Organizational network analysis, or ONA, is a step forward in people analytics. It represents the organization as a network of relationships, and at the same time reinvents the way we look at relationships between people in the organization. ONA data can provide us with unique and deeper insights into how better connectedness can improve performance and design initiatives that help team members thrive. ONA provides a better understanding of how people are connected, who they turn to for advice, who they trust and how they communicate, expounds Starling D. Hunter, Partner and Chief Research Officer at JOIN21. He will deliver a session with the topic The Business Case for Organizational Network Analysis focusing on why organizational network analysis can be used to bridge gaps in communication across departmental silos, hierarchical levels, and remote locations during the Nordic People Analytics Summit 2021.
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In his interview below, Starling D. Hunter shared more on the topic of organizational network analysis and how it extends the traditional people analytics approach relying on only attributional data, how it can help craft return-to-work plans and the trends that are to be expected in the field.
Hyperight: Hi Starling, we are excited to have you and JOIN21 joining us at this year’s Nordic People Analytics Summit. Before we go into more topic-oriented questions, please tell us a few words about yourself and your background so we can get to know you.
Starling D. Hunter: Glad to! I began my professional career in the aeronautics industry in the 1980s, working as an electrical engineer at Boeing Aerospace in the USA. After five years in that role, I decided to pursue an MBA at Duke University with a focus in general management—a big change, or so I thought! My first position post-MBA was in the HR group in the Engineering Technology division at Exxon Chemical, before it merged with Mobil. Being of the intellectually curious bent, I eventually returned to Duke to pursue a PhD in management.
I began my subsequent academic career as an assistant professor at the MIT Sloan of Management and continued it at Carnegie Mellon’s Tepper School of Business. While my teaching and academic research interests have always been at the intersection of technology and organizations, in many ways I remain an engineer at heart, that is to say, someone interested in the practical application of theory to real-world challenges. Thus, it’s no surprise that I found my way into a start-up where our focus is on applying ideas developed in academia and supported by mountains of research to the very real collaboration challenges faced by 21st-century leaders in technology-intensive settings.
Hyperight: Your Nordic People Analytics Summit presentation will focus on The Business Case for Organizational Network Analysis, where you will use the case of Tesla to explain how and why organizational network analysis can be used to bridge gaps in communication across departmental silos, hierarchical levels, and remote locations. Could you please elaborate more on organizational network analysis and how it can help organizations?
Starling D. Hunter: In short, organizational network analysis or ONA for short is a name given to a set of techniques for representing an organization as a network of relationships, as well as for diagnosing that network. The org chart is an example with which we are all very familiar. It represents an organization as a network based on the reporting relationship. That is to say, it shows us who reports to whom in the organization. This is also known as the chain of command.
ONA just extends the set of relationships under consideration. Those other relationships include, but are not limited to, knowing which people seek each other out for their expertise or advice, which people trust or provide support to one another, and which people communicate intensively via workplace collaboration platforms. The first thing you notice when organizations, as represented as maps of these other relationships, is that they appear much less hierarchical than organization charts.
What we know from the research is that better connectedness means better performance. First, we know that when connections between workers cut across the chain of command—departmental lines and hierarchical levels—the better that organization or unit or team tends to perform. Secondly, we know that the more such boundary-spanning connections an individual worker has, the greater their performance tends to be. That said, individuals and departments differentiate greatly in how well connected they are. Once a leader can see how and how well she is connected to others, and see the same thing for members of her team or department, then targeted interventions can be developed to help less-connected teams and members to flourish.
Hyperight: What are the challenges of traditional people analytics that ONA can help solve?
Starling D. Hunter: In short, while it shares the same goals as all other approaches to people analytics, ONA represents a different, yet complementary approach to achieving them.
All people analytics initiatives have the same goal—to help leaders make better business and talent decisions, decisions informed by higher quality data. The results should be improved performance—both internally and in relation to peers, as well as more streamlined processes like recruiting, retention, engagement, promotion, innovation, etc.
Like other approaches to people analytics, ONA aims to identify the factors that drive individual and organizational performance. The key difference is found in the data.
