Seize the Data Putting Analytics Behind Your Decision Making

to yours I've been helping them build modern business functions legal functions that are not only bespoke to risk management but also value creation and what is a modern law function um a marginal function operates on the principles of talent processes Technologies service providers and data and that is the topic of today and we're going to shortly just get to it I've got a great set of panelists today whom I've met over the years and have had the opportunity to observe their quest for prompting data and in making through analytics they represent a wide variety of sizes of organization experiences um you know they've come from organizations that are organizations and you know one-person organizations so without further Ado what I'd like to do is for our topic let's get through introductions and then we're going to set up our conversation on how do we seize the data how do we use analytics behind decision making so I will hand over the mic in the order as you can see people on the screen to Craig Greg if you want to introduce yourself a little bit about your experience and how how do you relate to this topic sure thanks Danish it's good to be here I want to be an OG Cowboy legal Ops professional since uh I started in the 90s with pricewaterhousecoopers and their financial Advisory Group that's gone on to become FTI uh began a consulting company that uh started doing technology for law firms and eventually began coaching corporate legal on how to do fixed pricing process Improvement and purchasing from law firms and then in 2014 I joined Kaiser Permanente as their head of legal operations and for the last nine years have been helping to lead a transformational journey where data is the heart of it I like to say our general counsel was kind of like the old Princess Bride story of The Dread pirate Roberts and he would come in and say well Leslie tomorrow when you drop that RFP and solve everything we won't need you anymore and I'd say I do not think you know what you're talking about it is not going to be a simple RFP drop but it's going to be really getting the kind of information that can help lawyers to make decisions about how to manage the work more efficiently and as we'll talk about today that can be a multi-generational journey so glad to be here with you all foreign I'll go next to Heidi all right thanks Danish and hello everybody thanks for joining us this afternoon or wherever you are in your time zones um I am Senior managing director at Moray Global and I lead our strategic advisory or Consulting practice talking with uh in-house legal departments as well as compliance departments my background in addition to Consulting includes 10 years of In-House working at the Sears and Sarah Lee legal departments I am someone who I love process and financial Improvement um I love to roll up my sleeves and dig in to that and help others and I've also kind of I think my whole career I've really had the Mantra of letting lawyers be lawyers so stripping away some of the um difficult system or process work having them involved but letting them be lawyers and with that I will pass it back to Danish oh thanks Heidi and I've known Heidi for a long time learned a lot from her and Live from Paris France Alex Gallardo hey hi I'm Alex guajardo I am the global director of commercial strategy at Brian Cave I just recently joined within the last six weeks from Shell and actually where I was there for almost six years and before that I started my career in legal I had a few small known law firms uh forward and Jaworski that is now Norton Rose was my first one but like Heidi and Greg I think a lot of the the passion came from trying to make improvements on things that were happening uh so process improvements and focusing in on that and also capturing value so being on the firm Side and being on the client side and then now going back to the firm side looking at what value means because value means something different to you know to the audience or to the people you're working for and how do you get the best use of not only the resources that are available to you but also working with the people that are on your teams are available to your team so with that I'll turn it back over well thank you very much Alex uh I know you've been traveling and you've been kind enough to uh still make it to the panel um before we jump into our topic of today I'd like to kind of know the attendees as well so while we kind of switch slides regret if all the attendees you could drop in your name and maybe your company or at least a location from where you're coming in into the chat it will be great um to kind of get introduced foreign slides and nothing blew up so kind of going back to our topic where we talk about seize the data uh putting analytics behind your decision making um legal departments have gone through a very transformative change in the last couple of decades I mean as we talked about as we've all talked about there's a there's a fundamental acknowledgment that legal departments are business functions and they need to operate and Elevate their operations similar to any other organization within the company and 2023 post coed I mean we're still seeing a lot of Economic and Regulatory challenges that are coming out and the topic we chose around data and specially announced spend was it's a it's a tangible item everybody has spend it is also helpful for people to understand in a Common Language uh but I mean our hope is at the end of this session you're going to be able to take the learnings and apply it to any area where you have data but as we see I mean a big percentage of our surveys in the market uh a big percentage of our respondents are saying legal they're facing legal department budget cuts either they've happened