August 10, 2011

Assumptions

Assumptions are terribly misunderstood.

Head out to Twitter to follow the #measure community, and you'll find a veritable plethora of criticism of Executives who make assumptions ... they're called "HIPPOs" or "Highest Paid Person's Opinion".

There seem to be at least three types of assumptions in the marketing/analytics world.
  1. Assumptions based on myth.
  2. Assumptions based on psuedo-statistics.
  3. Assumptions based on facts.
Assumptions based on myth are the ones that drive people crazy.
  • "Engaged customers are the most profitable customers, so we assume that our Facebook presence will significantly increase profit."
Assumptions based on psuedo-statistics are worse, because people are more likely to act upon them.  Often, the person making the assumption falls back on a research organization ... if the assumption fails, it isn't your fault, it's the research organization that screwed up:
  • "Woodside Research predicts that mobile sales will exceed $2.9 trillion dollars in 2016, leading us to assume that mobile will be the most important revolution in the history of e-commerce."
Assumptions based on facts are a whole 'nother deal.  These are the assumptions that most people shy away from, because assumptions in this realm require the marketer/analyst to be an expert.
  • "A year ago, only 1% of our visitors used tablets, converting at a 10% rate.  Today, 4% of our visitors used tablets, converting at an 8% rate.  Next year, we assume that 8% of our visitors will use tablets, converting at a 7% rate.  And in three years, we assume that 21% of our visitors will use tablets, converting at a 5% rate, causing us to completely rethink how we manage e-commerce, going forward."
Do you see the fundamental difference in assumptions based on facts?

Now, granted, the assumptions based on facts are questionable, anybody in your company can criticize you, and we all know that anybody/everybody will criticize you.  This is why we fall back on "Woodside Research", that way, we don't get blamed, they get blamed!


But assumptions based on facts lead us toward strategy.  It's irrelevant what "Woodside Research" or some Social Media Expert think, it's very important what YOU think!  If you have data that is trending in an interesting direction (tablets as a share of our e-commerce visitors are growing almost exponentially), and you project that trend into the future, you are almost required to face a future reality.


When the criticism starts, ask those who criticize you to come up with their own assumptions, in fact, demand that they publicly state their assumptions.  Ask ten of your critics to state their own assumptions.  Then average their assumptions with your assumption ... the result isn't likely to be all that different from what you originally assumed!  And if their assumptions are fundamentally different, see if their assumptions lead to a fundamentally different outcome.  Often, assumptions can be all across the board, with the end result being essentially the same.


There is nothing wrong with making assumptions based on facts.  Too often, we hide behind the lie that we don't have facts required to make good assumptions.  Instead, we need to stick our necks out there a bit more, faking confidence if necessary.  It is in the assumptions that we gain a vision for what the future may hold, and this vision leads to strategy.

2 comments:

  1. Brilliant post, Kevin! I actually think it would be interesting to hold research institutes more accountable in the future.

    Companies need to start asking for the facts behind those "pseudo" statistics or otherwise ignore them. Not only are they often highly inaccurate but also almost never really fitting the actual situation of the company.

    I've got some agency experience under my belt as well and can tell for myself. We used to love those stats because they look fancy (infographics) and clients like to buy into it to feel better in their decisions. This is in fact plain stupid but actually common in this industry.

    Once you realize this, it actually becomes so much easier to identify real problems and solve them. Thanks for this post!

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  2. I think assumptions based on pseudo-statistics can be positive, if they drive you to find more relevant and personal statistics to support the research. In that way they can act as a reason to find out more, rather than the support for a weak argument or assumption.

    Good post though - I'm a new reader, and am getting a lot out of your blog. Much more interesting than the million other social media "tips".

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