Traditional approaches to people analytics place on what we call “attributes”, i.e. key characteristics of individuals such as their personality traits, age, tenure, prior experience, educational level, skills and abilities, gender, potential, motivation level, place of work, career goals, etc. Data of this kind provide insights into performance.
ONA takes a different approach. It derives insights from what people do, specifically who they are connected and how. Again, there is a wealth of evidence showing that data obtained via ONA network data explains performance better than attributes alone and even better in combination with them. Thus, it’s complementary to whatever people analytics strategy a company is already using. That said, it requires some training to know how to collect, understand, and apply network data. Our suite of three—Join Baseline, Join Insight, and Join Collaboration—helps organizations do that.
Hyperight: As we are slowly returning to our new-old way of working, it becomes evident that Chief HR officers need a flexible and smooth post-COVID-19 recovery plan. What considerations should organisations take into account as they prepare their return-to-work plans? And how can people analytics and organizational network analysis help with that?
Starling D. Hunter: This is a terrific question. We’re working with former clients right now to help address this issue. In short, ONA offers some very unique insights. As you recall, ONA represents organizations as networks of relationships, not just the formal ones (who reports to whom) but also the informal ones like knowledge and information sharing, advice-seeking, friendship, trust, communication via collaboration platforms. Consider one unnamed organization that we worked with pre-Covid. From that prior work, we knew already how well the organization was connected across units, hierarchical levels, and locations. We also knew which individuals were most well-connected and whose connections spanned key boundaries and demographic groups. Our key finding is that the people in this vital—and often unrecognized role—are largely the same. What has changed is the strength of the connections between people. That is to say, the same people still trust and support each other; they are still communicating and seeking each other out for advice. They’re just doing so just less intensively and less frequently.
Technology in the form of email and collaboration platforms like Workplace by Facebook has played an important role, as well. People who communicated primarily in this way have largely continued to do so at pre-covid levels while those that relied on high-bandwidth communication like face-to-face meetings have seen the most decrease in the strength of their connections. A few interventions derive from these network insights. Firstly, because the strongest relationships were among people communicating in-person, time, space, and opportunity needs to be allowed for those people to re-engage, to re-establish their connections. Where people are coming back in groups, we recommend taking their pre- and post-COVID levels of connection into account. All else equal, people who’ve not stayed well-connected should be prioritized for opportunities to meet again in-person. Secondly, those key individuals who maintained high levels of connected, especially across key boundaries, need to be explicitly recognized for their efforts. In addition, debriefings with them about how they managed, what additional support they need(ed), what they learned, etc. should be undertaken. Similarly, the same needs to be done where the network of relationships fragmented the most. Valuable lessons are contained there for how work, the formal structure, and key processes need to be re-designed.
The future leaders of our best organizations will arise from those who understand and can leverage the value of connectedness across formal and social boundaries.
Hyperight: As a final point, how do you see people and workforce analytics evolving in the next couple of years?
Starling D. Hunter: ONA has consistently shown up on top HR trends surveys for the last decade but has yet to go “mainstream.” The reasons for this include limited knowledge of concept among leaders, poor communication of its benefits by its promoters, and a lack of user-friendly applications. Thus, we see ONA and software-based solutions that support it assuming a more prominent role in people analytics approaches. In addition, because network data is not expensive to collect, represent, or maintain, the benefits of ONA will, we expect, be equally available to small and medium-sized enterprises who may not have large budgets to devote to people analytics initiatives. Finally, we expect that through the addition of the network perspectives on people analytics, leaders and individual contributors will be able to view their organizations and roles within them differently. Recall that some of the first modern org charts were developed in the US in the late 1800s in the railroad industry. It was a patriarchal era where work was largely linear and mechanical. Industries and companies were organized hierarchically and knowledge, like formal power, came from the top. With the days of the Industrial Revolution now firmly behind us, the Information Revolution needs a new paradigm for organizations, one that emphasizes flows of knowledge in a direct, peer-to-peer fashion. The future leaders of our best organizations will arise from those who understand and can leverage the value of connectedness across formal and social boundaries.
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