Analytics and OD: Twins Separated at Birth?

During the development of the modern HR function over the past half century, four disciplines emerged that define the essential expertise for strategic HR: business strategy, organization design, organizational development (OD) and analytics. As Dave Ulrich has often noted, the traditional HR function was very inward looking. In contrast, each of these disciplines requires an outward orientation to the business. For those looking to hold on to the past, these expertise domains are like the Four Horses of the Apocalypse for traditional HR. For those who yearn for more strategic and effective HR, they are potential saviors.

Today, few would dispute the importance of understanding business strategy as foundational for HR’s success. Similarly, organization design is a widely recognized essential HR capability. For both, the state of current HR capability in most organizations falls short of what’s needed. Few would dispute the need to close those capability gaps, and today many industry-leading organizations already have quite deep HR expertise in both disciplines.

When it comes to OD and analytics, the gaps between the ideal and current states at first glance appear to be much smaller, compared to strategy and org design. OD has been a core capability in HR for multiple generations, and is widely believed to be important for HR’s success. Though most HR generalists would hesitate to call themselves OD professionals, the principles of OD are foundational for anyone in an HR business partner (HRBP) role. Analytics is much newer on the scene, with dedicated HR capability being built in earnest only over the past 15 years or so. But few would question the need for some kind of dedicated analytics expertise, with most organizations making substantial investments in both headcount and systems to raise the HR function’s analytics game.

Though both OD and analytics are essential for strategic HR, they are treated as two entirely different disciplines, with virtually no overlap in the expertise needed for success. More importantly,

HR professionals tend to sort into one of two virtually non-overlapping groups: those whose mindset is closely aligned with OD, and those who mindset is more closely aligned with analytics. It’s almost like the divide is between logical versus emotional orientations towards people and processes in the business.

The analytics mindset relies on data and objective facts to diagnose and drive decision making, and focuses almost exclusively on quantitative data. The OD mindset, in contrast, relies on qualitative data to focus on group and interpersonal dynamics, and the emotional and other non-logical reactions to change that people have which are not easily addressed by quantitative data and logic models.

OD and analytics are a lot more similar than you think – when practiced optimally. At first glance, OD and analytics appear to be quite different in how they are practiced and how different people within HR align themselves, including the day-to-day work of each group and how people spend their spare time honing their craft.

Analytics is consumed with collecting, cleaning, analyzing, visualizing and storytelling around quantitative data. When presented with a business or talent challenge, the first reaction from the canonical analytics professional is to look for where existing data can provide immediate insights, and then to where additional data can be collected for deeper insights. When not immediately responding to stakeholder questions, the analytics professional is happy to spend her spare time expand her toolkit of quantitative analytics techniques and software packages, to be on the cutting edge of data-based insights and decision making.

OD is consumed with organizational and interpersonal dynamics, including culture, team and group effectiveness, and complex organizational change – the kinds of issues best addressed with qualitative data gathered through interviews and direct observation. When presented with a business or talent challenge, the first reaction from the canonical OD professional is to ask who are the key stakeholders involved, how are they likely to view and react to the situation (what are their biases), what kinds of information or storytelling can help win them over, and where are the gaps between what should happen ideally versus what is practical given the culture, history, and realities of running the business.

Given these quite different orientations, most people draw a line with analytics on one side, and OD on the other, sorting everyone in an organization as aligned primarily with one side or the other: you’re either on Team Analytics or Team OD, either a quantitative “data-based” decision maker or a qualitative “gut-based” decision maker. They think analytics and OD have very different yet complementary ways of approaching business and talent challenges, so it’s best to have both camps engaged whenever possible. Yet it’s a bit of a false narrative that analytics and OD should be treated like different camps with very different perspectives.

There is a great deal of overlap in philosophy and the principles underlying each approach: they are much more like twins separated at birth than the yin-yang complementary disciplines people perceive them to be.

Rather than choose only a quantitative or only a qualitative approach, effective, efficient and lasting impact requires both be applied.

Consider the following 7-step processes for analytics and OD:

Credit is due to Alexis Fink for the analytics process, which aligns very closely with the analytics work I do with companies. The OD processes are two of many that can be found circulating among the practitioner community.

I chose OD process #1 to highlight that, viewed one way, the basic processes of analytics and OD are very similar. OD process #1 puts the data work up front, in steps 2 and 3, with actions based on the data following in steps 4-6. The analytics process focuses more granularly on the data steps. There are different emphases, but largely speaking OD process #1 and the analytics process are two different versions of the same thing.

OD process #2, in contrast, looks very dissimilar to both the analytics process and OD process #1. It also closely resembles the way that many OD practitioners and HR generalists would describe the essence of OD: a way of diagnosing what needs to happen and implementing change using an approach that is not necessarily heavily based on quantitative data. A main reason for the disconnect from quantitative data is that steps 5-7 often fall by the wayside when practicing OD: making the case for change, evaluating different change options, and implementing them is hard enough to do effectively. Taking the extra time to measure, evaluate and discuss what happened are typically viewed as luxuries: rather than spend extra energy and political capital on post-action review, OD specialists and HRBPs instead usually move on to the next org change battle to be fought, repeating steps 1-4 in OD process #2.