already or they're coming similarly as we talk about the not only the spam external spend but when we look at the head count and internal span a good chunk of 80 percent of the respondents to the Saxy survey that was done earlier in the year I responded that there's some effect of the head count that is happening now the question is what what does that mean and what can we do to address it and our goal today would be to take a proactive approach to try to build it instead of it happening to us or legal where everybody says hey we got to do the x or y or Z we're able to make a proactive determination of which path or which types of actions we can take now before we jump into our discussion I mean this is uh very interesting survey statistic that I've seen over in different uh formations uh in different places that as legal operations experts as business managers in ligo as a managing Council as general counsel our desire is to really do more when we are doing decision making to take the data to take all the data points and make an informed decision but the statistic also shows that we're very aware of how much we are able to do that so you can look at different aspects of matter outcomes Discovery costs selection of counsel selection of venue and I tend to focus on the right side which is sort of the dark blue that approximately 40 to 50 percent in each category organizations are not able to leverage data as they would like to so that is a very staggering statistic that there's still a long way to go so I'm just kind of looking at thank you very much folks for entering where you're from where you have it's it's good we've got some folks from Jersey City I've got folks from broadridge Dallas Texas Southern California uh we've got a good um uh cross-section of folks attending so with that what I'd like to do is um we're gonna go on to a little bit of a journey with each of our panelists and share that experience and what um over the years of experience that they've amassed what are some advice that they can give us for somebody who is starting to think about data or who's starting to think about systems and processes and what can they do to get going and then we're also wanting to make sure that we are going to address folks who are already in the middle of their Journey uh what are the things they can expect as they reach their goals um and so on so with that I'm going to pass that on to Greg we're going to have an opportunity to ask questions please drop your questions in the chat uh as kind of Greg takes us through his journey in three acts of his uh data Quest cool thank you Danish and you mentioned uh you know somewhere around an average of 50 percent of those stats are never even getting looked at so we're gonna talk a little bit about the journey to Neverland because uh sometimes when you get involved with data analytics it can feel like you're doing a whole lot of work and you're never really getting to the land you want to get to and I'm going to give you the hint spoiler you never actually do get to the Finish it's uh really at least at this point in our maturity as an industry and an ongoing journey and uh the thing to kind of ease your mind with is you know playing with data analytics is like playing a game and the good news is it's not a game of thrones so you're not playing to die sometimes it might feel like a game of chaos where you're just trying not to drown but the fact is it really is a game of cooperation and planning it requires a lot of different stakeholders it's not just we've got a system and we can pull out the data from a magic report and do it all it's really a lot more like putting together a winning team where you don't just need any one All-Star but you need a group who really can change the game by using data analytics to figure out that the three-point shot is 50 percent more valuable than the regular shot and hence the warrior so you know what what is important about good data analytics well it can be a whole host of things but in the center of it it's about outcomes and whatever you're going to do with data if it's not leading you to something that you can take action on and then make an outcome happen then it's really kind of all for naught but the kinds of data that we're looking at at Kaiser Permanente controlling costs looking out for the client's Interest being able to scale services and one that I think many of you are becoming more and more familiar with is diversity and how do we actually use diversity to move the the needle and not just have kind of the feel-good sessions and so what we've uh what we discovered at Kaiser is it's a multi-generational kind of approach so we started out nine years ago when I first joined and it was generation number one and my general counsel wanted to know how much were we spending I remember at the time the finance manager would require 30 days in order to give him the spend report so what we did was we dumped the data into a pivot table for those of you who are familiar with spreadsheets and pivot tables we went from 30 days to three hours now mind you when we gave them the result and I said well it looks like you've paid five million dollars in March that didn't mean that's what he actually did in March because the invoices were coming in so late that 3 million of that 5 million in March was from work done in December so early data is really about making the best use of just what you got and being able to use tools that can quickly do it and so the next step in our generation one was actually engaging a consultant somebody that could come in and full time start to do spreadsheet jockeying so that we could do more than just a pivot table we could start to put some bar charts together we should start to tell a story that the attorneys could make sense of and kind of believe it or not