okay we're gonna go ahead and get started so i have some people trickling in but that's okay so uh welcome to platform analytics academy uh my name is thomas davis thank you for joining uh good morning good afternoon good evening wherever you happen to be i'm glad that you're able to join today so let's get through some logistical information then we'll get right into a great presentation we have on tap for you today so as usual this is for you we try as hard as we can to bring fresh ideas better understanding and some practical guidance to things that you do around performance analytics reporting and other things inside of the platform this session is being recorded uh it will be out on the community event later on today and also out on our youtube channel uh if recording is an issue with your organization you can go ahead and drop now we will have a q a at the end as well as during if there are questions that come in during the presentation that are relevant to what's being gone over we may stop and actually ask that question uh if not we'll wait to the end and we'll answer all the questions that are pertaining to the presentation of today first and then get to any other open questions that are out there please use the q a rather than the chat if you can so we can make sure that we're monitoring that there are um other panelists on uh along with the presenter and myself um again i am thomas davis and today we have dan grady who's going to be presenting uh getting the why behind the kpi with in platform process mining going to be a really good presentation and of course we have dan on who is a panelist and also adam i think adam is here as well so uh he is around and forgive me adam for not putting you out there um and like i said today this is what we're going to talk about and with that dan if you're ready to go we'll give you as much time as possible to do your thing all right thanks thomas i am ready to go so i'm just going to take control of the screen here right yep perfect and i'll bring up my slide deck here and here we go perfect uh so just a quick introduction for those of you that i've not met before my name is dan grady i'm now an outbound product manager focused on our in platform process mining solution called process optimization but i've have a sense i may have interacted with a few of you over the years because five years prior to taking this role i was part of the now intelligence solution consulting team helping our customers understand all the different ai machine learning and analytics capabilities that exist on the platform what we're going to run through today is just a quick why and what of process optimization on on the platform then we'll talk a little bit about the process for optimizing a workflow there's a set of stages that you you tend to work through when you're looking to improve a given workflow on the platform so we'll look at that and kind of how different aspects of the platform play a role in each of those individual phases then we'll jump over to a demonstration and then i'll leave you with a bunch of resources that we have available for you when it pertains to this topic of process optimization i always like to start sessions like this with a quote and i think this one not only aligns to the session itself but also the solution that we're going to be talking about here today do the best you can until you know better then when you know better do better and why i like this quote is because this is essentially what process optimization again the brand name we give our in platform process mining capability allows you to do it it helps you x-ray your workflows and give all the stakeholders involved in the process visibility into where and how they can do better as it pertains to that workflow and this is a an interesting analogy if we think about anything that we're we're designing uh whether it be a or planning like an event like this one that we're at here today or a business process or even a park like the one you're looking at on the screen here we've got a vision in our heads for what the optimal path should be how things should play out right if we were designing a park like this we would probably put in a a sidewalk and pathways for people to walk on and ride bikes and rollerblade on we may put a a pond like they have in central park for people to take row boats out on and kind of share some time with a loved one let's say or maybe we'll put in a bunch of park benches for people to sit on and share a story or read a book and then we'll set up these grassy areas like this for people to lay down a picnic blanket and have some lunch or like my wife and i used to do on saturday afternoons we'd go to central park and we'd find an area like this and play scrabble we design for both efficiency and completeness to make sure that everyone has an optimal experience unfortunately though what we design is not always the reality that takes place and now in this example here this new reality might be the best experience for those people that wanted to get from par point a to point b in the park but it certainly isn't creating the optimal experience for my wife and i when we bring our scrabble board the next saturday that we go to the park same thing is true when it comes to our business processes right we design for both completeness and efficiency but the reality of what actually happens inside of our business processes is often not exactly how we've planned it out from the very beginning um unfortunately um getting that visibility into our business processes isn't as easy as seeing that new path or that alternate route that people are taking in the park um and very often when it comes to continual improvement opportunities and sort of initiatives inside of organizations they tend to be very manual time consuming and costly right we we spend all this time running reports and hones just reading through all the lines of data inside of the reports and then maybe we hold virtual and in-person workshops to get some input and then sometimes we even bring in third-party consultants to help us better understand our process and ways to improve it and then when we do all of this stuff here and we find an opportunity to improve a process uh then we have to get internal alignment on the best path to move forward with that that improvement and the way that most organizations move today at the speed that most of us move by the time we complete all of this the best path forward may have may have actually changed right well we're here to tell you um that there's a better way and that's where process optimization comes in again in platform process money and what we're able to do with that is in a couple of clicks give all the relevant stakeholders visibility into where the opportunities to improve are within their given workflow that they're responsible responsible for so they can start getting better immediately or making plans to get better immediately now if you think about it how this ties back to just classical performance analytics that we've been doing today we use performance analytics to answer questions like this how many tickets did we work which type of tickets are we working on how long did it take to close those tickets and how did we perform against our targets are our cycle times improving right these are all questions that we're using performance analytics to help us answer today and typically we kind of come in here and we set those up as key performance indicators and put them