Automating the OSS decision-making process

In a typical telecom environment, data to support systematic decision making can feel like “feast or famine”.
On the one hand, the amount of information available, when combined with the expertise of strategic planners with different backgrounds and experience, can be overwhelming. On the other hand, when launching new products into new markets, where the past is an unreliable guide to the future, data that provides guidance for critical decision-making elements such as pricing demand functions, demand for the product in particular geographies, or the cost of OSS/BSS implementation, may be missing or misleading
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TM Forum white paper.

In earlier posts, I’ve discussed knowledge bases and the concept of gamification as means of improving real-time decision-making, whether it’s fault restoration, network designs, traffic engineering, etc. Today it’s Decision Engineering.

Decision Engineering is a relatively nascent field (albeit built upon age-old concepts) that seeks to codify and visualise the decision-making process in complex systems.

Decision Engineering potentially has exciting implications for communications service providers and OSS because it potentially provides a mechanism for continual learning and improvement. It could have the same effect as musical scores had in their ability to spread information (songs) faster and more efficiently / consistently than before.

Perhaps knowledge bases, gamification and decision engineering form the closed-loop of decision making via DSS (Decision Support Systems) interfacing with OSS tools.

Knowledge bases (wikis) are a fantastic method for storing the accumulated knowledge of a CSP‘s environment. Unfortunately they require regular upkeep to capture new learnings. So, the question is broken into two parts:

  1. How to inspire operators to try new ways to solve problems within their OSS tools and
  2. How to then measure and benchmark those actual operator behaviour improvements, then codify them so that they can be automatically fed back as knowledge base content

I believe the first question is waiting to be answered by gamification techniques and the second is awaiting a decision engineering revolution.

The content of your knowledge base then paves the way to becoming a Decision Support System (DSS) that gives operators real-time decision guidance.

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