Ultimately, every day we get to spend with our (internal or external) customer is one step closer to knowing what the real problem is.
Finding a way to get to that dirty underbelly as quickly and intimately as possible means the difficult task of always trying to imagine being in our customer’s shoes … and then asking questions of the supplier with the intent to feel viscerally.
- What is the supplier doing?
- Do they really understand our problem?
- Is this all working??
And this is where storyboarding, with its ability to frame questions and answers in a way that invites dialogue, can come in handy for data science.
A few years ago, plagued by poor communications and outcomes, data science latched on to the concept of telling stories with data.
Having seen first-hand our audiences being overwhelmed by data-driven dialogue, we had to look for alternatives. And we found the WHY of using visuals and narratives as described by Brent Dykes in his “Essential data science skills” article simply too compelling to ignore.
It’s one thing carving out time to learn a new skill but how does one find motivation? For that, we went to the film industry … possibly the true masters of visual storytelling.
So we read Studio Binder’s guide to storyboarding and then went through its repository of movie favourites in storyboard form. And in all honesty, the thought of trying to wrangle a customer’s problem on a sketchpad first was a lot more inspiring!
Of course, that still left us with how to effectively work data into a storyboard for an audience of C-levels, engineers, managers and others. Thankfully, we found Nancy Duarte and gobbled up her ideas on humanising data.
For us, storyboards have now become guideposts for the path we and our customers need to take.
- 1 1. Storyboarding helps you validate that there is a problem
- 2 2. Storyboarding helps you reach common problem understanding with the customer
- 3 3. Storyboarding shows them that you are doing something
- 4 4. Storyboarding with early financials will give you a sense of how to get to a sound business case eventually
- 5 5. Storyboards can be tailored to reach different stakeholders
1. Storyboarding helps you validate that there is a problem
One of the early mistakes we made was starting our storyboarding process during data analysis. Too late … unless you’re confident you understand the problem as the customer sees it.
Now we start with the goal of making sure we can first see the problem via data, which isn’t always as easy as it sounds. But it gives us confidence that the problem is tangible.
2. Storyboarding helps you reach common problem understanding with the customer
By replaying the problem back to the customer in your words, they get to understand your process, and you get to understand theirs.
You also have the opportunity to refine the problem and the customer will likely sense that you’re genuinely trying to understand and acknowledge their pain.
3. Storyboarding shows them that you are doing something
Customers usually want to know that something is happening. A picture at a time, with a hint of progress, can do wonders.
More importantly, as they see what you’re doing, that black box becomes less of a black box.
4. Storyboarding with early financials will give you a sense of how to get to a sound business case eventually
We need to find out quickly what makes the customer tick, and preferably as far away from the finish line as possible.
Introducing cost estimates is a surefire way to get an early gauge of how bad the problem is, how much your customer cares about it and how off track you potentially are!
5. Storyboards can be tailored to reach different stakeholders
Like horses for courses, the same storyboards may not necessarily work for different tiers of audience in your customer domain. And that’s why it’s critical to use tools that allow multiple storyboards off the same underlying data.
Make no mistake, it is time consuming and exhausting. We’re in effect front-loading effort in the hope of more certain future gains. Clarifying the problem extensively never meant that all the other work of data cleaning, transformation, model building and machine learning application stops.
But it does give us the opportunity to self-correct before the last mile … without too much collateral damage.
And helps us build the all-important narrative and business case brick-by-brick with our customer.
“All his life has he looked away… to the future, to the horizon. Never his mind on where he was… what he was doing” — Yoda
The reality is, even if the business problem was defined adequately, any usable insight is unlikely to work if decision makers don’t believe the process of how we got there. And that usually happens if they aren’t part of the journey in the first place.
But if we participate in the customer’s version of the process, we give ourselves a chance. We might just end up spending enough time with them to allow trust and respect to naturally build up.
Of course, the quality of our work had better be decent and the numbers must work.
And then, they might just cross that bridge on your say-so …