A New Way to Improve your Team Performance

Use Network Science measure & assess performance accurately

One of the many surprises, when I entered the field of Operations, was how success is measured for an Operations team. Operations managers or Process Leaders are held to 3 key success factors:

1. How much their team produced,

2. The quality (or error rate) of their production, and

3. The cost-effectiveness of the production.

Employee or Team Management related metrics such as Attrition rate, Employee Satisfaction, or even Training and Development played a role in overall leadership performance metrics, albeit with minimal impact. If the operational metrics did well, the team related metrics were dismissed as irrelevant or assumed to be incorrect. These metrics only seemed to matter when team performance declined, but because of the disparate attention and importance given during “good times”, as an operations leader, it was easy to just do the bare minimum on these areas and myopically focus instead on the Operational metrics.

In addition, the team management related metrics were also primarily seen as HR metrics, not for Operational leaders. This inconsistency creates a two-pronged issue for organizations; firstly, that HR managers are held to metrics which have little impact on their day-to-day functions, and secondly, that Operational leaders who deal with the impact of high attrition, low satisfaction, and inadequate training, are not given ownership or credit for improving any of these metrics.

As the old adage goes, employees often do not leave companies, they leave their managers. And those who stay, often do not stay due to the # of units they did or did not produce, but because they identify with the team and company, and enjoy what they do and whom they do it with. Yet Operational leaders who create and manage teams that have strong trusting bonds are not always celebrated or recognized for those trusting bonds — they are only celebrated when their team eventually demonstrates higher productivity or quality, which sometimes can take months or years to materialize, if at all. This delay in recognition provides managers with a warped incentive of managing their team for the short-term results, instead of long-term sustainable success.

On the other end, akin to measuring a scorekeeper’s performance by measuring how well the team performed, HR leaders’ success is not always measured by the processes they perform, but rather by broad team related metrics over which they have very little impact. This results in an under-utilized function, whose role is severely handicapped due to confusion on how and what contribution they can make to the team. For example, one of HR success metrics tends to be ‘attrition rate’, yet if an HR manager identifies that key employees are “burning out” due to excessive workload, they neither have the power or the budget to hire more support staff for that team, nor do they have any control over a given employees day-to-day workload.


Operational leaders should be held accountable for the team dynamics they encourage, and the resulting work culture propagated across their teams. Detailed metrics such as Attrition, Employee Engagement/Satisfaction, Inclusivity, and Effective Onboarding and Training should be added as primary success metrics for Operational leaders, not HR departments.

These metrics reflect the realities facing the team on a more real-time basis than how many widgets went through the assembly line — mainly because the effects of a toxic culture or an over-worked team are only seen over the long-term when enough employees leave that the production levels are severely impacted. All too often, by the time this occurs, the culture and team dynamics have reached a point of no return, and it becomes much harder for any subsequent manager to turn the performance around.

However, measuring the employee related metrics, especially if captured multiple times a year, will allow managers the insight into the drivers behind team performance, and provide them with enough lead-time to correct course and ensure the right talent is retained and developed for continued success.

The employee engagement and attrition metrics are also similar to balance sheets on the financial side — they are accretive and provide a view on the team at a specific point in time, taking into account all the prior activities, instead of just a snapshot of a certain period (such as monthly or quarterly production metrics). This additionally provides insight for the leadership to ensure that their actions are in fact leading to consistent improvement for the team performance, not just a short-term jump in productivity or efficiency.


Employee Related metrics are often seen as capturing the “soft” side of performance and are duly discounted as being hard to measure and even harder to impact. While there are a lot of tools that do measure and try to gauge sentiments and opinions of employees, there are new and innovative ways being developed that actually marry these same sentiments with hard data on actual interactions and relationships between employees. These new tools help leaders measure and gauge how the team is feeling about the company and the work they do, but also understand the most likely root cause for these sentiments and how to effect quick change in the team and improve their performance.

Relationship Network Analysis, or Organizational Network Analysis, has been a field of study and research for more than 3 decades in the academic community. This fascinating field looks at how employees in an organization interact with each other in different scenarios (e.g. social vs. mentorship vs. knowledge sharing) and work to identify patterns of behavior and gaps in networks that can make the network, i.e. the team, as a whole operate more efficiently.

While this field of study has focused on interactions between employees, an equally fascinating industry of employee engagement surveys has popped up over the past 2 decades that purport to measure exactly how an employee is feeling about the organization. This industry has spawned multiple large companies, with to be more than $1B in annual revenue, and is one of the fastest growing sectors within what is considered Human Resources Tech or People Analytics field. These new innovative tools have made it relatively painless for the HR manager to “take the temperature” of an organization at any given time. The only major limitation to these surveys is often just the ‘survey fatigue’ from answering an average of 80+ questions per survey. The length of the surveys is due to their inherent design of using one-sided questions to determine the context behind the sentiments being articulated. While these surveys are very efficient in gauging the sentiment of the employees, their format does not often capture the organizational context of the sentiments, and neither do they fully identify the root causes behind the team performance and behavior.

