How to calculate the right jeopardy metrics in your end-to-end workflows

Last week we created an article that described how to use your OSS/BSS log data to generate reliable / quantifiable process flow diagrams.

We’ve expanded upon this research to identify a reliable calculation of jeopardy metrics. Jeopardy Management is the method for notifying operators when an in-flight workflow (eg customer order, etc) is likely to breach targets such as RFS date (ie when the customer’s service will be available for use) and/or SLAs (service level agreements) are likely to be breached.

Jeopardy management techniques are used to predict forward before a breach has occurred, hopefully. For example if an Order to Activate workflow for a particular product type consists of 10 steps and only the first 2 steps are completed within 29 days of a target of 30 days RFS, then we could expect that the RFS date is likely to be missed. The customer should be alerted. If the right trackers were built, this order should’ve had a jeopardy notification long before 29 days had elapsed. 

In the past, jeopardy indicators have tended to be estimated thresholds. Operators have tended to set notifications based on gut-feel (eg step 2 must be completed by day 5).  But through the use of log data, we can now provide a more specific jeopardy indicator for every step in the process.

The chart above shows every activity within a workflow across the horizontal axis. The vertical axis shows the number of days elapsed since the start of the workflow.

By looking at all past instances of this workflow, we can show the jeopardy indicator as a series of yellow dots. In other words, if any activity has ever been finished later than its corresponding yellow dot, then the E2E workflow it was part of has breached its SLA

To use a more familiar analogy it’s the latest possible date that you can study for exams and still be able to pass the subject, using time-stamped historical data. Not that I ever left it late to study for exams back in uni days!!  🙂

And yet if you look closely, you’ll notice that some blue dots (average elapsed time for this activity) in this example are higher than the jeopardy indicator. You’ll also notice that the orange dots (the longest elapsed time to complete this task across all instances of this workflow according to log data) are almost all above the jeopardy indicator. Those examples highlight significant RFS / SLA breaches in this data set (over 10% are in breach).

Leave us a note below if you’d like us to assist with capturing your jeopardy indicators and identifying whether process interventions are required across your OSS/BSS.

 

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