How to make your next big idea scalable
I recently came across a Freakonomics article that discussed scaling science–investigating why interventions that work well in experimental or research settings often fail to scale up.
“Scaling up a new intervention like a medical procedure or a teaching method has the potential to help thousands, millions, maybe billions of people.” –Stephen J. Dubner
Scaling, as we know, is essential to bringing any idea to market. When you fail to bring an idea to fruition, you also lose out on the impact it could make. There is a concept in implementation science (the study of methods and strategies that facilitate the application of research findings and evidence-based practice) called voltage drop that caught my attention. Because, not only is this a common pitfall among academics, many companies also fall into this trap when they begin to scale their innovations.
According to Freakonomics, a voltage drop is an identified good result in research that ends up being much less than the anticipated result when scaled. This is a bigger problem than many realize, because failing at scale can not only cost lots of time and money, it can create unexpected consequences such as losing confidence due to the initial over-hype of the idea. Failing to consider these issues as you scale means your innovation may never make it to market.
Factors that Contribute to Voltage Drop
One factor that contributes to voltage drop is setting admirably high standards for research. For example, say you want to source the best professionals to be a part of your research so you have the best results. You may start with 5-10 professionals, but when you go to scale, you need 100+. This forces you to either spend much more than expected to get the “best of the best” or dwindles the amount of talent in your pool. In other words, the impact goes down and the costs go up.
Let’s look at an example from John List, economist at the University of Chicago, who was part of the conversation in the Freakonomics article. In talking about the scaling revolution, List used the following example to showcase how critical it is to ensure original research is robust before scaling:
“Say I’m doing an experiment in Chicago Heights on early childhood, and I find a great result. How confident should I be that when we take that result to all of Illinois or all of the Midwest or all of America, is that result still going to find that important benefit-cost profile that we found in Chicago Heights? We need to know, what is the magic sauce? Was it the 20 teachers you hired down in Chicago Heights, where if we go nationally we need 20,000? So it should behoove me as an original researcher to say, “Look, if this scales up, we’re going to need many more teachers. I know teachers are an important input. Is the average teacher in the 20,000 the same as the average teacher in the 20?”
Fidelity is another core cause of voltage drop. In the case of innovation, fidelity means the level of functionality and like-ness that the prototype has to the final product, i.e. visual design, interactivity, content, functions and features, etc. For example, a low fidelity prototype is low-tech and basic; it’s not market-ready. A scaled idea reflects the integrity of the original. Therefore, you must be able to measure everything, even fidelity. This is critical to the implementation process. Ask yourself: Is this idea the same as it would present in the real world? Does it have the same components that will produce the same outcomes?
“Being able to measure fidelity well, from afar, provides another benefit to scaling up: it allows the people who developed the original program to ultimately step back. So they don’t become a bottleneck — which is a common scaling problem.” –Stephen J. Dubner
How To Prevent Voltage Drop
To overcome voltage drop, you must successfully find your way/experiment through it. Namely, it’s about the extended transformation journey. In other words, making sure that you truly adopt a mindset of trust as well as a learner’s mindset. Be willing to make adjustments; have humility. When you’re scaling, don’t assume the original idea is flawless. Where do you need to adjust?
Enter: Prototypes. Prototypes help you simulate fidelity and learn through a surrogate. You get to workshop/try on your idea in a “real-world” scenario. Then, you have the opportunity to work through any potential pitfalls before you actually launch the idea. In essence, practice makes perfect. Prototyping allows you to experiment and make adjustments as needed with lower risk. If you are able to address problems in the prototype stage, you will save time and money and have greater success when scaling the idea.
Learning to adjust your ideas is core to the work we do and the mindsets we teach and coach at Voltage Control. Learn more about how we can help you.
It’s also important to know that assumptions can even exist based on hard evidence, especially in the complex and shifting environment we all find ourselves in today. That’s why we must always stay curious and continuously learn.
How We Can Help
At Voltage Control, we are change experts that can use a vast array of facilitation and innovation methods to bring your team together to be more inclusive and accelerate the power of innovation; guide the process from start to finish. Our training can help you build the awareness and capability you need to not only overcome voltage drop but to make your ideas thrive in the market. We can also guide you through this process with our expert facilitation.
Some examples of how Voltage Control can help you combat voltage drop:
- Design a robust innovation process to promote continued dialog around efficacy and assumptions. This is why we institute a sustaining innovation cadence with all our clients.
- We lead you through the design thinking process to create prototypes, which help you simulate fidelity and learn through a surrogate.
Check out these services for more on how we can help:
Let us help you soar past voltage drop and bring your idea to (scalable) life today. Contact us for a free consultation.