This is where tools such as OrgAnalytix fit in. Their innovative combination of Organizational Network Analytics with Employee Engagement surveys help managers actually understand the causes behind the issues highlighted by the team, and the fastest, least disruptive way to correct course and address these issues. For example, finding out that 40% of your employees are not satisfied with the level of training provided is great information, but not immediately actionable. Even breaking this down to which gender or which functional team they are part of doesn’t show managers the cause — it just allows for a granular break out of the results. Instead if managers are told that employees are unhappy because they are not connected with the key knowledge sharing hubs in the company, and are on average 3 degrees away from the knowledge hub, then managers can start focusing on how to help knowledge flow more efficiently across the team, so employees feel that they have the right information and training they need to succeed. Without the network analysis, managers would have interpreted the results as more investment needed in training programs. In fact, the true root cause was not training program investment but changes to specific knowledge sharing and communication flow pathways.


Unlike Traditional Engagement surveys, network analysis data is gathered via a simple name selection method where employees have to select the names of their colleagues whom they go to for specific information or roles. They then have the option to then rank their selections. This simple process is augmented by some basic sentiment gauge type questions, such as ‘would you recommend this company to your friend’ etc.. Since the network portion of the tool already captures the context behind the responses, the sentiment related questions can be focused on the general feelings and opinions of the employees hence do not have to be as copious and intensive. This process is less taxing on the team while providing managers with more details, context, and root causes behind the employee related metrics.


This simple method of gathering data goes through several different machines for analysis. Firstly, the data collected becomes completely anonymized to protect the identities of the employees and their responses. The data then gets converted into network maps, one for each ‘Name Selector’ question asked. These network maps go through a variety of machine learning models which identify the roles and network/team dynamics articulated by the team. The ‘Sentiment’ and other Org data is then overlaid on to the network maps which is then analyzed and presented to each manager / the leadership team member, as appropriate for the organization. Any action plans and next steps are entered into the tool directly by each manager and used to track progress for any subsequent analysis completed for the team.


Engagement surveys are not the only tool that this type of analysis can replace. Another facet of the tool is to use these network analysis maps to conduct 360º reviews or understand how Inclusive your team is with regards to diverse employee backgrounds, etc. In addition, this tool can help managers understand which employees are most “in demand” by the rest of the team for certain team-related activities such as mentorship advice or training/knowledge share. Understanding this ‘intangible overhead’ can help managers be more effective in resource management and workload balancing and identify those ‘burn out’ or ‘hidden gem’ candidates faster.

The 3 additional features and applications of this analysis are as follows:

1. Replace your biased 360º Review Process

  • When this tool is used for 360º, we anonymize the names of the people who chose an employee but display the objective “review” on that employee from the rest of the organization.
  • BENEFITS: Because this tool does not limit the responders to just the direct line colleagues, or those chosen by either the manager or the employee themselves (which creates a selection bias in the data), this process is akin to a crowdsourced review on every employee.
  • This analysis also separates out the various roles that an individual would play within any team, such as that of Mentor, or a Cultural Ambassador or an Information Courier. This, coupled with the unique rating mechanism built into the data gathering system allows for a multi-dimensional analysis of every employee in the team.

2. Attract and Retain the Top Talent, including those from Diverse Backgrounds

  • The network maps and sentiment questions asked of the team can be modified to gather data specific to the inclusion, innovation, and sponsorship that employees feel within the organization.
  • Once the data is gathered, we then overlay any categorical information on gender, ethnicity, background, etc.
  • The analysis results will also focus on idea generation, support, and sponsorship of new ideas, and help managers track where and how new innovative ideas are being circulated and vetted and if there are any roadblocks preventing innovative ideas from being implemented.

3. Strengthen Accountability and Trust

  • This analysis helps managers understand the demands that the team and other members of the organization place on each employee, and understand if those demands pose any operational risk to the team.
  • Similar to the 360º review process, while we share the demands placed by the team on an individual, we would mask the identity of the selectors, thereby giving managers an anonymous view on how the team really interacts with each other and if they rely on one person more than the other.


Managing your organization for long term success means Operational metrics have to be updated to include the ‘Employee-related’ metrics, which have been heretofore erroneously been measured as HR metrics. Operational managers, however, need tools and analysis that are data-driven, actionable, and do not create a large overhead for the team. Despite the boom in People Analytics in recent years, managers are still left with a metaphorical Thermometer to measure and help correct complex organizational issues such as motivation, innovation, and collaboration. New innovation which marries the field of sentiment gauges with powerful organizational network analysis can help operational managers understand, assess, and track progress and understand the context around employee behavior, leading to better, more timely decisions for the team.

Learn more at info@organalytix.com or www.organalytix.com


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