This point is important for any engineer, but it is critical for those of us who deal directly with customers - Applications Engineers (AEs), for example. The following “Mixing Table” metaphor has been developed in this context. Setting up your own Mixing Table will help you to detect potential cross-cultural issues and, hence, defuse them before they cause problems.

The sliders of my Mixing Table can each move between two value-extremes. For example, some cultures place a higher value on individual contribution than on behavior that is supportive of the group. The slider for such cultures would be placed towards the “individual” extreme on an individual-group axis.

This general concept is not new – the oldest system of this sort explained people’s behavior by their relative levels of black bile, yellow bile, blood and phlegm. More recently, Hofstede proposed five dimensions of culture, based on worldwide research with IBM.

In contrast with these approaches, I propose neither the extraction of the client’s body fluids nor the definition of fixed cultural dimensions. I offer only a metaphor, a couple of examples, and some instructions on how to build your own Mixing Table.

Why this minimalist approach?

Have you ever noticed that when you write a script to analyse some complex data, that you learn more about the data by writing the script and you do from running it? It is the same with the Mixing Table. Building your own will, in itself, increase your sensitivity to cross-cultural parameters.

Further, one size definitely does not fit all when it comes to the analysis of a real cross-cultural situations. When we think of crossing cultures, international differences are the first that spring to mind. However, there are many other significant cultural sources: company, profession, age, sex, personality type, and so on. Basically, any trait that can characterise a group.

For example, I recently gave Applications Engineering training courses in Schenzhen, China to two different companies. The cultural differences between the two companies felt at least as significant as those which separate Europe and China. One group was very passive, the other much more inquisitive. Both were demanding, but in very different ways.

Not long after, when teaching in Japan, I found that the differences between senior (older than 40 years) and junior Applications Engineers were more marked than any other cultural distinction. This, according to the local Human Resources manager, can be explained by the evolution of the japanese education system over the past 50 years. In the seventies, it was still very traditional, with the teacher taking a role of absolute master and pupils having little opportunity to ask questions. This approach has gradually changed, and now japanese children receive more encouragement to speak up, and classes are more interactive. This is consistent with my observation that the younger members of the class were far more at ease with activities that required openness and interaction.

So what are the rules for setting up my own Mixing Table? In brief:

  • Each slider must be, as far as possible, independent of all the others (i.e. the axes of my model should be orthogonal)
  • The extremes of each slider must have labels with opposite meanings, but the same grammatical type (e.g.: expertise versus position - both are nouns; risk-taking versus prudent - both are adjectives)
  • For each slider defined, a short text should described the characteristic being measured. This exercise clarifies the concept that I wish to capture (for others maybe, but above all for myself)

Here is an example of a single slider – I normally have four or five on the Mixing Tables that I use in training courses and workshops:

{Prudent, Principles} versus {Risk-taking, Pragmatism} : This variable represents an important aspect of a culture’s management style. The first style extreme is very careful and seeks to stick to a certain way of doing things. The other is more open to taking risks and to using unconventional means in order to achieve a desired result. The variable correlates well with the UAI dimension of Hofstede.

There is no need to label this trait as a national one, a generational one, or whatever. The origin is not so important. It is simply necessary to be sensitive to the different styles and, if possible, non-judgmental.

Have fun setting up your own Mixing Tables!

To go further: