September 3, 2017
Iterating is THE Requirements DisciplineOK. Let's get serious about software requirements, shall we?
The part where we talk to the customer and write specifications and agree acceptance tests and so forth? That's the least important part of figuring out what software we need to build.
You heard me right. Requirements specification is the least important part of requirements analysis.
THE. LEAST. IMPORTANT. PART.
It's 2017, so I'm hoping you've heard of this thing they have nowadays (and since the 1970s) called iterative design. You have? Excellent.
Iterating is the most important part of requirements analysis.
When we iterate our designs faster, testing our theories about what will work in shorter feedback loops, we converge on a working solution sooner.
We learn our way to Building The Right ThingTM.
Here's the thing with iterative problem solving processes: the number of iterations matters more than the accuracy of the initial input.
We could agonise over taking our best first guess at the square root of a number, or we could just start with half the input number and let the feedback loop do the rest.
I don't know if you've been paying attention, but that's the whole bedrock of Agile Software Development. All the meetings and documents and standards in the world - the accoutrements of Big Process - don't mean a hill of beans if you're only allowing yourself feedback from real end users using real working software every, say, 2 years.
So ask your requirements analyst or product owner this question: "What's your plan for testing these theories?"
I'll wager a shiny penny they haven't got one.
December 8, 2016
What Do I Think of "Scaled Agile"?People are increasingly asking me for my thoughts on "scaled agile", so I though I'd take a quiet moment to collect my thoughts in one place.
Ever since that fateful meeting in Snowbird, Utah in 2001, some commercially-minded folk have sought to "scale up" the Agile brand so it can be applied to large organisations.
I'll give you an example of the kind of organisation we're talking about: a couple of years ago I was invited into a business that had about 150 teams of developers all effectively working on the same system (or different versions of the same system). I was asked to put together a report and some recommendations on how TDD could be adopted across the organisation.
The business in question was peppered throughout with Agile consultants, Scrum Masters, Lean experts, Kanban experts, and all manner of Agile flora and fauna.
Teams all used user stories, all had Scrum or Kanban boards, all did daily stand-ups, and all the paraphernalia we associate with Agile Software Development.
But if there was one thing they most definitely were not, it was agile. Change was slow and expensive. There was absolutely no sense of overall direction or control, or of an overall picture of progress. And the layers of "scaled Agile" the managers had piled on top of all that mess was just making things worse.
It's just a fact of life. Software development doesn't scale. Once software projects go above a certain size (~$1 million), chaos is inevitable, and the best you can hope for is an illusion of control.
And that, in my considerably wide experience of organisations of all sizes attempting to apply agile principles and practices, is all that the "scaled agile" methods can offer.
I've seen some quite well-known case studies of organisations that claim to be doing agile at scale with my own eyes, and they just aren't. 150 teams doing scaled agile, it turns out, is just 150 teams doing their own thing, and on a surface level making it look like they're all following a common process. But they're still dogged by all the same problems that any organisation trying to do software development at scale is dogged by. You can't fix nature.
Instead, you have to acknowledge the true nature of development at scale; that these are highly complex systems, not conducive to overall top-down control, from which outcomes organically emerge, planned or not.
Insect colonies do not follow top-down processes. A beehive isn't command and control, even if it might look to the casual observer that there's a co-ordinated plan they're all following. What's actually happening is that individual bees are responding to broadcast messages ("goals") about where the pollen, or the threat, can be found, and then they respond according to a set of simple internalised rules to that message, co-operating at a local level so as not to bump into each other.
In software development teams, the internalised rules - often unspoken and frequently at odds with the spoken or written rules - and the interactions at a local level determine what the outcomes the system will produce. We call these internalised rules "culture". Culture is often simple, but buried so deep that changing the culture can take a long time.
In particular, culture round the way we communicate and collaborate tends to steer the ship in particular directions, regardless of which direction you point the rudder. This is a property of complex adaptive systems called "strange attractors".
Complex systems have a property called "homeostatis" - a tendency, when disturbed, to iteratively revert back to their original dynamic state, as determined by their strange attractors. Hence, a heartbeat can rise to more than 150 bpm, but will eventually return to a resting heart rate of about 70-80 bpm.
We can apply external stimuli to a system to try and change the way it performs, but the intrinsic properties of the agents within that system, and particularly their interactions, will ultimately determine the outcome.
