HBR: The Risks of Quantification

The Risk of Quantification

Admitting uncertainty means facing reality — and our own needs for security. But admitting uncertainty is not enough. We must learn to actively embrace uncertainty and work with ambiguity.

As I sit in a two day meeting about drawing insights from data quantification, this article is very timely.  Obviously there’s merit in looking at your data and trying to draw as many insights as possible, but we as marketers can sometimes end up hiding behind the data, using them as an excuse to take no action in favor of gathering and analyzing more data.

There comes a time, however, where you have to accept whatever level of ambiguity you’re willing to accept, make a decision, and take action.  The question then becomes: When is the right time?  A better question might be: What do I get by delaying and gathering more data?  Am I falling prey to the law of diminishing returns?

As the ever-prescient Merlin Mann likes to say, “How do you know when you have enough [information] to get started?  What can you not do with the [information] you have right now?” 1

How do you overcome “Analysis Paralysis”?

  1. You can read more here or watch here.

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  1. #1 by Kris Kaneta on May 19, 2011 - 8:51 am

    In my particular business unit we maintain an “opportunity portfolio”. At any given point in time there are probably a dozen new ideas or projects we want to try out based on relative risk / reward and we are usually investigating, developing and/or piloting 5 or more of the ideas at once. How we avoid this exact challenge you point out is understanding the difference between “minimal” informal needed and “optimal” information needed.

    What are the one or two things that if known would keep us from proceeding to phase II? Then to phase III, etc. Once we address those (let’s say market need or operational capabilities), we ask ourselves, what are the next one or two things we absolutely need to know to take it one more step further. The process is iterative – so rather than focus on knowing everything at once or focusing on things that are just “nice to know” – we focus on uncovering the absolutely essential points of information needed to move forward.

    When you acknowledge that there are really only one or two things you absolutely “need to know” before taking the next step, the ambiguity becomes less problematic. Your team now has a clear goal irrespective of the other what-ifs that might otherwise cloud the issue.

  2. #2 by Sam on May 19, 2011 - 9:24 am

    I like that approach – knowing the difference between minimal and optimal data, and being able to quickly parse out what you need to know versus what you’d like to know to proceed to the next step. I constantly struggle with getting too deep into the data, playing with it rather than getting to some sort of decision point. I think part of it – at least for me – is fear of being wrong and missing something obvious in the data. Can’t speak for everyone everywhere, but I’d be willing to bet that some element of fear comes into it somehow.

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