Wednesday, April 4, 2018

The OD Quest: Part 7 – Integrating the mystical and the analytical!

"I don’t have an opening in my OD team now. But, you can join our recruitment team and do recruitment in the OD way”, I heard the Senior HR Leader telling a candidate who was hell-bent on joining the OD team. This was my fifth ‘encounter’ with this gentleman (See 'Passion for work and anasakti ‘, 'Appropriate metaphors for organizational commitment ‘ ,‘To name or not to name, that is the question’ and ‘A Mathematical approach to HR’ for the outcomes of my previous interactions with him).

I was a bit taken aback by what I just heard. I knew that often these kind of ‘solutions’ will end in tears or worse. However, similar to what had happened during my previous encounters with him, this interaction forced me to think a bit more deeply about the underlying issue - the application of OD(Organization Development) to the various functional areas in HR (Human Resource Management). That, in turn, has prompted me to write this series of posts on 'The OD Quest' where we will look at the possibilities  that arise when OD ventures into other parts of the people management terrain.

In the first post in this series (see
The OD Quest: Part 1- Mapping the terrain) we did a cartography of the Human Resources (HR) and Organization Development (OD) domains to map out the current world (the terrain) inhabited by HR and OD and also the evolving worldviews in HR and OD (ways of looking at the terrain). In the second post (see The OD Quest Part 2 : Doing Recruitment in the OD way) we made a visit to the land of Recruitment and explored the value OD can add to Recruitment. In the third post (see The OD Quest: Part 3 – Rendezvous with L&D) we covered the Rendezvous with L&D. In the fourth post we saw how OD can sweeten Rewards and make it ‘Total Rewards’ (see The OD Quest: Part 4 – Totally Rewarding). In the fifth post, we explored a domain (Industrial Relations) that has often been considered as the antithesis of OD (see The OD Quest: Part 5 - Face to face with the antithesis?). In the sixth post, we took our quest to the domain of HR Business Partners and explored the immense possibilities for mutual value addition (See The OD Quest: Part 6 – In the wonderland of HR Business Partners). In this post, let’s take our quest to the most quantitative domain HR – HR Analytics. For the purpose of our discussion let's define HR Analytics as the application of data science and statistics to improve the quality of people-related decisions.


Organization Development (OD) with its emphasis on social construction of organization reality and focus on work at the level of mindsets, values and basic underlying assumptions is as ‘mystical’’ as one can get in HR. HR Analytics with its emphasis on quantification and use of advanced statistics is as analytical as one can get in HR. So the question becomes, is there anything that the analytical and mystical learn from each other? It has been observed that the interaction between apparently unconnected fields often yields rich dividends. So, let us see what treasures can we unearth in this phase of our OD quest!

I have had the good fortune to straddle both these worlds - organization development and analytics. I have made a living out of OD for more than a decade. I have set up the HR analytics function in two of the companies that I have worked in. I am also a lean six sigma black belt (and hence familiar with both the possibilities and limitations of its fundamental approach of converting a physical problem into a mathematical problem, finding a mathematical solution and then converting the mathematical solution into a physical solution). Managing these two fields at the same time (without creating cognitive dissonance) has been a very interesting experience!  

To me, quite a bit of the apparent distance between the two fields came about because of the skill sets of the role-holders and the separation in the organization structure and not just because of ideological differences. In most of the organizations, people with OD skillet don't usually handle HR analytics and vice versa. Also, typically (stereotypically?!) OD professionals are more skilled in qualitative modes of  exploration whereas the HR analytics professionals are more skilled in quantitative modes of exploration. Again, while OD is usually housed within the HR function, the HR Analytics function is often housed in the Business Analytics function. This sometimes lead to a situation where people handling HR Analytics are mainly data scientists without experience in HR and they just take the requirements from HR Mangers, do the analysis and give the results back to the HR Managers (and hence in a way work mainly in the mathematical problem-mathematical solution part of the problem solving approach mentioned above). This compartmentalized approach can lead to significant loss of opportunity in deriving meaning and actionable inferences from the data.

While the most frequently used modes of exploration are different (qualitative versus quantitative) in the two fields, the fact still remains that both the fields are often exploring the same organization reality. This is the fundamental point of convergence between the two fields.

Of course, there are issues related to stereotypes. Many of the people in OD are skeptical about the seductive power of numbers and their ability to mislead  where as people in HR analytics are often vary about the fluffy and vague nature of OD and the pathological reluctance to define things precisely and in a standardized manner. But, the purpose of both the fields is to facilitate more effective problem solving and decision making in organization, especially on people related aspects. So, there is a logical need  to work together and based on my personal experience, I can confidently say that the possibilities for mutual value addition are immense.