you'll see on this game board we made it quite a ways on generation one because we actually started working with an outsourced dashboard provider and so we really would make our data dance even with the bad structure and the bad quality of it we were using outside resources that could really help massage it and very quickly make it look like we had very mature data so the good news is we could do all kinds of basic spend tracking we could do it quickly and in multiple Dimensions that had never been done before the bad news is we were having to make do with whatever the structure of the data was in the system at that time and we were having to make do with very dirty data and so you know at best we kind of were able to start to uncover who are we spending money with and how much are we spending and believe it or not we end up spending that kind of Pareto proportion of too much time with the people we spend too little money with and not enough of the time with people we spent a lot of money with so that began to prompt us into the second generation of well how do we actually manage our work not just track our spend and the thing that's interesting there is it didn't matter how much we had made progress in generation number one when we started generation number two we had to take a huge step back the first thing we were trying to do was put a new system in place that actually gave us the data elements that we wanted instead of just the data elements we had and we thought haha we're going to win now we're going to make it the way we want it to be well installing new systems implementing change understanding how those systems work actually required us to take some steps back so while we were so mature in these dashboards when we put this new system in with all this data structure we wanted it was like a couple steps back just to even do the basic spend reports right but over time we began to insource the ability to work with the data so no longer a consultant or an outsourced dashboard but one of our members of the team began to get trained in business objects and began to groom this sap business objects Universe to actually say the labels that you want and work the way you wanted and one of the tricks to the trade was not only bringing it in-house but then really hiring outside expertise in this case from Mitra Tech to be able to train our in-house data expert on how the system worked and what we were going to do with it but we still would actually use some outsourced capabilities or external Consultants to do kind of the one-off acrobatics when we needed to do really something more than our Basics spend tracking in our new environment but we wanted to look at how to manage a matter we would still use outside resources to be able to help do that in a one-off and quick kind of state and so really what it did was we at least started getting closer to how to manage the work so we weren't tracking the spend but we were starting to be able to see who's doing what and how they're doing and this is just a scatter plot of all the time Keepers it's amazing when you look at your outside counsel how many time Keepers you have and how much larger your legal department is if you factor that in and So eventually we started on the Journey of our third generation and the third generation one of the challenges there is really being able to start to take these reports out of business objects and making them more available to the users so instead of it being controlled behind the curtain of the team and given the leadership how do we start creating reports that we can schedule to be delivered to attorneys in their email boxes with spreadsheets and of course as we start giving more and more data out to more people what we realize is data quality becomes the essential Factor we're no longer able to control and groom and serve to leadership these things are going out automatically people are accessing it from different directions and so data quality continues to be one of our biggest challenges but we tried to begin to solve that by centralizing data entry and beginning to in-source building dashboards so we moved from just using business objects sap to using Microsoft business intelligence dashboards and having our internal team build those so we can start to make more data available to our users still very much so dependent on some outside resources because I mentioned our data quality was very bad even though we updated our guidelines to get outside Council to start coding their time entry so it'd be more useful believe it or not they didn't actually start coding it better so we would use outside services with an AI tool to groom that and be able to help us do more advanced kind of scorecards and analytics and so ultimately what we're trying to get to in third generation is not just spend tracking or managing the work but really how to analyze the performance and so as we go forward and we start thinking about generation four data quality and how do we automate data intake so it's not going to have data entry errors is going to be key and how do we continue to insource that ability for matter management and Performance Management and the thing I'll kind of leave you with at the end of this journey what is most important to you and where you're at whether you're on generation one two two three or four what I recognize is the most important thing is you have an Engaged user you heard Heidi talk about keeping the attorneys involved if you don't have an Engaged user you can invent quantum physics and it's not going to be worth anything so having somebody who really wants to work with you and use the data is important because they're the ones who know the context of it and they're the ones who are going to test to see if it's accurate and correct and ultimately if you're not giving