on a dashboard so we can get some visibility into one our targets as it pertains to those metrics the momentum that we have towards those targets right and just get an understanding of kind of how we're doing over time but invariably what happens when we do this and we do a really good job when it comes to performance analytics is people start to ask additional questions especially when those trends start moving in the wrong direction because information tends to be one of the most addictive and contagious things that's out there once people you give you people a little bit they always want to know more and that's where process mining comes in right because we can start answering some of those follow-up questions that typically come when we see a negative trend whether an important kpi of ours process mining is going to give us the ability to start asking and answering questions like where's our process stuck where are we wasting time where is there a whole bunch of rework happening or where are there certain inefficiencies inside of our process that we can address we can start answering all these different questions very very quickly when we start using process mining capabilities so what process mining essentially helps us do it helps us get to that why behind the kpi it helps us take a given workflow like in this case incident and visualize all the different hops that a ticket might be taking as it goes through it and gives us relevant information around the details behind each one of those individual hops that the ticket is taking and that's very helpful when it comes to identifying inefficiencies the good news is we recognize that there's a relationship between those high-level kpis that you're seeing inside of your performance analytics dashboards and the need and desire to get directly to the individual records and paths that things are taking underneath it so we've built in an integration right from a performance analytics dashboard you can get to the analytics hub and right inside of that analytics hub now in a single click you can generate a visualized process map for the records that you're focused in on at a given time period to get you to that why behind the kpi we've also started to blend together because the importance that kpis play putting the key kpis for a given process right there on the summary insights dashboard of our process optimization analyst workbench so for somebody that's analyzing the process in depth right there in the workbench we also allow you to set up given kpis so that they keep in mind the target goals that we've set for our targets and goals that we've set for ourselves as it pertains to a given process and we have an understanding of where we should be focusing our intentions in terms of improving that process so you're probably saying to yourself dan this is awesome but how does it work well well here's how it works most records on the platform have an audit trail kind of like anson hansel and gretel leaving little breadcrumbs so any ticket anything that's essentially extended for the task table usually has an audit trail associated to it i think we have audit logging turned on for about 120 tables on the platform by default and what we do is we have a mining engine on the platform now that's going to take the relevant audit data do some heavy duty number crunching on top of that and then spit out the results of that in a visualized process map we've also set up like we do everywhere else on the platform we try to give our customers jump start so you you may be familiar with kind of the content packs that you get with performance analytics that have out of the box kpis well we've done the same thing with process optimization we've come up with some consistent inefficiencies that we're seeing inside of different workflows and we call them findings and we package those up into content packs that get applied to the mining results so we start calling out things immediately for you on on that summary and insights dashboard like hey uh here's your multi-hop issues that you should be focusing in on hey here's the incidents that are direct that were open and closed by the same person that you might be foreign to focus in on so we've got a library of findings that we're continually adding to and then you have the ability to create your own findings as well we've also started to build integrations like you saw with other analytics and ai capabilities on the platform things like that linkage with performance analytics we just talked about or a linkage with continual improvement management so as you're using the process map and you find an opportunity to improve you can immediately create a continual improvement opportunity and link that map to that record so we can track that improvement initiative over time and make sure that it gets done too often in our organizations somebody sees something interesting and some data they go tell a friend or if the water cooler what they found and what they think we should do and then nothing ever comes of that this linkage with continual improvement helps us ensure that somebody pays attention to the opportunity that we've just discovered inside of the data now when we think about optimizing a process actually i should pause thomas are there any questions that have come up in the chat no no not not yet all right perfect uh so if we think about just what it takes to actually optimize any workflow that we're thinking about on the platform i really you can break it down into four phases detect analyze improve and monitor i mean you're probably already using capabilities on the platform that fall into that detect phase things like performance analytics and maybe some notifications on the targets and thresholds that you've set for yourselves or maybe you're using spotlight to identify some outliers or sla notifications these are all capabilities on the platform that help make you aware that something's not going according to plan and then when you're aware and you've detected that opportunity that's where process optimization comes in it really dominates the analyze phase of optimizing your process so you get things like that visualize process map you get things like bottleneck analysis root cause analysis variation analysis and an integration with automation discovery to help you really dig into the process and identify the inefficiency or the redundancies in your process and the things that you can improve upon which moves us up to the next stage which is improve which is what the servicenow platform is all about right so based on your findings you may choose to improve an intake experience using the virtual agent or you may choose to improve an assignment bottleneck with predictive intelligence to automate some of the tree housing process you may identify something that's happening in a very manual way in the process and you may choose to use automation engine and our rpa capabilities to address that problem or maybe it's not an automation it's simply teaching people to do something different using let's say coaching loops i once heard somebody say sometimes an improvement is just simply learning not to do something in a process maybe we have two levels of approvals and by taking out one of them we can save ourselves a week worth of throughput time so there's lots of different ways to improve and then the last stage or the last phase here is that monitor piece once you find the opportunity to approve and you act upon it you want to make sure