The Achilles' heel of OD is the inability to give confidence to the business leaders that the OD managers understand the hard realities of business and that that they can facilitate tangible improvements through the OD initiatives. Hence, many business leaders look at OD as something that is done to improve esoteric things like culture and that too only when the business leaders have some spare time after they have addressed the important business issues. I have also seen very senior OD professionals becoming uncomfortable and hence losing credibility with the business leaders when the discussion moves to pure numbers - business numbers and people related numbers/analytics. Working together with HR analytics professionals and enhancing the comfort with numbers and quantitative analysis can enable the OD professionals to start the conversation in the language that the business leaders are often more comfortable with and then (after some level of trust has been built) lead them to other modes of exploration. 

Of course, leveraging HR Analytics can facilitate better diagnosis and solution design during the OD intervention apart from helping in evaluating the implications of the possible solutions and in tracking improvements and in demonstrating the results of the intervention.

The action research method lies at the very foundation of the field of OD and it is a data-driven approach (systematic approach to data collection, analysis, feedback and enabling problem solving/decision making) to organizational change. Of course the data can be quantitative or qualitative in nature. May be because of the skillsets of most of the OD practitioners, use of qualitative data and data analysis techniques became more prominent. While these are indeed useful, they miss out on the insights on the relationships between the key variables that can be unearthed using  statistical modelling. Not leveraging quantitative analysis can also increase the risk of ‘dangerous half-truth’ creeping into the OD practice masquerading as conventional wisdom!
 
Similarly, the Achilles' heel of HR analytics is the inability to ensure that the analytics (the measurements and the analysis) accurately capture and is appropriate for the underlying reality that is being analyzed (See A Mathematical Approach to HR?). Another deadly temptation in HR analytics is to take a large database and then look for patterns in the data. This is more of 'data fishing' and not analytics. The problem is not that one cannot find patterns. The problem is that it is difficult to figure out which patterns are relevant or worth exploring for supporting decision making. Even when a significant pattern is detected, it might not be a simple matter to figure out how it should impact the decision-making. For example, if the analysis of employee attrition and its business impact clearly shows that early attrition is very costly to the business and that the early attrition rate among female employees is twice that among male employees what action should it trigger? Don't hire female employees (so that the cost can be avoided) or make extra investment/efforts to retain them? Obviously, this is a matter of what does the organization 'value' and why. OD can help in facilitating this kind of deeper exploration.

OD can also help in terms of facilitating a deeper understanding of the underlying reality and in creating conceptual models so that better hypothesis formulation for testing through analytics can be enabled. This is especially critical now, as the expectation  from HR analytics is shifting from descriptive analytics (that mainly describes the past) to predictive analytics ( that focuses on predicting the future). OD can also be very helpful in creating a compelling narrative based on the results of the analysis that can maximize the chances of the analysis actually informing the decision making process. Also, unless this (leveraging analytics to inform decision making in a consistent manner) is taken up as an integrated change management initiative, there  is very limited possibility that something truly useful would come out of HR analytics.Since OD is essentially about facilitating change, OD can be of immense help here.

So where does this leave us? A triangulation approach of combining an essentially qualitative method ( the traditional domain of OD) and an essentially quantitative method (traditional domain of HR analytics) can almost always lead to much more comprehensive understanding of the organization context/reality and hence facilitate much better decisions.

At some level, this is about enhancing your toolkit so that you are not limited by your tools so that there is less chance of all problems looking like a nail (e.g. problem with the culture of the organization) because the only tool you have is a hammer (e.g. culture mapping tool). At a deeper level, it is an acknowledgement of the complex nature of reality (that needs different lenses to see clearly) and the fact that human affairs are often over-determined (there are multiple causes to a situation). As the organization contexts becomes more complex and dynamic, this becomes an absolute must. If the initial sense of 'strangeness' between OD and HR Analytics is overcome by working together and getting to know each other's craft better, an immense amount of mutual value addition (and value addition to the organization that employs both of them) is possible!

Any comments/suggestions before we take our OD Quest to the next domain in the HR land?

2 comments:

Little Miss Muffet said...

The question is how to develop mutual trust between OD and HR analytics folks. Would love to have an integrative approach developed and disseminated or taught by someone like you, who understands the inherent biases and strengths of each camp and who takes a neutral position.

Prasad Oommen Kurian said...

Thank you Kavita. To me, the key for building trust is to generate more awareness on the shared objective of the two fields (enabling better people related decisions) and on the mutual value addition possible. While classification/labeling of tools or approaches as OD tools, statistical tools, six sigma tools etc. has its uses from an academic point of view, these classifications create artificial boundaries and do more harm than good from a practitioners' point of view. After all, what really matters is the appropriateness/fit of a particular tool in the given context.