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Our expertise, collaboration, deep insight and innovation delivers better outcomes 

Energy

Solutions & Services

  • Capacity and Network Performance Measurement
  • Decision Support Tools & Predictive Modelling
  • Asset Lifecycle Management
  • Our Approach to Value Delivery
  • Our Team
  • Energy Case Study: Transpower NZ (PDF)
  • Telecommunications Case Study: Telecom NZ  (PDF)
  • Company Profile (PDF)
  • Harmonic's R Expertise - News Update

Decision Support Tools and Predictive Models

Harmonic develops predictive models and customised software solutions, to support decision making. We help our clients by developing models that turn organisational data into a valuable asset.  Predictive modelling is a technique used to predict or forecast future behavior or events, assess risk and the consequences of change.

Benefits:
  • Gain insight from data to understand your unique cost and productivity drivers
  • Informed, pro-active decision making
  • Asset efficiency - mitigate asset failure risk
  • Reduce your inventory
  • Manage infrastructure transition
  • Optimise resources and improve operational excellence
  • Flexibility to phase investment without compromising service
  • Continuous improvement

OUR EXPERTISE

 
Our highly qualified professionals apply a range of quantitative techniques and tools to help you to achieve the best outcome. 

Harmonic predictive model examples:
  1.  Lifecycle Management Solution. A proven and scalable asset management decision tool designed to help manage asset, inventory and resource utilisation. This solution was developed for Telecommunications operators and can be applied to a range of networks including; energy, mining, transport, and broadcasting.  
     
  2. A powerful Planning and Management tool for Energy Supply.  View Case Study (PDF) Harmonic developed a smart analytics solution that allows our client to analyse performance across their network to quickly identify 'hot spots' and to take remedial action. This addresses the issue of being able to retrieve time-critical information over a heavily utilised network.
    • A sophisticated predictive model was developed as part of the tool enabling our client to make hypothetical changes to network configuration in order to assess the potential impacts of performance and particularly the delivery of time-critical data from the field.
    • By understanding the demand drivers on the network our client is able to make changes to the existing network to ease the load and to proactively manage any additional demand.
 
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