XMPRO Recommendations - Event Intelligence Applications

XMPRO Recommendations are advanced event alerts that combine alerts, actions, and monitoring. You can create recommendations based on business rules and AI logic to recommend the best next actions to take when a certain event happens.

Go to https://xmpro.com if you want to learn more about how you can build real-time applications with our low-code Event Intelligence Platform.

Transcript

ex-emperor recommendations are advanced

event alerts that combines alerts

actions and monitoring it creates new

event alerts based on business rules and

or AR logic and it recommends the best

next action based on expert suggestions

it also monitors the actions and the

outcomes to close the loop on event

response

this means that operations can respond

to critical events based on expert

knowledge in the organization before the

opportunity expires while managers can

close the loop by monitoring that it's

done in a timely and appropriate manner

let me run you through the exemplary

recommendations creating simple

applications thought by bringing in data

from multiple data sources and we create

some application or visualization around

it and then put that in front of users

to respond to key or critical business

events with recommended actions based on

the knowledge of those experts in the

organization and that is the role of

recommendations in there in the

excellent pro system so let me show you

how that works this is an example of an

XM pro event app it was configured with

our app designer and it features an

event board in this instance that

highlights key events that are starting

to happen across certain areas of my

plant and certain equipment and for each

of those they are recommendations which

were triggered based on conditions for

this as well as recommended actions on

what to take and again there's some

other additional information from a

application point of view that might be

interesting for us what I'm interested

in at this stage is the recommendation

around this bump now I could drill into

the actual bump and look at it but what

I'll do from here is just have a quick

look and see what this recommendation is

what the alert was that triggered it and

what the recommended action is around

resolving this let me draw into this

bump so this is the data that triggered

that recommendation for certain

conditions when

it and I'll demonstrate that in a minute

what those rules are behind this but

this was the die turn that they

triggered that these are some of the

instructions around how to potentially

do this but because I've been working on

this blonde for a long time and I also

know some of the other conditions and

other equipment I could provide a

comment and you from my expert point of

view and provide input to the person

that actually needs to go and do

something on this now in this example

there's potentially a problem with the

in-line fault on the cooling tower and

that's why we're eating something around

the block suction pipe and it's causing

a challenge with the discharge pressure

so this is one of the mechanisms of

capturing knowledge that's been there

for a long for a long time people who

have had experience on that plant or

that type of equipment you can very

quickly identify some of the key things

that we might need to do so now that

I've done that I can either

automatically create a work order or

work request into a back-end system but

in this instance I will just put in this

work request number that I've created in

my yeah M system or plant maintenance

system and it will then as soon as I

save this and it finds that a

maintenance plan or someone has created

a work order for that it would then

bring that work order information back

for me in real time so that I can see

this has been actioned that information

is then brought together in terms of

looking at how we follow this process so

I can now monitor and that there was an

alert that I put in a request and that

request at some stage is turned into a

work order and I can also monitor the

work order status to make sure that

these alerts are being addressed now

how we set these alerts up is under the

rules side of it so we manage the

recommendations and again this is a kind

of a global view of all the

recommendations and I can resolve them

are they individually or as a group but

what I'll do in this instance is

actually look at the rules behind them

how do we set up these recommendations

now that specific one for the pump on

the discharge brazier and I'm gonna this

is not a detailed explanation but just a

very high-level explanation of how you

would put that together we had that out

of efficiency range rule so that you can

have multiple rules that you set up and

in this instance this information for

this rule comes from the data stream

that sits behind it so we've got real

time flowing data and this then

interrogate that data based on the

frequency that you said it could be

every second every five minutes if

you're half an hour half a day or a day

or whatever works for this specific

business guys in terms of how frequently

we want to run and check that against

this rule we've said the the parameters

for that it doesn't have to be a numeric

number it could also bring back me if I

use for example feed right and versus

flour right so if the flour is really

less than the feed right then I might

want to trigger this so this is how you

set up recommendations and those

recommendations are the ones that you

saw at the front where it creates those

red bubbles or red dots to tell me that

there's something wrong and I can now

quickly see key events I can quickly see

what the recommendations are and then I

can start monitoring the process in

terms of how long did it take to

generate in terms of someone being

assigned assigned to resolve and on how

long does it take us to resolve these

and also how many of these

recommendations are being acted upon and

that provides the full feedback loop to

make sure that we don't only alert but

we also recommend what to do and then

check that that is being done in the

best and timely way

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