Final Thoughts

Hopefully, it can be said that making intelligent purchasing isn't too difficult if you don't mind spending the additional time to lay the equation out. Of course, purists would argue that if it took you 2 hours to build a working model of the component pricing environment and only "saved" $2, you've just subconsciously quantified your time at $1 per hour. On the other hand, given some practice and intuition, most people can build models like these in just a few minutes.

Of course, modeling in this manner is not without limitations. The first limitation is that a typical computer user's habits can be very dynamic. It can be very difficult to quantify the Quality of several computer components without a clear indication of what applications will be used. Furthermore, it can also be very difficult to model several dependent components at a time, since relatively little performance data exists. Buying a new video card and processor combination might make more sense than buying more memory, but buying more memory might make more sense over buying each one of those components individually. Although we do our best to benchmark as much popular hardware as possible, sometimes picking relative values for Quality is not as cut and dry as we would like.

For those of you who enjoy the more theoretical and mathematical side of this buyer's guide, we may revisit this guide in the future or perhaps build more complex models using a much vaster criteria and budgets. In the meantime, feel free to try out your own ideas in the spreadsheets that we've provided. For example, let's say that you can afford $2 per day for upgrades - take it out of your food budget. This might describe an individual who likes to stay on the high end of computing performance, and suddenly, it starts to make very little sense to hold off upgrading. Just remember to adjust the quality values relative to what you currently have.


Putting it all together
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  • PrinceGaz - Monday, January 31, 2005 - link

    Just to take the above example one step further, if the quality of card A in the above example was only 90% instead of 110%, so it is slower than what you already have; the graph in your sheet still shows it as the best choice.

    Spend $100 and get something slower :)
  • stephenbrooks - Monday, January 31, 2005 - link

    "What do we do to indecisive people who ask us when to upgrade?"

    "Confuse them with graphs!!"


    Sorry. It was a good idea. But as previous posters have said, what would be über-cool is to have the realtime pricing and entire benchmark database linked up to your formulae, and then let the user tweak the weighting factors on which things they find most important, and see what the site says. I guess it's a heck of a lot of work, though... maybe in 2010... :)
  • PrinceGaz - Monday, January 31, 2005 - link

    I'm afraid your calculations are fundamentally flawed from the point of view of upgrading.

    You assume that a product which is equal to what you already have (so it's not an upgrade at all) has a quality of 100%, and something twice as fast is 200%. That's fine if you are not upgrading but buying something totally new instead, but when upgrading you have to deduct the quality of what you already have from each of the potential upgrades, so subtract 100% from the quality as you already have that before upgrading. That would mean something that is the same as what you already have has a quality of 0% when considered as an upgrade, an upgrade twice as fast has a quality of 100%, three times as fast has a quality of 200%, and so on. Something half as fast would have a quality of -50% as it is not an upgrade.

    If selling your existing hardware when performing the upgrade, you should also deduct the amount you expect to sell it for from the cost of each potential upgrade option. The amount you can sell it for is likely to go down over time so that needs to be taken into account as well.

    To take a theoretical (but plausible) example and use the sheet you presented-

    Card A- $100, 110%
    Card B- $200, 170%
    Card C- $300, 240%
    Card D- $400, 260%

    the graph clearly shows card A is the best option, followed by B, then C, then D. But who in their right mind would spend $100 to upgrade to a card that is only 10% faster than what they already have?!

    Deduct 100% from the quality of each of those cards and the graph makes a lot more sense, with card C coming out on top, then D, then B, then A far behind the rest. Which is what you would expect as an upgrade to something 10% faster is a waste of money.

    Until the sheets and article are corrected, it is a very poor guide to upgrading.
  • KristopherKubicki - Monday, January 31, 2005 - link

    It should be Quality to Price - that will be fixed very soon.

    Thanks,

    Kristopher
  • CannonFodderjm - Monday, January 31, 2005 - link

    "Price to Quality" is best when high?!

    This confused me until the end, when I just gave up trying to understand your analyses and realized you made a "naming" mistake. It should be reversed.

    Great analysis, but this was too distracting.
    Please fix for the sake of others' sanity!
  • gimper48 - Monday, January 31, 2005 - link

    This was a great article but really leads to analysis paralysis. I am happy you guys do this for us. We really really appreciate it especially those of us who forget to carry the zero.

  • MarkM - Monday, January 31, 2005 - link

    #32, "I don't see those charts and formulas changing this all that much. You can tell which group you're in by checking your needs and your bank account," with all due respect, that was exactly the issue that the article so thouroughly addressed - for people who fit into ANY of your 3 categories, to identify the place in which to most effectively apply resources to address the perceived problem. You are the exact kind of person who could use a methodology like this, the person who's computer is slower than they want and/or need to do some specific task(s), but whose current approach to addressing a quantifiable need is nothing more rigourous than "Look at the Price Guide for the hardware you want [ed: I thought we were addressing a NEED, not a WANT?] to upgrade. Look at the components from lowest performing and go up from there. When you see the big price jump stop" Where in any of this methodology do we find ANY attempt to answer the question "will this upgrade resolve my slowdown"???
  • guest - Monday, January 31, 2005 - link

    Maybe now should be a good time to post an article about when to stop buying hardware :)
    In some cases it's better I think not to upgrade at all.
    Like when you don't buy anymore games or just do the occasional OS upgrade or just browse the internet.
  • LordConrad - Monday, January 31, 2005 - link

    People who upgrade (or buy a whole new computer) fall into one of three categories, either by choice or due to financial concerns:

    1. People who upgrade immediately when their computer starts to get a little slow.

    2. People who wait until the slowdown gets annoying.

    3. People who wait until their computer laughs at them when they try to run a program.

    I don't see those charts and formulas changing this all that much. You can tell which group you're in by checking your needs and your bank account. Why over-complicate things.
  • LordConrad - Monday, January 31, 2005 - link

    What the heck was all that crap? Upgrading is much easier than that and has two steps:

    1. Keeping your performance needs in mind, find the bottlenecks that are keeping you from reaching that performance.

    2. Replace the component(s) that are causing the biggest bottlenecks, while staying within your price range.

    Choosing Price/Performance:

    Look at the Price Guide for the hardware you want to upgrade. Look at the components from lowest performing and go up from there. When you see the big price jump stop. The item just before the big price jump is usually the best as far as Price/Performance.

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