I eat out a lot – exempting breakfast (I don’t eat it), I would say that I’m at a restaurant for about 10 of every 14 available meals. Never mind what this does to my budget, let’s focus on the food. Now, I’m a pretty simple eater – in fact, I love things plain. When I go to McDonalds or Burger King, I get the burgers with nothing on them – just meat and bread. Add in some fries and a drink, and I’m a happy man.
So in most situations, I’ve got three components to my meal: an entree, a side and a drink. Statistically speaking, there are eight possible combinations of quality (assume that each item can only be good or bad):
bad burger, bad fries, bad drink
bad burger, bad fries, good drink
bad burger, good fries, good drink
bad burger, good fries, bad drink
good burger, bad fries, bad drink
good burger, bad fries, good drink
good burger, good fries, bad drink
good burger, good fries, good drink
Thus, for any given purchase of just these three components to my meal, I have a 1 in 8 chance of getting all three “good” items. That’s a .12512.5% [thanks to John O. for correcting my math] chance – WAY less than 1% that I’m going to enjoy all three items. On the other hand, there’s also only a 1 in 8 chance of having all three be “bad”. There’s a 3 in 8 chance that one will be “good” and a 3 in 8 chance that two will be “good”. So what do I do?
I set my expectations accordingly and know that there’s a 50% chance that I’ll enjoy at least two of the items (the 3 in 8 that two will be good plus the 1 in 8 that all three will be good). Yes, I know that there’s a 50% chance for the reverse – but remember also that there are some other variables that we need to account for. In all name-brand fast-food joints, there are quality standards set by the franchisor. McDonald, Burger King, Chick-Fil-A, Wendy’s, Arby’s, KFC, Taco Bell, etc… they all have: food that is pre-packaged and sent to the stores (reducing the likelihood of differentiation by store); cooking standards (look behind the counter some time and see if you can find the poster showing the correct “doneness levels”); even standard equipment (fryers, etc) to reduce variations.
So in actuality, there’s a better than 50% chance that my food will be “good” (meeting the corporate standard) because of these outside variables.
OK, so what does this all have to do with software, services and service levels?
Well, it’s 100% the same. Service levels are quality-based promises a customer seeks from a vendor. There are a lot of variables (such as the software), a few standardized items (usually the hardware), and you try to pick a few key metrics that you think will be able to give you a quality rating on the meal (the service itself). The question is whether you can appropriately gauge how often you’re going to be satisfied with what you’ve purchased and cope with it when you’re not.
In the software and services world, service levels are typically measured in response time or uptime, used to enforce the vendor’s sales-pitches that the particular good or service will be as incredible as it was during the demo. Vendors, of course, don’t like service levels, and customer’s predictably, love them. However, in all of the years I’ve been playing this game, I very rarely see service levels that benefit either party.
To be effective, service levels have to be SMART (as made popular by Peter Drucker): Simple, Measurable, Attainable, Relevant and Time-Bound (we discussed these earlier when talking about writing SOWs, too). So while you might have a service-level grid in your template agreement, for any particular product or service, you have to evaluate those pre-defined levels and see if they make sense for whatever it is that is being purchased. This is no easy task and requires a lot of input from your colleagues down in IT support, architecture, engineering and management. You have to look first at the product or service’s use (Is it customer facing? Is it mission critical (yes, be honest on this one)? Is it internal-use-only? Is it backend-use-only?) Then you have to look at WHEN the product is going to be used (day, night, weekends, random).
But most important, you have to look at the actual impact of being without the product or service and for how long you can be without it before a real negative impact sets in. So, for example, how long could you be without your word processing application company-wide before productivity takes a significant hit? Can you actually calculate the damages that would result if noone had access to e-mail for an hour or two? Probably not. So you’re left with guess work. Which makes a vendor (and many customers) pretty squeemish about putting hard dollars to soft numbers.
Over the next few posts, I’m going to talk about a few specifics and we’re going to re-visit the Myth of the Nines. Get out your red pens and engage track-changes… we’re going to alter your service level perceptions.
Oh, and because I was talking about the 1 in 8 chance of getting three good food items earlier, well, it happened yesterday. The Burger King in the Charlotte Airport nailed a plain Whopper, fries and a coke. And it was at a time when I was REALLY desperate for good food, too. Less than 113% chance, perhaps, but still possible.
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