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Facts not fears, confidence not certainty, critical thinking not wishful thinking

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Syndicated from BeyeNetwork

Madeline Albright gave a great presentation at the SAS Global Forum in Washington DC this week. Several of her bon-mots are in the title but there were many others, some of which are below. Each of them struck me as relevant to readers of this blog:

  • Facts not Fears
    Businesses all too often do things based on their fears, not on the facts. They price lower than they could because they fear customer won’t buy, for instance. Use analytics to find out the facts (and to find out what the facts mean) and use business rules to act on them.
  • Confidence not Certainty
    Being confident is critical to automating decisions – you must be confident in the rules you are proposing, for instance, if you are to allow them to treat your customers on your behalf. But you should not be certain, you should test and re-test assumptions, simulate the changes you are considering before deploying them and challenge your approach using adaptive control.
  • Critical Thinking not Wishful Thinking
    Wishful thinking like “I want customer retention to improve so I will set that as a target” is not as useful as critical thinking like “I want customer retention to improve so I will identify the decisions that make a difference to customer retention and design decision making strategies that will make a difference”
  • Diligence in testing assumptions
    Decision analysis – the use of performance management tools to manage the decision making process itself – is essential to being usefully critical of your own decision strategy. Adaptive control is key to these three as it provides the approach and the infrastructure to constantly challenge the way you do things. You don’t pretend to be certain or that your assumptions will always be true. You don’t hope you have the best approach in use, you test and learn.
  • From information scarcity to information overload
    with so much information more and more potential consumers of data will not be able to cope. Analytics with its ability to focus in on the business implications of all this data has much to offer.
  • Any summary is dependent on the perspective of the summarizer
    And this increasingly means the math geeks (metaphorically) in the basement. Is their perspective the same as yours? Do they measure model accuracy in terms of K-squared or business results?
  • Comparative and Historical Perspective
    Decision analysis should involve both kinds of analysis.

Two other great phrases she used included Henry Kissinger’s “constructive ambiguity” in public utterances/press announcements and Secretary Albright’s description of herself as “an optimist who worries a lot”. She was a fabulous speaker and both interesting and amusing, despite the seriousness of her topic.

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