The Role of Network Analytics (ONA) in Ensuring Team Collaboration and Well Being
Whenever I speak to a Head of People Analytics or one of their teams, the topic of Organisational Network Analysis (ONA) invariably comes up. Along with continuous listening and how to infer skills, it’s the analytical technique I get asked about most.
Indeed, the article I published two years ago – The role of ONA in People Analytics - is the most popular article I’ve ever published and continues to get an average of 300 new views every week.
There are plenty of good reasons for this high interest in the topic. ONA (or the term I prefer, Relationship Analytics), whether active or passive, can provide fresh insights on the inner workings of an organisation such as how people work together in teams, how teams collaborate with each other, and who are the key influencers that can support with a business initiative or transformation.
The current Covid-19 crisis has spiked further interest in Relationship Analytics as companies seek to understand the ramifications of the biggest remote working experiment in history. Many organisations we work with at Insight222 are using ONA to answer questions such as:
Are our newly remote teams collaborating enough (or too much)?
What is the level of connectedness within and between teams?
Who could be at risk from burnout?
In the last week, I jumped on a virtual call with Manish Goel, CEO and Co-Founder at TrustSphere, where I am a board advisor, to learn more about how companies are using relationship analytics to solve challenges related to Covid-19 as well as other typical use cases. We also discussed tips for organisations looking to get started with relationship analytics including those associated with data privacy.
1. Thanks for talking to me, Manish. Firstly, there’s still some confusion as to what Organisational Network Analysis is and what it isn’t. So, please can you let our readers know what ONA is, and also the difference between active and passive ONA.
Thanks David, a pleasure to speak with you.
As a starting point - an organisation’s networks essentially define how work in an organisation gets done. They represent the ‘fabric’ of human connections and relationships through which work occurs.
ONA is the science of making visible the key pathways of collaboration and information flow across these networks, beyond the often hierarchical, formal reporting structures.
Active ONA typically refers to the use of surveys to collect data about these pathways. Passive ONA generally refers to the collection and analysis of continuously generated data from an organisation’s collaboration systems (e.g. email, calendar, Microsoft Teams, Zoom, Slack etc). The two approaches are highly complementary.
At TrustSphere, like you David, we prefer the term ‘Relationship Analytics’. Relationship Analytics combines ‘passive ONA’ and graph analytics to understand and baseline an organisation’s dynamic structure of relationship based workflows – both internally and externally. This is referred to as its ‘relationship graph’. Relationship graph data allows exploration and analysis of complex inter-relationships between individuals, teams and organisations.
Think of the relationship graph as an organisational ‘MRI’. An effective MRI should provide actionable insights. This requires improving the ‘signal to noise ratio’ across an organisation’s significant volume of collaboration data. It means being able to distinguish between mere connections and relationships. Network analytics algorithms and machine learning improve the signal by measuring the ‘strength’ of connections.
Organisations can use this relationship graph to understand meaningful patterns of engagement, collaboration and inclusiveness across teams and business units. The relationship graph produces an unbiased, empirical understanding of how an organisation functions through a network (ONA) lens (see overview in Figure 1).
Fig 1: ONA – A real-time network view on how an organisation is collaborating (Source: TrustSphere)
2. I know that several companies and people analytics teams were already using Relationship Analytics as part of their work, but the Covid-19 situation seems to have accelerated the extent to which these companies use it and also prompted several other organisations to get on board. Is this what you’re seeing too, and if so how can ONA help companies in confronting Covid-19? What questions and use cases are organisations trying to solve?
Absolutely, David. During a crisis or period of rapidly unfolding change – access to an empirically robust, real-time view on how an organisation is functioning across its underlying networks becomes even more critical. It becomes a map which an organisation can use to navigate these otherwise ‘invisible’ networks.
The unprecedented transition to remote working as well as dramatic shifts in business models as a result of the crisis have made Relationship Analytics an even more important source of decision-making data.
In her recent Covid-19 trends report to investors, Mary Meeker outlined the key “top-of-mind issues with large-scale remote work.” The top three questions she noted that organisations will need to address will be how to:
“1. Ensure creativity is captured and productivity is maintained
2. Determine which teams are optimized by working together in-person all the time /some of the time / rarely
3. Maintain engagement and culture(s), recruit / train / develop / retain people, and manage human resources.”
Across our clients we have been typically seeing an increase in overall digital interactions by around 25%-30%. One interesting pattern we are observing is a contracting of some of the network structures – which means that in some instances even though people might be more active they are collaborating across a reduced breadth of relationships. In this environment, comparative data (across time and teams) allows leaders to quickly identify areas of vulnerability and understand patterns for optimal workplace collaboration at both the individual and team level.
