I would suspect this depends on the type of work you are doing. Working for a start-up that is trying to innovate and rock the tech world? Deliver and over-deliver, in my humble opinion. Working for an Enterprise company that does SaaS, PaaS, or some type of aaS? Deliver on the dot, no more, no less. It doesn't help you any - you'll be bored sick - but it's reality, and you're best saving your "awesome" for those FOSS projects you hack on the side, until you can nail that primo job where over-achieving is not only expected, not doing it can get you canned! Cheers.
They don't link to a paper, but I'm curious if they looked at the effect of "dosage" as it were. That is to say, a slightly better seat might be insignificant to many people, whereas other sorts of benefits would be more appreciated. Also, people may have random seat preferences where they don't actually like front-row seats or what have you.
In other words, they may have proven that people don't value seats very much, but I'm not sure that applies to every possible reward. Something where preferences are less abstract (e.g. cash) might turn out differently for all we know and there's no way to tell if the authors already investigated this or not from just this story.
My thoughts were along the same line, how do you measure better seats? Isn't this at least a little personal? It would seem to make more sense to for example, give a voucher for extra free drink at the venue...
The odd thing is that I couldn't find this particular experiment mentioned on the linked paper[0]. There were several other experiments that seem more clearly defined in terms of failing/meeting/exceeding expections.
To test that theory, they asked college students to imagine using an online company to buy concert tickets for Row 10. The participants then were randomly instructed to consider receiving seating that was either worse than, better than, or exactly as promised. They then indicated their level of satisfaction with the purchase, as well their likelihood of both using the online ticketing company again and recommending the service to friends.
From paper:
One hundred and twenty University of Chicago undergraduates (N ¼ 60)
Personally I don't find the sample size, nor method very compelling.
> To test that theory, they asked college students to imagine using an online company to buy concert tickets for Row 10. The participants then were randomly instructed to consider receiving seating that was either worse than, better than, or exactly as promised. They then indicated their level of satisfaction with the purchase
Does anyone else find this type of study completely unconvincing?
I assume that the students are being asked to pick a number 1 through 10 to express their level of satisfaction. They're just going to pick an arbitrary point which is going to be different for everyone. You can label the points (10 is winning gold at the Olympics, 1 is your spouse dying) but it's really hard to place something like buying concert tickets onto that scale.
The only way you could get actual information out of such a study would be to ask the same student how satisfied they are with a row 10 seat, a better seat, and a worse seat, but that will only tell you the obvious - that they are to some extent more satisfied with the better seat and less satisfied with the worse seat - and not give you any interesting information about whether it's a significant difference.
Other ways would be analogous. I can't think of any way to do this in a hypothetical lab situation such that it's not vulnerable to my criticism. Can you?
What you could do is look at actual data (for concert tickets, plane tickets, train tickets, etc) and see if complimentary increases in ticket quality really correspond to increased purchases in the future. You might also be able to rig up an exit survey with objective questions like "do you regret your ticket purchase" and "would you recommend us to your friends" and compare the answers given by regular ticketholders and those given by ticketholders given a complimentary increase in ticket quality. But, again, that wouldn't work in a lab setting.
An old boss of mine used to try to "under-promise, and over-deliver". Keep a lid on the client's expectations, so that we could be confident that we would exceed them. Anyone who plans on over-delivering is using the same strategy, whether they realise it or not.
Certainly, i think he hoped we would earn extra goodwill by over-delivering. These studies seem to shoot that down.
But there was also a risk-control aspect. If things went wrong, and we couldn't deliver as effectively as we'd hoped, then we still had a chance of at least meeting the expectation. That still seems useful.
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[ 3.9 ms ] story [ 42.1 ms ] threadIn other words, they may have proven that people don't value seats very much, but I'm not sure that applies to every possible reward. Something where preferences are less abstract (e.g. cash) might turn out differently for all we know and there's no way to tell if the authors already investigated this or not from just this story.
The odd thing is that I couldn't find this particular experiment mentioned on the linked paper[0]. There were several other experiments that seem more clearly defined in terms of failing/meeting/exceeding expections.
[0] https://news.ycombinator.com/item?id=7798367
Worth Keeping but Not Exceeding: Asymmetric Consequences of Breaking Versus Exceeding Promises
http://spp.sagepub.com/content/early/2014/05/08/194855061453...Does anyone else find this type of study completely unconvincing?
I assume that the students are being asked to pick a number 1 through 10 to express their level of satisfaction. They're just going to pick an arbitrary point which is going to be different for everyone. You can label the points (10 is winning gold at the Olympics, 1 is your spouse dying) but it's really hard to place something like buying concert tickets onto that scale.
The only way you could get actual information out of such a study would be to ask the same student how satisfied they are with a row 10 seat, a better seat, and a worse seat, but that will only tell you the obvious - that they are to some extent more satisfied with the better seat and less satisfied with the worse seat - and not give you any interesting information about whether it's a significant difference.
What you could do is look at actual data (for concert tickets, plane tickets, train tickets, etc) and see if complimentary increases in ticket quality really correspond to increased purchases in the future. You might also be able to rig up an exit survey with objective questions like "do you regret your ticket purchase" and "would you recommend us to your friends" and compare the answers given by regular ticketholders and those given by ticketholders given a complimentary increase in ticket quality. But, again, that wouldn't work in a lab setting.
Certainly, i think he hoped we would earn extra goodwill by over-delivering. These studies seem to shoot that down.
But there was also a risk-control aspect. If things went wrong, and we couldn't deliver as effectively as we'd hoped, then we still had a chance of at least meeting the expectation. That still seems useful.