welcome and good morning to everyone to this webinar where we will cover performance analytics and talk about some of the best practices and do's and don'ts on setting up and activating performance analytics in your servicenow instance um before i get started i would like to very briefly introduce my colleague peter and myself peter maybe you can introduce yourself briefly yep thanks paul uh hi everyone my name is peter jorvis uh i'm a product manager for itsm and devops primarily focused in the media region but we're a fairly small team so we try to cover all the areas as much as possible and uh i've have been working with paul for a very long time i know and i think paul you have a you have a quiz question for that one i don't but i i'm thinking i should have so both peter and myself joined servicenow as a result of the the first acquisition service now ever did so i don't have an official poll for that but if you happen to know that acquisition um kudos to you anyway it was 2013 so both peter and i joined back then and we're now both part of the album product management team for it service management so we have that pa background as part of that acquisition of the company back in 2013 which i'll not mention if people still want to guess uh there we go right uh moving on to a few housekeeping rules uh we will stay on mute for uh the most of this the most part of this session and there will be a q a after the presentation so if you have any questions uh use please use the q a feature to ask those questions and we'll be either responding to them during the presentation or i feel them after the after the presentation um if you have any questions at the end of the session feel free to introduce yourself and ask any questions the session will be recorded as i'm sure you have seen and it will be shared on the servicenow community after the session after these sessions ends we would love for you to fill out our short survey we would love to hear what you think of it and if there's any uh room for improvement i'm sure there will be we would like to hear from you on that um all right that's as far as the um the housekeeping goes first poll question and this is more out of curiosity but also maybe to adjust my presentation a little bit to the audience have you already implemented performance analytics i'll say one i have not started but i'm interested in how best to get started answer two i'm in the process of rolling ipa within my organization and answer 3pa has been rolled out and is actively used within my organization if you could please fill out that poll question i'd love for you to hear so have you not yet started which is a good reason to join a webinar on how to get activated how to activate and configure pa but also if you're in the process over even if you have implemented performance analytics those people are more than welcome and hopefully you can pick up some of the uh some of the the things that we see as best practices within our within our customer use base um i don't think i have visibility into the incoming results uh so i'm not sure if the results are coming in and if so they can be shared and there they are all right um fairly similar mix to the previous session we did a couple of hours ago so a little more than half have not yet started um one third maybe in the process of rolling it out and um and then the remainder having it fully implemented interesting interesting mix and of course welcome to all of you uh we'll make sure that we have um some hopefully some relevant information for all for all of you um what i'd like to do is i would like to start off with a very short two or three slides on putting performance analytics into context and then dive into how we see customers are getting most value out of using performance analytics to its fullest and one of the ways to do that is to to understand what drives improvement in your organization so talk about that and then i'll do a short demo and then there's uh one more thing one more topic on how to to find the relevant indicators within your processes before we go to the closing remarks right so i'd like to start off with a slide that is a high level depiction of a process and a process consists of input work and output i think of input into your process as requests incidents or any other form of required information or help from your employees that that needs to be worked on in the middle part and then results into responses fixes etc right so an incidence that is resolved leads to a resolved incident right so that's how to look at this and now what i'm what i want to plot on this process is where we would position performance analytics and maybe some of the other ids and pro products to have a bit of an idea of the context of what we're talking about first of all there's reporting this is not the same as performance analytics in most cases what we see reporting is focusing on is the output of a process i'll give you an example if you look at a status report the report that you'll be using at the end of the week or beginning of the week when discussing how things went you're looking back at past performance and you're looking back at how do we do things like an sla report or a status overview or even a financial report or whatever overview it's always looking back at how do we do and then based on that we can see if there's any room for improvement if you look at the analytics it does that too in the form of executive dashboards right i would like to see how we're measuring up against those objectives that we've agreed upon but it also provides information um that reflects to the work going on things like cues where is work queuing up where are my piles of work queuing up and is there anything i can do about that is there any bottleneck in my process that i need to address can i set targets and are those targets realistic can i measure against those targets does that make sense you can even look at something called spotlight which is part of performance analytics which i'll cover