My company's part numbers are in the form 00-0000. After enough conversations about how to convert back to this format from the date Excel changes it to, we've finally just decided to change our sku format. A rolling change though, so we'll still be dealing with it till the current 5k sku's are all EOL.
I also hate the scientific notation default, in addition to the leading zero. Guess what, UPC's exist and no one wants them in scientific notation.
But when someone sends you a CSV file (a very common format for database exports and EDI), Excel does the type conversions automatically when you open it. You don't get a chance to change the cell format to Text beforehand. The ' workaround is a huge time-waster if you are dealing with a large amount of data, plus it screws up the file for use outside of Excel.
There really needs to be an option to turn off all type conversion globally for all files in Excel.
The real problem arises when you ask someone to send you data in CSV format. If, in between exporting it from their database and sending it to you, they happened to open and save it in Excel, you will get corrupted data. Usually the sender is blissfully unaware of what Excel's automatic type conversion does to their data.
CSV has been made unreliable as a format for data exchange between companies (aka EDI) largely because Microsoft decided that CSV files should always be opened in Excel by default in Windows. At the very least they should turn automatic type conversion off for CSVs.
Excel ignores double quotes around the fields, it just uses them to escape commas inside the fields.
The official way to do it is to insert a single quote at the beginning of every field that you don't want auto-converted. In practice this is a time-wasting pain in the neck and ruins your data for use outside of Excel.
The problem isn't the lack of workarounds. The problem is that we have all departments - Purchasing, Marketing, Operations/Warehouse, Sales, Finance, IT - working with sku's in spreadsheets. Every single time, every single person needs to know the workaround(s), and as other people are mentioning, you then have to hope it's not somehow saved as something else. And also as mentioned, if someone else has worked with the data before you get it, good luck restoring it to what it was before.
Postini setup process and support are a joke. You can call someone who tells you to look at a help file, and the help files point to help files, which have no screenshots, and reference menu and navigation options that don't exist. Also asking them how to get Postini to work with Google Apps was like speaking a foreign language to them, as if we were the first person to need this. Despite the fact that it was up-sold to us as an add-on to Google Apps.
Other than Postini, though, I do like Google Apps.
I have an iPad 3 and a Chromebook. I like and use the Chromebook much more, because of the built in keyboard. I know plenty of people who would hate using a Chromebook and much prefer their iPad for everything. To each his own.
Regarding the unhelpfulness of online reviews, my company has problems with manufacturers/sellers writing 5-star reviews of their own product listings (ASIN's) on Amazon. We've begun (manually) data mining 5-star reviews to identify whether each 5-star-reviewer has any other reviews (or wish list, to indicate the possibility of a real user account), then calculating the % of reviews written by no-history user accounts. Of the ASIN's we've assessed, the gut-level-doesn't-seem-like-heavy-review-fraud listings can be in the 6% range, whereas the looks-like-review-fraud ASIN's are above 20%. We're working with Amazon to identify and penalize these manufacturers/sellers, but internally at Amazon the Seller Performance team is separate from their Community (user review) team, so it presents a challenge. Also hard for them to separate valid complaints from sour grapes complaints.
"but internally at Amazon the Seller Performance team is separate from their Community (user review)"
Indeed, my suspicion is that organizational politics have more to do with the lack of a better rating system than any technical limitation.
The approach I use is to read 3 star ratings first before biasing myself with the more extreme ratings. I also check to see what else the reviewer has rated and if there's nothing there then I immediately dismiss the review.
Amazon review fraud is rampant, and with enough effort, they'll do something about it. I've worked w/teams there who, over time, develop very complex queries on the back end, and use these to remove sellers who violate policy. There are all kinds of additional tricks sellers or manufacturers use to make their reviews look legit, such as using Amazon gift cards to prevent tracing back to a specific credit card holder, and to ensure the "Verified Amazon Purchase" indicator shows on the review. Helpful votes are crucial and there seem to be very complex rules behind which votes get counted and which don't. Some combination of accounts being related via credit card on file, IP address, possibly length of user account history, etc. One difficulty for Amazon is that their community review policing department is disconnected from their seller performance team. My company's work with them has improved the communication, as well as the realization that user accounts that leave fraudulent reviews cannot be treated as merely rogue buyer community members, but rather have to be tied back to sellers and manufacturers who are the real benefactors of these fraudulent (positive or negative) reviews.
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