Wouldn’t it be nice to understand exactly who the influencers are in your organisation? Social capital is critical to people and organisations, and has an emerging role to play in the HR Analytics field.
What if you could also accurately identify potential high-performers early in their careers? Would this change anything about how your company nurtures talent?
Organisational Network Analysis (ONA) is not a new phenomena, but it is a new trend for HR Analytics, aided by technology developments. The benefits of ONA for organisations are numerous, with some even suggesting that it can play a critical role in achieving digital transformation.
How does ONA and HR Analytics work together? Let’s take a closer look:
What is organisational network analysis (ONA)?
Organisational Network Analysis (ONA) is a scientific methodology for visualising and analysing the formal and informal relationships within an organisation. It is a structured way to visualise how communication flows through your organisation, how information is gathered, and how decisions are made.
Deloitte provides a great explanation of how this works. Their description states that every organisation has nodes (people) who are the central conduits for information. They break down the different types of “nodes” in the following manner:
- Central node: These are the people who seem to know everyone. Central nodes share lots of information and influence groups quickly. Central nodes can be anywhere in the hierarchy of an organization, are often well liked and highly engaged in company news and developments.
- Knowledge broker: These people create bridges between groups. Without knowledge brokers, information and idea sharing grinds to a halt.
- Peripheral: Easily overlooked and unconnected to the rest of the company, high-potential peripherals can be a risk to organizations. Exceptional Java coders who don’t teach others best practices not only stagnate product development, they are also easily convinced to take their talents elsewhere.
- Ties: Ties are the formal and informal relationships between nodes. Establishing optimal relational ties between central nodes and knowledge brokers helps ensure useful information moves easily between and within groups.
The diagram below shows an example of these different nodes and how they might be structured:
At a minimum, ONA helps organisations identify where each of their people sit and how information typically flows. As Michael Arena of GM put it, ONA provides organisations with “a new lens to evaluate how people show up in an organisation.”
Why is Organisational Network Analysis important?
Many organisations just don’t operate under traditional hierarchical structures anymore. At least, if they do on paper, they often don’t in reality. As CEO of Innovisor, Jeppe Vilstrup Hansgaard says; “all organisations have informal networks, beside the formal structures.”
This is illustrated by the diagram below, which shows the formal organisational chart at the left, then the ONA of how communication is really occurring at the right.
What you will notice is that the Senior Vice President is more at the periphery of communication and knowledge transfer, and is potentially an untapped resource. Cole, a middle manager, is a “central node,” communicating with everyone across different groups. You can also see that Sen sits well at the outside, a potential turnover risk and maybe a loss to the company, especially if Sen is highly skilled.
As organisations continue to shift toward more agile structural models, ONA helps us to understand how those structures are working. This gives us the opportunity to try new programs or make improvements where needed. For example, the organisation in the diagram might look for better ways to use Jones as a resource.
At its core, ONA can help organisations unlock potential for innovation, productivity and improved performance. It also helps for identifying where the company can do better, for example how they can enhance the employee experience.
Overall, organisations see ONA as an opportunity to gain a competitive advantage. If you’re making the best use of your resources, you’re facilitating strong communication and creating a great employee environment. You’re also creating a strong climate to drive performance and success.
Greg Newman writes that ONA adds the dynamic of “social capital” to the typically static “human capital” data that HR Analytics teams have traditionally relied upon. Social capital includes the networks and relationships that people utilise to get their work done, whereas human capital refers to the traits and skill sets that they use.
Social capital plays a big role in team performance because workplaces don’t typically rely purely on skill sets to do the work. If you were to examine teams that aren’t performing up to their potential, you’ll often find that they could use some improvements in their social capital. Where teams are overly hierarchical and block communication flow, for example, this can result in poorer performance.
Where does ONA fit with HR Analytics?
To put it succinctly, HR Analytics is concerned with accurate data analysis across many applications, while ONA is one such form of data analysis. Analytics leaders across many organisations have expressed that their goal is to learn more about ONA and apply it to their work.
Where does the data come from? David Green describes “passive” versus “active” ONA, with data either coming straight from what people report (active), or being mined from what people do (passive). Using a combination of the two helps to build a more accurate picture.
It is the role of HR Analytics to use ONA to generate insights and recommendations. Here are a few examples:
- Pairing employee schedules with ONA data to help make better scheduling decisions
- Identifying silos of information and finding ways to help improve information flow
- Identifying skilled employees who are sitting at the periphery and looking for ways to engage them
- Identifying early who potential high-performers are and finding ways to enhance their development
- Pinpointing who the central nodes are – these are important people to engage with for ensuring any changes are successful, for example.
Case study: GM
Michael Arena, Chief Talent Officer at GM wrote a book detailing how GM is “changing the way they change.” In Adaptive Space, he talks about how he views change as iterative or dynamic, rather than the more traditional fixation on “one size fits all” practices.
GM has used ONA to disrupt themselves from the inside and stimulate an innovative environment. The old-fashioned top-down structure which is still employed by many large companies was stifling to innovation, so a new model was needed.
GM began by analysing the connections between employees. This allowed them to determine who would be good candidates to be brought together. They wanted those who would be likely to have the biggest impact on innovation and product design to be working together. They created an environment which would be conducive to the sharing of ideas, which became known as “adaptive space,” just like Arena’s book.
One of the things that makes this approach different is that it was initiated by HR. In most traditionally-structured companies, grouping for innovation wouldn’t be in HR’s job description. However, the use of ONA put Arena and his team in the unique position of having the best information at hand to set up the teams.
Since implementation, GM has been able to launch several new products with much more agility than under previous models. As Arena says, organisational adaptation is social. It has much more to do with the way you link people up than the traditional processes for change.
Final thoughts
Organisational Network Analysis (ONA) has been around for about a quarter of a century now, but newer technologies have helped it emerge as a trend in HR Analytics.
This is a big deal for HR because ONA opens up many possibilities for practical application. It’s not just about identifying communication flows, but finding likely high performers, identifying ways to improve the employee experience, and much more.
I anticipate that this is a trend that will continue to grow and become an essential skill for HR Analytics practitioners.