that you're communicating the impact that you're making through let's say performance analytics to kind of set up a kpi to say based on what we didn't i want to start tracking and trending the difference or the improvement that we're making based on this change i'm always surprised how few customers actually close that loop um in terms of their improvement initiatives and this is something that we think is a tremendous advantage that we provide our customers is the fact that you can do closed loop process improvement on the servicenow platform because we have pieces that help you in each of these phases detect analyze improve and monitor if we just look at one high level example uh most workflows have some sort of analysis around throughput time that you're doing or you're looking to improve throughput time speed i mean we could say let's say in the detect phase we may see a trend in performance analytics of our throughput time increasing over time then right from there in a single click we can drill and create a process map for the data behind that the spike that's there and maybe we identify that there's assignment group changes that are leading to a four month of flooding oh you know what the improvement initiative we would create might focus around using predictive intelligence to auto classify and categorize those assignments to speed that or to eliminate some of that assignment group changes or bounces back and forth and then once we do that we'd want to create a kpi potentially focused on the percent of incidents resolved on the first assigned group or first call resolution rate because those that would be a good metric to indicate that um we're getting better uh based on the the improvement change that we made and there's so many common findings and optimization opportunities across the different workflows on the platform that process optimization helps us look at so things like channel performance or ping pong analysis or vendor comparison or looking for the most inefficient transitions that are out there there's all of these things that we can start using process monitor to help us get answers to and improve upon in these different areas and these are the things that we've packaged up into those findings content packs so for example the itsm process optimization content pack comes with four pre-packaged continual improvement initiatives it comes with five process model definitions for incident uh there's two for instance one for state and assignment group problem change request and then there's 13 finding definitions and those finding definitions again are those common inefficiencies that we see and of course you have the ability to create your own models you can tweak the ones that we give you in the content pack just like everything else on the platform ultimately when it comes to process optimization it's about improving in these areas these three areas one it's going to help you identify opportunities to increase the speed in which work gets done inside of the organization it's going to help us identify automation opportunities to remove potential manual steps and increase the productivity in the organization and the other thing that it does is it gives us visibility into the variability inside of our processes and where we're not conforming to our designed plan and that helps us identify opportunities to get more conformance and remove risk inside of the organization so these are the three areas where we see the biggest impact from process optimization and as i go through the demo you're going to see how that all plays out all right thomas before i get to the demonstration i know i just dropped a lot of knowledge on folks but i'll pause there see if there's any questions comments thoughts about any of the stuff that we we've covered so far yeah we we did have one question come in and i kind of gave some servicenow docs to it but maybe you might want to speak more to it it says is this available with all itsm skus it's not available today with all itsm screws excuse sorry it uh today it's bundled as part of the itsm enterprise offering um but i i would say on that one to to contact your your account team and and if this is something you think will add value and we we're always willing to see if we can find a way to work with customers there okay great and then another one actually just came in and you may actually talk about this during the demonstration but it says how can we we detect a bad process of historically it has never been good and you wouldn't find a spike on through put time that's a fantastic question and it's actually one of the things you'll see in the demonstration there is that detect analyze um improve uh monitor flow that's there but that's where i think sometimes you know you're just gonna start with process mining in the analyze phase and as you'll see in the demonstration it's going to shine a light on opportunities to improve and things that you would never review inside it just the insights and opportunities just jump right off the page when you visualize your data in this way it's one of the things that i've found consistently when working with customers is the uh when they when they see the the truth behind their process it's it's sometimes shocking okay for those of you that are familiar with the movie a few good men right when when tom cruise says you know i want the truth and then jack nicholson you can't handle the truth there's some people that that think they want the truth behind their processes and some people just can't handle it when they see it but then they're they're always interested in kind of what we're showing them and how to improve it great thanks sure anything else that's come in there that's it all right let's uh jump on over here to a demonstration i'll probably have to log into my instance again and i will be showing this in in san diego uh for those that uh are interested in that but it is available in rome as well and quebec uh so let's let's come here and i'm gonna start actually i'll just show you kind of how we get here real quick from a dashboard i'll say extended session hopefully that extended so i could be on a dashboard like this and i could be looking at things like my backlog my mttr my first call resolution rate and perhaps then i see a spike in resolution time or any one of these right from here i would potentially drill in to my my analytics hub and then i could use my go to process optimization button right there in the upper right to get me to this map for just that data and it will take me to the the workspace so it's as easy as that one click to get here and start mining that data behind anything that you're seeing on on a dashboard like that now for purposes of this demonstration i'm going to want to use as much data as i possibly had so i'm going to come back to a larger set not just that subset but i wanted you to see kind of what that transition might look like in a single click from pa to get to the y behind the kpi i'm going to open up this this project that i've created for myself for incident process optimization and just walk you through some of the things that are on uh as on this workbench um as we mentioned earlier i'm gonna land right here on the summary insight and insights page i'm gonna get some high level information around the data that i mined and this screen is going to give me visibility into my kpis that i've set up that are important to this process and obviously with the incident process things like average