Methods like SAFe, LeSS and DAD are attempts to exert top-down control on highly complex adaptive organisations. As such, in my opinion and in the examples I've witnessed, they - at best - create the illusion of control. And illusions of control aren't to be sniffed at. They've been keeping the management consulting industry in clover for decades.
The promise of scaled agile lies in telling managers what they want to hear: you can have greater control. You can have greater predictability. You can achieve economies of scale. Acknowledging the real risks puts you at a disadvantage when you're bidding for business.
But if you really want to make a practical difference in a large software development organisation, the best results I've seen have come from focusing on the culture: what do people really value? What do people really believe? What are people's real habits? What do they really do under pressure?
You build big, complex products out of small, simple parts. The key is not in trying to exert control over the internal workings of each part, but to focus on how the parts - and the small, simple teams who make them - interact. Each part does a job. Each part will depend on some of the other parts. An overall architecture can emerge by instilling a set of good, practical organising principles across the teams - a design culture, like we have in the architecture of buildings, for example. The teams negotiate with each other to resolve potential conflicts, like motorists on our complex road systems trying to get where they need to go without bumping into each other.
Another word for this is "anarchy". I advice you not to use it in client meetings. But that is what it is.
I think it's very telling that so many of the original signatories of the Agile Manifesto have voiced scepticism - indeed, in some cases been very scathing - of "scaled agile". The way I see it, it's the precise opposite of what they were trying to tell us at Snowbird.
This is why, as a professional, I've invested so much time in training and coaching developers and teams, rather than in management consulting. I certainly engage with bosses, but when they ask about "scaled agile" I tell them what I personally think, which is that it's a mirage.
November 8, 2016
Business Benefits of Continuous Delivery: We Need Hard DataSomething that's been bugging me for a while is our apparent lack of attention to the proclaimed business benefits of Continuous Delivery.
I'm not going to argue for one second that CD doesn't have business benefits; I'm a firm believer in the practice myself. But that's just it... I'm a believer in the business benefits of Continuous Delivery. And it's a belief based on personal and anecdotal experience, not on a good, solid body of hard evidence.
I had naturally assumed that such evidence existed, given that the primary motivation for CD, mentioned over and over again in the literature, is the reduced lead times on delivering feature and change requests. It is, after all, the main point of CD.
But where is the data that supports reduced lead times? I've looked, but not found it. I've found surveys about adopting CD. I've found proposed metrics, but no data. I've found largely qualitative studies of one or two organisations. But no smoking gun, as yet.
There's a mountain of data that backs up the benefits of defect prevention, but the case for CI currently rests on little more than smoke.
This, I reckon, we need to fix. It's a pillar on which so much of software craftsmanship and Agile rests; delivering working software sooner (and for longer).
Anything that supports the case for Continuous Delivery indirectly supports the case for Continuous Integration, TDD, refactoring, automation, and a bunch of other stuff we believe is good for business. And as such, I think we need that pillar to unassailably strong.
We need good data - not from surveys and opinion polls - on lead times that we can chart against CD practices so we can build a picture of what real, customer-visible impact these practices have.
To be genuinely useful and compelling, it would need to come from hundreds of places and cover the full spectrum of Continuous Delivery from infrequent manual builds with infrequent testing and no automation, to completely automated Continuous Deployment several times a day with high confidence.
One thing that would of particular interest to Agile mindsets would be how the lead times change over time. As the software grows, do lead times get longer? What difference does, say, automated developer testing make to the shape of the curve?
Going beyond that, can we understand what impact shorter lead times can have on a business? Shorter lead times, in of themselves have no value. The value is in what they enable a business to do - specifically, to learn faster. But what, in real terms, are the business benefits of learning faster? How would we detect them? Are businesses that do CD outperforming competitors who don't in some way? Are they better at achieving their goals?
Much to ponder on.
October 11, 2016
Code Quality is a Requirements IssueThe most fundamental aspect of Agile Software Development is responding to change. Whatever software we deliver today, the real value is in what we can learn from that, so we can deliver something even better tomorrow.
It's nature's search algorithm: evolutionary design. So it should come as no surprise that the cost of changing software is pivotal to our ability to succeed. The more change costs, the less change we can accommodate. The less change we can accommodate, the slower we learn. Simples.
In this respect, the cost of changing software can be thought of as a requirements discipline - ever bit as much as user stories and Specification By Example. Indeed, if we're being genuinely Agile, iterating is the requirements discipline, and everything else is about tweaking our seed values to make the search a little more efficient.
