How To Make Developers Happier And Deliver Products Faster

When you’re building an innovative product, you can never be 100% sure that you’re focusing on the right things. The best you can do is hedge your bets.

You have a portfolio of bets, much like an investment portfolio. By choosing a mix of low-risk, low-reward and high-risk, and high-reward bets, you can optimize your overall chances of success.

There are different ways to do this. We rely on an approach called digital acceleration. It’s rooted in the history of the industry, as it brings back some things from the original Agile Manifesto. We’ve enriched it with insights from two decades of progress and our own experience gained from building hundreds of products.

Four ways to accelerate your product development

It’s not just about finding the fastest way to build software. Digital acceleration is about going from uncertainty to certainty in the fastest way possible. It’s about finding the path of least resistance toward a product that is actually useful and commercially viable. On this accelerated path, you will want to avoid:

• Distractions
• Processes replete with loopholes
• Slow decision-making
• Strong dependencies between individual elements of complex systems

They’re like the monsters from Stranger Things. If you don’t want them to pull you into the horrifying Upside Down, you need to fight back!

Your fight starts with taking a look at the quality of your process, and making improvements in the most critical areas:

1. Dual-track agile – instead of a linear process of discovery followed by development, you run development and discovery in parallel. New ideas are tested while features are being built, discovery insights inform development and vice-versa.
2. Customer-biased prioritization – stakeholder opinions can’t be the only basis for setting project priorities, because they often drive the team away from focusing on the end user. The only acceptable bias (focus, really) should be toward customer needs.
3. Fast experimentation with low-code/no-code – to reach product-market fit quickly, you want to test things quickly, learn from failures, and repeat. You want to experiment a lot, but also cut failed experiments immediately and without sunk cost bias. Low-code/no-code tools are perfect for this, allowing even non-technical workers to whip up a prototype. AI tools will make this even easier, enabling everyone to build software using just text prompts.
4. De-risking – proactively limit the risk of your bets by adopting a scientific mindset. Prioritize user and market research, and commit to always collecting data and making informed decisions, not guesses.

Though these are fairly standard ways to do things, extracting full value from these approaches is still difficult. Luckily, there are many market-tested methods that make it easier.

Methods to improve your development process

It’s not about what you use, it’s about how you use it. Any tool, framework, or methodology can only be as good as the person using it. The human element is the single most important make-or-break factor here.

To facilitate healthy change in your development process, you must convert all people involved to your ideas, and make sure that these changes fit into your company culture and business context.

You’ve surely heard of some, if not all of the nine methods below. You may have even applied them in your process, with varying degrees of success.

Avoid the common mistakes that I have listed next to each method, and you’ll increase your chances for meaningful process improvement.

1. Lean experimentation

Lean experimentation saves you from decision paralysis. Not sure what to do? Create a hypothesis, design an experiment, collect data, and validate.

One of the biggest mistakes people make here is a lack of commitment.

If an experiment fails, you cut it ruthlessly.

If you want to test a hypothesis, you need to be ready to dedicate the necessary resources toward it. When you do this half-heartedly, you end up with incomplete data, premature conclusions, and missed opportunities for innovation and improvement.

2. Outcome-Driven Innovation

ODI is based on the Jobs-to-be-Done framework, used to understand the exact outcome your customers need to achieve and how your product can help drive that outcome. Instead of starting with a product idea and trying to fit it to the market, you get a deep understanding of customers first, and then build what they need.

In their rush to reach the market, many executives might want to skip over the problem definition stage. The most important stage of this method!

If you’re going to use ODI, you simply must arm yourself and your team with patience, and take the time to understand the customers, their context, and their needs. Remember that the more knowledge you gain here, the faster the actual development process. So, you’re not wasting time if you spend a while at this stage, you’re actually saving yourself time in the future.

3. North Star Metric

Your North Star Metric is the guiding light for your business. The biggest value it provides is that it can end an extended discussion quickly, because if something doesn’t contribute to your North Star, then it’s not a priority, and you can ignore it for now.

On the other hand, if you choose the wrong metric it will become a siren’s call instead of a guiding light.

The wrong metric can be too broad or narrow, impossible to measure, or it might be out of line with the product’s value proposition.