Rather than map out separate processes for analytics and OD, consider Figure 1 which combines both approaches in an integrated end-to-end rigorous process:

Figure 1 shows why it’s reasonable to say that analytics and OD are more like twins separated at birth, rather than two halves of a yin-yang approach.

When you consider what should happen ideally, from beginning to end as part of a complete end-to-end process, it’s clear that analytics and OD operate from the same principles and objectives.

In practice, analytics has evolved to emphasize the Analysis part of the end-to-end process, whereas OD has evolved to emphasize the Org Diagnosis and Action parts; and neither analytics nor OD takes the time to do the post-action Evaluation. Ideally, all four parts are needed for the best identification of what should happen and design of effective interventions to improve strategy execution and organizational effectiveness.

What’s the best way to build integrated analytics and OD expertise in HR? The objective of any strategic HR function is to have the capability to conduct the complete end-to-end process in Figure 1. Taking a bifurcated approach to building analytics and OD capabilities is not the best way to accomplish that objective, yet that is what passes for “best practice” in most organizations today.

Many HR functions would benefit from having a larger number of dedicated OD professionals, but the reason for the gap more often comes down to tough decisions about how to spend limited resources: the widespread rollout of the HRBP model typically required redeploying resources away from COEs, and specialized OD groups bore a large brunt of the impact. CHROs know they need both HRBPs and dedicated OD professionals, but when push came to shove they had to choose one or the other, and the HRBP role won. In place of an OD COE, today many OD responsibilities fall on HRBP shoulders who usually don’t have a lot of formal OD training. They make the best of it, but need more support and guidance on how to do the OD parts of their job. And that means the full end-to-end process in Figure 1, not only the subparts that are popular among many OD professionals and HRBPs, such as only steps 1-4 in OD process #2 (which entirely fall within the Org Diagnosis and Action first and third parts of Figure 1).

With OD resources stretched thin, OD projects tend under-deliver because they shortchange the Analysis part of the end-to-end process. Analytics projects, on the other hand, tend to under-deliver because they shortchange the upfront Org Diagnosis and follow-through Action parts of the end-to-end-process.

On the analytics side, there is a perfectly reasonable explanation for how we got to this point. The growing complexity of data warehouses, proliferation of tools, and professionalization of people analytics are more than enough to keep any analytics professional occupied full-time. Yet in order to realize the full potential of people analytics, the profession and the people leading it have to broaden out to include at least the first three parts: Org Diagnosis, Analysis, and Action.

The current division of labor between analytics and OD, with each group swimming in its own lane and not venturing out of its comfort zone, is preventing the effective end-to-end process in Figure 1. The solution requires building greater capability for doing Org Diagnosis and Action among analytics professionals, and building greater Analysis capability among OD professionals and HRBPs.

How hard is it to build this type of cross-functional capability among people who start off oriented strongly towards only analytics or only OD? Easier than it might seem at first glance. We have known for a generation that in order for HRBPs to be more strategic they have to have much more of a business orientation, which means embracing strategy and business logic – both of which are closely tied to the hard-nosed, quantitative data-based diagnosis and decision making on which analytics is founded. Similarly, when doing org diagnostics, OD professionals and HRBPs have to employ a type of systems diagnostics that includes tools that rely on qualitative data, case study analysis, scenario planning, and logic models, all of which go beyond what can be measured and reported with quantitative data analysis and statistical techniques. Such qualitative and descriptive analysis tools are foundational to the work of strategy consultants and C Suite members, and yet have not been embraced by the analytics community because of an incorrect perceived lack of rigor and relevance.

Strategic HR professionals need a comprehensive toolkit that includes both the quantitative and qualitative, whether they would self-identify as being analytics professionals, OD professionals, or HRBPs.

Some specialization will still be needed, including having dedicated analytics COEs and HRBPs whose primary role is to work with the business. But rather than the inefficient, siloed handoff of tasks in the end-to-end process of Figure 1, in that future state the lines between who does the Org Diagnosis versus Analysis versus Action steps will be much more blurred – and the insights and change that emerge will be much more effective, strategically relevant and long-lasting. 

For a deeper dive into OD tools and frameworks applied to the work of People Analytics, please join the People Analytics and Change Masterclass. The masterclass addresses how to integrate people analytics with organization development and change methodologies, and systems diagnostics, for greater data-based insights and business impact. February 19-20, 2020 at PepsiCo in Dallas, TX.

The Enterprise Effectiveness Network brings together senior HR business partners, COE heads, and their teams from leading companies to address organizational diagnosis, work design and strategy execution challenges using integrated analytics and OD approaches.