This is a review of a chapter from ""Competing on Analytics"-
Typical Analytical Applications for Internal Processes:
  1. Activity Based Costing
  2. Bayesian Inference (predicting revenues)
  3. Biosimulation (pharma "in silico" research
  4. Combinational Optimization (optimizing a product portfolio)
  5. Constraint Analysis (product configuration)
  6. Experimental Design (AB Testing)
  7. Future-Value Analysis (NPV)
  8. Monte Carlo Simulation (R&D project valuation)
  9. Multiple regression analysis (determine how non-financial factors affect financial performance)
  10. Neural Network Analysis (predict onset of disease)
  11. Textual Analysis (assess intangible capabilities)
  12. Yield Analysis 

Main pieces- related to healthcare for internal analytics are financial and HR. 

My Thoughts:
This chapter falls a little flat. Perhaps it is trying to do too much and say too much, but instead it says way too little. It comes off as a list of some areas to employ metrics. But we need more detailed information. For example, if you want to create some analytics to measure the performance of financial results, Which metrics would you use? This is where the rubber meets the road and is the difficulty. 

I see business analytics, the use of "big data" as more than just reporting. It encompasses reporting, but it is more. It needs to provide insight, help you understand the data, and something a little more than what you already have from intuition. Our brain works against us, and data analytics needs to work to solve those problems. Among them are:

  1. We are not programmed to seek truth, we are programmed to "win". See an article on argumentative theory of reasoning, and a NYT Times article. Basically this means that we may be programmed to use "reason" in order to win an argument and not to just find truth. 
  2. Our brains don't understand probability. It is called neglect of probability. Our brains were not built for it. We didn't evolve to understand complex probabilities and how they may apply to us. 
  3. We think everyone is out to get us. This is called The Trust Gap. Problem is, it is a self-fulfilling prophecy. When you assume someone is lying, you just walk away.
  4. We think others are more in control of their situation than they actually are. This is called The Fundamental Attribution Error. Observers attribute other people’s behavior to internal or dispositional factors and to downplay situational causes. It's a universal thought process that says when other people screw up, it's because they're stupid or evil. But when we screw up, it's totally circumstantial. Like if you notice a coworker showing up to work late, it's because he has complete disregard for people's time, is lazy, and a jerk. But if you show up at work, it's because you had a flat tire. 
  5. Facts don't change our minds. This one is called confirmation bias. People display this bias when they gather or remember information selectively, or when they interpret it in a biased way. 
These are the problems we are fighting against. It is not just to get a report or a new metric. We are fighting against our own humanity that is harming us. We need to provide ourselves with the tools to fight and create a culture that allows the tools to work. Let us use data to seek truth, let us see visually risks and probabilities, let data show that people really are out to get us, that help explain how we can change the circumstances to get the behaviors we desire. And let us change our culture to follow the data, regardless of our original hypothesis. 


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