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Laboratorios Sophia embarks on its People Analytics journey


  1. ONA - Organizational Network Analysis to uncover informal leaders and collaboration patterns.

  2. Relationship between benefits and level of performance of the sales team.


Execution Year: 2021 and 2022


About Sophia Laboratories:

Sophia Laboratories® is a global company with over 1,100 employees. The company is deeply committed to visual health and the ophthalmic community, placing the patient at the center of all their efforts. Today, they are an internationally recognized company with a worldwide infrastructure, prepared to be present in international markets with innovative products and solutions in favor of ophthalmology.

With over 70 years since its inception, they are now the leading laboratory in research and innovation in ophthalmic medications. Their state-of-the-art facilities and advanced technology worldwide enable them to produce a wide variety of ophthalmic products. They currently have a presence in international markets and a global vision with the goal of expanding their presence to more countries.

Sponsor of the Projects: CHRO Latam, Juan Carlos Martinez.



First project:

Laboratorios Sophia has embarked on its journey in People Analytics to harness the power of data analysis in the field of human resources. By implementing analytical techniques and tools, the company aims to gain valuable insights into its workforce and make data-driven decisions to optimize people management. With this approach, Laboratorios Sophia seeks to drive performance and engagement among its employees, as well as enhance efficiency and strategic decision-making in the HR department.

ONA - Organizational Network Analysis to uncover informal leaders and collaboration patterns


The organization needed to understand who the informal leaders were in order to carry out a change management initiative associated with the implementation of their "Lean Meetings" strategy. To achieve this, an Organizational Network Analysis (ONA) study was conducted using passive data generated from Microsoft 365 collaboration tools, Teams, and Calendar.

Based on this data, collaboration patterns were analyzed, and individuals with the highest degree of centrality in the Sophia Laboratories network were identified. The 30 individuals identified showed high levels of connectivity and relationships, not only within their own teams but also with people from other areas and hierarchical levels.

Additionally, collaboration patterns of the Directors and Managers from each area were studied to identify bottlenecks, risks, isolated individuals, and the diversity of the network.

In the case of Sophia's influencers, these individuals were invited to participate as ambassadors for the "Lean Meetings" initiative due to their high degree of influence.

The analysis also provided insights into collaboration patterns, such as:

  • Cost of meetings

  • Average meeting time by seniority and demographic criteria

  • Percentage of Lean Meeting methodology usage

  • Number of received and sent emails by Directors and Managers to analyze productivity

  • Level of participation in meetings

  • Types of meetings (scheduled, spontaneous, recurring, others)

  • Time spent in meetings per week

  • Number of collaboration hours



Second project:

Relationship between benefits and level of performance of the sales team


The organization wanted to understand the correlation between non-compliant benefits provided to the sales teams and the number of units sold.

As a first step, since the sales process is not direct, a correlation was conducted to determine if the number of sales visits was a predictor of units sold. Since the sales level does not depend directly on the sales executives, the relationship between the number of client visits and units sold was analyzed.

After validating that sales visits are a predictor of units sold, "sales visits" were used as the business variable to correlate with the benefits. This approach generated several insights to understand the extent to which each benefit influenced the number of units sold, acting as a driver.

Additionally, the optimal point for the number of daily visits that predicts the highest number of units sold was also identified. This data was utilized by the Sales department to calibrate targets and create new sales practices.

From the Human Resources department, the client was able to understand and prioritize which benefits were truly driving the sales executives' performance.



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