resolution time and percent percentage of incidents resolved in the first assignment group which is the leading indicator for resolution time are key metrics to me and then as i move down the screen we start getting to those improvement opportunities and these are those finding cards that i was mentioning that come within those content packs that based on the data that i chose to mine it kind of buckets it into opportunities uh in the area of let's say performance conformance and quality so we've got things like hey culture of bad cleanup records that take longer than seven days to go from resolved to closed now you may say we have our process works a little bit differently and then you would simply come in here and adjust this finding card to align to the way your process works we have things like slow resolution time so incidents that took more than 12 hours between work and progress and resolved or multi-hop issues where incidents are going through two or more hops and you can see right here on the card that of the 22 000 records that i i mined six percent of them fall into this multi-hop issue category their average time to a time impact is six days that's what's being caused here and then the total impact time for these tickets that went through this multi-hop there's 20 years worth of i like to say productivity loss that's that's captured in these things that are in this multi-hop and i could jump right to the map or do some root cause analysis or cluster write from this card you're going to see that in a few seconds then as i move down the screen i get visibility into what we call variation analysis so this is showing me all of the individual routes that tickets have taken uh based on this this this mining so we've got 3 200 different routes that these incidents that we mine took this is showing us the highlights but i could start doing things like hey let me look at the the ones that have taken the most steps that's pretty pretty involved there or maybe i want to come in here and look at the ones that have the average the longest average duration and see what that route looks like here and i can drill right from here to the map and start analyzing just this subset of data if i wanted to do that and then as i move down the screen i get even more visibility here and with something we call bottleneck analysis so what this is looking at is each of the transitions that an individual record would take so i want to focus in on just the ones that went from resolve to closed or the ones that went from assigned to in progress or assigned to resolved right i just want to focus in on a certain hop and the tickets that went through that particular hop i can do that as well i mean we'll see how this plays out in the demonstration as well so that's right there on the summary and insights page and it's really what we're trying to do is surface potential improvement opportunities right there without even digging into the map itself but of course we always want to get to the map and this is i find with customers one of the most exciting things is when they first see their process visualized on this map things just immediately start jumping off the page then like whoa whoa what's going on there i'm just going to walk you through how this this map works so you can get a sense of some of the flexibility you have when you want to start digging in and analyzing your process first thing that we'll look at here is i'll just look at some basic model statistics so right now we looked at we've got 2200 or 22 000 records that we're looking at as i mentioned earlier those 22 000 records have taken 3.2 000 individual paths to get to closure their average duration is three weeks their average standard deviation or the standard deviation sorry is three months which means there's a lot of variability in this process lots of room for improvement and the median duration is one week so i've got my basic stats about the workflow i mean you may be saying to yourself well dan it says that there's 3 200 individual routes but if i look at that map i don't see 3 200 individual mass routes and that's because what we do by default is we narrow it down to the top 20 percent in terms of routes that are most taken to kind of eliminate a lot of the noise because if i were to kind of expand this out to let's say look at 80 percent of those routes it's going to get really messy really really fast i mean and this is one of the biggest benefits i think to process mining is you know every very often in our organizations you hear like a one-off bad experience or somebody had a bad experience with this this uh this workflow or this process and kind of we react to that one-off type of thing what process mining really helps us do is focus in on the areas in which we could make the biggest impact from an inefficiency and improve or improving upon an inefficiency inside of our workflow so i obviously that variability in the routes is one of those areas where somebody that's on the risk side of the house is going to get very very concerned because there's all these little one-off paths that things can be taking that could potentially cause a problem so showing that's important i mean getting a handle on that is important but focusing in on kind of improvement opportunities uh that are kind of that hit focusing in on the high volume inefficiencies um is where you're gonna see some of the biggest impact um from an improvement perspective the other thing i always like to do here is right now we're looking at the volume i'll just make this a little bit bigger we're looking at the volume of tickets through each of the individual hops so we can see that 8 000 of them kind of came in here to assign and then from a sign 3 000 i went to in progress and kind of moved through these pieces i also like to always add in a second metric like average duration so we can start looking at the velocity as well so how things are moving through in volume wise but also the velocity it's taking to get from one place to another and the first thing i always call out to customers when they're looking at a map for the first time and kind of saying where should i be focusing my attention i typically like to look at anywhere i see a line going back up the hill here or going back up so in this case here where it's going from awaiting color info back to in progress i like to call that one out and i like that it's an easy way to see kind of where an inefficiency potentially is i usually compare these maps they look like ski trails to me i mean when i used to ski anytime i had to go back up the mountain for a reason that was usually a bad experience and something that usually went wrong if i had to go back up the mountain same thing in our processes in many cases right so i can focus in on just these 2 400 tickets that are going from a waiting caller info to in progress and look at those and i can see for that hop i've got 2 400 total occurrences 1800 unique occurrences that means that there's there's at least 500 or 600 that have gone back and forth between this path more than once and one of them's even went back and forth in that path six times and these tickets that are moving through this route just this piece the total duration of the time here is 11 years it's 11 years of productivity that we can somehow reclaim potentially by finding why this inefficiency is occurring all right so i can do some things here on this card i can view the records i can view those analysis of you clusters