The 2011 movie “Moneyball” staring Brad Pitt, is an account of the Oakland Athletics baseball team's 2002 season and their general manager Billy Beane's attempts to assemble a competitive team. In the film, Beane (Brad Pitt) and assistant GM Peter Brand (Jonah Hill), faced with the franchise's unfavorable financial situation, take a sophisticated sabermetric approach towards scouting and analyzing players,
In one scene, Billy Beane is in a meeting with his talent scouts discussing potential signings.
This is a review of a chapter from ""Competing on Analytics"- Typical Analytical Applications for Internal Processes:
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:
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. This is a review of a chapter from ""Competing on Analytics"- Companies that successfully compete on analytics have analytic capabilities that are:
Hard to duplicate: It is one thing to replicate IT applications or its products and their attributes and a very differetn proposition to replicate processes and culture. Unique: The way every company uses analytics is unique to its strategy and market position. Adaptable to many situations: Use the metrics in other innovative ways. For example can use a "cutomer experience life cycle" and apply to "employee experience life cycle" Better than the competition: Some organizations are just better at exploiting information than others. Can you break apart a category or a metric and get more analytical advantage? Renewable: Needs to be continued improvement and reinvestment. My Thoughts: If you are doing business with a company, and they have better analytics than you do, they have the advantage. If CMS has better analytics than you, you are at a disadvantage. If the hospitals have better analytics than you, you are at a disadvantage. If the insurance company has better analytics than you, you are at a disadvantage. I think in healthcare the "competition" is a little different. Competition occurs in a market and healthcare competes in several markets as a buyer and seller. Attracting physicians and other employees, attracting referrals and patient visits, attracting better contracts with the hospitals and with insurance companies. Buying equipment, buying or leasing realty, hiring employees, and making IT purchases. In a general sense- attracting the money in the market- CMS and insurance premiums, which is a problem individually and collectively by specialty as they demonstrate value. This is a review of a chapter from ""Competing on Analytics"- Analytical competitor is an organization that uses analytics extensively and systematically to outthink and out-execute the competition.
My Thoughts: Difficult to create a culture of analytics, when it is risky proposition to invest and spend time and resources. One issue I have seen is a prior attempt and investment in analytics that failed. But, with new technology that makes it cheaper and increases the likelihood of success- the organization could have made a move to improve, but felt married and committed to the investment in the older, more difficult technology. 5 Stages of Analytical Competition
My Thoughts: It is important in an organization that each stage be a successful experience in analytics. There are a lot of moving parts- and a lot of complexity that can go wrong- and interesting analytics can be a difficult process. Making sure you select the right: software, hardware, technical people who can deliver the data, technical people to install software and hardware, analytical people who can analyze the data, and managers who can allow the time spent on all of the above activities. This is not all, then you need to believe and act on the data, and implement the findings. Test the results and review the impact and then improve the analytics. I suppose this is why the first 4 attributes are important- because many things can go wrong. Although, I would add a thought here and a plug for Bern Medical. Many of these issues are what has helped lead us to where we are with Bern Medical, our solution, our business model and distribution model. It has molded us, so that we can take away a lot of these risks to practices and billing companies. This is a review of a chapter from ""Competing on Analytics"- Intro to Analytics
Touching first on an omnipresent example of analytic prowess Netflix. The Company, created a culture of analytics and a "test and learn" approach to its business. They use a combination of quantitative and qualitative data (like surveys) to present a better customer experience. Netflix makes recommendations of movies and shows based on history. My Thoughts: This is something that Netflix does much better than Amazon Prime- which enables watching the same types of online streaming of movies and shows. My personal experience has been that Netflix does a much better job of making recommendations. This gives it an advantage over Amazon that will take some time to catch up. But, Amazon eventually will have a solution- in fact they were one of the pioneers of the strategy- "Customers who bought this item also bought..." What are Analytics? "Analytics" is the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions. Chapter touches on "Moneyball" and its use of analytics. Which was the concept that traditional baseball metrics didn't describe the entire value of a player - and that wins could be generated on undervalued attributes that describe performance, like "on base percentage, "on base plus slugging percentage". My Thoughts: I have the movie "Moneyball" in my queue on Amazon Prime. Need to watch it, perhaps tonight... My thought here is that what Moneyball teaches is that there may be different metrics than what is the standard in the industry. There can be hidden and undervalued trends that describe performance better than the outward and obvious "box scores". |
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June 2013
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