Saturday, January 19, 2013

A632.1.4.RB Multistage Decision-Making


         After reading the chapters we were assigned this week I have realized that my decision making skills have gotten much better with age!  Every day we faced with decisions on every level.  What will I wear today?  What should I pack for lunch?  Should I take the highway because it may be faster?  Some decisions are no brainers and we don’t think twice about these decisions.  But what about the big decisions?  How do we decide about the important and what steps do we take to make sure we are making the right decisions?
            I have tried many different forms of making a decision about life changing events from praying on it, making a list of pros and cons to simply taking a leap of faith.  I will admit that I have been myopic (nearsighted—had to look it up) in my approach at times and this is something that I have learned doesn’t work out well in the end.  You have to be able to look forward by using dynamic decision solutions as the chapter suggestions like forward planning and optimal learning.  It is these two concepts that I will use for my examples.
            I have had to make many life changing decisions in my life and I will talk about one of them here.  In March of 2008 my now ex-husband told me that he no longer wanted to be married to me.  This was a huge blow to me especially since we were on vacation at the time and were getting ready to celebrate our daughters third birthday.  I was not a position to up and leave and thought that if I stayed things would work out.  I was very ambiguous about everything at the time.  I was only thinking of right then and there. 
            After a month of trying everything under the sun I realized that I was not thinking about the future I was only trying to put a band aid on something that was hanging by a thread at that point.  Sitting down one night I got a piece of paper out and made a list of pros and cons.  I was utilizing multistage decision making without knowing that is what I was doing. First decision was whether to stay in Texas or move back home to Florida.  I had my in-laws who were more than willing to put me up in South Texas but my family was in Florida.
If I stayed there was no promise that things would ever work out for us.  Looking ahead I decided that moving back to Florida would be better for us long term because I had family there that we could stay with until I got a job.  I also had roots at Embry Riddle having worked there for many years and being alumni I knew my chances of getting a job back there were much better.  I also had to think about the future of my daughter.  What would be the most beneficial to her?  I didn’t want to take her away from seeing her dad everyday but weighing my options and looking to the future I knew that how often she saw him would be up to him and it was not enough to hesitate on my decision for our future.
            Reading chapter three I found that this is the harder part, being able to look at the future instead of right now and basing decisions on what the future outcomes may be.  For me it worked out well to move back to Florida.  Weighing all my options and thinking back on past experiences this decision was the best and smartest move for me.  From this decision, I have a great job, excellent credit, a great place to live and working on my masters which if I had stayed I may not have any of these things. 
            Looking at optimal decision making I can use these to help predict how decisions I make today will affect my future.  I understand that sometimes I can pull from my own life experiences for the answer and this is ok to do.  If I do make the wrong decision for the most part my environment is forgiving of this and this can lead to trial and error…figuring out what works best by repeating the things that worked better and avoiding the ones that did not.  We all go through this trial and error in many ways.  It can be as simple as trying a new route to work and realizing that it takes longer so you adjust the time you leave and learning that leaving 10 minutes earlier gets you there in plenty of time by doing this you are using reinforced learning.  


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