during the demo uh that will help you prioritize work so it will set prioritization across incoming work before the word gets into that middle part of my process right so this this is where pa fits in a little bit and then there's more aspects that i said on itsm pro things like uh classification framework and predictive intelligence or things like advanced work assignment uh that can help predict the best possible assignment group for a piece of incoming work right based on machine learning we can say well this is the most likely assignment group so that's focusing on setting fields before it gets assigned to the workforce they're in purple violet similarity recommendations and other aspects of predictive intelligence where we provide the agent with similar incidents or similar problems or related outages or similar knowledge based articles and then this virtual agent obviously this is something that takes place before word gets assigned to the workforce hopefully being able to self-service the requester and in doing so deflecting incidents and providing a better service to the end user things like continual improvement management and vendor and service workspace those are also part of idsm pro and they take place in that work section where you define your improvements and you assign them and you monitor and manage them and then last but not least bottom right hand side benchmark not a part of itsm pro it's a opt-in but i would like to not leave that unnoticed here because it is uh something that really ties into measuring performance seeing how you're doing and then with benchmark being able to compare that to how peers in your industry or your your geography or your your company size are doing right so always good to compare and see where you're under over performing so this is a little bit context setting now one of the things that you may have picked up is that we would like to focus on the work so the question where does a modern experience take place if we really want to have that modern experience for the end users we should focus on things that we can influence not necessarily reporting on output so one of the reasons that one of the aspects of performance analytics that is is really important and relevant and understanding how we're doing and where we should where we should impact performance is the context of time so if so you can see a horizontal axis at the bottom depicting time that's today plus one plus two days or weeks or whatever time frame you want and then there's a score let's assume that's a customer satisfaction score of zero to five right and if we're measuring where we are now we can see we're currently today at 3.2 ish 3.25 maybe but that doesn't tell us very much other than we're currently at 3.2 is that good is that bad are we improving are we declining is there anything we need to do we really can't tell based on that one data point if we now bring in trend information we can see that oh historically we were lower but we also were close to four so whatever we did there we might want to have a look at um so but now we can put this into perspective and 3.2 is not that bad even though i think we can do better we can probably get to four right so we can now set a target saying i'd like to be at 4. we can identify a gap an extrapolated trend view that shows if nothing else changes and there's various algorithms to support this predictive outlook then we'll get there in four days or weeks or periods from now right big question however is is there anything we can do to get there faster and this goes equally if the trend will be downwards right if you would see well if nothing else happens then we're hitting rock bottom in terms of customer satisfaction in a few days what is it that we can do right so in terms of terminology uh the first bit is often known as descriptive extrapolating is known as predictive and prescriptive is where you prescribe or suggest measures for improvement now in order to to understand where you can find measures for improvement you need to understand how you can impact impact the performance or the behavior of people and in order to understand that we would like to use we typically use the concept of leading and lagging indicators leading and lagging indicators can help you focus on what's important to drive or to improve your business performance now before i go explaining about leading a lagging indicators second poll question are you familiar with leading a lagging indicators um one i have no clue two i am familiar with the concept but i would like to hear you explain that again or i'm curious to hear how you how you figure that and then number three we have deployed this concept in our pa implementation obviously this is for those folks who are either in the process of implementing or have implemented uh it would be interesting to to hear about those experiences from those folks as well so familiar with leading and lagging indicators um nope not a clue a little bit but you can explain it nevertheless and three we have used leading unlagging indicators in our pa implementation um i'm curious to see the results here oh no implementations with leading and lagging indicators but quite a number of folks almost half of the people in this session or at least who have responded who are familiar bit of a 50 50 there right so uh that's good i'll be more than happy to explain it to everyone and uh this is not the one right way of explaining it but this is our take on that and the way we use this terminology in terms of pa implementation so leading and lagging indicators are not a servicenow term it's more of a generic term you can use this also outside of service now right so leading indicators are used and lagging indicators well lagging indicators are more output oriented right so they focus on the output of a process the outcome of a process you can say they're pretty easy to measure you can think of them very easily and this is one of the reasons that they show up in a lot of reports they're a bit harder to