out data and reports that's actually being useful then the data the reports don't matter so whether you're at generation one two three or you're ready to start saying your ABCs as long as you're actually doing something that's going to make a difference so somebody can use it then your data reporting is successful and when you go through enough Generations then you can join me in singing your do re Mis and we can see what Great Heights we can all Advance the industry to so I just wanted to set up a little context of a data journey and Heidi is going to be able to share us a little bit more detail about some specifics that go into her data journey and solutions that she was sold Greg had a question when you look at this what I mean in everybody's journey is a little bit different from a time frame perspective what did your generation want with Generation 3 Journey look like and and now in high side do you think it you would have taken a different path you know that's a great question uh Danish I I think that I'm a big believer in the power of three and it just so happens that each of these Generations took about three years so from 2014 to 2016 we were in that generation one we were able to use it to consolidate legal budgets and create more accountability around spend management generation two began with the new system install that kicked off in 2016-17 and ended in 2019 and then generation three were really just coming to the end of that so I think so much of what we do is dependent on the teams of people we put together the clients we're engaging with and how you're actually getting to an end result and usually that is kind of a three-year Journey right you're putting the team together to know what to do you're engaging the client to get what they want and then by year three you're actually starting to practice results and usefulness and just as you get it's kind of like okay now we're ready to go to the next one so the nine years has kind of encompassed those three-year cycles of a generation and that might seem a little bit long to some people but you know it's better to make measured and reasonable Pace than it is to expect things to happen in nine months and nine years later you're still at the starting point so basically you're saying your GC said you can take as much time as you want I don't need this yesterday well you know I mean there's always the expectation for wanting it now and yesterday but then there's the reasonableness of getting something useful in a reasonable amount of time and that's why I talked about having an Engaged user so that DC hey we were able to condense 30 days into three hours and start to give results right so along each of these steps of the journey you make sure that you're creating some kind of bit of progress right you're not just taking three years to get to the end result it's a journey of a thousand steps begin with the first step and when you're 300 steps in you're a lot further along even if you're not exactly at your aspired vision or destination that's wonderful and I think that's a great setup to you know Heidi and Alex as we move towards you and then we're going to come back and try to put this all into perspective honey you had a different sort of problem you had a department that was not necessarily in you in control of your spend you were being told things so your battle was a little bit different than even being asked for a report or something talk a little bit about that yeah I'm going to take um kind of building on on Grace and go into just a really specific um use case and this it kind of ties back to one of the findings on the slides that Donna shoe began with with which was the extent um that the respondents used Data Mining and analytics to predict matter or Department budgets so this this use case is about Department budgets so this is this is based on my personal experience in-house but something that I continue to see in our clients in terms of working within your company and with kind of your overall fiscal responsibility within and your annual budgeting processes with Finance as well as then even kind of your throughout the year how you are updating or working with the business in in my example uh we did charge back legal costs to the business which is a big point of this use case but how this began was when I got there the kind of the annual legal budgets from what I could tell it was just kind of a roll of the dice um both for our cost center within legal as well as I could not figure out how the line items for the business were being figured out so it did seem like it really was just it had been sort of historical spend and then plus or minus some percentage based on kind of overall companies spending expectations which to my mind having been in the legal industry for a while at that point I thought how is that going to be accurate and isn't there you know isn't there data or something that we could use rather than that data the other thing too in this was the the business was just they were making their own decisions on that line item again to me which didn't seem like they were the kind of informed user to know what the legal line item should be and there wasn't any process where they conferred with us in legal so none of this was really making sense to me um the other interesting piece was just that I would get our you know monthly Financial reports from Finance working with fpna and with the controllers and there would be random charges that would be hitting hourly legal cost center and I realized after a while anybody who thought something sounded like something legal they would code it to Legal um and it wasn't really ours and so I would spend time tracking that down and trying to figure out whose cost it really was because it didn't seem right that it was hitting our our budget so