we can do that in a minute um but i wanted to show another way that we could look at this and that's with our bottleneck analysis so i could come in here and again bottleneck analysis shows me the individual hops uh that each of these things are taking and if i wanted to focus in on just the ones that we're looking at there in progress to a weighting caller intro and then back a waiting caller and photo in progress if i look at that loop that's going on there there's 22 years of of total productivity loss so let's focus in on on just those that are kind of moving through that phase um so i can click on this and just focus in on the waiting color info but i can also use this transition filter to do that so i want to show you how this works i can set up and isolate the data that i'm looking at in this map based on a certain path or transition in this case we're just going to be using one thing i want to say show me all of the tickets that went through the note of awaiting caller info but if i wanted to say if i awaiting caller info to um in progress and back to awaiting color info i could build out a more advanced filter criteria or transition criteria here this is useful for analyzing certain hypotheses that you have around kind of ping pong effects between groups you can do that here set that up here and then i'm going to hit apply and this is now going to change the map and narrow it down to just the records that are going through that awaiting caller info node and i can see the stats for that piece here i have changed so now i'm looking at uh there's only there's 1 800 routes there's about 30 or 33 percent of my tickets are going through that right now and i can look at the standard deviation in the average duration the other piece now on the left-hand side that i can use to help me analyze this is my breakdowns so i can start looking at these records by assignment group i can start looking at them by category a very popular type of analysis is channel analysis where we looking at here of these tickets that are going through a waiting caller info i can see that a large the largest volume is coming in via self-service right so that would make sense self-service typically generates some additional questions or person the intake the vehicle might not be optimized and we might be not getting all the information that we need and i can see that the average duration of these self-service tickets is about one week but then the other one that jumps out at me here is email right and why email jumps out of me is because again you would expect a very unstructured way to intake channel right where there'd be uh probably some additional questions the agent would need to ask about or get information from the user but i can see that these ones are coming in via email they're a full week taking a full week longer to resolve than the self-service ones so that's an area that i want to focus in on so i can isolate the email a channel and i can just apply that filter and again i'm going to now my map is going to adjust and it's going to show me hey here's the ones that are going through a waiting holder info that came in via the email channel and then i can do some additional analysis again in the platform i can always get to the records if i have the rights to do that i can view root cause analysis and what this does is it kind of runs some machine learning that shows me the leading influencers in specific areas and i can see that of these tickets that came in via email that are going back to awaiting user info at some point about 21 of them are categorized as employee portals so that's an area of interest to me and i can narrow it down even further and then right from here i can view clustering analysis and for those of you that are not familiar with clustering what clustering allows us to do is look at the unstructured data inside of our tickets and start identifying some trends and patterns and let's say the short descriptions and the descriptions so right from here i can see that these are my biggest clusters and i can see things like tickets are all about email and support and these types of things and i can get to those records and what will immediately jump out here is that i've got a lot of tickets that kind of are taking a very inefficient path that two weeks of time for just people that want to change their email address as part of their profile and that to me sounds like something that i could create a virtual agent conversation to allow somebody to do or create a catalog item to allow somebody to do on their own in a self-service fashion and maybe we even have a catalog item for that already we just need to market it a little bit better in either case this is an opportunity to improve um from an organizational perspective that we can do something to to make this a little bit better um and remove some of that inefficiency and some of that 22 years worth of wasted time that for these tickets that are moving through this hop uh here now once i find something like that i can start doing some additional things one is i can share this finding with somebody else and say hey take a look at this map here i can also then start collaborating with other people and add a note that says hey at mike i think i have a mic take a look at this and i can attach this view of it i can then start comparing this with other models that i may have maybe i want to do a vendor comparison in some cases outside of the example that i just used but maybe i want to say okay vendor a versus vendor b i want to look at all those tickets that are being handled one way or the other i can do a comparison and get some different statistics there if i want to and then lastly this tie-in with continual improvement initiatives right so right from here i can link this to an existing continual improvement initiative or create a brand new continual improvement initiative based on the the findings that i i've i've come up with as i've done my analysis here that way we have a record to assign people to to alliance to to kind of make sure that the improvement that we've found or the proven opportunity gets worked in some way shape or form now last thing i want to show you on this is just this tie-in with automation opportunities so if you're not familiar with automation discovery it helps us identify automation opportunities using some machine learning techniques and we've built this into the analyst workbench here or the process optimization analyst workbench so that when people run a mine we automatically run an automation discovery um against that subset of data that you just mined to help maybe surface some other automation opportunities based on the data that you've you've mined here so we can start seeing things like hey we've identified some hardware troubleshooting issues here here's some basic statistics about this if we had a virtual agent conversation out of the box you'd have the ability to kind of link to that right from here and take some action on it pause there thomas as i went through that did any questions come in yeah we have a few questions that have come in um i'll just go just from the top to the bottom here so first one is so if i have itsm pro and i'm on rome this is available is it enabled via plugin perfect so that's a good question so as i mentioned earlier today and again i would contact your account rep about this it's available in its enterprise but um any customer has the ability to turn this on in their subprime instance and run process