Whats it for?
The standard method of identifying the cause of issues is to manually hunt through multiple sources of information, looking for common attributes to focus efforts on a specific technology area or, more often, change.
Playbook 6 uses the end-to-end data captured by Operata to make it easy to find these correlated attributes; here's how:
Data on the left-hand Side of the Playbook is filtered for the desired customer entered criteria, including time period, Agent Reported Issues and Softphone errors.
Data on the Right Hand Side show unfiltered data for the same period to act as a baseline.
The tabs across the top of the report shift the data focus across different agent and technology areas.
Comparing the data across both columns quickly shows where the filtered instances (LHS) are out of step with the total number of instances (RHS)
To further aid the process, a Call List of all instances is also created, and there is the ability to filter both the LHS and RHS using a common Estate Filter.
How to use it?
The first step is to define the filters you need to correlate the data against using the Filters feature, then select APPLY FILTERS at the bottom of the page.
The main dashboard, Issue Explorer, will then filter the data, which is shown in two columns:
Left Hand Side - this shows the filtered results, when Error, Agent, Agent Reported Issue or Disconnection Reason are selected as filters.
Right Hand Side - this shows the un-filtered results, to act as a baseline number.
There are a number of tabs across the top of the dashboard, which bring focus to different areas of data collection.
The second tab, Call List, tab shows the Agents and Calls that meet the Filter criteria you have set.
The third tab, Estate Filters, tab lets you filter the Right Hand Side of the Dashboard to narrow down the comparisons.
Playbook 6 - example use
Here's an example of how to use Playbook 6.
Scenario: There is an increasing number of ice_connection_timeout errors occurring, you need to identify any commonalities to focus your resolution efforts.
First use the Filters to select the ice_connection_timeout error state and then select APPLY.
Once the LHS of the dashboard filters for ice_connection_timeout, you can move across the tabs, from Call Details through to Audio Levels, looking for where the number of filtered instances does not line up with the proportion of events seem on the RHS of the dashboard.
In this example the Network IPs shows that most ice_connection_timeout issues (97%) happen for calls using the Internet Gateway IP address range ending in .64, yet this network takes only 10% of the calls.
Using this data, the customer identified that their Proxy bypass rule, missed this range of IP addresses, as soon as the change was made the issues reduced to normal low levels, spread across all networks.