EMPLOYEE ASSISTANT

QUANTITATIVE AND QUALITATIVE RESEARCH

PROBLEM

Centrica People Services (CPS)- the call centre that handles employee problems is not very efficient - only 50% of calls are resolved. HR asked us to help them identify the most valuable problems to fix and were keen to know how artificial intelligence could possibly reduce the need for CPS by helping employees self-serve and reduce cost to company.

APPROACH

  • Call log data analysis through Natural Language Processing 

  • Call times analysis

  • Heuristic evaluation of employee help system

  • User Journey mapping

  • Employees surveys

  • Prototype a conversational interface

  • All finding collated in report

OUTCOME

Based on our research, a conversational interface has been commissioned by HR. We are now working with the AI team in iterative sprints to build, test and refine a desktop based conversational employee assistant.

CLIENT RESPONSE

"You've done a great job at speeding up the process and connecting all the dots. Keep doing what you're doing!"

Jeremy Orr - Director - Global Digital Enterprise Systems

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