use as if you want to decide or if you want to impact the performance of a team or a group of people right or an organization leading indicators on the other end are focusing on input they're a bit harder not so much to measure but to think of so what's a good leading indicator leading towards the desired outcome you'd have to give that some thought but once you have them you can use them to impact the performance right so lagging indicators measure outcomes and leading indicators drive behavior interesting let's see if we can bring up an example to bring this to life now if i want to lose five kilo in the next 90 days all right so three months worth uh three to three months of time uh very tangible objective i can i can measure whether i'm on track by standing on a scale and at the end of the three months i can also measure myself and see whether i've met my objective that's useful because that will tell me whether i achieve my objective or not what it's not useful for is telling me what i need to do if after one month i haven't lost a kilo or i've lost three kilos i would like to know what i need to focus on in order to do better or keep doing that now a leading indicator would be measuring how much exercise you do for example or more generically the calories taken in and calories burned right as long as you burn more than you take in in theory uh you would be doing well you would be on your way to losing weight right and we all have our own methods of doing that but generically speaking if i would eat healthier or less and start exercising more that's a leading indicator i can measure that and in itself it doesn't tell me whether i met my objective but it probably gives me an indication that i'm on the right way or if i'm just eating cake every day i may realize that i'm not on the way to losing five kilos right so leading indicator is input and it tells me something about my behavior that i can impact i need my lagging indicator still to see if i met my objective now if i translate this example to a business example right let's talk about service level management my objective is to solve 95 of my p3 incidents or cases within five days my lagging indicator is easy because that's just measuring the percentage of p3 cases that were solved in five days it's measuring the out the outcome of my process did i do well this is what you'll see on an sla report right you met your objective because you achieved 95.7 percent good or you didn't because you met you only sold 92 that's outcome doesn't tell me what i need to do it's useful to know that i met or didn't meet my sla but what do i need to focus on and here is where it becomes a little tricky so what do i need to focus on in order to mute my sla now some of the leading indicators i can think of is i could look at my p3 cases or incidents that i haven't worked on for 24 hours right if that percentage is growing this is where trending comes in i can see that it's less and less likely that it will be my objective why if i'm not working on incidents for 24 hours i'm not solving them either so if i need to solve 95 percent the lower that percentage the higher my chances of meeting my objective same with the other one percentage of open three open p3 cases older than four days if that's zero or three that's probably good if that's 70 probably not so good a high chance of me missing my objective this is where leading indicators help you focus on things that drive behavior in order to meet an objective heating indicators are input oriented what am i putting into that process output oriented are my lagging indicators okay so that's the concept of leading a lagging indicators now we need to add one layer of complexity or precision to it what's leading for one is lagging for another and that's not nice because it would be much nicer if certain indicators were always leading and others were always lagging but that's simply not the case now let's have a a look at this here's that that little person again with the um was it a phone i think a very old-fashioned one looking at a lagging indicator and the lagging indicator is an objective to improve net promoter score by five points in 90 days that objective can easily be measured by measuring minor promoter score all right i can measure it now can measure in 90 days if it's five points higher i met my objective what do i need to do in order to to make sure i'll get there so we start with the objective and we say in order to improve my net promoter score maybe i should focus on lowering my mean time to resolve right that's the assumption that if i get a a a a resolution or a response earlier quicker i'm more likely to be positive about my net promoter score i see assumption right first time fix is another one right or there's a few other ones you can think of now this could be the it manager's objective right the assignment is improved net promoter score this is what i'm telling my team managers to um to focus on my team leads focus on lowering me in time to resolve that then becomes an objective for the team lead and then says well in order to achieve that what do i need to focus on or maybe we should avoid cases not working for five days again that's leading towards that lowering me in time to resolve and there's others you can think of but that could be contributing to achieving that objective now you can see what is leading for the it manager at the top here this one that same indicator becomes a lagging indicator if you cascade that down one level below so if you um we depict that differently here's the executive or it manager a service owner and a frontline worker i could have that high level objective there which will then lead to these indicators as being leading i would like my people to focus on increasing first time resolution lowering me in time to resolve eliminate reaching out for more info because people don't like that right i'd like to have a solution i don't want somebody to ask me what exactly it is that i mean to the extent that you can even