iterated around the build-measure-learn loop as fast as they could.

What the Nordstrom team ended up with wasn’t really “high quality software” – it was more of a jankety prototype that worked well enough so that they could leave it behind and measure the stuff that mattered most: did sales people actually use the application? Did they actually sell more as a consequence? And, did Nordstrom customers like the experience of buying this way better? Honestly, the jury is still out on all those questions. Notice that you won’t see this application running in a Nordstrom store near you. But that’s not failure. It’s learning. In the words of my friend David Hussman:

“The difference between learning and failure is how much money you spend to do it.” — David Hussman @davidhussman

Discovery teams quickly figure out that what takes the longest time isn’t building working software, it’s getting time with customers in order to learn something that really slow you down. The Nordstrom team solves this problem by placing their small discovery team inside a teaming pool of customers that they could learn from. This allowed them to get around the learning loop many times a day. That’s a super-fast learning velocity.

Keep the spirit of Agile, and discount the dogma

If you’re in software development today, you really need to understand Agile development. But, if you’re a startup, be aware that common Agile practice is about predictable delivery and is best suited for the times when you’re confident you’re building the right thing. By using an Agile time-boxed development cycle, you can more predictably build it right.

If you’re biggest risk is building the right thing, focus on building your learning muscles.

Go back to original Agile values and principles. Remember that Scrum and Extreme Programming are good delivery approaches to using Agile thinking, but not the only approaches. As a team frequently ask yourselves these questions:

  1. Are we working together as a team collaboratively and effectively?
  2. Are we making our ideas visible fast so we can learn fast, whether it’s working software, or a simple paper prototype?
  3. Are we learning directly from our real customers, the people that will buy and use our product?
  4. Are we stopping frequently to take stock of what we’ve learned and to re-think our product idea, our plans, and the way we’re working?

Those four questions are what the manifesto really means from a startup’s perspective. Keep those basics in mind, forget all the other agile dogma you hear, and you’ll be using Agile right.

Design Studio Recipe

A simple recipe for using collaborative sketching with Agile and Lean UX teams

design studio pitchDesign Studio is a quick collaborative approach to considering lots of possible solution ideas for a new product, a feature, or enhancement.

In a design studio, everyone sketches and shares ideas. By everyone I really mean everyone: UI designers, developers, testers, product managers, business stakeholders, end users, customer service people, and anyone else interested. Everyone feels involved and engaged. Everyone quickly learns that the best ideas aren’t any one person’s but a mashup of everyone’s. And, on top of all this, it’s fun. And, you deserve a little fun.
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