Copernicus Consulting

Entries from June 2008

WalMart’s milk jug: great design or flop design?

June 30, 2008 · 7 Comments

The New York Times is reporting that WalMart’s new fangled milk jug is getting mixed reviews.

What’s not to like? Plenty, as it turns out.

The jugs have no real spout, and their unorthodox shape makes consumers feel like novices at the simple task of pouring a glass of milk.

The design of the milk jug is so bad that WalMart has taken to doing in-store demonstrations of “how to pour” with this new jug.

WalMart\'s new milk jug

This jug is a design flop! Right?

Well not so fast. It seems that the designers of the milk jug created it for a specific purpose: to save money. The new jugs are stackable, saving shipping costs and space. The company saves up to 70% of labour costs using these new jugs. The milk arrives at the store fresher, sometimes even the same day. This jug is a great design! Right?

The truth is somewhere in the middle. If business requirements trump user needs, this product is a winner! It saves time, energy, and most of all, money. It’s easier to ship, easier to manage, and much more efficient.

But if user needs trump business requirements, then this jug is a total flop. No  one knows how to use it. They spill it. Their children can’t pour it themselves, forcing parents to spend more time to use the jug. They feel stupid when they can’t pour it correctly.  Talk about crying over spilled milk! WalMart’s new milk jug off-loads all its design failings onto its users, keeping all the benefits of the new design for itself.

WalMart is famous for putting its business needs ahead of its workers and its communities. Off-loading the negative effects of this milk jug onto its consumers? That’s another in a long line of WalMart putting itself and its shareholders first.

Great design aligns business and user. There are trade-offs in every phase of product design. But not knowing what your users before making a design change makes it impossible to do this. The verdict? Not a total flop, but clearly a business-driven design. Truly great design balances the user’s needs with the business’s needs.

Categories: product design · user experience
Tagged: , , ,

The Myth of The “Average”

June 25, 2008 · Leave a Comment

We bandy about the word “average” all the time. What exactly IS an average, and how does it help design research?

Use the average to quickly summarize something that is already a number: minutes, ages, heights, visits, etc. Don’t use the average to explain something that needs more detail. And keep in mind, the average gets “dragged up” or “dragged down” by extreme values. Sometimes it doesn’t tell you much of anything.

An example design research project might be about how people use their stoves in their kitchens. How can we use “the average” to help us design a new stove?

The average, in statistical language, is actually called “the mean,” which is a measure of “central tendency.” Researchers use central tendency to describe all their results quickly. Other measures of central tendency include the mode (the most common response) or the median (50% of responses are higher than this; 50% are lower).The mean describes the “typical” or average result.

But here’s the big myth: there is no such thing as “the average” in your data. If you ask 500 people to rate your new stove design on a scale of 1 to 10, and the average is 4, there is no guarantee that any single person actually said 4! In fact, the majority of responses could be higher than 7, but some 1s or 2s could “drag down the average.”

Worse, it makes no sense to use the “average” or “typical” in qualitative research. If you do interviews or observations, there is no way to calculate “the average.” So when you say, “the typical person has a four-element stove,” you’re actually doing a calculation. This may be actually quite false. What you may mean to say is “most people in our study have a four-element stove” (which is the mode).

Qualitative research does not accept the “typical.” It actually looks at each case individually and in enough detail to allow for exceptions or outliers. There is no “typical” case in qualitative research because you do not do calculations. You do not summarize your data in that reductionist way.

That said, how could you use “the average” in your kitchen stove study?  You can do a back-of-the-envelope calculation to summarize your data. The “average age” of your respondents, for example, will tell you about how old people are. The “average number of minutes spent cooking” will give you a snapshot of how long people spend in their kitchens. The “average purchase price of a stove” will also give you a quick snapshot. Using “the average” is to quickly summarize something that is already a number.

But the “average use of the stove”? That doesn’t make sense. Nor does the “typical grocery shopping process,” or the “average complaint of stove use.” These cannot be summarized in “the average.”

Categories: Research Methods · product design · qualitative research · quantitative research
Tagged: , , , , , ,