I’m really excited by a just-finished OSS analysis

In your travels, I don’t suppose you’ve ever come across anyone having challenges to capture and/or optimise their as-is OSS/BSS process flows? Once or twice?? 🙂

Well I’ve just completed an analysis that I’m really excited about. It’s something I’ve been thinking about for some time, but have just finished proving on the weekend. I thought it might have relevance to you too. It quickly helps to visualise as-is process and identify areas to optimise.

The method takes activity logs (eg from OSS, ITIL, WFM, SAP or similar) and turns them into a process diagram (a Sankey diagram) like below with real instance volumes. Much better than a theoretical process map designed by BAs and SMEs don’t you think?? And much faster and more accurate too!!

OSS Sankey process diagram

A theoretical process map might just show a sequence of 3 steps, but the diagram above has used actual logs to show what’s really occurring. It highlights governance issues (skipped steps) and inefficiencies (ie the various loops) in the process too. Perfect for process improvement.

But more excitingly, it proves a path towards real-time “predict-forward” decision support without having to get into the complexities of AI. More has been included in the analysis!

If this is of interest to you, let me know and I’ll be happy to walk you through the full analysis. Or if you want to know how your real as-is processes perform, I’d be happy to help turn your logs into visuals like the one above.

PS1. You might think you need a lot of fields to prepare the diagrams above. The good news is the only mandatory fields would be something like:

  1. Flow type – eg Order type, project type or similar (only required if the extract contains multiple flow types mixed together. The diagram above represents just one flow type)
  2. Flow instance identifier – eg Order number, project number or similar (the diagram above was based on data that had around 600,000 flow instances)
  3. Activity identifier – eg Activity name (as per the 3 states in the diagram above), recorded against each flow instance. Note that they will ideally be an enumerated list (ie from a finite pick-list)
  4. Timestamps – Start/end timestamp on each activity instance

If the log contains other details such as the name of the operator who completed each activity, that can help add richness, but not mandatory.

PS2. The main objective of the analysis was to test concepts raised in the following blog posts:

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