From mobile and FTTH, broadband, internet, MPLS VPN, VoIP, hosting / cloud, to security, telco service providers offer a range of services across domains: But every service is different. 

As a result, there are usually tens-of-thousands of orders in progress and hundreds of variations within the usual service patterns. The result is often a slow and inefficient process. Data gets lost, and service orders are delayed or broken. The ability to see where orders are in the process doesn’t exist. There is also little idea about which activities offer the most value.

Process Diagram

The challenges are numerous:

  1. A slow and inaccurate order and provisioning process slows the sales-to-revenue cycle and results in incorrectly configured services.
  2. OSS systems in the order management and orchestration space are expensive, complex to implement and still rely on an idealised business process. 
  3. Embarking on a big bet OSS system implementation can be risky and time-consuming. They don’t deal with brownfields solutions and the process only generates value many years later.

Operations teams attempt to use business process, systems integration and workflow across multiple legacy systems (each with their own data needs, limitations and users) to get this right. But it doesn’t have to be so difficult.

Simon finds and analyses data from all service instances, then converts it and automatically takes action. Simon does this by learning what the service should look like and implements these patterns across the systems.

Simon helps you:

  1. Understand exactly what’s going on, in real time.
  2. Automate and optimise actions to deliver.
  3. Speed up service implementation.

It uses existing and new data to automatically configure service patterns onto existing systems, enabling a faster order implementation and activation.

Who Benefits?



  • Real world operations: acknowledges the different state and quality of systems, processes and people
  • Much faster with better service implementation
  • Deals with brownfields needs
  • Teams can focus on exceptions and higher order client demands


  • Drive service implementation when you embrace data and ML
  • Deal with complexity and poorly defined services through practical learning
  • Lower costs and lower risks during implementation
  • A better support system for your business and delivery teams


  • Lower cost to implement
  • Fewer risks and faster time to see and realise value
  • No ongoing license costs or dependencies on expensive systems and outside vendors

Need help? Get in touch with aJurumani consultant.

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