optimization against a subset of 4 000 records for a given process so if you're on on roam you should be able to go in turn on the plug-in and run this against a subset of your data to kind of get a feel for how it works and we've got some information in a knowledge article in an article on the community that we can share with the group after i'm going to share some links to kind of the process optimization community page the faq um and there's some additional information on kind of how to go about turning on which plug-in and get started okay great um is there a way to apply the pro this process from virtual agent perspective focusing on the user journey and interactions chat bot or may exist is there one that exists out of the box no not today so on the kind of that user journey from a conversation perspective but um you do have the ability you could mine interaction records um and link those interaction records to kind of uh let's say um incidents that were created from those so you can build that that linkage between tables uh into a map so you can start seeing that and that's one of those things i i did not use the safe harbor slide but safe harbor uh slide in play in tokyo we're enhancing that what we call multi-dimensional modeling but that that ability to build models that go across different tables and workflows so you can kind of see a let's say use we'll use hr onboarding as an example right an hr onboarding case is going to have a lot of sub tests that may touch a number of different processes you'd be able to visualize that in a single map uh here okay great i should have had that safe hardware so i apologize as well um next is it possible to use process optimization for data mining without having kpis established already our kpis is still very much a work in progress in trying to determine if this could be used to gain insight into establishing those baselines that's actually a fantastic question and i'm glad you asked it because it reminded me that i wanted to show you how this actually works from here as well so the answer at a high level is yes right you want to have those kpis obviously because that's going to be part of that detect and that monitor phase if we look at the book ends of this process but if you wanted to use process mining you can start using it today without your kpis and i wanted you to get i think it's really important for you to get a sense of like how easy this is to do um because i you know typically when you talk when people think about process mining there's a lift in their heads if they've went through a project with a let's say another tool uh process mining tool there's a lot of effort that goes into the data preparation uh for running a process finding exercise and it's not the case it's one of the advantages that we have as an in-platform solution we understand our data and we we've kind of eliminated any of the data prep that you need to do which really is as easy as this so i'm going to come in here and i'm going to say pa academy process mining and i'm going to come in you could set up a short description a goal that might be aligned to this you might want to use a template and i'm simply going to come in here and i'm going to pick my incident table that i want to mine against then what you would do is you would apply some filter criteria typically you know we want to apply this to let's say um closed records and what we we say for customers this is a question that typically comes up is like what's the right amount of data to use is there any minimum number of records that i need to use and the the answer to that question is no what you want to use is you want to apply this to relevant data for whatever process you're thinking about for a lot of customers relevant data when it comes to incidents is let's just say um closed on the last 30 days right on i think we would do something like this the last let's say class closed in the last month right now for my purposes my demo data that i have here i'm just going to leave it like this and hit preview so i can do it but you would set up a criteria that makes sense and in this case i have about 30 000 instances that match this and then i'm going to save this and the only other thing that i have to do is i need to create this activity definition and what an activity definition is is essentially what do i want to start visualizing from a transition perspective on the map right so by default this is gonna you know the one that most people like to start with is state and i'll add this and i'll submit this you can put assignment group in here you can put any number of different things inside of here and you can look at all of those different hops on the map and then you can set up your breakdowns if you want to but essentially this is all i need to do and then in a single click i can come in here and i can generate my model and this is going to take depending on the data a couple of minutes we'll see how fast this goes in this session but that's how easy it is to create and visualize create that process map that you saw or visualize your data and start doing the analysis that i was doing there you don't need to have your kpis set up i think it's important an important piece for the entire optimization process but you don't need them for sure you can do exactly what i just did and get going like that it's probably a long long-winded answer but i i did want to show this how easy it is to set up because it is it is kind of this something that's really important to our solution on the platform yeah definitely i think it's awesome showing that um and along those same lines um let's see would the incident process optimization analysis work let's say if the org has some has defined some non out of the box incident states yeah so what you just saw me go through there you probably noticed um when i went to like pick state that was just a list reading off the table so if you've got custom fields or custom elements of different states that you've set up that are unique to your organization we're just going to pick those up we're not going to you're not going to have to do anything special um from a process optimization standpoint we're going to kind of when you filled out this form like i just filled out here your custom fields are going to show up in the drop down lists and your custom elements are going to show up in the the analysis okay great and then uh does itsm enterprise include license licensing to automation discovery as well yeah that would be covered underneath um i i should say i should preface this with i'm not uh on the sales side but uh i believe that is covered underneath your pro entitlement because it's a machine learning based or predictive intelligence based solution um if there's a moderator on the call that knows differently than me uh please chime in adam best sounds like you may have the right answer and uh we have we have a couple more that are in but it looks like josh cooper actually joined so he's doing he's answering some questions uh by typing them so uh he may be it looks like the two questions are related so he may be on top of those so if you yep he's gonna answer that one so if you're if you want to continue you're good we've got all questions up today at this point perfect so i mean i think it was for those of you that have witnessed that i mean in less than a couple of minutes we set up and my set up a project a process process optimization project mined some data and got ourselves to a visualized