eliminate that then that becomes a leading or lagging indicator for the service owner and for that lower mean time to resolve he or she can then tell her team to focus for their frontline workers on avoiding cases now worked on for more than five days or avoid case reassignments why because that takes time i've read through the incidents i've tried to find the solution couldn't find it assign it to someone else maybe escalated to second level that person then needs to start from scratch again so they need to read through it need to understand what it is so if you want a lower mean time to resolve avoiding case reassignments or incident reassignment is a good indicator to focus on right so if you translate that to a performance analytics implementation a high level objective score could be a single score on a executive dashboard or maybe on a mobile device obviously using the servicenow app we can very easily show pa scores there as well in order for the service owner to get an understanding of the relationship between lagging and leading indicators we have something called a workbench widget i'll show that in my demo how to how to use that but that's really that was designed more or less for this purpose to get an understanding between the an understanding of the relationship between leading and lagging indicators and the ability to take action on them and then there's something called spotlight spotlight will help you your frontline workers to focus on the work that is more that is most important in addition to priority setting you can use these leading indicators to drive which which incident is more important than the other all right so in summary leading lagging indicators leading our input lagging our output we need leading indicators to drive behavior we need lagging indicators to know where we are and whether we're meeting our objectives all right that brings me to my live demo right so i'm switching to a pa instance or a servicenow instance with a set of nice dashboards um so i'm looking at a cio overview dashboard and this is just um uh a nice dashboard a bit of a show of that will actually show sort of all sorts of visualization but it's relevant information what you'll find here is not a lot of detail you don't see overviews of open incidents right it's just very high level this is about availability and reliability if i zoom into it service management i can see again service availability i can see customer satisfaction score that's at seven score as i said earlier it's a bit of trend views but not too fancy i can see a breakdown of my services by service so i can see a bit deep detail if i want to but this is really somebody who's just interested in are we doing well or not you can see what a color coding some things are not going that well others are really going well you can see some trend views here and i if i want to i can zoom in i can get more detail but most executives won't right so if we then switch to i was going to say the man in the middle but the process owner right um incident process owner can see a dashboard that shows a bit more detail here you can see open incidents in real time that's the actual time here in the netherlands in 1825 um in reddit right that's more than what we wanted to and also the trend is up so we could see that we've had a lot more incidents since the previous time we measured that first resolution that's green that's good but only just see that's just just above target and there's a trend here on incident age and backlog now the incident h is that line right backlog is the blue area blue area is fine it's going down a little bit a little bit stable here so not too much going on incident h however is going up incident age was 3.7 here it's currently gone up to 12 days that's not a good sign here's where you can see that there's more of one way to looking at the backlog right yes my incident backlog is going down that's good maybe we're focusing on easy to close incidents if my incident age is going up maybe not maybe we just forgot about a few incidents we haven't activated that auto close for all of our incidents so maybe some of them i just left there and we just forgot to close them i want to know what's going on so if i zoom in i can get to the incident etc but instead of doing that what i'd like to show you is the workbench widget that i mentioned so here under state analysis is an example of a workbench widget first of all i'm looking at incidence by state so look at my process here there's one incident in state new 46 in progress 117 on hold et cetera and obviously these states this is all configurable if you have different states or more or fewer then that's something you can easily configure now i'm looking at the ones that are on hold that's 117 on today if i hover over that i can see on march 18 that was 165. here was 94. i was currently on a pretty stable right so again you can see that um that backlog is not changing a whole lot maybe a little bit but not nothing to worry about on the other hand if we're looking at the average open age in that same period that is currently 22 days right i'm looking at the incidence for this state that's why it's a different number than on the previous tab 22 days there used to be three or four days so something's going on and i want to find out what is going on first of all if i if i go back to scrolling over this view here if you look closely i'll keep scrolling if you look closely to the smaller widget you can see that they move at the same rate the same speed if i fix this point for example so i click and i fix this in time i can see the values of march 14th average open a was five every assignment time was really low average last update age was pretty high etc so i can see the relationship between those which you can call leading indicators right and the actual state of the work the number of open incidents once more i can see the number of open incidents broken down by priority and i'm currently looking at the number on march 14th or if i go back here