As so many have commented in recent years, failing on code quality means failing on agility. You can Lean ScrumBan all you like. But there's more to Agile than turning up to planning meetings.
September 30, 2016
Software Development Doesn't Scale. Dev Culture DoesFor a couple of decades now, the Standish Group have published an annual "CHAOS" reported, detailing the results of surveys taken by IT managers about the outcomes of IT projects.
One clear trend that emerged - and remains as true today as in 1995 - is that the bigger they are, the harder they fall. The risk of an IT project failing outright rises rapidly with project size and cost. When they reach a certain size - and it's much smaller than you may think - failure is almost guaranteed.
The reality of software development is that, once we get above a dozen or so people working for a year or two on the same product or system, the prognosis does not look good at all.
This is chiefly because - and how many times do we need to say this, folks? - software development does not scale.
If that's true, though, how do big software products come into existence?
The answer lies in city planning. A city is made up of hundreds of thousands of buildings, on thousands of streets, with miles of sewers and underground railways and electrical cabling and lawns and trees and shops and traffic lights and etc etc.
How do such massively complex structures happen? Is a city planned and constructed by a single massive team of architects and builders as a single project with a single set of goals?
No, obviously not. Rome was not built in a day. By the same guys. Reporting to one boss. With a single plan.
Cities appear over many, many decades. The suburbs of London were once, not all that long ago, villages outside London. An organic process of development, undertaken by hundreds of thousands of people and organisations all working towards their own unique goals, and co-operating or compromising when goals aligned or conflicted, produced the sprawling metropolis that is now London.
Trillions of pounds has been spent creating the London of today. Most of that investment is nowhere to be seen any more, having been knocked down (or bombed) and built over many times. You could probably create a "London" for a fraction of the cost in a fraction of the time, if it were possible to coordinate such a feat.
And that's my point: it simply isn't possible to coordinate such a feat, not on that scale. An office complex? Sure. A housing estate? Why not? A new rail line with new train stations running across North London? With a few tens of billions and a few decades, it's do-able.
But those big projects exist right the edge of what is manageable. They invariably go way over budget, and are completed late. If they were much bigger, they'd fail altogether.
Cities are a product of many lifetimes, working towards many goals, with no single clear end goal, and with massive inefficiency.
And yet, somehow, London mostly looks like London. Toronto mostly looks like Toronto. European cities mostly look like European cities. Russian cities mostly look like Russian cities. It all just sort of, kind of, works. A weird conceptual cohesion emerges from the near-chaos.
This is the product of culture. Yes, London has hundreds of thousands of buildings, designed by thousands of people. But those people didn't work in bubbles, completely oblivious to each others' work. They could look at other buildings. Read about their design and their designers. Learn a thousand and one lessons about what worked and what didn't without having to repeat the mistakes that earned that knowledge.
And knowledge is weightless. It travels fast and travels cheaply. Hence, St Petersburg looks like the palaces of Versailles, and that area above Leicester Square looks like 19th century Hong Kong.
Tens of thousands of architects and builders, guided by organising principles plucked from the experience of others who came before.
Likewise, with big software products. Many teams, with many goals, building on top of each other, cooperating when it makes sense, compromising when there are conflicts. But, essentially, each team is doing their own thing for their own reasons. Any attempt to standardise, or impose order from above, fails. Every. Single. Time.
Better to focus on scaling up developer culture, which - those of us who participate in the global dev community can attest - scales beautifully. We have no common goal, no shared boss; but, somehow, I find myself working with the same tools, applying the same practices and principles, as thousands of developers around the world, most of whom I've never met.
Instead of having an overriding architecture for your large system, try to spread shared organising principles, like Simple Design and S.O.L.I.D. It's not a coincidence that hundreds of thousands developers use dependency injection to make external dependencies swappable. We visit the same websites, watch the same screencasts, read the same books. On a 10,000-person programme, your architect isn't the one who sits in the Big Chair at head office drawing UMLL diagrams. Your architect is Uncle Bob. Or Michael Feathers. Or Rebecca Whirfs-Brock. Or Barbara Liskov. Or Steve Freeman. Or even me (a shocking thought!)
But it's true. I probably have more influence over the design of some systems than the people getting paid to design it. And all I did was blog, or record a screencast, or speak at a conference. Culture - in this web age - spreads fast, and scales rapidly. You, too, can use these tools to build bridges between teams, share ideas, and exert tacit influence. You just have to let go of having explicit top-down control.
