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As a data analyst, you need to use decision analysis techniques to recommend decision alternatives

June 1, 2021
Christopher R. Teeple

As a data analyst, you need to use decision analysis techniques to recommend decision alternatives or optimal decisions based on expected profit payoff for the upcoming holiday season.

Respond to one of your peers’ initial posts, and complete the following:

Identify the sequence of actions you need to take to start this decision process.

Explain each sequence and justify why it will help you with your decision.

Propose a risk profile for each choice.

PEER’s POST THAT NEEDS RESPONDING TO IS LISTED BELOW:

As an acting data executive, I would have to consider several factors. The know factors that are a given and the unknown factors on both toys that we are selling. By getting using both known and unknown I can arrive at a decision.

Toy 1 known factors

New to market: excitement and newness.

No competition: first to introduce.

Holiday season: customers plan to spend more money during this season of gift giving.

Toy 1 unknown factors

Receipt of toy: highly successful, successful, not successful.

Expected profit payoff.

As the data executive I will need to the unknown answered to add to my known factors. I would ask the analyst of the company to give me a payoff table and decision tree. On the decision tree I would want to if after research the toy would be highly successful, successful, not successful, based on current market sales and the emotional attached value factor tied to the toy. With this information I can tell if the toy will sell as we are expecting or not.  There are three general type of decision makers as we learned from Sharpe, N. D., De Veaux, R. D., & Velleman, P. F. (2019).

“First, a risk-averse individual will sacrifice EV for lower variation, Second, a risk- neutral individual will try to maximize EV and Third, a risk- tolerant individual may be willing to absorb greater variation in return for the chance of a high payoff. To compute the expected value, we start by placing the probabilities on the decision tree in the appropriate place. With these values in place, we can find the expected value of each outcome. The probabilities are associated with each state if nature and are the same regardless of the action. We place these values on the branches associated with each state of nature, repeated for each one of the possible actions (the circle nodes), which is a choice made by nature.”

Toy 2 known factors

As been on the market -known to consumers.

Is in demand – two other companies selling the toy.

Toy 2 Unknown factors

The quantity each company has available to sell to customers.

I would use a decision tree as before with the same information. I am wanting to gather as to if the toy will be highly successful, successful, or not successful. We already know the demand is high which is why our company plus to others are selling the same toy. We need to know the emotional attachment placed on getting and giving the toy. Humans are emotional creatures. Parents want to give their children the toys they want during the holidays to create a memory and show how much they love their children. If the toy is in demand common sense would tell you that it will sell out.  As stated by Sharpe, N. D., De Veaux, R. D., & Velleman, P. F. (2019).

“choosing actions based on worst- and best-case scenarios rarely leads to the best business decision. Instead, successful small business executives rely on knowing their market so they can make fewer absolute decisions.  A more realistic modeling approach considers how frequently the decisionmaker expects to experience each of the states of nature and finds the optimum under that model.’

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