that's kind of the setup and again I do see this at still quite a few clients and when I think about that finding I think it was over 60 percent of the respondents to that survey either never use data to help with predicting their budgets or intend to do more I think it was 60 or perhaps a little bit more but so then going on to kind of the solution um so this was a combination of Technology of good data and also winning hearts and minds of the lawyers as well as the business and also Finance of just kind of everybody working together to put a better better more defensible and truly kind of data driven process in place to predict and to then agree upon those annual budgets but a couple of policy things that we did too um put in place a policy that only the legal department could retain or engage outside Council and I I work with quite a few companies who do that but we did take that then a step farther in working with Finance they were able to take our I don't know if we had I think we probably had sap at the time and make it so that nobody could actually hit the GL account for legal fees so it kind of became it was only used by legal which really simplified things a lot um we also worked very closely with the business trollers talk more about this process of how we could put a more accurate budget in place for them because as you can imagine or as maybe those of you on the webinar here are experiencing if a business or even with corporate finance put in an unrealistic budget for legal expenses we all know what that looks like after you get you know halfway through the year you can begin the year with some favorability and then they try to decrease your budget they take it away they don't understand the how you can't straight line legal costs um and it ends up with everybody being frustrated or being upset with legal so we got to a point where this process then by using really good data everybody understood the process they understood the inputs and we had realistic budgets so how do we do that we had clean data and I can talk a bit more about that but policy wise within the legal department every every matter that utilized outside counsel it was just required to have a budget and I've heard objections to that in the past of I don't know what it's going to be or it's going to change a lot or the dollar value is too low those are all objections that you can overcome um we had thresholds for example of an even like a you know drop downs where if it was under a five thousand dollar budget Etc there were things like that that you could do to simplify it we also did allow for budgets to be changed the matter budgets and these were done for current year and next year for the two data points that we tracked because those two then enabled us to do this budgeting and forecasting so every matter required those the lawyers or paralegals could change those budgets it was all tracked so we could I could see how that changed and with that good data and agreement from the lawyers that this was accurate we got to a point then when it became August and September and we were beginning the annual budgeting process both for our corporate legal cost center as well as then for the legal budget that the businesses would receive from us that was all based on real data so it was based on the open matters and what was still out there for the budgets as well as the next year budget and then of course everybody's going to say well what about the work we don't know about yet of course we all know that happens too you don't have all of your legal costs aren't known in September for the next year but I was able to do a look back at the data the data was pretty clean at that point and I was able to do a look back of kind of running data from that time period and then looking at what actually happened and with enough data I was able to get an average that by September there were still approximately 30 to 35 percent which kind of makes sense right of the unknown so we would take what was out there in terms of the actual numbers in in the tool that we used and agreed with the lawyers we talked about any sort of outliers that were coming for example if we had a shareholder litigation or something that truly was an outlier but we would add in then that percentage that again through data proved that historically it was pretty accurate and we were able then to get to that budget for the next year the businesses then more or less sort of had to accept the budget that we gave them but because it was defensible we could show them the process that we went through to get it pretty hard to refute our job then illegal and as the lawyers was just to manage that work as responsibly as possible and to then throughout the year provide in in our situation in that case we provided quarterly updates with the head of the business and with the controller for those businesses and showing exactly where we were relative to those forecasts and whether or not anything had changed and had changed our assumptions to the positive or the negative overall and ended up being a pretty smooth process I think the lawyers ended up liking it a lot after a little bit of convincing because I think at first there was quite a bit of resistance to every matter having a budget for example but it got to be pretty straightforward I think after they realized that it was okay to make changes and they didn't have to know everything perfectly um it became just part of our routine we did have our initial data in the system and this goes back a while but this was with e-council at the time we brought in data from what had been a homegrown system and we we cleaned that data I mean we made sure that was good data um we made sure then that everybody was utilizing the system in the same way and of course we had the new budgeting fields for current