Throwing hard-earned cash down for computer purchases is never an easy task. Computer hardware can be a particularly tricky purchase, considering the sheer number of revisions, designs and price points at any one time. ATI and NVIDIA have over 100 cores combined for the AGP video market on shelves today. Yet, somewhere in that haystack of video cards lies the perfect video card, equally balanced in performance and price. Finding it can be a bit of a pain though. What we have decided to do today is step away from the specific type of guide format and look at buying components on a more general basis using mathematical modeling and historical data. We aren't going to tell you which hardware to buy per se, but we will show you the same methodology that we use when determining our picks for the week. We get really theoretical for the first few introductory pages before we get into the historical data, so bear with us if we sound like a college text book for a little while.

Let us cut right to the chase. When buying computer hardware – at least with a sane perspective – there exist only two goals in mind: minimize the Price and maximize the performance. Performance can be somewhat ambiguous, so in this analysis, we will refer to performance and features as Quality. We find later that Price and Quality are both predictable, yet dynamic equations, but the most basic building blocks of any economic model for computer hardware exist as Price (P) and Quality (Q).

It is actually very easy to put a data type on Price - it's just the dollar/yen/euro amount that the component costs. Quality, Q, is a little harder to quantify in the general sense. Everyone has different computing needs, and thus, it's virtually impossible for us to put a numerical value on the performance of a processor or video card in every application – but fortunately, we have benchmarks to simulate a vast majority of real world scenarios. The most critical and difficult step when computing your next purchase cost comes when we attempt to quantify Q. Don't let the name "quality" fool you either. CPUs, for example, make it easy for us to quantify Quality in specific applications because one product is always arbitrarily faster than another. Video cards, on the other hand, make it a little harder, since we need to put a value on additional features like TV tuning or Image Quality. We will get more into these concepts on the following pages.

When to Upgrade?

The million dollar question that we get asked every day, thousands of times a day is "When should I upgrade?" Actually, the questions are usually phrased like:
  • "Should I wait six weeks to buy a Radeon X800 XL?"
  • "Is it worth it for me to upgrade to an SLI motherboard?"
  • "Should I buy more RAM?"

Finding the right time to upgrade shouldn't revolve around the next best thing or even a particular component. The right time to upgrade can usually be modeled around how Valuable additional Quality is to you. The moment when you feel your Athlon XP 1700+ has put you behind a performance curve is the most opportune moment to start calculating how valuable an upgrade is to you. However, this can actually be quantified as well, and we will get more into that in the next couple of pages.

Another thing that we stress in our Buyer's Guides and Price Guides is to look at the entire picture when upgrading and not just a single component. You may feel that your Athlon XP 1700+ is too slow and that you need a new processor, but perhaps we can achieve better performance or Quality for cheaper by upgrading the video card instead. The solution actually hinges on looking at everything in the picture and not just individual components.

On the next few pages, we are going to determine the Value and Quality of some components and determine where the best upgrade path exists. This should answer the few example questions above, but the methodology can be applied anywhere we like when buying new computer hardware.

Quantifying Price


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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.


  • 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"??? Reply
  • 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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