In need of a 125 response/discussion to EACH of the following forum posts. There are (3) different Forum posts. Agreement/disagreement/and/or continuing the discussion.The three interactive posts should each be substantial, relevant, and engaging. Origina

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In need of a 125 response/discussion to EACH of the following forum posts. There are (3) different Forum posts. Agreement/disagreement/and/or continuing the discussion.The three interactive posts should each be substantial, relevant, and engaging. Original forums discussion/topic post is as follows: (Use/Cite references to support your ideas)

*** This posts are based off of these statements: There are many pressures in making decisions based on information you are working with. There is a high cost of testing for reliability and competition for getting your product in the market as soon as possible. Discuss the trade-offs between analyzing the data to make an informed decision or making a quick decision to beat the competition.***

FORUM POST 1:

Good evening class,

Leaders today make decisions all the time based on their experience and what their competition is doing. In order to do this they need to use some sort of analytics. In order to make a sound decision, leaders of different corporations utilize analytic programs such as R and Python which are Open Source analytic tools. They also use commercial analytic tools such as Excel and SAS. Both types of tools are used in many corporations such as GOOGLE, FACEBOOK, NETFLIX, GROUPON, Coca-Cola, and HSBC. Each type offers a different aspect of analytics. Open source is Free and open to the public whereas Commercial you have to pay for. It really depends on the big data and the size of the business that would decide on which way you would go.

Depending on the nature of the company will decide if you as a leader/ manager will utilize analytics to make an informed decision. If you have no competition and a budget that you can work with, than the use of analytics will help make the right decision. If you have competition than the use of analytics could hinder on the production of a product to come out on time and at the same time could better prepare your item for production. Some times your competition will have done the work for you, and all you have to do is improve the process. Shooting from the hip means you have a 50/50 chance of being correct on the choice that you make. In order to stay competitive, choices need to be made, whether they are good or bad. Today’s technology gives businesses the options that they need to be successful. Sometimes experience is the better choice.

FORUM POST 2:

Hello Class,

I think this week’s discussion topic is a very real concern for any serious business. In a perfect world, I would personally prefer to make a fully informed decision. However, based on my own experiences, information is often requested with very little explanation and an unrealistic deadline. As such, you work frantically without the opportunity to spend additional time to fully analyze the data. Further, you are not sure why upper management is asking for the data, which further limits how you might otherwise organize and present it. I think this situation may often be the case with higher levels of management as well. More specifically, when decision makers are faced with a problem, they must sometimes weigh their options quickly or risk losing out on a potentially profitable venture. However, if they act too hastily, they might make the wrong decision and again miss an opportunity for success. So which approach to decision making is best?

My response to this question would be that it depends on the context. For example, if it is something as simple as deciding between several different healthy lunch options, I doubt it would be worth investing the time to do a thorough analysis of each option. Instead, just pick one and if you don’t like it, then pick a different meal the next day. However, if you were making decisions as to retail pricing for your product line(s), I think a more in-depth review and analysis of the data might be warranted.

In addition, I also think sometimes it can be beneficial to wait and see how the competition is doing before taking action. A great example of this is the competitive space that currently exists between Amazon and Wal-Mart. Both of these companies have studied each other to determine what is working best and then, from this analysis, make decisions on how to up their own game. More specifically, Wal-Mart has experienced a great deal of growth in recent years, which is largely due to the addition of a fresh produce department. Amazon, hoping to compete with Wal-Mart, tuned into this fact and ended up purchasing Whole Foods. Likewise, Amazon is a highly successful online business. As such, Wal-Mart purchased multiple online retail businesses and has been working hard to build and expand their online presence.

Finally, I think in some cases you may be forced to make quick business decision(s). For example, suppose you have just implemented a new process at your factory and quickly discover this is incapacitating your business. In this situation, you may be forced to make hasty decisions to correct these problems and/or delay further expansion to address the problems you have encountered. As a way of example, recently the IT group, where I work, upgraded the company firewall. They did such a great job of locking outsiders out that they also locked everyone in the corporate office out as well. In this situation, a quick response was needed by IT to identify and correct the problem. Taking days to analyze the situation, would have crippled the business.

FORUM POST 3:

Hello Class,

Analyzing data to arrive at an informed decision vs making a quick decision can best be summed up by looking at one of my favorite business upsets: Netflix and Blockbuster. Netlfix struggled in the video rental marketplace for years, even asking Blockbuster to purchase them, before finally upsetting the market and putting the former video rental giant into bankruptcy.

Netflix originally approached Blockbuster and asked offered to be purchased for around $50M. Blockbuster rejected the offer, standing firm on their business model of brick and mortar video rental stores. How much research was put into this decision is tough to say but I think some market research into the Netflix business model and online DVD rentals could have shown the direction things were to go a short while after the offer was rejected. DVD player prices started falling and customers wanted the convenience of ordering from home and renting as many movies as they wished for a set price.

Blockbuster then attempted to emulate the online rental model of Netflix but found themselves losing money due to paying overhead costs on their still open brick stores. When Netflix started signing deals with major companies to gain the rights to stream their movies online, Netflix took off even further and Blockbuster ended up filing for bankruptcy.

Blockbuster decided that their model which had worked for years was the only way to do business. Their failure to analyze a changing market and seize an opportunity to continue dominating that market, just in a different way, led to their demise.

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