Xmpro Best Next Acti...

This short video demonstrate 3 different styles of Best Next Actions in XMPro

"Best Next Actions" is a powerful feature to advise the best step based on external data, what people previously...

Transcript

This short video demonstrate 3 different styles of Best Next Actions in XMPro

"Best Next Actions" is a powerful feature to advise the best step based on external data, what people previously... in this short video I will demonstrate

three different styles of best next

actions in XM Pro I'm currently logged

in as Tim Clark who's the sales manager

and if I look at Tim's to-do list or

task list under the market and sell

products and services

category you'll see that there are

currently two transactions waiting for

him to do two items requiring his

attention

Tim can have a look and see how it got

to him so in the order Trail as it

builds up the order Trail he can see

that it was started by Keith and went on

to Jim and it even includes the XM Pro

social discussions component this is

covered in a different video and I

suggest that you have a look at that in

terms of how discussions can be part of

the transactional order Trail to get

back to the best next actions Tim Needs

to decide on one of the four options on

the right hand inside exm Pros

event-based architecture allows you to

call events like these independently and

they are not wired together at the back

through

workflow now we can embed what we call

inflight analytics to use exm Pro

transactional information or to use

third party transactional information to

help you with the decision so this

information can come from exm Pro

information or any third party business

bus application that you may have

another way of providing some decision

support is to provide some process goals

now these goals follow the process as it

steps through the transaction in this

instance we're looking at information

from the Erp budget to see where we are

currently with our sales um for the

quarter for example and we're also

looking at what is our Prospect pipeline

look like from the external CRM solution

once again this can be ex prob based

information or it can be external

information that will help you with

deciding on what what the next step is

the last component and we will show you

three different examples of this B next

is to look at what the system tells you

what the best next action is and in this

instance it looks at the previous

occurrences this is a simple algorithm a

simple formula it just looks at what

people did before me and out of the 250

odd transactions in here I can see that

the advised action is to do a legal

review so that will allow me if I'm a

new employee or someone uh that needs

guidance that that doesn't know any

other context or don't have any other

information to choose a legal review the

system doesn't make the decision for you

it purely advises what you should do

next because you may still have

information at hand that

will for take you to either do a finance

check or to do recasting you may have

heard something around the credit status

of the customer and decide to look at a

credit check rather than to do a legal

review let's look at another example a

different style example and in this

instance I'm going to log in as John

Smith and John has a different if I look

at his

cases under Life Sciences he's got a

completely different style so in this

instance there's donor verified donor

information this is in the medical area

or uh uh life sciences area and in this

instance when we look at his best next

action so he's got certain information

here and based on that it's either refer

to a specialist um approve the

enrollment get more information or

reject it so his best next action based

on information that is currently filled

in on the screen there's a risk rating

calculation that we do so this best next

action is algorithm driv

driven and the algorithm will

then determine what the current risk

profile is based on a number of

parameters and it also tells us if we

look at a th transactions that happened

before this if we look at the history

only

9.73% of users were approved for this so

based on the risk profile and the trend

of this not being approved the best next

action once again is uh suggested not

enforced so in this instance it is

reject enrollment there might still be

contextual information information that

this case officer knows and as a result

of that they may want to refer it to a

specialist rather to than to reject it

outright so that is the second example

of best next action the last example

example that I'd like to show

you is and you can log in with any one

of the providers I just use the exm pro

authentication for the

demonstration so if I log in as Ted Ted

is a financial manager and he has got a

task waiting for him around procurement

so there's author uh approval uh for a

new supplier and in this instance we

actually we've done a ofac review in

terms of the foreign individuals looking

at some a new supplier that we want to

do business with and in this instance

there was a initial lodgment of the

request and some of the information that

have come back from the web services

search that we've done against the ofac

database has returned some information

now this is not a direct match so in

this instance it was referred to um Ted

to have a review and what Ted will do is

run through a

algorithm uh uh sort of a best practices

and and there's certain information that

based on the correctness of the

information he will answer yes or no yes

or no and if for example if he answers

yes it will direct him to request a

concession suggest that if I go back and

I say no and I say yes over here it will

say report to the ofac hotline so that's

the other one or if that is a no you

will see that this is approved for

onboarding so you can put a logical

algorithm here as well it doesn't just

have to be databased it can help as a

decision support system for someone to

decide what the next best action is

thank you very much for your time and I

hope to see you in one of our other

videos

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