Author: Nadine Touma Nadine Touma is a consultant in Insights, Strategy & Innovation based in Dubai. In her blog, Let’s talk business, she shares her 20 years experience in the corporate world and 5 as an independent consultant with real-life stories, simple advice and a no-nonsense approach that characterizes her work Original Post
Powerful insights cannot be drawn without quality data (well sourced, smartly collected, questioned, and benchmarked), however, quality data don’t automatically translate into powerful insights. As much as data analysis depends on the good functioning of our left brain (detail-oriented, systematic, structured, rational), insights, in my view, require us to tap into our right brain (holistic, synthetic, connective, intuitive). To me, insights are more art than science and I will address them in 3 parts:
Part 5 will talk about storytelling, Part 6 about putting that story into an impactful format and finally Part 7 will talk about delivering said story to an audience.
Insights are all about telling a story and, as such, they require you to make choices.
The example I chose to develop in Part 4, the case of COVID, to illustrate the importance of benchmarking, is a perfect example of making choices. I chose certain benchmarks and calculations to frame a senseless amount of raw data and tell a certain story… With different benchmarks or calculations, the story would have been different.
Truth is… You can make data tell any story you want. The key is to tell the story that matters to the business. In the words of Nobel Prize winner, Ronald Chase:
“If you torture data long enough, they will confess to anything”.
Making choices require a certain degree of confidence and courage that, I find, comes with experience and maturity. There is something reassuring in having plenty of data, spread across 100 slides, projected behind you… Somehow it makes you feel smart… And conversely, there is something a bit unsettling in presenting a 3 slide executive summary or a 20 slide top-line report with mainly key words and figures. We have all been there and hidden behind unreadable tables, wordy paragraphs, acronyms and scientific jargon. There is no shame in it, the only way is up!
Just as you should be able to easily summarise the plot of a book (without needing to enter into complex details, psychology of characters, and intricacy of settings), anybody walking out of your presentation should be able to summarise the main conclusions with relative ease.
Keep it simple but not simplistic.
You cannot and should not talk about everything your data tell you. Yes, even if it took you countless days and hours to get there and you had to get through 10,000 excel rows multiplied by 100 columns. You might find the slightest detail riveting but your audience has limited time (and attention) and will definitely lose focus if you enter in too much detail. You need to present the essence of it while being prepared for questions on the details if they arise.
Simplifying your data does not mean you take your audience for idiots but, on the contrary, that you are respectful of the time they allocated to you. It is not their job to make sense of what you are serving them. It is yours.
Simplifying is no easy feat as too much of it and it becomes simplistic and unfortunately then… you are the one turning into the idiot (gasp!)…
It’s all about the audience. It’s not about you.
My filter for simplifying data is understanding who my audience is and what is important/useful to them. Not what they want to hear, but what they needto hear. Believe me, when you look at things this way, it helps you sieve through all your data and retain the essential story. Separate what is good to know from what is critical to understand to make an informed decision.
Your audience is C level? Keep it big picture and highlight the major incidences on the business.
Your audience is operational managers? Show them how to use your data to engage consumers better / sell more / or whatever their objective is.
Your audience is fellow geeks? Well, go ahead and have a ball with the technicalities.
Bottom line is, you are not here to show off how smart you are but how useful your data is. Boring your audience to death will not put that point across. Trust me.
Insights have their own flow. They do not follow the chronological sequence you used to analyze your data.
My first job was at Disney Consumer Products and I will always be grateful for that first experience in my life that shaped me as a professional. I always say that I was lucky to be raised by the French, who account for my acute sense of analysis and critical thinking, but was equally lucky to work with Americans who taught me how to communicate impactfully. Let’s face it, the French are pretty bad at this.
One of my first assignments back then was to write a document to convince companies to sponsor a promotional magazine. I attacked the subject in the only way I knew how to (the French demonstrative way): Introduction: I tell you nothing… Core part (développement): Point 1, 2, 3, 4 (from less important to super important)… Conclusion: Tada!!!! You have to sponsor! My Marketing Director, who was an American back then, listened to me carefully for 15 minutes. After a short silence, he turned to me and said: “Why don’t you put the end at the beginning?”. Shock! Horror! Does that peasant know nothing about the art of demonstration????
And yet, he was so right. The gist of his advice was the following: “You have to sponsor because of 1, 2, 3, 4 (introduction). I have your attention? Great, let me elaborate (core / “développement”). No? Let us not waste anybody’s time”. Voilà!
Not every insights presentation can follow that type of structure. Often I had to demonstrate before revealing the conclusions. However, I always kept that great teaching in mind, in each slide I was designing. The key point has to be prominent, clear, and simple, the details (not too much) following at a different level. I will develop more on this topic in Part 6 as it refers a lot to how to format your insights.
Insights are connective while data are linear.
Insights take a piece of data and will give it context (benchmark), importance (ranking), relativity (connection to the rest of the data), and relevance (what does it mean for you).
Insights are all about interpretation/decoding for the business and this is why I find there is a part of intuition that has to fuel it (to then be backed by science and figures).
A few years back I had to work on segmentation of Gulf luxury consumers based on work that was done globally. To achieve that segmentation, we had to go through what is known in statistics as a “cluster analysis”. To put it very simply, it is a way to form groups that have characteristics in common and are differentiating from other groups (or clusters). The whole thing was done “scientifically” with the appropriate statistical software blah blah blah. However, what science was concluding, over and over, is that we had a group of Kuwaitis and Qataris that shared the same characteristics when it comes to their luxury behavior. Now if you know the region a little bit, you know that is impossible. You cannot have two consumer targets that are as dissimilar as Qataris and Kuwaitis. It took me months, going back every time with new statements/items to try to cut that group in two because I could not present that type of insight. Although statistically correct, it was operationally majorly inaccurate. If you are curious about the why of that particular conundrum, results showed that way because Qataris claimed to be a certain way, quite far from their actual behavior, and that made them look statistically like Kuwaitis. Mind you, it took me months to come up with that simple conclusion and then demonstrate it with data.
The truth is you can be great at data analysis and not great at insights. I have observed that the more gifted you are in mathematics, statistics, or any other scientific/technical skill, the more you might struggle in taking a bird’s eye view on your data, looking at the big picture, connecting the dots, and telling that story. One major reason is probably that, if you have that kind of profile, you tend to be far from the business and struggle in keeping the end in mind: what’s in it for me? How does it help me commercially, operationally, or strategically?
Knowledge of the market, understanding of the industry, awareness of your audience and their specific challenges are key to drawing powerful insights.
Data for data’s sake, unfortunately, leads you nowhere, is boring to your audience, and could discredit the work you’ve done, even when it is of high quality.
Always take the time to understand the above better, it will be time well spent, believe me. And pay particular attention to the way you are visually presenting your insights… The format is as important as content, perhaps even a bit more… Yes, I know it is very disappointing but the truth of the matter is average insights, well presented, will have more impact than brilliant insights, badly presented and confusing… Tune in for Part 6…