And that's how you scale software development.
September 6, 2016
Empowered Teams Can Make Decisions The Boss Disagrees WithComing into contact, as I do, with many software development teams across a wide range of industries, you begin to recognise patterns.
One such pattern that - once I noticed it - I realised is very prevalent in Agile Software Development is what I call the Empowered Straightjacket. Teams are "empowered" to make their own decisions, but when the boss doesn't like a decision they've made, he or she overrules it.
Those who remember their set theory will know that if the set of all possible decisions a team is allowed to make can only include decisions the boss agrees with, then they are effectively working in the same set (or a subset) of the boss's rules.
That is not empowerment. Just in case you were wondering.
To have truly empowered development teams, bosses have to recognise that just being the boss doesn't necessarily make them right, and disagreeing with a decision doesn't necessarily make it a bad decision.
Unfortunately, the notion that decisions are made from above by more enlightened individuals has an iron grip on corporate culture.
Moving away from that means that managers have to reshape their role from someone who makes decisions to someone who facilitates the decision-making process (and then accepts the outcome graciously and with energy and enthusiasm.)
Once we recognise that there are other - more democratic and more objective - ways of making decisions, and that the decisions are just as likely to be right (if not more likely) than our own, then we have a golden opportunity to scale decision-making far beyond what traditional command-and-control hierarchies are capable of.
To scale Agile, you must learn to let go and let teams be the masters of their own destinies. You have no superhuman ability to make better decisions than a team full of highly-educated professionals.
The flipside of this is that developers and teams have to allow themselves to be empowered. With great empowerment comes great responsibility. And developers who've been cushioned from the responsibility of making decisions for a long time can run a mile when it comes a'knocking. Like prisoners who can't cope on the outside after a long stretch of regimented days doing exactly what they tell exactly when they tell you, devs who are used to management "taking care of all that" can panic when someone hands them a company credit card and says "if you need anything, use this". It reminds me of how my grandmother's hands used to shake when she had to write a cheque. Granddad took care of all that sort of thing.
This can lead to developers lacking confidence, which leads to them being afraid to take initiative. They may have learned their craft in environments where failure is not tolerated, and learned a survival strategy of not being responsible for anything that matters.
In this situation, developers rise up through the ranks - usually by length of service - and perpetuate the cycle by micromanaging their teams.
Based on my own subjective experiences leading dev teams (and being led): ultimately, developers empower themselves. The maxim "it's easier to ask for forgiveness than permission" applies here.
Now, t'was ever thus. But the rise of Agile Software Development has forced many managers to at least pretend to empower their teams. (And, let's face it, the majority are just pretending. Scrum Masters are not project managers, BTW.)
That's your cue to seize the day. They may not like it. But they'll have to pretend they do.
August 30, 2016
TDD 2.0 - Training Bookings & Book PreviewJust time to mention some Codemanship news.
I'm now taking advanced client bookings for the new & improved TDD 2.0 training workshop.
Incorporating lessons from 7 years delivering the original workshop for over 2,000 developers, the TDD 2.0 is more practical, in-depth and hands-on than ever.
There's more on refactoring, more on design principles, and... well, just more!
I've ditched the PowerPoint slides, beefed up the demonstrations and turbo-charged the exercises. The workshop's available in a 1, 2 or 3-day version to suit budgets and time constraints.
Attendees also get an exclusive 200-page book that goes into even greater depth, with a stack more exercises you can use to hone your TDD craft after the workshop. Ongoing practice is all-important.
You can find out more about the workshop, and grab a free preview of the first 7 chapters of the TDD book, by visiting the website.
I'm taking bookings now for delivery from Oct 10th and beyond.
August 9, 2016
TDD 2.0 - London Saturday Oct 8thJust a quick plug for the launch of the new and improved Codemanship Test-Driven Development workshop in London on Saturday October 8th.
Incorporating all the lessons learned from years of training and coaching developers in TDD, plus nearly 2 decades of real-world TDD experience, the improved workshop comes with an exclusive new 200-page book that goes into even greater depth and takes you to places that a 1 or 2-day workshop simply doesn't have time for.
The average price of a 2-day TDD training course in the UK is £1,300, and they're typically delivered by less experienced contractors rather than by the person who actually designed the course.
