Making Money Through Science

Businesses exist to make money; their purpose isn’t just to generate revenue, but to create profits, now and in the future. Generating profits means delivering products or services that people want to buy. The creation of what people want is the entire purpose of delivery pipelines. (NB: The rest of this article will use ‘product’ to refer to both products and services.)

Generate an idea

Determining what people want is not easy, but it can be simple. The best way to determine whether people want to pay for something is to put it in front of them. Some companies do this by creating a completely finished product which has been fully designed, architected, and tested before a customer sees it. They want it to be perfect before showing it to customers and getting feedback. There’s only one problem with this approach: they can’t be sure what the customer wants until it’s in front of them. It’s entirely possible to waste an entire product or service delivery budget creating something nobody wants. It’s a huge risk, whose upside (if you’re exactly right) is often more than outweighed by its downside (what if it turns out the product doesn’t actually have a market?).

Hypothesise

The only time we find out if a product is valuable is when we get feedback from the customer. That means the faster we get feedback, the faster we can decide whether we want to continue, change, or cancel the product. The same is true when changing products – a change is only valuable once a customer is using it, and can provide feedback on it. (The corollary to this is that until a product is being used by a customer, it has absolutely no value.)

The logical extension of requiring customer feedback to find value is to work in ways that enable feedback as quickly and frequently as possible. Get your product in front of a customer, and see what the feedback is. Then adapt. This is also known as applying the scientific method to product development – generate an idea, form a hypothesis about the idea, create a means of testing the hypothesis, test it, draw conclusions, and adapt.

Image is CC-SA

In order to test whether your new approach works, make sure you measure what matters – how long does it take for an idea to come into the company from the customer, be developed, tested, released, and be back in front of the customers, happily being used. Don’t measure the time in each stage, as the customer can’t see them. The only thing the customer cares about is how long it takes to deliver a working, usable product, from end to end. And all you care about is whether that time is stable (with some degree of predictable variation), and whether your changes are improving it.

Test

Shortening feedback cycles means changing the way you organise product development. Rather than focus on who answers to who, and drawing it in an org chart, focus your teams on rapidly delivering products to customers. The focus should move from working on each phase of development to working on what customers need.

If you need analysis, development, and testing, then put them all together so they can figure out how to respond to customers quickly. If you write software, put in testing and deployment automation, so you can rapidly deploy small changes that customers see immediately. If you work on a large product, with lots of dependencies, start working on separating the components so development in one area doesn’t require testing and changes in a completely unrelated area.

Conclusion

You’ve changed your company. You’re now looking at how product development works, rather than on how people work on product development. And you have a measure you can use to determine success. It takes less time than it did before to deliver new features and products. They’re higher quality, and customer feedback is improving. Your measures indicate that you can get new features out the door in a predictable amount of time ( between X & Y days).

Your focus is no longer on production, but on flow. Keeping it there can be difficult, but it’ll significantly improve delivery, which will improve profits now, and in the future.

Adapt

Your first experiment worked. Now it’s time to see how you can continue to improve it. What factors contribute to product delivery timelines? After you’ve identified them, think about how changing them will change your delivery time scales, and whether a change in one area will impact another adversely. Focus on the areas that appear to be bottlenecks, and improve them until they stop being bottlenecks. Then repeat.

Feedback

Help me adapt. Leave a comment, or reach out to me on Twitter (@nrcantor) to let me know what you think and what you’d like to hear about next time.

I first wrote this article for the OpenCredo blog

Fear Kills Improvement

I originally authored this piece for The Register. This is the original, unmodified version.

Fear is the Great Motivator

Fear is a great motivator. Fear pushes adrenaline. It primes our fight-or-flight response. It primes us for a confrontation. Fear shuts down our higher cognitive functions, priming us for a visceral response, on top of which we layer rationalisation. Fear ensures continued survival of our species in times of dire straits. When we are afraid, we have only our intuition and built-in responses to draw on. When we are afraid, we cannot accept feedback, respond to things which run counter to our expectations, or learn. And so, a culture in which fear operates is one in which no learning takes place. Fear kills change.

In the last 200 years, work has changed significantly. Most of us do not face daily threats to our continued existence. But our fear response remains. We still respond with adrenaline when threatened, or embarrassed; we still shut down; we still lose our capacity for higher reasoning and openness. And it kills improvement at work. It kills creativity. And it's common.

