A low level API is indeed not interesting enough certainly not in relation to the amount
of work it will take. What (imo) is interesting though is getting access to outcome of the
queries and to the images. The company I work(ed) for want's to show this data in the
webapp of the specific application for several reasons:
- marketing wise (look and feel)
- authorization wise (often already implemented in that app, implementing it also in
the/a/one of the consoles is double (or more) work
- functionality wise (they can decide what to show, what not etc.) Give labels a name etc
(see also response below)
anonymous wrote :
| Are there any plans to support business indicators (KPIs)? Because people usually
don't really reason about "the number of process instances", more about
"outstanding orders",
|
Since this is very process specific, (labels), information from processdefinitions
(process name, task name etc.) can (should?) be used to overcome this.
From my (not very broad, but still) experience, the time to complete
an order (one specific I assume you mean here) is only partly interesting. It is
combinations of data that tells a manager how to act.
Some small examples:
- number of open orders goes up, average of the duration of handling an (from the moment
is is really being acted upon) stays the same, then the conclusion is that there are more
orders coming in then can be handled. 'Downdrilling' is not needed
- If the number of open goes up, but the average also goes up and the average of a
processdef. (including stdv) also goes up, then there most likely is a bottleneck in an
external actor (system or human) being used. Downdrilling to the individual times of nodes
is interesting then to see which task/node/... is causing the problem and downdrilling to
get detailed info of e.g. this tasknode can be needed, e.g. is on human always slower than
others, is a generic system always slow, or is it related to data!. The latter may sound
strange, but we've had an issue where a fraud system required a licenseplate number to
be passed to it where the customers told us they did not want a check on validity (e.g. is
the combination of characters a probably existing one). So many users used
'000000' for that in specific circumstances that the system became slow when
searching for possible fraudulent actions with this license plate number).
To me, these are 'fairly simple' to implement when using e.g. Pentaho and these
are operational. Thresholds are needed to be able to have a clean/empty dashboard when
everything is within configured thresholds. The tresholds themselves can come from
analytical data
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