Establishing a Cause & Effect Relationship

Does X lead to Y i.e. does X cause the effect Y? Well it might, but how do you validate this relationship?

A lot of thought and effort goes into designing such an argument. It is not always possible to design perfect cause & effect (C&E) relationships in business because of its dynamic nature, but we can always question a C&E relationship to validate it to a reasonable extent. Validated C&E relationships lead to better decision making, however, validation comes at a cost.

Lets take an example to show how a sound argument is designed (example courtesy Prof Amit Das at NBS)

Suppose we claim that a particular training program improves productivity.

How do we support such a claim? To start with we could show that participants coming out of the program are productive.

But someone could challenge us saying that those who participated in the training are no more productive than those who did not. To counter this, we will need to measure the productivity of both, the people who attended the training and people who did not and show that there indeed is a difference in the productivity levels of the two groups.

However, someone might again challenge us saying that the people who participated in the training were already more productive than others (i.e. training did not increase productivity rather the people chosen were already more productive). We can dismiss this argument by measuring the productivity of the training participants before and after the training and show that there was indeed an increase in the productivity.

Next, we could be challenged with the argument that people who did not attend the training also became more productive over time (i.e. everyone gets more productive over time and training did not have an effect on productivity). To thwart this argument, we can measure the productivity (before and after) for the people who attended the training as well as for the people who did not. We can then show that the people who attended the training had a relatively higher increase in productivity levels than the people who did not attend the training.

The challenger's next argument could be that the people who were sent to the training were smarter than the people who were not so they improved faster than the rest (i.e. the increase in productivity was not on account of training). To eliminate this, we have to make sure that those who went for training and those who did not were comparable people.

Another argument against us could be that the productivity improvement was not because of training as such but maybe due to other differences like training location (maybe Bahamas) which might have improved the morale of the participants and hence led to productivity improvements. Well, to dismiss this argument we could have two groups attend two different training programs in the same place and then measure the productivity of the two groups and show that our training program is more effective, other things kept constant. (Frankly speaking this is going too far, most probably we would not have to go to this extent for business arguments).

All said and done, some thought put in designing our argument goes a long way in determining how useful will that argument be for decision making. A casually made argument without proper validations might lead to erroneous decisions costing companies pots of money (Say if in our case the training program was actually not useful, but just a casual argument like 'the training increased productivity' might cause a company to spend loads on that training).

Lessons to be learnt -
1. If designing an argument, put in a little thought and make it as sound as possible.
2. If encountered with an argument, do not accept it without challenging its validity.