Needless to say, fear is a response borne of perception, not reality. There doesn't need to be a tiger in the bushes in order for us to think there's one there, and react accordingly. There doesn't need to be a threat to our continued existence for us to believe there is one. In a world where we are taught to define ourselves by how successful we are at work, how much money we make, how influential we are, and how people see us, threats to our continued existence do not have to be life-or-death. Job loss, income loss, prestige loss, or promotion loss all generate a similar response. And the idea that trying something, but not succeeding at it, is frequently tied to more than one of those losses, making us risk averse, and afraid of experimentation.

"The ability to learn faster than your competitors may be the only sustainable competitive advantage." - Arie de Geus

Knowledge-heavy roles (such as IT or management) require learning in order to be effective, or help the company succeed. Learning through experience and mistakes is necessary in any role that brings about change, whether the goal is figuring out how to convert page views into sales, or transforming your business into a leaner, more effective organisation.

Knowledge economies are driven by learning - the converting of information into knowledge and understanding. Without learning, we cannot progress; without learning, our companies can't adapt; without learning, we are doomed to eventual replacement by companies with newer ideas that we couldn't test. And this is a problem, because it's culturally ingrained - we are taught not to speak out in class, if we don't know the answer; we are taught not to ask too many questions; we are taught to keep our heads down when we don't know the answer. We are taught to fear failure. And so failure gets swept under the carpet, never to be acknowledged, never to be embraced, never to be learned from.

Agile, Lean, Kanban, and DevOps all attempt to remove this fear by explicitly creating conditions where experimentation and learning are encouraged. All too often, however, the adoption of these processes fail, not due to failures in the processes, but due to their incompleteness. To see how important addressing fear is, all we have to do is look back to the theory that gave birth to every one of these movements - Deming's Theory of Profound Knowledge.

Deming, A (Very) Brief Introduction.

Edward Deming revolutionised Japanese manufacturing, starting at the end of WWII. He went into Japanese companies, spoke with Japanese executives, and told them that in order to succeed, they would have to start thinking of organisations as systems, where optimising the system and optimising parts of the system are not the same thing. Deming had 14 points for management; point 8 is

"Drive Out Fear: Encourage effective two way communication and other means to drive out fear throughout the organization so that everybody may work effectively and more productively for the company."

Deming recognised something that has been shown repeatedly through research - fear inhibits learning. Deming encouraged management to see mistakes as opportunities for learning, and failure as a stop on the path of progress.

The Value of Mistakes

Mistakes are inevitable. By punishing mistakes a company (explicitly with firing, or implicitly through reduced career or salary progression) doesn't eliminate them, it merely ensures that nobody will talk about them. And nobody will talk about the fact that nobody is talking about them. The entire organisation will collude in hiding mistakes in order to avoid feelings of embarrassment or threats (Argyris, Knowledge for Action). Any company in which failures are not openly discussed, in order to be learned from (without any sense of blame or shame), is not learning effectively.

Companies rarely explicitly punish failure. Instead, there are unspoken rules about the acceptability and impact of failure - fewer promotions, reduced raises, fewer hours, worse reviews. These unspoken rules leave no room for improvement, and must be changed for a company to start learning. Words won't change them. Changing unspoken rules requires action. Admitting failure requires vulnerability, so creating a culture that learns from failure also requires vulnerability, usually in the form of managers making their own failures, and learnings, more visible. Making it obvious that everybody makes mistakes, and only by admitting them can we learn from them. This, in turn, gives their employees the opportunity to experiment, fail, learn, and improve, more visibly.

The scope for improvement through vulnerability is downward facing, only, meaning that managers can start improving things by admitting vulnerability to their staff, but the only way to create organisational change is for senior managers to admit their failures, to themselves, to their peers, and to their subordinates.

Conclusion

Admitting failure isn't easy. It can make us feel vulnerable. The alternative is worse. The alternative is not admitting failure, not admitting mistakes, not learning from things we know are, or were, wrong. Companies which can't learn from mistakes stagnate, and eventually fail.

Fear and change are mutually exclusive. Any organisation that creates a place for one necessarily drives out the other. If we choose change, and adaptability, and learning, we choose an organisational life with difficulties, challenges, and hard work, in order to maintain a culture that embraces and reinforces learning, whatever the source. While it sounds difficult, it's the only life I'd choose.