map it's it's that easy to set this up and get going so i think again power to power that comes with using an in-platform process mining solution is the ease it is to kind of set it up and start seeing the insights inside of your workflows all right now i'm going to transition back i i do want to leave you i mentioned that we we have some resources so a couple of things that i wanted the call out that are available to you to follow up after this session one is that we do have a specific community form for process optimization now unfortunately it doesn't come up in that cool list on the left hand side of the screen when you click on forums so you actually have to search specifically for process optimization to find the form itself but it it's there so if you you've got additional questions that come up after today or if you're you're out there and you you want you turned on process mining on your sub prod and you're playing around and you've got a question don't hesitate come here to the forum post it i monitor every day and uh other people on the team monitor it every day and we'll get that question answered second thing in the upper right there there is an on-demand training it's about 60 to 90 minutes called process optimization essentials that's out there on the now learning site so this this if you're going to be turning it on i highly recommend that you walk through process optimization essentials get a lay of the land it'll give you everything you need to know to get started um we do have a faq article out there on that community site or forum that we talked about earlier so a lot of the questions that came up today they were answered on that site in addition to other questions that you may have check there also this faq has got links to a lot of other relevant material that you that may interest you as well one of the links that is that it that's there is a link to well you just sat through this so you probably don't need it but if you wanted to show other people what you just saw here today there is a link to a recorded overview presentation and demonstration out there as well other thing and i noticed thomas as we were going through this i'm going to need to get this added to your your intro is that we are starting our own process optimization academy um that you can register for on that community forum that's out there the first session is targeted for july 15th and we'll be running them every every two weeks as well uh so the first thing the first session is going to be focusing on kind of turning on process optimization and creating your first model so that's going to be july 15th and then we'll have sessions every every two weeks after that uh i will get that added dan yeah this is the what to do next i already covered this but i would say if you're saying you said what do i do next here's what you do next you go out you take that process optimizations essentials course on now learnings and then you go into your subprime you activate the plugins process optimization and the itsm process optimization content pack and you get mining um and i we started with a quote i'd like to end with a quote and this one's from winston churchill to improve is to change to be perfect is to change more often and why i'll leave you with this one as i think and i hope and actually i know what you witnessed today is that we're going to be able to provide you with process optimization significant efficiency gains in terms of being able to see where there are opportunities within your workflows to improve and you're going to be able to find those opportunities in such an a more efficient way now that you'll be able to get better more often which is which is what we're trying to do here that's what i i plan to cover today thomas if there's any any other questions or if we want to open up the floor to questions i'm i've exhausted the materials that i've brought to the table uh dan this this was just uh really incredible and and i know that um people would get a whole lot out of this um and and they have really great questions is a good thing what i would like to do and this is completely voluntary of um dan kane and and adam and even josh but uh i think that you've covered everything greatly and i don't think that there needs to be any talking over you of what you've done but i know that quite often uh different thoughts come in uh especially of ways to to use something like this and and things like that so uh dan or or adam or josh if there's anything that you'd like to add as as other questions may came come in please feel free uh i know adam always has a very high level way of thinking and thinking of things so i have to wonder if there's things he was thinking about during the the present presentation that's awesome it's it is i mean adam you know this it's becoming everyone's favorite process optimization is everyone's favorite now everybody loves it yes everybody loves it everyone's favorite that's my deep thought nice i love it i mean it's some of the best deep thoughts are awesome i mean it's really it says everything so i am good with that um well i mean i'll say this is is that with with pa we could do we could we could do some of this stuff but it's really manual um and i think one of the values we get from servicenow is that you don't have to think about everything it's not just a tool that that lets you visualize data but that it allows us that we have people here thinking about how do we solve our problems right we understand it's it's not just about all of our analytics um and intelligence it's not just about data but it's about tasks and and cis and and cases it's stuff we all do um so when we see a problem that that all of us have we're able to build a solution that solves it it doesn't solve every problem out there it solves the problems we have which are the ones we care about so it's really important um when you're looking when you're trying to solve a new a new problem you're trying to you're trying to introduce a new process that you always look at what servicenow has and what the platform has to offer with the other solutions that are out there because what you're going to find is you can invest you know months and months of time and lots of labor and customization and build it um you often can do that the platform's incredibly flexible unless you build unless you build those things but why would you do that if you can just install a plugin right again app store um you know some of the stuff has additional costs but the the cost that you're gonna incur to develop and maintain it is way out there and the the team that uh dance team and the pros optimization guys incredibly smart i've been focused on this for years now um on on how to make this work for you and optimize it and as dan showed you don't have to figure it all out you just go i want this on this table state ready to go yeah and let us do that thinking for you adam you just remind me reminded me and i think that people on this call would appreciate it for sure um some of those questions that it answers you know just out of the box for you back in the day you can still do it today i guess but you would have to set up metric definitions right and capture that data in metric definitions and then report on top of those metric definitions and build kpis on top of the metric definitions to get some of that information around in between the hops or kind of how long something is sitting in a certain state which is not it's doable but it's