I had a rather annoying experience last week, with a transaction I did, related to my Notebook.
It won’t let me log in after an upgrade to Windows XP SP3, notifying me of some domain name error. I tried some online help but was not successful.
So, I opted for some professional help and gave in the notebook to a well reputed electronics hardware chain. I signed up for their Store Membership and they offered me a reduced fee of $64 to fix the problem. When I offered to pay upfront, I was told to wait till the service was done. Fair enough, I thought.
Next day, I got a call from them saying the problem could not be fixed and re-installation was the only way out. And if I wanted any data to be recovered, it would cost me additional $80! I reluctantly agreed.
After a couple of hours, I got another call from them, saying the hard-disk too needs to be replaced, and at an additional cost of $140! I agreed but was clearly annoyed this time. I inquired if they anticipated any more costs and issues before I finally got my notebook fixed! I was beginning to think if this was why they had refused upfront payment!
Anyways, I got my notebook back without any further surprises, but only after paying $220 more than what I had initially thought I would pay!
This was a typical example of Adverse Selection quite prevalent in Service Industries. Adverse Selection is when one party in a transaction has more information than the other party. And the party having more information uses it to its advantage in that transaction. As in the above example, the service person knew the health of the notebook much better than me and also knew my dependability on him for such information. There is always room for Prices to be unfair, when information levels among transacting parties are not the same. And that adversely affects Transaction Volumes and ultimately the Bottom Line at Company level.
In these times, when companies are clearly struggling with their bottom lines, it will be good if they identify any cases of adverse selections in their processes and attempt to narrow such information gaps. It will likely affect their revenues and their bottom lines in a very positive way.
It won’t let me log in after an upgrade to Windows XP SP3, notifying me of some domain name error. I tried some online help but was not successful.
So, I opted for some professional help and gave in the notebook to a well reputed electronics hardware chain. I signed up for their Store Membership and they offered me a reduced fee of $64 to fix the problem. When I offered to pay upfront, I was told to wait till the service was done. Fair enough, I thought.
Next day, I got a call from them saying the problem could not be fixed and re-installation was the only way out. And if I wanted any data to be recovered, it would cost me additional $80! I reluctantly agreed.
After a couple of hours, I got another call from them, saying the hard-disk too needs to be replaced, and at an additional cost of $140! I agreed but was clearly annoyed this time. I inquired if they anticipated any more costs and issues before I finally got my notebook fixed! I was beginning to think if this was why they had refused upfront payment!
Anyways, I got my notebook back without any further surprises, but only after paying $220 more than what I had initially thought I would pay!
This was a typical example of Adverse Selection quite prevalent in Service Industries. Adverse Selection is when one party in a transaction has more information than the other party. And the party having more information uses it to its advantage in that transaction. As in the above example, the service person knew the health of the notebook much better than me and also knew my dependability on him for such information. There is always room for Prices to be unfair, when information levels among transacting parties are not the same. And that adversely affects Transaction Volumes and ultimately the Bottom Line at Company level.
In these times, when companies are clearly struggling with their bottom lines, it will be good if they identify any cases of adverse selections in their processes and attempt to narrow such information gaps. It will likely affect their revenues and their bottom lines in a very positive way.
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