Published on March 24, 2020
Data quality issues holding back automation? Here’s how to get federated inventory right, once and for all!
By Mae Kowalke
There are quite a few jobs in our society that most people would deem necessary but unenviable. Increasingly, it seems as if working in telecom operations may fall into that category. Operations staff spend 80% of their time fixing problems rather than preventing them (Heavy Reading, 2019). During outages, 38% of resolution time is spent just trying to figure out the root cause (Heavy Reading, 2019. These teams are also being crushed by shrinking budgets and greater expectations.
It’s no wonder these numbers are so high when you consider that 25% of operations data is incorrect or incomplete, and 44% of operators are not able to see dependencies between systems (Heavy Reading, 2019). This lack of visibility and integration inevitably leads to outages... or, worse, ongoing service degradations that contribute significantly to churn.
But wait, it gets worse.
Outages have increased 22% over the past few years, and almost a quarter (24%) of these are caused by unintended consequences! (Heavy Reading, 2019). For example, a third-party contractor may inadvertently perform updates simultaneously to primary and secondary servers.
As we discussed in a previous blog article, the notorious inaccuracy of inventory systems plays a big role in this unfortunate reality. It doesn’t help that operators typically use 7-9 separate inventory systems! (Heavy Reading, 2019.)
Look at it this way: if you consult three different inventory systems to answer a specific question, and each has a 25% chance of being incorrect, that means collectively there’s only about a 30% chance the systems will align. Making appropriate decisions, confidently is impossible under these conditions.
The need to automate, and the ways in which siloed, inaccurate systems hold that back, is the elephant in the room: 89% percent of operators say data quality issues are hampering their automation efforts (Heavy Reading, 2019). After all, you can’t automate something that’s wrong. Solving data quality problems is crucial.
Change management planning relies on accurate inventory as well as accurate topology. Operators need to be able to see what’s going on (updates, faults, etc.) and understand how these factors impact each other. Getting this right has a big impact. For example, with proper automation and federated inventory, an operator can reduce their automated provisioning error rate from 44% to 5% (Heavy Reading, 2019).
Is there any good news here? Yes!
Technology and methods now exist to properly set up federated inventory and topology in weeks instead of years, with a transformative effect on user quality of experience (QoE). The 71% of operators whose inventory federation projects previously failed (Heavy Reading, 2019) can now get this right without spending a fortune (again) or losing years on wasted efforts.