Responsive (rather than purely reactive) decision-making during a crisis requires effective prioritisation and targeted leverage of resources toward vulnerable teams and areas of organisational risk. Companies also need to meaningfully engage with, rather than burden, employees at a time of increased stress and pressure. Because relationship analytics provides diagnostic and predictive signals about organisational resilience and employee wellbeing – it is being used to enable leaders to make rapid, informed decisions by using network telemetry.
We have been in close touch with many of our clients across different sectors and the most pressing questions they are trying to solve with ONA fall into three broad categories:
First – they are looking to understand the impact on individuals and teams of the shift to remote working. As a leading indicator, Relationship Analytics can signal which teams are at risk of becoming isolated or at high risk of overload or ‘burnout’; enabling organisations to continue to protect employee work-life balance and maintain cultures of innovation.
Second – companies are looking at the impact on customer pipeline/revenue as a result of the increased risk of relationship disruption during the crisis. Relationship Analytics helps identify which customer accounts in the sales pipeline are vulnerable or ‘at risk’ of attrition. Relationship Analytics insights can be utilised to ‘nudge’ sales teams to re-engage with these customers.
And third, organisations are increasingly focused on navigating business model change while preserving organisational resilience, innovation & collaboration. Relationship Analytics can identify an organisation’s key ‘influencers’ (central nodes), helping leaders understand how to engage and mobilise these key employees as change agents to ensure resilience.
Through ‘continuous listening,’ Relationship Analytics also allows companies to rapidly measure the effectiveness of the interventions they are implementing.
3. Can you provide any specific examples from your clients?
Certainly, David I would be happy to share a few examples:
Global Healthcare provider
A global healthcare provider recently used ONA to optimise cross-functional collaboration across the organisation. Relationship Analytics helped identify cross-functional ‘boundary spanners’ – individuals who act as connectors across diverse teams and groups within the company. This group of cross-functional influencers being surveyed more frequently during this period of rapid change, to provide feedback on organisational issues and challenges from the frontline during the current crisis.
Rapid and responsive decision-making by organisations requires the ability to mobilise an agile network of teams that include such ‘boundary spanners’ who often exist outside the traditional hierarchical structure.
Financial services company
We have worked with a financial services client who wanted to understand the impact of remote work on different job functions. They used Relationship Analytics to compare how their customer relationship and technology teams (some working remotely, others located in the office) manage their internal and external relationship networks. As organisations navigate longer term operating model change toward remote and flexible working arrangements, it will be important to measure and evaluate the appropriate mix to support continued network collaboration.
Technology company
Another example - a technology client used our network relationship transition-reporting tool for new and re-assigned sales professionals to help quickly transition customer relationships and prospects in order to protect the sales pipeline. Onboarding can be even more challenging in a fully remote working environment. In this case, the organisation was able to reduce the ‘time to productivity’ for such employees by around 70%. Remote onboarding will likely become more prevalent in the new environment.
4. What data sources does TrustSphere typically analyse?
Typically, TrustSphere analyses data from the enterprise communication and collaboration systems e.g. email, Microsoft Teams, Slack, Zoom etc. To protect privacy, we never analyse any content or subject lines – just log data to understand the patterns of interactions.
In our experience, the network analytics signal can be enhanced when contextualised with other data sets. As a result, we also work with a variety of partners (see Figure 2) to analyse HCM data, CRM data, conduct active ONA analysis and also help with ethical sentiment analysis as clients require.
Fig 2: TrustSphere’s Relationship Analytics Platform (Source: TrustSphere)
5. I know from speaking to a number of companies that concerns around privacy and compliance have slowed them from getting started with Relationship Analytics. How do you manage privacy?
This can certainly be a challenge. It is worth noting that in many organisations, communication data is already being captured and analysed within the existing enterprise applications (such as CRM systems). In our experience, privacy and compliance concerns are best addressed by placing employee interests front and centre and precisely defining the intended use of data.
At TrustSphere we have developed a ‘data privacy and security by design’ methodology. We have built this from our experience across a wide range of client environments of differing complexity – geography, size, industry, cloud and on-premise etc. We regularly work with People Analytics leaders to help them navigate the privacy approval process including advising on their Legitimate Interest Assessments (GDPR Article 6(1)(f)) and staff communications.
Interested in learning more about Python, ONA and People Analytics? Take a look at our online People Analytics & Digital HR training courses on myHRfuture
Within its core design and operation, our Relationship Analytics Platform has embedded privacy and data protections to ensure compliance with global privacy legislation (e.g. GDPR), ethical codes of conduct and other regulatory frameworks. These include protocols for data de-identification, data aggregation, and data minimisation (i.e. log data only, never content or subject line analysis).
Our key use cases have also been developed to be fully GDPR compliant. Importantly, we have always set our standard as ‘beyond legal compliance’. We have established an employee centric, ethical protocol for communicating and explaining Relationship Analytics for diverse environments including highly regulated industries. Our approach is based on notification, consultation and ‘opt-out’, which ensures trust, transparency and choice for employees when organisations implement our Relationship Analytics platform.