look at march 2nd those days those numbers will change to the actual numbers that were on hold on that day some of them some of those may be closed maybe all of them are closed but on march 2nd that's the number if i want to see the actual records i can see the actual records here so the 83 records of incidents that were on hold at that point in time you can see here if i scroll down you can see that that's the whole list of incidents and that's the total number of 83 right so i have a historical timestamp of the number of incidents the breakdowns and the underlying records of those incidents over time i can also switch to showing that by category right so i can see the numbers of incidents on hold by category but also i can say well let's go back here maybe let's see here maybe at that point in time now look at my average open age that was 18 days i can see 47 of them were requests but if i click on this leading indicator i can see that same breakdown but now showing the average open age so what's that telling me it's telling me that on april 14th the average age of open incidents and stayed on hold for inquiry with 30 days and that's the highest number and then network was 22. let's filter that down by assignment group right so now i can zoom in i can see the the highest number here was i t securities the average was 18 but it secures we're doing particularly bad you can see the upward trend in all of them so something is going on there but you can see the outliers by zooming in so this gives you a lot of information and then obviously you can drill in to see that that detail of the 24 days uh for that assignment group right so you can get here i can do all my my detailed analysis of that trend over time right if i want to go down to the incident this is a calculated indicator so i need to open up the formula and i can find which incidents were were on hold and we're taking so so um so much time right so this is why this is called a workbench it's not a report it's not just a dashboard it's actually something that you can use to improve the performance of your organization right and it really shows the the the how leading and lagging indicators can can be visualized together and you can see the added information it brings to you right and it also allows you because the leading indicators to improve performance because it's very easy to to pinpoint the outliers and take action on them i can really go into the incident and say i need to reassign that or i want to put this at the top of the list again or just make a comment saying why is this not being closed or maybe you understand why it isn't a whole because it's related to an open problem etc right so all of that information is available at my fingertip but now is driven by those those those leading indicators right so that was the incident process owner now if i go one step lower in the hierarchy i get to the servers as worker services worker this is a tab that says prioritize work and the reason that it says prioritize work is that next to some indicators see critical incidents some trend views here and maybe a breakdown for assignment groups i can see that for some reason this incident has a score of 2300. now what does that score mean now if you remember the picture that i showed in my powerpoint we're at the lowest level we can say we need to focus on maybe avoiding tickets that have been open too long or maybe we want to avoid reassignments right those are all parameters characteristics of an incident that you can use to put a weighing factor on specific incidents on all incidents right so in this case open instance is not updated for five days so this is something we can easily measure once that is the case for a specific incident we'll give that incident a hundred points this one has user impact we'll give that a thousand points uh another value for 30 days another thousand points it's a p2 100 points etc and obviously you're free in determining your criteria and your weighing factors but ultimately that leads to a total score of 2 300. and the only purpose for that score is to uh to to tell is relevant no it's relative sorry it's relatively important against other incidents right so if i if you think back of my powerpoint where it says these are the leading indicators at the worker level that we we want to focus on those are the ones that once you've determined them that can determine the score of those incidents right if you want to avoid reassignments anything that's being reassigned more than two times is added to give 500 points whatever does it will show it up higher in the list so you can say well this one is a focus one i need to focus on that well i want to make sure that now we get this resolved and i'll reassign it again right been over for 30 days that's way too long give it a thousand points etc that's how spotlight works spotlight is a part of performance analytics it's also one of the best kept secrets within performance analytics but really powerful and useful for those organizations that are actually making use of it all right so quick recap i talked about needing a lagging indicators i talked about i showed you some of the dashboards but you also want to know a little bit about how to set up performance analytics right that's also the title of this this workshop so let me take you through some of the basics so all the things that you see in that score this one for example number of critical incidents or the mean time to resolve or whatever average age or backlog all of those are indicators and indicators can be defined and per indicator you can define what and how you want to measure the scores right now luckily you don't have to event at the wheel and invent everything from scratch we have a couple of hundred kpis i think or indicators out of the box um that are out there so definitely advise you to to to leverage those but let me take you through some of the basic steps so what i have here let me open up my menu you can see what i'm doing here i'm looking at what is called