Also, your North Star shouldn’t be the only metric you measure, naturally it has to be supplemented by other relevant metrics and qualitative feedback.

4. Lean analytics

Some ignore analytics entirely. Others buy many tools, but never get as much value as they’re paying for. Define exactly what you need to measure, invest in tools only measuring that and nothing else, and keep a lean analytics stack to avoid being distracted by noisy, useless data.

The main thing to avoid here is going too broadly and measuring too many things. You want the key metrics that are tied to business goals and reflect the customer's experience. If you measure everything you can, you’ll just generate lots of confusing data with few actionable insights.

5. Empowered product teams

It’s easy to lose sight of what’s best for the product, especially when everybody is focused on realizing a vision without validating it or analyzing alternatives. An empowered product team is encouraged to challenge management’s decisions and assumptions, and to fight for the good of the product and its users.

The biggest issue with this approach is that executives might not be willing to give up their control over the development process. It’s a problem of company culture, and it can be fixed by providing product stakeholders with evidence that empowered product teams deliver better outcomes.

6. Unshipping process

Shipping is great, but do you ever do the opposite and remove unnecessary features? It’s a great way to reduce code bloat, untangle project complexity, and stop tech debt from accumulating.

To do this properly, you need analytics and a tight feedback loop with your users. Otherwise, you might end up removing features that users actually love and drive them away. You shouldn’t rush the unshipping process, especially if you aren’t 100% sure that you’re not removing something important for the user or the business.

Always evaluate the impact of unshipping on the customer experience, revenue, and overall product strategy.

Be transparent and communicate the reasons for unshipping clearly and transparently to stakeholders and customers.

7. Design Sprints

The Design Sprint is a specific series of steps that you take in five days to build and test a prototype. This process was created and perfected at Google, and it’s the type of thing where you should really stick to the recommended steps and trust the process.

It can generate a lot of value, but it comes at a cost because a whole team is going to be focusing on this and nothing else for five days. Also, similarly to ODI, it’s easy to rush through the first stages of problem definition and research. These are critical for solving the right problem and building a solution that will resonate with customers, so don’t skip them if you want the sprint to generate meaningful results.

8. Pre-mortem and post-mortem analyses

A post-mortem analysis is pretty self-explanatory. After a project has ended, you take a close look and see what went wrong. But what if you did that in the beginning? There’s a lot to be gained from imagining the many potential ways your project could fail.

It’s a difficult exercise because we all want to be problem solvers, not problem seekers.

Nonetheless, this is one of those rare cases where it’s good to let your cynical flag fly and analyze your plans with a critical eye.

Honesty is a huge part of this process, and the main mistake here is simply not admitting to one’s own mistakes. If team members don’t feel comfortable being honest about their own mistakes, failures, or shortcomings, or if there is a culture of blame or defensiveness, this process will be worthless. You must create a safe and supportive environment and focus on learning and improvement rather than assigning blame or criticism.

9. Automation, automation, automation

Automation isn’t new. There’s different automation software for every type of company, and it’s relatively easy to find a solution that will suit your needs. If you haven’t invested in it yet, it’s time to take the leap! Even a few simple Zapier routines can already save you hours every day. There’s no telling how much time you could save if you really dig deep and take the time to automate all repetitive, manual tasks.

Consider tools like GitHub Copilot for coding assistance, which helps developers by suggesting code snippets and completing code automatically, reducing the time spent on writing boilerplate code.

For design-to-code automation, tools like Locofy transform designs from platforms like Figma into production-ready frontend code, streamlining the development process and saving significant time. This type of automation allows teams to focus more on creative and strategic aspects rather than mundane tasks.

Before you automate, make sure that you’re not automating a poorly designed business process.

An inefficient but automated process is not great because you’re perpetuating inefficiencies and wasting resources. Take the time to analyze and optimize the process before automating it. Consider the impact of automation on employees, and provide training and support to ensure a smooth transition and adoption of the new process.

To accelerate, get your process in shape

Making changes to your process will require lots of effort. Not just from key stakeholders, but also developers, designers, researchers, and all other teams. It won’t be easy, but it’s unavoidable.

The whole tech market is waking up to how much procedural fat had accumulated when the markets were all smooth sailing. Exercise the fat away, and your organization will be in much better condition to handle the challenges of the future.