Ideation: Where The Creative Meets The Scientific
In its most basic definition, ideation is the creation of ideas or concepts. Many see ideation as a purely creative process delivering innovative opportunities for individuals and organizations. As such, ideation is quite a powerful tool for designing the future. However, if the power of ideation isn’t harnessed in a way that allows for perceptive action to be taken, then it can’t be productive. Productive ideation is structured creativity culminating in testable hypotheses.
I define ideation as the process through which possible solutions to objectively identified root causes of a need or pain point, are brainstormed, prioritized, and formulated into hypothesis statements.
You might be thinking, “That doesn’t sound creative at all!” Oh, but it is. The art (and dare I say, fun) in the ideation process lies within the boundaries created by data. Data tells us where we need to focus our creative efforts. It also, along with other constraints, creates a space where we’re challenged and engaged.
Insights from our data analysis reveals a customer pain point that, if solved would improve the overall customer experience, and thereby our customer satisfaction and net promoter scores. We construct the barriers the data have provided us, and then begin the process of identifying possible solutions. It is up to us to creatively work within those barriers to come up with new and innovative ways to eliminate the root causes of the customer pain point. Somewhere between the barriers, resourcing constraints, and likely, several other obstacles, we must find testable solutions — this is where we meet the creative challenge.
There it is — the space or element of the ideation process that enables us to produce what is truly innovative — the creative challenge. Ideation without a creative challenge is unproductive and wasteful. Focusing the ideation process, with a creative challenge at its core, to resolve a pain point allows us to harness the power of ideation to address a specific problem in the context of the broader picture.
Important: Please notice that I said, “in the context of the broader picture”. No matter what you’re focused on, the big picture must be considered. Developing solutions without first understanding the big picture is a trap that many individuals and organizations fall in to — leading to unanticipated, and often undesirable up and down-stream impacts. This issue probably warrants its own discussion. For now, just keep it in mind.
Within the space of the creative challenge, we find a playground for problem solving.
Note: If you’re looking for inspiration, Michael Michalko, in his book Thinkertoys: A handbook of creative-thinking techniques provides readers with fun and ingenious ways to take on the creative challenge. I’ve used many of Michalko’s techniques, and I find that they remove some my preconceived notions allowing me to see what I may not have otherwise.
Think of the creative challenge as the smooth cream between two crunchy wafers. One wafer is made of data boundaries, and the other is made of hypotheses. When put together, you get the sweet cookie sandwich of the ideation process. These crunchy wafers are — yep, you guessed it — the scientific portions of the ideation process.
What do data provide us? Nothing, in its raw state. You have to analyze it, beyond basic statistics to extract the discernible information. True analytics takes a deep-dive to figure out where the pain is coming from, and why it hurts. This often includes immersion in and observation of the problem at hand. The result are insights. Insights create our data boundaries, which help to frame the creative challenge.
Insights are also vital for hypothesis building. Insights are what we know to be true based on the information we have available. These truths become the building blocks of our hypotheses.
The word hypothesis may take you to back to a dreaded college class you still have nightmares about, but I’d like to take the horror out of it.
What is a hypothesis, really? It is a proposed solution. The proper definition says that it is a proposed explanation, but for application in ideation I use the word solution. You can break a hypothesis into three distinct parts.
1. Problem or question
2. Insights (data-based)
3. Variables (independent and dependent)
Each part provides information that is used to create a single statement — the hypothesis statement. I’ve found that the most effective hypothesis statements involve one dependent and one independent variable. Getting scary again? Well, this example should help.
Phrased as a problem: Production for Medication Z needs to be increased due to demand. Extract from Plant Y is required for production, but Plant Y’s growth rate is too slow to support the needed increase.
Phrased as a question: Can Plant Y’s growth rate be improved to support increased production for Medication Z?
- Medication Z production, using extract from Plant Y, could be increased if Plant Y had a faster growth rate.
- Chemical X makes plants in the same family as Plant Y, grow faster when applied to plant leaves.
Dependent: Plant Y Growth Rate (the observed element that is expected to be impacted by the independent variable)
Independent: Chemical X (the outside element being applied)
If Chemical X is applied to the leaves of Plant Y, then Plant Y will grow faster.
In this simple example, the proposed solution is to use Chemical X to try to make Plant Y grow faster, so the extract can be produced more quickly to increase production of Medication Z. Not so scary, right? We actually formulate hypothesis statements all the time about things in our daily lives without realizing it. (And unfortunately, without the proper insights to support them, but I digress.)
“If we hire another project manager, we’ll eliminate overtime for the other project managers.”
“If I rearrange the furniture, it will make the room appear larger.”
“If I dye my gray hair, I’ll look 28 instead of 38.” No? Just me? Okay. Well, you get the point.
The Creative Meets The Scientific
Let’s make the cookie!
The crunchy scientific wafers — data boundaries and hypotheses — are what make ideation purposeful and actionable. The creamy creative challenge is what makes ideation innovative and inspired. Ideation is not the delivery of a solution, it’s merely the means by which solution options are developed. Hypotheses are the output that can be tested for feasibility and viability. It’s important to remember that as long as humans, and then by default, human emotions and biases are involved in solution development, all possible solutions must be tested before full implementation. This is true for problem-solving on the individual level, as well as the organizational level.
Not all our hypotheses will be proven through testing. For example, I did’t really look 28 again when I dyed my hair, so if I want to look 28 again, then I’ll need to find a new solution (or give it up). For this reason, testing or evaluation becomes the next step in solution finding. You cannot skip from identifying the problem, directly to solution implementation. Well, I guess you can, many actually do. If you do, however, you’ll likely be left with even more problems.
The ideation process is just a piece of the problem-solving puzzle, but it’s a critical one. Taking the time to properly formulate possible solutions will put you or your organization in an infinitely better position for not only solving the problem at hand, but also making sure the solution doesn’t create more problems for you to deal with later.
Who wants a cookie?!