certainly not the easiest thing to do and requires maintenance and things like that that's i was showing this to somebody the other day though i had to set up a whole bunch of metric definitions to answer that question i was like yeah look at that we just taken two clicks and it came from no right it's i mean this is like like to adam's point a lot of this just feels like pa you know with some intelligence thrown in and about six hours with a white board right to like where you're taking those pa measurements and you're putting it all together to understand the process it's just doing the understanding for you and helping to visualize it sometimes you want to add well i was going to say this didn't come out of a vacuum this this was a very organic solution from us that came from some people who worked on pa and as dan said you know you can do it i think we have labs that walk you through how to set up all those metrics and it was us sitting around going it shouldn't be this hard it is hard it took us a while to develop it there's a lot of you know there's a lot behind it but it shouldn't be that hard to get this answer and that driving factor because again we're looking at the because we're talking to you you're talking to us you're telling us your use cases it's why these these sessions are so important by you saying i'm trying to do this it makes sure that we understand what are you trying to do and then how can we help you do that right and whether it's get it out by oh we'll just use this formula in pa do this in a report um or hey we'll build a new application that is purpose built to so to help you solve your problems quickly efficiently and give you the information that you need that feedback and these conversations are so key for that and and process optimization is one of those one of those things just said this is the answer we're trying to get it's not about the tool it's about it's about the outcome we're trying to achieve even if we had to build a new application to make that happen that that's what we needed uh you just reminded me again adam so speaking of use cases on the in the process optimization community forum there is an article that details the 26 to 30 common use cases and findings that we've come up with so far so i recommend people go and check those out um because it's posted there but also if you've got you've got scenarios and use cases in your head that you're interested to understand whether process optimization would help you identify inefficiencies rework redundancies opportunities to improve go there post a question there we're constantly looking for feedback on on use and input on more use cases so you know post it there and we'll we'll we can answer it for you and kind of show you how to do it or maybe we set up a session where we show it um as i mentioned we're going to be kicking off that process optimization academy and i imagine over time some of those sessions are just going to be dedicated to how do we how would we create this finding card specific for this use case or how would i use the map to identify that this is happening so if you've got use cases in your mind and you don't want to share them here today please go to the community and share them there great and and we did have um we did have another one come in that josh kind of hit on but i think he had some questions for you in it but i'll just so hr case management is this available um safe harbor he was talking about it maybe tokyo so yeah great question so yes um our goal again safe harbor our goal from a servicenow perspective is to make this available for all workflows on the servicenow platform right all workflows on the servicenow platform today it's itsm and csm in the san diego release in tokyo we're expanding it to hr and then to create a workflow so you can apply process optimization um and then over time you're gonna start to see it become available for additional workflows on the platform so hr is coming in in tokyo um and that's the plan and uh yeah so we'll be able to do that and again safe harbor but one of the the key capabilities uh the enhancements from a tokyo perspective is this ability to do multi-process um mining and that that's key for the hr life cycle event uh type use case where you can start saying okay here's the parent case and then i want to start seeing how it branches off into other tasks and activities uh to complete that that life cycle event so that's that's certainly coming in in tokyo awesome well i think we've answered all of them and let me say dan thank you very much for this this is great information and it's going to be really great to have this out um in the community and so people can refer back to it and a great resource for us to actually direct people to when questions uh do come in but also direct them over to uh your new academies that you'll be starting uh soon so uh thank you again and always great to hear you speak and do presentations so um what a pleasure thank you very much i appreciate the opportunity and i look forward to working with everyone when it comes to this new exciting area everyone's favorite process optimization awesome thank you um so with that i'll go ahead and close out so we can um get done with everything so let me get over here so uh as usual just some quick slides use the community as much as you possibly can there's great information like this that'll be shared out a little bit later on today and also plenty of questions that have been asked and answered by not only servicenow uh but also customers that have really great knowledge around different things so uh if you had a question in this that we didn't get to or you didn't like asking that question uh please feel free to go to the community and ask that question and then of course get to all the different links of the other things that we have available there um again like i said this will be out uh later on today and also be out on our youtube channels as well so look for that and the um question was asked will the slide be there the slide deck will be there it'll be saved as a pdf and it'll be attached to the community event so you'll be able to look at that um but again the recording will be there uh for you to access as well um make sure that you're using now learning there's some really great training that is there not only for performance analytics and reporting and things of that nature but also as dan said for process optimization the essentials so go out there and take advantage of all of that uh there are the p or the pa advanced uh is now on demand so go and check that out as well it doesn't have to be an instructor-led um and then also here are some other great academy sessions and on the next one uh the process optimization academy will be added to this slide for dan uh but go out and check these out as well some really great uh other academies that give you can give you a lot of great information into many of the great tools that are inside of the platform uh and then two weeks from now we're going to talk about acl assessment for reports uh so please come back in two weeks if you have um some curiosity around that and if you don't and you're just curious what that is then come back in two weeks and check that out as well um thank you as usual for joining and giving us uh the lunch time for some of you the breakfast for others and perhaps the dinner for others as well but thank you for coming and um if nobody else has anything then thank you and we'll see you in two weeks