automated indicators right so this is a list of indicators that are collected automatically right so for all the indicators that i want to collect automatically this is 99 of your indicators right you don't want to manually collect anything so uh number of open incidents if i type that in yeah the the first chord that's the number of open incidents i'll take that as an example right this one has almost 500 indicators so that's quite a lot we would definitely not advise you to start off with 500 indicators so what's in that indicator the indicator definition obviously contains a name and a description which is for the end users to understand what it is that we're measuring and also maybe in this case how we're defining an open incident well open incident result date is empty right that's what we define as open incident so then what else some of the characteristics like minimize we would like this to go down so if this trend goes up that's a red arrow up another green arrow up um we want to measure that in numbers not in percentage or in the us dollar so etc so and then here's probably the most important field right the indicator source so this is the definition of what we want to measure the indicator source let me open up the indicator source is defining where we and for under what conditions we would like to apply the measurement right so what we're looking at here is how we have a fax table incident meaning we want to reach out to the incident table and count the number of incidents that match these conditions right needs to be open on today or before today anything that was opened yesterday and still is open that's fine and result is empty that's also where we put it and that's your description right so anything that's not resolved so we want to measure that and i'll get to this one in a second but first of all if i would measure that now go to my incident table and look at what was opened either today or before today resolve this empty that could be 44. currently we have 44 incidents that number 44 is then captured and stored into a separate table in servicenow and that separate table is a big collection of numbers and those numbers are the basis for my charts we'll get to that in a second but just so you know that's what it does so data collection doesn't count on the incident table for all the open incidents whatever result it comes back with puts that into a table now what is resolved after today mean right that's that's very strange because i'm not sure when this will be resolved now what i just the example i just gave you is i'm going to collect this now probably want to collect it again tomorrow so and the day after that's how we build a trend right so we do a daily collection of probably all the indicators that we have or at least most of them and then all the scores and those results will be stored into that separate table now what if i want to collect historically what if i want to go back and say i want to know how many incidents were opened five days ago well that's a bit different because we really don't have that view uh anymore now right because it could be resolved now but it was open five days ago that's where this comes in so in a historical data collection i'm going to see an incident that was open on the 12th of march but closed or resolved on the 14th accounts for an open incident on the 12th because the resolve date is the 14th it also counts for an open incident on the 13th because that's still after the 14th but it was when it was closed that's still after the 13th but it's no longer an open incident on the 14th because dennis says no result is not after today and it's not empty so that at that point is no longer an open incident so we support historical data collection and that's the reason that we have these these conditions in that indicator source right so i mentioned data collection uh let me show you what data collection uh looks like uh just picking one i mean this is way too many you would never have 140 data collection jobs i would guess so this is a daily collection job it would have to be set to active to actively collect data uh and it would just for the past day it would measure so it would collect the numbers for all of these indicators so a job is a collection of indicators and then an indication whether you want a daily collection or maybe this is a one over you want to do a historical data collection when would you do that well probably at the beginning of your implementation so you'll have some history you don't have to wait three months uh to have three months worth of trending you can go back in time and do a historical data collection or maybe in the case that you say we have a new indicator and rather than just waiting three months to get some trend information let's go back and just for that one indicator or maybe a few do a historical data collection once you have that you can then say okay now i have all those scores what about formula indicators what about the average number of onboarding activities i'm not exactly sure what that means but anyway so the way to set this up a calculated indicator is just as easy as it actually set up a calculation in excel i want to divide cell a2 over cell b7 that's really what this says so you can pick from a list all your indicators and say i would like to divide this indicator over that indicator and then the result can be percentages can be a number can be a score can be anything right the good thing is about formula indicators you don't have to do any collection it's always based on either automated indicators that hopefully have some data against it or you can use formula indicators on top of other formula indicators and again you probably have your data immediately right so indicator indicator source data collection to collect numbers those numbers are stored into a separate table what about visualization how do i create a visualization in the dashboard let's go back to that cio dashboard right and in this case obviously i have tons of indicators and tons