For our new product Envato Elements, I convinced our boss to let us use Outcome Driven Innovation (ODI) to guide our approach. This generated useful insights about how customers measure the success of our chosen job-to-be-done of “sourcing digital assets for a creative project”. But most importantly, the results from our ODI project gave us the focus & confidence to make bold, product-shaping decisions.
Based on this experience, I’ve written an article on Medium that explores the step-by-step process we took to successfully implement ODI research for a new product in a short space of time. It includes screenshots and examples of the surveys, collateral, and end output to help provide practical guidance for those considering using ODI for their own products. Plus you’ll also find a summary of the important lessons that we learned in the course of this work.
This week I fulfilled a long-held dream of attending the annual meeting of Warren Buffett’s company, Berkshire Hathaway.
To mark the occasion, I’ve written a post on Medium about what it’s like to be there (hint: crazy & amazing), together with a summary of the top lessons on investing that I’ve learned over the years from following Warren Buffett.
These are just a few of the many biases that lead to flawed decisions.
Focus on where the holes ain’t
A classic example is a story about plane improvement in World War II. As bombers returned from battle, researchers analyzed the bullet holes in extensive detail. The military then reinforced the parts of the planes most often hit by bullets.
That is until one bright sparkpointed out they were reinforcing the wrong parts of the plane. They had been looking at places where a plane could get hit and still return safe to base. Instead, they should reinforce the other parts, where a bullet stops you making it back!
This is a classic situation of information bias and survival bias. We have plenty of available data, so we jump straight into analyzing it. But it’s actually the data we don’t have that matters. That is, the data about where bullet holes cause the planes to crash.
Avoid the narrow frame
Here’s another example. Various initiatives exist to help more women progress to senior roles in organizations. For example, more attractive maternity leave, childcare subsidies, and gender specific quotas.
But arecent studyfound a surprising fact. What was the number one initiative linked to a higher percentage of women in senior roles? Paternity leave. That’s right, an initiative not aimed at women at all.
This is a good example of framing bias. If we see female advancement as a women’s issue, we focus our solutions specifically on women. But the narrow framing of the problem prevents us from seeing other effective solutions. It turns out that when men get more involved in family life, then women get more opportunities at work. Plus, they also get the support at home needed to pursue senior opportunities.
Don’t just listen to the usual suspects
One last example. Think of the last time you did some customer research for your organization. How did you source your participants?
Chances are you used email, website notifications, in-store promotion and/or social posts. All these methods are convenient, easy to use, and very low cost (if not free). You may even have achieved a reassuringly large sample size.
But stop and think: did you hear from all the people you need to?
Did you go out of your way to survey people who are not currently your customers? What about inactive or occasional customers? What about those who haven’t even heard of your brand?
Your survey results could be like the bullet holes in WWII planes: obvious, available, and ready to analyze. But they may also be dangerously misleading.
Ask yourself: what am I missing?
So before you make a key decision or crunch some important data, stop and pause for a moment. Ask yourself: am I missing something?
Do I have the full picture? Have I got input from outside the usual suspects? Have I sought dissenting views or had people challenge my assumptions? Am I using too narrow a frame to define the problem?