Research and a three-year-old

The incident that triggered the thought process behind this post happened when my son was about 3 years old. This was the time when he was trying to figure out 'cause and effect' relationships. So he used to say things like "If I shout in the class, my teacher will scold me", "I ran very fast in the park. That is why I fell down" etc. Those days we used to have an evening ritual. I would put my son on my shoulders and go for a walk. This 'sitting on the shoulders' arrangement made conversations easy even when there was a lot of noise all around. So this led to a lot of interesting discussions. There is nothing quite like a conversation with a curious, confident and talkative three-year-old to force one to be aware of and to question one's assumptions!

These walks would take us near a manned railway crossing/gate. Since he likes to see trains, we would stand there for a long time. After a few days he told me about a 'discovery' he has made "The gate has closed. That is why the train is coming"! Now, we all know that the 'causation' (if any) is the other way around. But purely based on his observations this was not so. He sees one thing happening (gate closes). After that something else always happens (train comes). Based on his 'life experience so far' (or his understanding of the 'system'/'universe') it was reasonable for him to think that if something happens and something else always happens after that the first thing might be causing the second thing (this principle had worked for him in the two examples mentioned above - running in the park and shouting in the class).

So, how would I convince him that his conclusion was wrong? The only way that I could think of was to tell him about the larger system (the railway system in this case - that makes the trains run and the gates close). This solution 'worked' only because there was someone around who knew about the larger system. He could not have come to the 'correct conclusion' purely based on his observations and his life experience thus far (i.e. based on his understanding of the 'system' at that point) .

Now, if we look at the research in behavioral science (or may be research in general), often we don't have the luxury of fully knowing the larger system in which the phenomena that we are observing are happening. Also there might not be anyone who has an adequate understanding of the system to 'enlighten' us. Actually, such understanding might not even exist! (as all the 'possible' events/system behaviors might not have been observed or even taken place so far - e.g. unusual/rare events/system behaviors like those that could result from malfunctioning of railway signals, human error, train breakdowns, accidents etc. or events like 'two trains passing through the railway gate at the same time on parallel tracks' that could arise from from a peculiar/uncommon combination of factors - if we stick with our original example). Often, there is no way we can study the 'entire system' (actually it would be very difficult even to determine the exact boundaries of the relevant 'system' in a particular study). We might not be in a position to look at all the data. So have to decide what data we would study and what data we would leave out. This could bring in biases (e.g. selection bias, survivorship bias etc.) and limitations. Thus, there is a significant risk that we might make the wrong inference (since we are limited by our observations and our current level of understanding of the system).

In addition to this, there are the standard problems with spurious correlations, mistaking correlation for causation, determining the direction of causation ('A causes B' or 'B causes A' or 'C causes both A and B' etc.) and assumptions regarding the homogeneity/uniformity of the system (assuming that findings that are valid in one part of the system are equally valid in other parts of the system). Of course, there are ways of expanding both our 'current level of understanding' and our data set/observations (e.g. study of the existing 'research' in the domain- if relevant and available). But, if we examine most of the 'research' that happens within organizations (for diagnosis and decision making - to solve the immediate problems in particular organization contexts), the pressures of time and resources might dilute the efforts to expand the 'understanding and data set'. Again, it is possible that the 'system' might have changed (in subtle but significant ways - without us noticing it) from what it was at the time we studied it/derived inferences on system behavior. Considering the nature and pace of change in many of the human systems that we are taking about, this could pose a big challenge for making available 'valid actionable inferences' to guide our decision making. Keeping all this in mind, can we expect to do always better than what my three-year-old had managed to do?

Note: I am not saying that useful behavioral research can't be conducted in organizations. My point is just that it requires a convergence of 'realistic expectations', 'will' and 'resources' - which, unfortunately, is not very common in most 'real world' organization contexts. If the 'research problem' can be defined narrowly, I would not even rule out the possibility of 'experiments' (though 'experiments' might not be a 'politically correct' term in organization contexts ; 'pilot studies' might be more appropriate). If such experiments can be conducted in the filed of medicine (where - literally - 'life and death' issues are involved), why can't we try them in business organizations (with proper precautions)? Of course, the problems like the ones that I have mentioned above (e.g. too many variables, difficulty in conducting 'controlled experiments', insufficient understanding of the system, biases in selection of data, assumptions about homogeneity and stability of the population/system etc.) still apply. But we might still get some useful information and/or insights.

Any comments/thoughts/ideas?

See somewhat related posts here, here and here.