of data but let's assume you have at least a few indicators and some data you can very easily say i would like to add a tab how did i do that in the previous session again oops i thought like that no you know what why don't i just add a widget here on this page don't even have to add a tab so i'm going to add a widget a performance analytics widget and as you can see you can add all sorts you can add reports you can add content blogs gadgets all sorts of elements from the service now platform feeds etc that you can enter onto a dashboard but for now let's just go with performance analytics one of the performance analytics widgets i'd like to use a time series here's a workbench widget that i showed earlier let's add a time widget and let's not use any of the existing ones that just create a new one right i'd like to create a new one and there we go there's my new widget now in that new widget i can configure what i would like the widget to be i would like that to be the number of new incidents number of new incidents there we go and i would like that to be a time series present as a column chart submit let's see what that does there you go as my time series of new incidents now this is all as i said a representation of the collected numbers that were stored into that separate table but in this case this doesn't really give me a lot of information because i can't see a trend right with open incidents there's a lot more stable new incidents well people don't work over the weekend or working from home but not too hot then you don't see a lot of new incidents in those two days so why don't i just add oops a time series for that and let's take this seven day running average now what it does is it represents the same data in a different way note that you don't have to collect the seven-day running average numbers because you're just collecting daily scores but a seven-day moving average is a calculation that i can apply to those daily measures for representation purposes now i can see a trend now i can see that there was a peak around 40th of march and went down around the 28th of march it went up again right this is how easy and then i can obviously resize that and drag and drop and make a total mess of it but i can very easily create my dashboards and the one below here that is a combination of indicators very simple go in and say next to the number of new incidents i would like to add a widget indicator add the number of closed incidents right i can see that the same the same chart right so visualization i would say is technically the easy part obviously the challenge is to keep it simple and make sure that it's understandable by the end users all right so hopefully that gives you some idea of some of the basic principles indicators indicator sources i haven't touched some breakdowns but i'll cover that next week and then formula indicators and how to display some of the information on a dashboard we talked about leading and lagging indicators and i would like to add one more oops one more angle to that because i've made it very easy with my weight loss example but how do i go about finding leading indicators in my existing processes and i'd like to take an example of an incident process right here's where the customer or employee that can describe an incident or a problem will then be going up to what is called first level support that said gray swim lane and if they can solve that's all good that's the green part if they cannot then it gets assigned to second level support that has wide swim lane they can do some assessment and analysis and if they can't solve it can even go up the third level eventually there will be a solution for the problem that was raised now there's a couple of flows you can think of that workflow can flow through this this process first level can solve when the customer is happy that's the the best possible flow you can't wish for anything more smooth through that process than this flow not too much work only one person minimum amount of time a different use case is when first level cannot solve i assign that to second level uh second level can't solve and the customer is happy not too bad this is what the process was designed to do a bit more work though two people involved now at least and a bit more time and then there's the process you don't want right the use case you don't want first level console let's assign that to second level oops wrong assignment let's reassign that uh oops the second level needs additional information so it needs to contact the customer uh it turns out we can't solve that uh we need to get third level support involved needs some additional information oops that's not what the customer wanted this time first level can solve and um and that's my resolution you can imagine a lot more work a lot more people involved taking a lot more time now what does this have to do with leading a lagging indicators if you want to measure the efficiency of a process a good starting point can be to look at the decision points within your process all the options for a token to either go left or right right so the percentage of uh incidents right no the percentage not the number but the percentage of incidents that are assigned to second uh level support and for those that are assigned to second level support i would like to know which category they were which type and is there anything that we can do to avoid that right because that's an inefficiency any reassignment that we need to do which incidents typically are reassigned whether we have trouble finding the right assignment group other specific incidents what percentage and if so which ones we always need to reach back to the customer et cetera et cetera so those are good leading indicators to to if you want to focus on the efficiency of a process what's a lagging indicator just measuring how long it took right not looking at what's going on in the process but measuring the outcome my very first slide there right this is the outcome of my process and that tells me