A632.1.4.RB - Multistage Decision-Making

Decisions are made every day, really every moment in the workplace, and as technical or not technical a decision is, you can choose to arrive at a decision in a number of ways. Our text highlights equations and technical methods to arrive at an optimal decision. Hoch provided tools of analyses that can derive an optimal decision, that doesn’t leave too much room for human error. Though there are some serious assumptions about the environment that have to be made for the theory to work properly.

Personally, my favorite part of the theory, and the one that I think is is most applicable to my work environment is that optimal answers are often obvious. Especially in the field of marketing, overthinking solutions can lead to a crowded and confusing marketing piece of end user experience. The rule of thumb is if you have to explain it then really you should drop it. For example, when updating a fiduciary calendar website for my company I attempted to streamline the number of clicks that the end user had to interact with to arrive at the custom calendar that they were seeking. In doing so I was able to enhance the entire user experience on the fiduciary calendar website, and subsequently I was able to eliminate the video that explained how to use the site to the user. I think this is a perfect example of the optimal answer being optimal.

In the future, though many parts of the theory are applicable to my own decision making, I can certainly see myself utilizing learning by trial and error. Being rather new to the workforce learning by trial and error has infiltrated my work life. In my work environment we like to call it “check and adjust”, try something out and then check and adjust. I implement this strategy for my social media campaigns, my working relationships, design, and partnerships with outside vendors. So I can guarantee that when I am strategizing how to go about a project or marketing campaign in the future I will ensure to check and adjust, and really implement a strategy of trial and error as long as its applicable and does not take away from the end user experience.

An extension of trial and error is learning from the past, and this is certainly something that is applicable to my work life. So much so, that before presenting a key strategy it is customary that we provide key learnings from our previous trials and strategy. Though this is so pertinent to my type of work I realize that humans are bias and that is something to be concerned and aware of while speaking to past experiences and how the impact the future. All in all I think every decision should be made with a number of considerations in mind, but applying optimal decision making tactic can certainly help support your decision making process.