We're offering this intensive 1-day workshop for a mindbogglingly affordable £99, for which you get a packed day of learning, direct from the person who created the workshop, with a book worth £30 included in the price. The only thing a £1,300 course offers that we don't is catering. That's a very expensive lunch!
And we're running it on a Saturday, so you don't even have to get permission from the boss. I'd rather be surrounded by keen developers than be rich any day!
October 8th is the launch of the improved workshop, and the book, so join us and be the first to get your hands on it.
To find out more, and book your place, visit our Eventbrite page.
July 23, 2016
On The Compromises of Acceptance Test-Driven DevelopmentI'm currently writing a book on Test-Driven Development to accompany the redesigned training workshop. Having thought very hard about TDD for many years, the first 140 pages were very easy to get out.
But things have - predictably - slowed down now that I'm on the chapter on end-to-end TDD and driving internal designs from customer tests.
The issue is that the ways we currently tackle this are all compromises, and there are many gods that need appeasing, just as there are many ways that folk do it.
Some developers will write, say, a failing FitNesse test and come up with an implementation to pass that test. Some will write a failing automated customer test and then drive an internal design using unit tests and "classic TDD". Some will write a failing automated customer test that makes all the assertions about desired outcomes (e.g., "the donated DVD should be in the library"), and rely entirely on interaction tests to drive out the internal design using mock objects. Some will use test doubles only for external dependencies, ensuring their automated customer test runs faster. Some will include external dependencies and use their automated customer test to do integration testing as well. Some will drive the UI with their automated customer tests, effectively making them complete end-to-end system tests. Some will drive the application through controllers or services, excluding the UI as well as external back-end dependencies, so they can concentrate on the internal design.
And, of course, some won't automate their customer tests at all, relying entirely on their own developer tests for design and regression testing, and favouring manual by-eye confirmation of delivery by the customer herself.
And many will use a combination of some or all of these approaches, as required.
In my own approach, I observe that:
a. You cannot automate customer acceptance. The most important part of ATDD is agreeing the test examples and getting the customer's test data. Making those tests executable through automation helps to eliminate ambiguity, but really we're only doing it because we know we'll be running those tests many times, and automating will save us time and money. We still have to let the dog see the rabbit to get confirmation of acceptance. The customer has to step through the tests with working software and see it for themselves at least once.
b. Non-executable customer tests can be ambiguous, and manually reconciling customer-provided data with unit test parameters can be hit-and-miss
c. The customer rarely, if ever, gets involved with writing "customer tests" using the available tools like FitNesse and Cucumber.
DEV TEAMS who do BDD/ATDD: who writes your Cucumber/FitNesse/RSpec etc tests?— Codemanship (@codemanship) July 18, 2016
We're probably kidding ourselves that we even need a special set of tools distinct from the xUnit frameworks we would use for other kinds of tests, because - chances are - we're going to be writing those tests
d. Customer tests executed using these tools tend to run slow, even when external dependencies are excluded
e. Relying entirely on top-level tests to check that the work got done right can - and usually does - lead to problems with maintainability later. We might identify a class that could be split off into a component to be reused in ther applications, but where are its functional tests? Imagine we could only test a car radio when it's installed in a Ford Mondeo. This is especially pertinent for teams thinking about breaking down monolithic architectures into component-based or service-based designs.
f. When you exclude the UI and external dependencies, you are still a long way from "done" after your customer test has passed. There's many a slip twixt cup and lip.
g. Once we've established a design that passes the customer's test, the main purpose of having automated tests is to catch regressions as the code evolves. For this, we want to be able to test as much of our code as quickly and cheaply as possible. Over-reliance on slower-running customer tests can be at odds with this goal.
With all this in mind, and revisiting the original goal of driving designs directly from the customer's examples, it's difficult to craft a workable single narrative about how we might approach this.
I tend to automate a "happy path" test automated at entry point to the domain model, drive an internal design mostly through "classic" TDD, and use test doubles (stubs, mocks and dummies) to exclude external dependencies (as well as fake complex components I don't want to get into yet - "fake it 'til you make it".) A lot of edge cases get dealt with only in unit tests and with by-eye customer testing. I will work to pass one customer test assertion at a time, running the FitNesse test to get feedback before moving on to the next assertion.
