Manager, Process, Data & Analytics at Hugo Technologies

ROLE OVERVIEW

• The Process, Data & Analytics team is responsible for using data and analytics to continuously improve recruiting, performance, and retention in our Customer Support teams.
• This includes
  • Creating/redefining the operational processes that touch each aspect of the agent life cycle;
  • Capturing, organizing and managing the aggregated data in a way that ensures its credibility, usability and practical applicability toward improved operating outcomes;
  • Analyzing captured data in order to garner unusual insights and/or practical recommendations for operational improvements;
  • Operationalizing these insights via tests, experiments and wholesale changes, alongside key stakeholders across the Customer Support organization, to drive improved outcomes;
  • Automation.

KEY RESPONSIBILITIES

• You will be measured against the backdrop of both (1) being an owner - charged with designing and building data systems, and making your own decisions in this regard; and (2) being a operator (change-agent), charged with the responsibility of bringing about operational changes that drive toward performance and outcome improvements (again, based on your work with data).

Culture-wise, “what will you build this week” and “what did you build last week” will be the driving questions that focus all conversations. 

• Operationalize Data Collection Processes: First, we must understand and agree that no structures, processes or frameworks exist to capture any of the data that you will ultimately analyze and make useful. 
• Data Capture: Hugo’s current data, both re: its volume, diversity and integrity, is weak, non-existent or not credible. We will thus not seek to draw any conclusions from it. 

Instead, we will seek to capture, verify, and stress-test our own primary data ahead of any analysis/application. Single sources of truths (“SSOT”) will be a necessary requirement for all data types.  

• Analysis/Analytics Capabilities: Analyzing data to arrive at insights, truths and conclusions about our business, but that are also grounded in practical opportunities for change that drive operational/performance improvement.  
• Operational Improvement. There will always be 2 sides to this coin. (1) improvements that allow for new, more accurate or different sorts of data to be captured; or (2) improvements that drive better outcomes, workforce or service delivery wise. Approaches to operational improvements include:
  • Tests. E.g. A/B testing.
  • Experiments - thesis/data-driven.
  • Wholesale Changes to operation.