Business forecast

 

Find an example of a business forecast that turned out to be completely wrong. What happened? What did the forecaster fail to anticipate? Finally, what were the consequences of the failed prediction(s)?
In your own experience as a customer, can you think of a time when a company certainly (or almost certainly) lost money on a specific transaction with you? If so, what happened? Write about the experience and speculate as to whether the company’s assessment of your Customer Lifetime Value could have played a role.
Using the def keyword, write an original function in Python. Describe the purpose of your function in words, and demonstrate the way it generates output based on user input. (you may either upload an HTML file generated in Jupyter Notebook that includes your code, results, and written statements, or a screenshot of your results in Jupyter along with your written statements — either way is fine).
Choose one of topic above wirte 250-300words with references

 

Sample Solution

Business forecast

It is scary how often ideas or concepts are rejected. History is littered with examples of people who wrote off a piece of technology, or said someone wouldn’t amount to anything, and later had to pull their foot from their mouth. An example of an embarrassingly bad business prediction is that of Steve Ballmer on the iPhone`s failure. He said “Apple`s iPhone is the most expensive phone in the world and it doesn’t appeal to business customers because it doesn’t have a keyboard which makes it not a very good e-mail machine…” Steve Ballmer, Microsoft`s CEO, uttered this famous quote in 2007. Needless to say, he missed the mark entirely. Today, Apple is the top smartphone vendor in the world. Business customers are buying it and using it for e-mail among many, many other things. Apple`s famous touch screen also became one of the biggest selling points of the phone, proving Mr. Ballmer wrong yet again.

Sealed first price bid: also known as the blind auction, this is a form of auction where all the bidders instantaneously submit their sealed bids in a way that no participant knows the bid of any other bidder. The highest bidder pays the price they submitted. This form of auction is different from the English auction, in that bidders can only submit one bid each. Moreover, since bidders are not allowed to see the bids of other bidders, they cannot change their own prices as a result. This type of bid has been argued to be tactically comparable to the Dutch form of auction. The sealed first-price type of auction is commonly used for tendering for procurement by companies and organisations, particularly for government contracts in Nigeria today.

WINNERS CURSE.

The winner’s curse is an occurrence that may happen in common value auctions with high asymmetric information. Furthermore, the winner’s curse postulates that in a sealed bid auction, the highest bidder will tend to overpay. The winner may overpay or be “cursed” in one of two ways:

1) The winning bid exceeds the value of the auctioned asset such that the winner is worse off in absolute terms; or

2) The value of the asset is less than the bidder predicted, so the bidder may still have a net gain but will be worse off than expected.

However, an actual overpayment will normally occur only if the winner fails to account for the winner’s curse. The winner of an auction is the bidder who submits the highest bid. Since the auctioned item is worth approximately the same to all buyers, they are distinguished only by their individual assessments of the market value of that particular item. The winner, then, is the bidder making the highest estimate. If we assume that the average bid is accurate, then the highest bidder overvalues the item’s value. Thus, the auction’s winner is likely to pay higher for that item. There is often confusion that winner’s curse applies to the winners of all auctions. However, but when the item is preferred irrespective of its average market value, winner’s curse does not arise. Similarly there may be occasions when the average bid is too low relative to outside market conditions. For example a scenario where a dealer identifying that an item or commodity is highly marketable in another place when the bidders do not have the necessary expertise.

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