Truths stretched too far - Part II : Let them learn all by themselves

This is the second one in the series of blog posts that look at how some very valid research findings ('truths') tend to get misinterpreted/misused when they get 'stretched too far'. As mentioned in the first post in the series, the 'stretching' happens because of many reasons like extrapolation of the validity of the research findings to contexts other than that in which the research was conducted, using 'inferential leaps' between the actual research finding and assumption(s) underlying the HR practice in question, ignoring other factors (other than the factor covered in the research) that have an impact on the current context/ situation etc. There are also situations where these 'stretched truths' are used to rationalize/justify particular HR policies/ practices instead of using research to improve the HR policies/ practices. Sadly, this sounds similar to the saying about the 'drunkard's use of the lamp-post' , that is , 'for support and not for illumination'.

In this post let us look at the popular research finding "Less than 10% of the learning takes place through formal training". I think that this finding is very much true. Most of the learning happens through job experiences and through interactions/relationships. The problem happens when this finding is used as an excuse for 'cutting training budgets without establishing any concrete mechanism for facilitating the learning through job experiences and interactions'. Since 'job experiences and interactions' are outside the traditional domain/mandate of the training function, it is easy (and very convenient for HR) to jump to the conclusion that 'the entire responsibility for ensuring that this type of learning happens lies with the managers and the employees'.

Unfortunately, this type of learning (through job experiences and interactions) does not always happen automatically. Even when the learning does take place, it could be incomplete or too slow. There is a need to put in place a mechanism to structure, facilitate and track this type of learning. This is especially true in situations where there is rapid growth and the workforce consists of relatively inexperienced employees and first-line managers. In these 'high growth - high attrition - large span of control - inexperienced team profile', managers are under too much pressure and hence 'surviving' could take precedence over 'learning and facilitating learning'. Hence we come back to the need for institutionalizing practices that would facilitate and maximise learning through job experience and interactions.

For example, 'the way a job is structured' is a critical factor in deriving learning through on-the-job experience. This calls for an intervention at the job design level to ensure that the jobs have sufficient authority/responsibility and scope/variety. 'Job rotation' and 'special/stretch projects' also offer high learning potential. This would require that the organization puts in place policies/ practices that encourage job rotation and assigning people systematically to special/stretch projects. Similarly, to maximise the learning through interactions/relationships there is a need to institutionalize systems/practices for coaching, mentoring, 360 degree feedback etc. While the learning value of formal training programmes is limited, some times they can serve as a mechanism for creating awareness and to build very specific knowledge/s kills that could facilitate/ maximise learning through job experiences and interactions.

Truths stretched too far - Part I : Blame it on the managers

These days HR practices are supposed to be 'research based'. As HR professionals, when we recommend/implement a particular practice/policy in the people domain, we want to substantiate it with 'solid research findings'. There could be many problems with this. The first is the validity of the research findings in contexts other than that in which the research was conducted. The second problem occurs when there is a 'chain of reasoning' (and sometimes even an 'inferential leap') involved between the actual research finding and assumption(s) underlying the HR practice in question. It is also possible that other factors (other than the dimension covered in the research) that have an impact on the outcome gets ignored (In the people domain, and in life in general, most important things are 'overdetermined' - i.e. they have more than one cause). Of course, there is also the ever present danger of confusing between 'correlation' and 'causation'. In this series of blog posts, we would look at some of those research findings ('truths') that tend to get misinterpreted when they get stretched too far.

In this post (which is the first one in this series) let us look at the very popular research finding "People leave managers and not organizations". I think that there a lot of truth in this finding. The immediate supervisor is a key influencing factor in employee engagement and retention. The problem happens when other factors that influence employee engagement and retention are ignored and the entire responsibility(or even blame) is put on the managers. Often there are other significant factors involved (e.g. the basic nature of the job, 'Rewards' strategy, work environment, lack of career advancement opportunities etc.) over which first level managers don't have much influence. So when the attrition level goes high, the tendency is to respond with 'training the managers on engaging and energising teams'.

This response also suits HR admirably. The factors like basic nature of the job, 'Rewards' strategy, work environment, career advancement opportunities etc. are more difficult influence as compared to 'sending the poor managers for training'. While this gives HR the satisfaction of having 'responded quickly to the business challenge of attrition', unfortunately this does not solve the problem adequately. It also leaves the managers (who are already facing the consequences of attrition in their teams) more confused and frustrated. Hence we come back to the point that 'system level issues' have to be addressed at the system level (and no amount of manager training can obviate this need).

Related Links: Next post in this series , related post