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Hello these are discussion post that are meant to be responded with only 75 -90 words using your own words 1.Instructor: We often want those silver bullets—quick answers that will solve our problem

Hello these are discussion post that are meant to be responded with only 75 -90 words using your own words 1.Instructor: 

We often want those silver bullets—quick answers that will solve our problem…but there are no silver bullets in life! I am referring to JIT inventory and EOQ here…but I suppose there are other examples. Your reading covers these concepts this week. 

JIT & EOQ work, but we have to understand they are based on models….and change a parameter of the model or an assumption……and the model does not work! That means we have to understand the math!! Both assume demand is known and constant. Get an increase in sales, a decrease in sales, seasonality etc….and your known demand has changed. You will then have too much or too little depending on how the math worked out. So knowing what is divided into what and how the math works you can predict how the model will respond when an assumption changes. If you like math that is great! If you do not, please walk away knowing what approaches use models……and know that a change in the assumptions of the model will change the results of the model. 

When the pandemic hit, or any supply chain change occurs, supply chain professionals should be looking at what is model-driven and adjusting accordingly. That may mean going back to manually driving until stabilization is confirmed over a certain time period. 

This ties to our week 1 ChatGPT response to the discussion question. If you know the subject matter deep, you can critique it. If you do not, you may assume it is correct. If you assume the model is correct without understanding how the math is affected when the model starts to break, you will be caught off guard. This may be why we saw supply chain disruptions during Covid. Covid did not cause them, it did expose their weakness. A few areas of weakness were accommodated, but when there was multiple ‘root causes’ exposed, it was deemed fragile and could not recover. 

This is why our exercise this week is to think about and comment on Forecasting, Inventory etc…….(at minimum) to be sure there were not multiple breaks. Fixing one break will not fix the supply chain in a permanent way, All root causes must be identified. 

One of the most difficult to recover from was in Chip manufacturing. Some of you may choose to research that one (from gaming systems to cars), so I will not go deep here. Over many years we have moved manufacturing from the US to other countries for various cost reasons etc. The pandemic exposed some of the ugly with this strategy. Now we have government involvement to get Chips back in the US….and that means bringing skills in from other countries and incentives, etc…..and it is a longer-term solution. It did not happen overnight and unfortunately; the solution will not be quick either. Still, if you root caused to a chip shortage, we can solve for that, but it may not happen quickly. 

Comments? 

Wiles, R. (2022, December 9). When will it open? how can you find jobs? 5 things to know about Phoenix’s TSMC semiconductor plant. The Arizona Republic. https://www.azcentral.com/story/money/business/2022/12/07/what-to-know-phoenix-taiwan-semiconductor-factory/69707994007/

2. Student:  

Brief description of the fulfillment failure (item specific)

The item I researched that experienced fulfillment failure was Google Glass. Google Glass hit the market in 2013 and was pulled just a year later. If you don’t know know already, Google Glass are handsfree glasses. They look much like reading glasses except they are much bulkier due to the technology in them. They promised augmented realities, directions on site and access to photos and live videos. They set the expectation that the glasses could be used in a work setting and help speed up processing times by having a hands free information device that could transmit data easily and quickly.

Dissection to root cause: (Walk through Forecasting, Inventory, Information, Other considerations for the item)

When creating the glasses the Google team and a hard time forecasting due to the fact that they couldn’t decide on if the glasses would ultimately be fashionable or the new lead in workforce technologies. The glasses themselves would cost upwards of 1.5k and was said to have short battery life and limited systems control ( random restarts) in its initial launch.  The price of the glasses were too high for the average consumer and could very well have caused inventory to overflow and become stagnant. They had several ideas for the glasses and with so many ways they could go they did not settle on a clear concise idea that could be advertised easily to the masses. This is where I think the main issue seemed to root from. The managers and creators could not decide on the glasses altogether, instead mashing a bunch of ideas together and running with it. The glasses where apart of whats called a moonshot program, being the first of its kind of technologies to explore future technologies and its usage. This caused the Google team to have a lack of information on how exactly to launch and build their product as it had simply never been done in a successful way before. Essentially, they were building something that wasn’t necessarily needed but could become the norm if implemented and built correctly. They wanted to raise their competition level but overall could not anticipate the issues arising from the tech nor lack of marketing successfulness. One thing that really hurt the marketing of the product was the privacy laws that were in question, seeing though the glasses could record at any moment.

The Fix so it never happens again

There are many things that could have been done differently with Google Glass, and although they exited the market to come back and launch again in 2017, the product was still officially shut down by 2023. My initial fix of the glasses would have been to get control of the actual idea Google is trying to implement with the glasses, and break the glasses down from there. I would most likely introduce some kind of six sigma process to rid the glasses of wasteful and unneeded features. Secondly, multiple control groups should have been implemented before the product hit the market not just one or two. Although Google took this into consideration after its second launch, it failed to do this with the first and it cost them a heavy percent of marketability. There were already too many questions surrounding the product that Google had no answer for, but could have investigated beforehand such as the privacy issue with the camera. I would also take a look at the cost of the device and compare it to other devices already existing with the same kind of technology. Is it worth the buy? Can the average American afford it? Instead of trying to make the product popular, Google should have made the product accessible. Being the first of its kind is a huge deal, and having the demand of the consumers would be needed to get the product accepted in the field and eventually garner popularity through consumerism on its own. Since then, we’ve seen the launch of Amazon’s VR and other virtual technologies. It would’ve been interesting to see what Google could have done with those glasses in todays time and space.

References

Weidner, J. B. (2024, July 3). Why Google Glass Failed. https://www.investopedia.com/articles/investing/052115/how-why-google-glass-failed.asp

X.Company. (2018). Google Glass Helping people work faster and safer with smart glasses. 

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