Editor’s note: The following is a guest post from Heap. If you’re interested in writing a piece for us, contact firstname.lastname@example.org
Sacsayhuaman is a large, fortress-temple complex located outside of the former Inca capital Cuzco. Built in the mid-15th century CE, its structure accommodated over 1,000 Inca warriors, served as a temple and location for Inca ceremonies, and stored vast amounts of textiles, weapons, metals, ceramics, and armour.
Designed by four architects, the fortress is an engineering marvel. Rather than use mortar to join its blocks together, the Incas used finely cut polygonal blocks — many over four metres tall and weighing over 100 tons. The stones are interlocked so tightly that a piece of paper can’t slide between them.
Though the mastery of the Sacsayhuaman architecture has puzzled researchers for years, retired architect and construction manager, John McCauley, offers this theory:
“…the steady rise in mankind’s mastery of technology has taken place over thousands of years of trial and error; mastery of a successful technique in moving heavy stones, or in carving them, has only occurred because of the knowledge passed on through the failure and success of countless ancient engineers who were willing to experiment with a new thought, and have at their disposal a seemingly endless field of labor to execute their ideas.”
Trial and error.
Failure and success.
Willing to experiment.
Sound familiar? They should; they’re the same principles we apply to products today! It took workers more than 60 years — and countless small wins — to build the ancient fortress. Indeed, the mastery of Sacsayhuaman’s architecture shows us just how important incremental progress is on the path toward major innovation.
Striving for perfection or missing out on growth?
Every product leader wants to build the next product that changes the world. Because of this, it’s easy for product folk to obsess over what the final version of a product should look like — before they even begin to build it.
One of the biggest mistakes we see product teams make is shooting for perfection at the beginning. Not only does the state of perfection rarely exist, but even when does, it’s nearly impossible to reach right away.
At Heap, we believe that product teams can build and improve their product most effectively when they take a data-driven, experimental, and iterative approach to product development. This involves forming and testing hypotheses, figuring out what to measure, making small improvements, and learning from every single experiment — whether successful or not.
Another way to think about this: Try as many things as you can. See what works, find out what doesn’t work, and then understand why.
In the book, “Art & Fear: Observations on the Perils (and Rewards) of Artmaking,” authors David Bayles and Ted Orland recount a story: a ceramics teacher divides his class into two groups. Students in group A were graded on the quality of one piece at the end of the semester. Those in group B were graded simply on the volume of pieces they made, regardless of quality.
On the final day of class, the teacher noticed something interesting: students in group B — whose only instruction was to make a lot of pieces — ended up with sculptures that were better in quality than those from group A. Why? While the students in group B were churning out work, and learning from their mistakes, the students in group A spent their time theorizing about perfection instead of incrementally improving their work.
So, what can product managers learn from this lesson? The more experiments you can run, the more lessons you can learn. The more lessons you learn, the better your ability to build a high-quality product.
Small wins make big impacts
Sure, it’s easy to say incremental progress leads to big and amazing things, but what do small wins actually look like in action? Let’s take a look at some companies known for their incremental, experimental product development approaches: Netflix and Airbnb.
Netflix is a great example of how to achieve innovation with small wins. For example, every product change Netflix considers goes through rigorous A/B testing before it can become the default user experience.
It’s not just major product redesigns that undergo extensive testing; the product team even experiments with images and titles to determine different combinations that increase content viewership. This is also how Netflix ended up producing its lauded “Skip Intro” feature. Each of these iterations within the product helps Netflix incrementally evolve and provide a more tailored, enjoyable user experience.
Then there’s Airbnb, another company that relies on experiments and testing to shape its user experience. Like Netflix, its product team also runs controlled tests (like A/B testing or split testing) to analyze the impact of feature changes and then decide whether to accept (or reject!) potential product changes. In addition to running loads of experiments on everything they do, Airbnb is committed to formulating hypotheses before validating them.
For example, say the results from a recent feature launch seem surprisingly higher than expected. Rather than just accept that data as the truth, Airbnb rigorously investigates the data by running different dummy experiments that can verify that its system—and its data—is working the way it’s supposed to.
Applying an experimental approach
At Heap, we believe that incremental improvements, when implemented constantly and repeatedly, pay enormous dividends. Many of our strategies are about pursuing smaller wins, forming and testing hypotheses, figuring out what to measure, making small improvements, and learning from every experiment.
Remember: As long as you’re being creative with your ideas and both rigorous and methodical about testing them (including recognizing when hypotheses are wrong and having the humility and ambition to change directions as needed), you’re doing it right.