Seth Godin gets it wrong

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Knowledge Matters...Seth Godin authored a recent post (“When data and decisions collide“) in which he cited a few examples in which data proves not only to be counterintuitive to our natural instincts in decision making, but he alleges that data is also more accurate as the basis for sound decisioning. While this may be true in certain circumstances, it is clearly not the case in all, or for that matter even most circumstances, as not all data is good data.

Put simply, data is not the same thing as information, and information is not as highly evolved as knowledge. Moreover, as a leader you will often find yourself in circumstances where timing may simply force your hand into relying solely upon gut instincts. In the text that follows I’ll put forth a bit more detailed look at decisioning filters that constitute what I refer to as the hierarchy of knowledge…

While I tend to agree with Seth on most things, I think he gave the issue at hand short-shrift, and perhaps broadening the topic of Seth’s post is necessary to give a more valuable framework on what considerations should by applied to decisioning. The question most people should be asking themselves is ”what is the best way for me to synthesize the overwhelming amount incoming information I receive while making the best decisions possible in a timely fashion?” While I have written often on the subject of decision making, it never becomes a dull topic, as it remains one of the single largest contributors to both personal and professional success or a lack thereof…

Understanding that a hierarchy of knowledge exists is critically important when attempting to make prudent decisions. Put simply…not all inputs should weigh equally in one’s decisioning process. By developing a qualitative and quantitative filtering mechanism for your decisioning process you can make better decisions in a shorter period of time. The hierarchy of knowledge is as follows:

  • Gut Instincts: This is an experiental and/or emotional filter that may often times have no current underpinning of hard analytical support. That said, in absence of other decisioning filters it can sometimes be all a person has to go on when making a decision. Even when more refined analytics are available, your instincts can often provide a very valuable gut check against the reasonability or bias of other inputs. The big take away here is that intuitive decisioning can be refined and improved. My advice is to actually work at becoming very discerning.
  • Data: Raw data is comprised of disparate facts, statistics, or random inputs that in-and-of-themselves hold little value. Making conclusions based on data in its raw form will lead to flawed decisions based on incomplete data sets.
  • Information: Information is simply an evolved, or more complete data set. Information is therefore derived from a collection of processed data where context and meaning have been added to disparate facts which allow for a more thorough analysis.
  • Knowledge: Knowledge is information that has been refined by analysis such that it has been assimilated, tested and/or validated. Most importantly, knowledge is actionable with a high degree of accuracy because proof of concept exists.

Even though people often treat theory as knowledge, and opinion as fact, they are not one in the same. Making executive decisions in today’s world has never been more complex, and when under extreme pressure I have seen many a savvy executive blur the lines between fact and fiction resulting in an ill advised decision. Decisions made at the instinctual or data level can be made quickly, but may offer a higher level of risk. Decisioning at the information level affords a higher degree of risk management, but are still not as safe as those decisions based upon actionable knowledge.

Another aspect that needs to be factored into the decisioning process is the source of the input. I believe it was Cyrus the Great who said “diversity in counsel, unity in command” meaning that good leaders seek the counsel of others, but maintain command control over the final decision. While most successful leaders subscribe to this theory, the real question in not whether you should seek counsel, but in fact where, and how much counsel you should seek. You see more input, or the wrong input, doesn’t necessarily add value to a decisioning process. Volume for the sake of volume will only tend to confuse matters, and seeking input from sources that can’t offer significant contributions is likely a waste of time. Two other issues that should be considered in your decisioning process as they relate to the source of input are as follows:

  1. Credibility: What is the track record of your source? Is the source reliable and credible? Are they delivering hunches, data, information or knowledge? Will the source tell you what you want to hear, what they want you to hear, or will they provide the unedited version of cold hard truth?
  2. Bias: Are there any hidden and/or competing agendas that are coloring the input being received? Is the input being provided for the benefit of the source or the benefit of the enterprise?

Good luck and good decisioning…


Image credit: On Being

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    Keith Bossey

    November 4, 2009 at 2:44 pm

    Mike, I couldn’t agree more. A couple of points that I blogged about yesterday and today (in response to Seth’s post). #1 your data is only as good as the tool used to gather it, bad tool/bad data. #2 Is data meaningful, does it actually lead you to information that makes sense. #3 Is the data really correlated with outcomes or do they just appear to be correlated? We have all been rushing to measure everything under the sun. Some things can’t or shouldn’t be measured.



    November 4, 2009 at 8:11 pm

    Hi Keith:

    Thanks for comment. As I mentioned earlier, I typically find myself in agreement with Seth on most things, but he flat missed the boat on this one…

    If I’m to give Seth the benefit of the doubt, my suspicion is that his logic was a failed attempt at oversimplification. That said, your comment nails it in just a few sentences.:)

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