it took 3.2 days on average right you can split that down by a specific incidence that's telling you how you did what do you need to do in order to improve look at those leading indicators inside the process this is a good this is a good starting point to get to get uh after those leading indicators all right uh we're coming to the end of this session i would like to share a few more things with you um not too much detail but um this is a high-level view of what a what a a rollout could look like right there's an initial an initiation phase uh where you define um why are we doing this to define a vision are we just trying to replace our existing reports or are we actually trying to get a grip on where we can improve our processes um as performance and analytics readiness checklist i'll make sure that you'll get the the links to those checklists and readiness guides then it's time to start planning the activities so definitely review the available out of the box content uh chances are that the first 25 indicators that you think of are part of that out of the box content right this is based on years and years by now of customer experience so very likely that you'll you'll find your indicators in there and if they're not you can easily build them but don't start by building them from scratch always look at the out of the box content first execution phase this is activating the plugins execute data collection jobs et cetera get all of that set up to deliver in the next phase and the results and then set targets in the last phase you could wonder why that's not in the first phase why are we not selling targets at the beginning one of my earlier slides i said well unless you have a good perspective on how you're performing it's not very realistic you just set targets and say i think we should do better and this is how much better i would like us to do so get an understanding of how you're doing and then set realistic targets maybe five or ten percent better than the average of the last three weeks something like that right but you need that insight first uh this is an example of a page of the readiness guide so that's a really good checklist again we'll make sure to share the links to the readiness checklist the out-of-the-box content i cannot emphasize this enough don't start from scratch don't think you are that unique that none of the out of the box content applies to you very likely that we have a thought of something similar maybe wooded is slightly different but there's a lot of good content out there in the out of the box content now and uh another decision that you'll have to make for those of you who haven't started yet is are we going to self-implement are we going to make use of partners or are we using servicenow's expert services and all three are possible paths to success the different paths well you know i always say it never hurts to uh to get some advice at the beginning of your implementation right you'll you better start off on the right foot but if you decide to self-implement definitely leverage all of the information in our community there's a community of people who have probably come across the same questions or have run into the same problems or or know of the pitfalls and definitely make use of that wealth of knowledge out there in the community training sessions yep we'll probably provide you with some links around the right training availability as well and then partners and expert services so my next and this is really out of curiosity we're not using this information for anything else and just uh the discussion that we're having now and next week what are your plans or what are your what is your current path are you looking at self-implementing um are you working with a partner or you're planning to work with a partner or are you thinking of maybe using servicenow services for deploying performance analytics so again um we're not doing anything with this result other than just fulfilling our curiosity to see what it is that you that you that you are doing what i i'm not sure if there's any results it's a bit quick maybe maybe a bit more time oh i can see there we go self implementing 75 percent uh 3 out of four uh and partners right okay as i said uh all paths can lead to success but but definitely reach out to others and learn from others uh through the community regardless of what party you will be taking and then again we really don't have an advice there but leverage all the information and knowledge that's out there um all right that brings me close to the end of this session i would like to draw your attention to next week's session so next week thursday march 24th i see we have two sessions for the americas uh this is a a round table session so rather than me talking and uh you listening this is uh not necessarily the other way around i'll probably do a bit of talking but it's more sharing of ideas right any specific things you run into some experiences you want to share i think of this as a physical roundtable where there's a lot of customers sitting around the table sharing experiences and then peter and myself will be there as well to uh maybe help you in some cases or ask questions and i would i really like you to sign up for that the link to sign up for it is shared in the chat so it would be nice to to meet everyone next week bring your friends if you know of other people in your organization i would be interested in hearing more about performance analytics uh by all means uh so that's next week uh same uh same day in a week thursday and there's two time slots there or is it one time slot let me see i think it's one time slot at one specific time and the other is eastern time that's probably it i'm hoping yep i guess that's it all right yeah i'm sure you can figure that out more better than i can last bit of information again we'll share the links in the chat and we'll share this slide deck as well make sure to out downl the right training sessions that are offered with that we've come to the end of this session