When people talk about the forecasting/predictive analytics process, there is one crucial part we tend to miss out – the presentation. It is like running a marathon where we pour our blood sweat and tears into training, then in the race, we stop at the final mile. Everything you have done up to this point will all be for naught unless you get across the finish line. Similarly, with predictive analytics, our efforts will be fruitless unless our insight is effectively presented to people who can use it.
It goes with saying that the answers predictive analytics provides only create business value if your organization understands and can use them. Whether it’s a report, executive dashboard or meeting presentation, it is very common for insight to be overlooked due to lack of focus, being overly technical, or poorly presented.
Nobody Likes Boring Facts & Figures, So Tell A Story
I have made the statement a couple of times that demand planners are storytellers who use numbers as their language. It is important that you just don’t present numbers and a forecast but present a story that people can follow. Some people may think a story around the data is an unnecessary, time-consuming effort. They may feel the facts stand on their own and should influence the right decisions. Unfortunately, this is based on the flawed assumption that business decisions are logical and not emotional.
Our goal is to influence others to listen so they employ our numbers
This is the difference of reading an owner’s manual and a novel – while one has the facts, the other is what people actually like to read. And ultimately this is our goal – not to come up with a number, but to influence others to listen so they employ those numbers. To do this we need to present forecasts and data in a way that is simple and easy to understand.
When telling a data story, it is not unlike storytelling in general. Stories have a logical structure containing a beginning, middle and end. All stories have conflict which, in our case, is business questions like balancing supply and demand. The protagonist, or hero, is data insight, and he/she will answer those questions. It is the demand planner’s task to weave a narrative to enlighten the audience about the problems the company is facing and how they can be solved
Find The Right Format To Present Your Insight
Stories can be told in writing, in art, in a song, or a one-man monologue. I am not saying you should sing about your data, but you do need to identify the most meaningful format for presenting your forecast and data. To increase the effectiveness of your communications and presentation, this step should really be on your mind throughout the entire data analysis process. The purpose of the information and the type of audience should determine the format of your presentation.
It is important when putting a presentation together to determine what communication format will be most useful to your audience so your data inspires action instead of falling on deaf ears. Think about your audience – would they best respond to an executive summary or one pager encapsulating your narrative and facts? Or do they need a whole book containing your methods, iterations, assumptions and data?
We live in a visual age – whenever possible ditch the text and visualize the story
They say a picture speaks a thousand words. We live in a visual age – whenever possible ditch the text and visualize the story. Your data is only as powerful as your visual presentation of it. Graphs are often easier to understand than tables and have a more meaningful impact on the audience. A chart that takes 30 seconds to understand, compared to visual representation of the forecast or data that takes only 2 seconds, could mean the difference between accepting or rejecting your analysis.
Know Your Audience
Too often when we present our data, it will make sense to those who do the analysis but not to those who might actually use it. Determine what is most important to your audience – it is easy to summarize all the data you’re working with, but some pieces of data are more important to your audience than others. Often, large data sets are presented, and the demand planner explains only the dominant trend or the one measure of most interest to them personally.
The audience is sometimes left to wonder things like “Why is that data point there?” or “What caused that point to be low/high/odd?” Try to foretell what questions may come up and consider when presenting if the data adds value and supports your narrative and provides exactly what the audience needs, rather than raising more questions.
Consider when presenting if the data adds value and supports your narrative
It is important that you also calibrate data altitude optimally. Present forecasts and data in measurements that are meaningful to the decision makers. If you are not talking to other planners or data scientists, don’t say “statistically significant,” “r-squared,” “k-means algorithm” etc. unless you are sure that they know what you are talking about. You can never assume the audience fully understands what you are saying. Simplicity is critical to getting your message home.
Consolidate Information To Get To The Point As Quick As Possible
Good data stories include enough information to state a case, but not so much information that the audience struggles to understand the point. A common criticism of ineffective data stories is that they fail to get to the point fast enough. The demand planner needs to avoid clouding up their story with information and data that do not directly add to the narrative of the analysis and help answer the question at hand. Don’t distract your audience – keep your story clear, simple, and impactful.
A common criticism of ineffective data stories is that they fail to get to the point fast enough.
Typically, far too much time is spent on explaining what went into the analysis. I can understand the tendency to do this. After all the time spent on defining the need, data collection and analysis, you want to show them all the data process stuff that got you to this point. I get it, you want to demonstrate your value and instill confidence in your findings by dazzling the audience with your skills and techniques. Maybe you want to give the audience all of the information so they can make their own decision because you feel it isn’t your job to assume what they need or what they should do. But make no mistakes, they’re relying on you to point them in the right direction with your insight.
Busy charts with multiple data sets put a lot of stress on your audience
A lot of times, you could take just 10% of what you have done, leaving your audience with the real value of your insight, and you make data (and yourself) the hero. Every piece of data presented on the chart demands a portion of your audience attention. That is why busy charts with multiple data sets put a lot of stress on your audience. Try to focus not on what you have done, not on what you can do, not on everything you may think they need, but consolidate data and information so your audience can make a good decision.
Statistical data is often presented in a dry, clinical manner. Perhaps the theory is that the audience should naturally be excited about data? Like predictive analytics and forecasting, data storytelling may lack a connection to business outcomes. If an insight isn’t understood and isn’t compelling, no one will act on it and no change will occur. Try to tell a compelling and exciting data story by finding your narrative and format, understanding your audience, and giving them the right amount of information so they can take action.
Eric will reveal how to update your S&OP process to include predictive analytics to adapt to the changing retail landscape at IBF’s Business Planning, Forecasting & S&OP Conferences in Orlando (Oct 20-23) and Amsterdam (Nov 20-22). Join Eric and a host of forecasting, planning and analytics leaders for unparalleled learning and networking.