This does lead to three issues:
1. It's not a system test, so there's still more TDD to do after passing the customer's test
2. It produces some duplication of test code, as the customer test will usually ask some of the same questions as the unit tests I write for specific behaviours
3. Even excluding the UI and external dependencies, they still run much slower than a unit test
I solve issue #3 by adapting my FitNesse fixtures to also be JUnit tests that can be run by me as part of continuous regression testing (see an example at https://gist.github.com/jasongorman/74f6a0a049e03b7030ab46e8b01128e7 ). That test is absolutely necessary, because it's typically the only place that checks that we get all of the desired outcomes from a user action. It's the customer test that drives me to wire the objects doing the work together. I prefer to drive the collaborations this way rather than use mock objects, because I have found over the years that an over-reliance on mocks can lead to maintainability issues. I want as few tests as possible that rely on the internal design.
Being honest, I don't know how to easily solve issue #2. It would require the ability to compose tests so that we can apply the same assertions to different set-ups and actions. I did experiment with an Assertion interface with a check() method, but ending up with every assertion having its own implementation just got kerrrazy. I think what's actually needed is a DSL of some kind that hides all of that complexity.
On issue #1, I've long understood that passing an automated customer test does not mean that we're finished. But there is a strong need to separate the concerns of our application's core logic from its user interface and from external dependencies. Most UIs can actually be unit tested, and if you implement an abstraction for the UI logic, the amount of actual code that directly depends on the UI framework tends to be minimal. All you're really doing is checking that logical views are rendered correctly, and that user actions map correctly onto their logical event handlers. The small sliver of GUI code that remains can be driven by integration tests, usually.
I don't write system tests to test logic of any kind. The few that I will write - complicated and cumbersome as they usually are - really just check that, once the car is assembled, when you turn the key in the ignition, it starts. A dozen or more "smoke tests" tend to suffice to check that the thing works when everything's plugged in.
So I continue to iterate this chapter, refining the narrative down to "this is how I would do it", but I suspect I will still be dissatisfied with the result until there's a workable solution to the duplication issue.
July 16, 2016
Taking Agile To The Next LevelAs with all of my Codemanship training workshops, there's a little twist in the tail of the Agile Software Development course.
Teams learn all about the Agile principles, and the Agile manifesto, Extreme Programming, and Scrum, as you'd expect from an Agile Software Development course.
But they also learn why all of that ain't worth a hill of beans in reality. The problem with Agile, in its most popular incarnations, is that teams iterate towards the wrong thing.
Software doesn't exist in a vacuum, but XP, Scrum, Lean and so forth barely pay lip-service to that fact. What's missing from the manifesto, and from the implementations of the manifesto, is end goals.
In his 1989 book, Principles of Software Engineering Management, Tom Gilb introduced us to the notion of an evolutionary approach to development that iterates towards testable goals.
On the course, I ask teams to define their goals last, after they've designed and started building a solution. Invariably, more than 50% of them discover they're building the wrong thing.
It had a big influence on me, and I devoted a lot of time in the late 90s and early 00s to exploring and refining these ideas.
Going beyond the essential idea that software should have testable goals - based on my own experiences trying to do that - I soon learned that not all goals are created equal. It became very clear that, when it comes to designing goals and ways of testing them (measures), we need to be careful what we wish for.
Today, the state of the art in this area - still relatively unexplored in our industry - is a rather naïve and one-dimensional view of defining goals and associated tests.
Typically, goals are just financial, and a wider set of perspectives isn't taken into account (e.g., we can reduce the cost of manufacture, but will that impact product quality or customer satisfaction?)
Typically, goals are not caveated by obligations on the stakeholder that benefits (e.g., the solution should reduce the cost of sales, but only if every sales person gets adequate training in the software).
Typically, the tests ask the wrong questions (e.g., the airline who measured speed of baggage handling without noticing the increase in lost of damaged property and insurance claims, and then mandated that every baggage handling team at every airport copy how the original team hit their targets.)
Now, don't get me wrong: a development team with testable goals is a big improvement on the vast majority of teams who still work without any goals other than "build this".
But that's just a foundation on which we have to build. Setting the wrong goals, implemented unrealistically and tested misleadingly, can do just as much damage as having no goals at all. Ask any developer whose worked under a regime of management metrics.
Going beyond Gilb's books, I explored the current thinking from business management on goals and measures.