6. What advice would you offer to companies and People Analytics teams looking to get started with Relationship Analytics?
For many People Analytics teams and the organisations they serve, ONA / Relationship Analytics might be a new source of data analytics. To ensure optimal implementation a staged, considered approach is often the best way to ensure meaningful impact. Often companies start with a pilot project and build from there.
When setting up a pilot we recommend the following:
Start by identifying a specific problem that matters to the business and articulate the sought after impact. The journey map below (see Figure 3) shows some of the high-level use cases and their ‘degrees of difficulty’.
Keep the scope manageable and set expectations appropriately. While ONA maps might be visually attractive, the value comes through producing actionable insights.
Find a strong business sponsor who will be able to help ensure buy-in from diverse stakeholders.
Involve the IT and Privacy teams as well as employee representative groups such as Works Councils early in your discussions and together define a clear project scope (this will help ensure their support).
Consider partnering with a vendor (there are several good ones out there) who can help you navigate the journey to a successful Relationship Analytics pilot experience
Fig 3: Relationship Analytics (ONA) Journey Map (Source: TrustSphere)
7. How can companies use the insights that Relationship Analytics provides? What are the typical benefits for Executives, Managers and Employees?
Relationship Analytics use cases are wide and varied in scope and scale – ranging from improving key HR processes (e.g. onboarding) or meaningfully impacting diversity and inclusion outcomes, to supporting organisational transformation (e.g. measuring levels of integration post M&A).
In developing our Relationship Analytics approach we have kept a primary focus on ‘democratizing’ data by ensuring that individual employees, managers and organisational leaders are all empowered to utilise the appropriate insights to impact well-being, performance and inclusion.
For example, employee ‘nudge’ reports can help sales professionals better manage their own relationship capital. Network collaboration reports can help managers build appropriate cross-functional relationships with key colleagues across the organisation. At the C-level, executives can look at a ‘Post Merger Integration MRI’ report, which shows them the teams that are continuing to operate as silos versus the teams that are demonstrating high levels of integration post M&A.
The table below (see Figure 4) shows some examples of how organisations are deriving value from Relationship Analytics insights.
Fig 4: Relationship Analytics Use Cases (Source: TrustSphere)
FINAL THOUGHTS
The full implication of the Covid-19 pandemic and its impact on business, the future of work and HR are still unknown despite numerous commentators rushing to talk about ‘resets’ and the ‘new normal’. The crisis is so abnormal that the truth is that we just don’t know. Nevertheless, it is probably fairly safe to state that people analytics has been elevated by the crisis and that the same can be said for ONA (or Relationship Analytics). Whatever challenges the post-Covid world brings, the shape and structure of our organisations will likely shift, digital transformation will likely accelerate and a greater proportion of the workforce will work remotely more of the time.
As such it will be critical for organisations to better understand and take action on topics like collaboration, wellbeing, inclusiveness and productivity. Relationship Analytics is one of the primary tools to help provide executives, managers and workers with the insights required to be successful.
THANK YOU
Thanks to Manish for sharing his time, knowledge and expertise in this article. If you want to find out more, you can connect with Manish on LinkedIn, you can follow Manish on Twitter and visit TrustSphere’s website. I also recommend watching the video below, which features Manish and RJ Milnor, the then Global Head of People Analytics at McKesson, speaking at the 2019 Wharton People Analytics Conference about how McKesson and TrustSphere partnered to identify the networking behaviours of high-performing sales professionals and teams.
ABOUT THE AUTHORS
Manish Goel is the Co-founder & CEO of TrustSphere, a pioneer in Relationship Analytics & ONA headquartered in New York. Manish is passionate about helping organizations and their people leverage their most valuable asset – their collective relationship network. He set up TrustSphere to develop solutions based on Relationship Analytics to enable organizations to successfully navigate their digital transformation journeys. Manish has over 20 years of experience in the software and services sector. He previously worked with PwC Venture Partners as well as PwC’s Strategic Change Consulting practice where he focused on Post-Merger Integration and Digital Transformation. He has also served as the Chair of the Online Trust Alliance – a not-for-profit focused on ensuring individual privacy and digital trust. He can be reached at manish.goel@trustsphere.com
David Green is a globally respected writer, speaker, host of the Digital HR Leaders Podcast at myHRfuture, and executive consultant on people analytics, data-driven HR and the future of work. As an Executive Director at Insight222, he helps global organisations create more cultural and economic value through the wise and ethical use of people data and analytics. Prior to joining Insight222 and taking up a board advisor role at TrustSphere, David was the Global Director of People Analytics Solutions at IBM Watson Talent. As such, David has extensive experience in helping organisations embark upon and accelerate their people analytics journeys.