Eight to Late

Sensemaking and Analytics for Organizations

The story before the story – a data science fable

with 5 comments

It is well-known that data-driven stories are a great way to convey results of data science initiatives. What is perhaps not as well-known is that data science projects often have to begin with stories too. Without this “story before the story” there will be no project, no results and no data-driven stories to tell….

 

For those who prefer to read, here’s a transcript of the video in full:

In the beginning there is no data, let alone results…but there are ideas. So, long before we tell stories about data or results, we have to tell stories about our ideas. The aim of these stories is to get people to care about our ideas as much as we do and, more important, invest in them. Without their interest or investment there will be no results and no further stories to tell.

So one of the first things one has to do is craft a story about the idea…or the story before the story.

Once upon a time there was a CRM system. The system captured every customer interaction that occurred, whether it was by phone, email or face to face conversation. Many quantitative details of interactions were recorded, time, duration, type. And if the interaction led to a sale, the details of the sale were recorded too.

Almost as an aside, the system also gave sales people the opportunity to record their qualitative impressions as free text notes. As you might imagine, this information, though potentially valuable, was never analysed. Sure managers looked at notes in isolation from time to time when referring.to specific customer interactions, but there was no systematic analysis of the corpus as a whole. Nobody had thought it worthwhile to do this, possibly because it is difficult if not quite impossible to analyse unstructured information in the world of relational databases and SQL.

One day, an analyst was browsing data randomly in the system, as good analysts sometimes do. He came across a note that to him seemed like the epitome of a good note…it described what the interaction was about, the customer’s reactions and potential next steps all in a logical fashion.

This gave him an idea. Wouldn’t it be cool, he thought, if we could measure the quality of notes? Not only would this tell us something about the customer and the interaction, it may tell us something about the sales person as well.

The analyst was mega excited…but he realised he’d need help. He was an IT guy and as we all know, business folks in big corporations stopped listening to their IT guys long ago. So our IT guy had his work cut out for him.

After much cogitation, he decided to enlist the help of his friend, a strategic business analyst in the marketing department. This lady, who worked in marketing had the trust of the head of marketing. If she liked the idea, she might be able to help sell it to the head of marketing.

As it turned out, the business analyst loved the idea…more important, since she knew what the sales people do on a day to day basis, she could give the IT guy more ideas on how he could build quantitative measures of the quality of notes. For example, she suggested looking for  emotion-laden words or mentions of competitor’s products and so on. The IT guy now had some concrete things to work on.  The initial results gave them even more ideas, and soon they had more than enough to make a convincing pitch to the head of marketing.

It would take us too far afield to discuss details of the pitch, but what we will say is this: they avoided technical details, instead focusing on the strategic and innovative aspects of the work.

The marketing head liked the idea…what was there not to like? He agreed to support the effort, and the idea became a project….

…and yes, within months the project resulted in new insights into customer behaviour. But that is another story.

Written by K

June 15, 2016 at 10:00 pm

5 Responses

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  1. Which application have you used in developing this explainer? I would love to try it out myself. I loved this metalogue of a story that sets out to tell how data science projects too begin with stories.

    It’s funny that after I turn 30, I realize how much more stories are so powerful than “stuff” in the world that they can even threat the entire essence of all the “stuff” in the world? Have you read the book Sapiens? Among other things, the book beautifully elucidates this point.

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    venky

    June 15, 2016 at 10:28 pm

    • Hi Venky,

      Thanks so much for taking the time to read/view and comment…doubly so for calling out my hat tip to Bateson, the master of the metalogue form.

      I reckon you’re right that stories are in a sense as real as “stuff” because it is through the latter that we reach an understanding of the former. So it is with data too.

      Sapiens goes on my reading list, thanks for the tip.

      Regards,

      Kailash.

      The application I use to create my whiteboard vids is VideoScribe.

      Like

      K

      June 15, 2016 at 10:50 pm

  2. […] Kailash Awati tells the story before the story – a parable about setting business expectations before beginning a data science project. Just 5 minutes, safe for work. […]

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  3. This story is interesting as it has some hidden meaning. If one can understand then will understand the secret of projects. Thanks for sharing it is educative.

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    Edna

    June 22, 2016 at 8:26 pm

  4. […] The story before the story – a data science fable […]

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