First, we need to identify goals from multiple stakeholder perspectives. It's not just what the bean counters care about. How often have we seen companies ruined by an exclusive focus on financial numbers, at the expense of retaining the best employees, keeping customers happy, being kind to the environment, and so on? We're really bad at considering wider perspectives. The law of unintended consequences can be greatly magnified by the unparalleled scalability of software, and there may always be side-effects. But we could at least try to envisage some of the most obvious ones.
Conceptual tools like the Balanced Scorecard and the Performance Prism can help us to do this.
Back in the early 00s, I worked with people like Mike Bourne, Professor of Business Performance Innovation, to explore how these ideas could be applied to software development. The results were highly compatible, but still - more than a decade later - before their time, evidently.
If business goals are post-conditions, then we - above all others - should recognise that many of them will have pre-conditions that constrain the situations in which our strategy or solution will work. A distributed patient record solution for hospitals cannot reduce treatment errors (e.g., giving penicillin to an unconscious patient who is allergic) if the computers they're using can't run our software.
For every goal, we must consider "when would this not be possible?" and clearly caveat for that. Otherwise we can easily end up with unworkable solutions.
Just as with software or system acceptance tests, to completely clarify what is meant by a goal (e.g., improve customer satisfaction) we need to use examples, which can be worked into executable performance tests. Precise English (or French or Chinese or etc) just isn't precise enough.
Let's run with my example of "improve customer satisfaction"; what does that mean, exactly? How can we know that customer satisfaction has improved?
Imagine we're running a chain of restaurants. Perhaps we could ask customers to leave reviews, and grade their dining experience out of 10, with 1 being "very poor" and 10 being "perfect".
Such things exist, of course. Diners can go online and leave reviews for restaurants they've eaten at. As can the people who own the restaurant. As can online "reputation management" firms who employ armies of paid reviewers to make sure you get a great average rating. So you could be a very highly rated restaurant with very low customer satisfaction, and the illusion of meeting your goal is thus created.
Relying solely on online reviews could actively hurt your business if they invited a false sense of achievement. Why would service improve if it's already "great"?
If diners were really genuinely satisfied, what would the real signs be? They'd come back. Often. They'd recommend you to friends and family. They'd leave good tips. They'd eat all the food you served them.
What has all this got to do with software? Let's imagine a tech example: an online new music discovery platform. The goal is to amplify good bands posting good music, giving them more exposure. Let's call it "Soundclown", just for jolly.
On Soundclown, listeners can give tracks a thumbs-up if they like them, and thumb's down if they really don't. Tracks with more Likes get promoted higher in the site's "billboards" for each genre of music.
But here's the question: just because a track gets more Likes, does that mean more listeners really liked it? Not necessarily. As a user of many such sites, I see how mechanisms for users interacting with music and musicians get "gamed" for various purposes.
First and foremost, most sites identify to the musician who the listener that Liked their track is. This becomes a conduit for unsolicited advertising. Your track may have a lot of Likes, but that could just be because a lot of users would like to sell you promotional services. In many cases, it's evident that they haven't even listened to the track that they're Liking (when you notice it has more Likes than it's had plays.)
If I were designing Soundclown, I'd want to be sure that the music being promoted was genuinely liked. So I might measure how many times a listener plays the track all the way through, for example. The musical equivalent of "but did they eat it all? and "did they come back for more?"
We might also ask for a bit more proof than clicking a thumbs-up icon. One website I use keeps a list of my "fans", but are they really fanatical about my music? Judging by the tumbleweed when I alert my "fans" to new music, the answer is evidently "nope". Again, we could learn from the restaurant, and allow listeners to "tip" artists, conveying some kind of reward that costs the listener something somehow.
Finally, we might consider removing all unintended backwards marketing channels. Liking my music shouldn't be an opportunity for you to try and sell me something. That very much lies at the heart of the corruption of most social networks. "I'm really interested in you, Now buy my stuff!"
This is Design. So, ITERATE!
The lesson I learned early is that, no matter how smart we think we've been about setting goals and defining tests, we always need to revisit them - probably many times. This is a design process, and should be approached the same we design software.
We can make good headway using a workshop format I designed many years ago
Maintaining The Essence
Finally, but most important of all, our goals need to be expressed in a way that doesn't commit us to any solution. If our goal is to promote the best musicians, then that's our goal. We must always keep our eyes on that prize. It takes a lot of hard work and diligence not to lose sight of our end goals when we're bogged down in technical solution details. Most teams fail in that respect, and let the technical details become the goal.