Juice Analytics

The job of each slide in a presentation is simple: 1) the headline should fit neatly in the logic flow of the presentation storyline 2) the data on the slide should provide the best possible analytical underpinning for the headline.

I have worked out a simple hierarchy of supporting data. As you are building your slide, challenge yourself to move as far up this hierarchy as possible.

Best

• Irrefutable data: trended, statistically-significant, robust data. Even a hostile audience has to admit your data closely reflects reality.

• Substantial data: point-in-time data or directionally accurate data. Small surveys are likely to point you in the right direction, even if their precision is questionable.

• Expert commentary: quotes from industry experts can be considered a synthesis of a lot of information

• Anecdotal data: one or two data points or examples that support your case.

• Quotes: Comments from customers, suppliers, employees, etc. can be powerful evidence to make your case. However, a clever audience recognizes that it isn’t too hard to pick out a few quotes that make your case.

• Your opinion: From the perspective of the audience, your opinion is too biased to be considered supporting evidence.

Worst

The best presentations are compelling stories. The audience is along for a ride carrying them from an initial understanding to a new, shared understanding.

However, the storytelling style used in most media (TV, movies, fairytales) isn’t well suited to business presentations. Mimicking this style is a trap that is easy to fall into. Instinctively, we want to write a presentation that carries our audience from one clue to the next until we arrive at an exciting, even surprising conclusion.

The structure of classic storytelling (as outlined by Tim Knight & Associates) is as follows:

1. Context: setting the scene
2. Foreshadowing: hint at the unexpected ahead
3. Dramatic unfolding: building interest, conflict, tension
4. Climax: outcome and resolution
5. Denouement: wrapping up the story

Though tempting, this approach is bad for a business audience. While it may flow easily for an author, it is frustrating for the audience.

For busy executives, getting to the point is of the essence. It is far better to use a structure that gives away the climax in the beginning, such as:

1. Climax: Conclusion
2. Context: Background to ensure everyone understands the situation
3. Dramatic unfolding: a) analysis framework; b) supporting evidence
4. Climax: Conclusion, again

Boring, I know. But respectful of your audience.

I’ve recently developed an interest in “edge cases” – the extreme situations or data points that fall far outside the norm.

It was first piqued when I read a post by James Vornov about the impact of extreme cases on decision making. He notes: “Studies of decision making have shown that people are strongly influenced by single, uncommon events. Even when the pattern of frequent events indicates one type of behavior, the uncommon event prevails.”

Edge cases do more than create the deepest impression; they also offer rich ground for learning. Consider two catalysts for learning: 1) frequent but ordinary events and 2) extreme events. Each offers a different type of lesson. When we learn from the ordinary, we gain the ability to predict likely outcomes and put clear dimensions around expected results. Learning from the edge cases is wholly different: it helps us define the bounds of reality. It tests our assumptions and creates sharp contrasts.

Storytelling is just one example where edge cases are a teaching tool:

• The legal profession uses the extreme cases to define precedents and test the limits of laws
• Engineers conduct stress testing on materials or products to understand the limits of capabilities. Similarly, programmers test code by defining edge cases.
• Individually, I think we learn most about ourselves in situations when we experience something new, unusual, and challenging.

Another way to view edge cases is that they test our common sense. Tato on Everything2 points out that “as science pushes our understanding of the universe and our selves, we are confronted with new complexities and edge cases where these instincts [common sense] are actually dysfunctional, or wrong.”

Michael Feldstein offers a similar view in his blog when he says: “In any field of inquiry, the edge cases are where some of the most interesting work gets done.”

In each case, edge cases help us understand the far reaches of the possible. They help us map out reality. In a future post, I want to talk about how businesses can use edge cases, in particular outlying customer data points, to better understand their products, customers, and marketplace.