year next year and we reported throughout the year with the Department the change management point there again I think with any system and with any kind of a process like this where you want to have good data that you can use for predicting and for and for really solid decision making you really have to have to to Greg's point you really have to have engaged users engaged users and stakeholders and in this example this use case is the lawyers and it was also finance and then the business controllers um also too we over time we just had sufficient data you know if you get if you end up in my experience if you have a minimum of 18 months of clean data um it can be pretty predictive I in my experience in my 10 years in-house it was really my 18 months that was most predictive of the next 12 months if I went back three years well that sounds better it actually in my experience at that time it was not I ran both calculations and it was more accurate to have used the prior 18 months um but that's my very specific case study and use case of a really deep dive into how to use data to help with an expected and reasonable corporate process in the annual budgeting so with that back from Danish well it's a it's a great example Heidi I mean you were very specific in explaining it let me ask you a question so what did that do for your legal operations team or even your legal department as a general was this activity more of a scene like a land grab getting back the finances and people in the business didn't like tip or did it really elevate your position in the in the organization that legal knows what they're doing great question it was really more legal knows what they're doing um we worked so at first Finance really did a lot like working with legal because the prior process had been the poor guy in finance had to go to individual lawyers to gather information and he did not like that process so we centralized it right in legal operations um and then with the business I again we were very proactive so they liked that we were coming to them with what and again it was it was defensible right we had we had the data to show it and they really liked it because they didn't like the prior version which too many surprises right where they had a budget that was based on you know nothing based on fiction but they had a budget that they would end up not meeting or being mad at legal because by you know July we had blown the budget because there was something that they hadn't factored in so it became very much legal from a fiscal responsibility fiscal stewardship became viewed very positively wonderful so I'm sure folks in the chat and the attendees have a lot of questions I think right now would be the time to start typing in some questions uh as we sort of hand over the mic to Alex you've heard from Greg sort of his overall journey and how you know they kind of look at different generations of improvement we've heard from Heidi how she was able to take sort of from ground zero a journey towards fiscal more fiscal management and I I would love to hear from Alex how we can look at a framework that gets us there I mean all of us know about billing Systems Technology systems Elm and a lot of the Technologies are thrown there or financial models are from there but Alex in your opinion you've been both in the law firm side you've been in-house you've been speaking a lot about this can you give us some sort of framework and guidelines that you know as folks are either doing this or starting to think about this what do they need to have in mind to make this successful thank you so um as a one of the things that we are looking at and something I'm looking at now in my new role is um I say we're data challenged and that when I say that I mean we have a lot of data in a lot of places um we don't know what's outdated what's good what's not and unfortunately not all data points are helpful I mean there's a lot of data out there that do not tell any kind of story but we're supposed to come up with some magical analysis of a story and and help people make some decisions and that's not always the case so um everyone always says that it's a very very well-known cliche data doesn't lie the data doesn't lie but the stories that happens around the data certainly do because sometimes we get incomplete data and that can tell one story um and then there's the data that's uh you know that's appended by uh when it's when we don't know the the duration or how old it is like Katie talked about uh you know when it's 18 months versus three years and now you think you're only looking at the last 12 months the later the data could certainly tell um an unrealistic story so where do you start in looking at this it's it's a little overwhelming right when you come in and there's nothing there you're trying to figure out what's important you really have to hone in on what are the problems that you're trying to answer and what are the questions you're trying to address but at the end of the day not all questions um you know and not all data will point you to an actionable result and that is one of those things that you know in order to get to an actionable result is making sure that the data that you're capturing really is going to be measured in a specific way and with that I'll talk a little bit about what is a good kpi and I you know we've heard this when you're talking about goals this has been said many many times that goals should be smart and you know there's all this information out there why because if it's not measurable it's not helpful and there's nothing you can do about you can't achieve a goal if you don't know what goal what is your actual goal the same thing with kpis key performance indicators in my previous role we had lots of them and unfortunately you know when you set up a bunch of them you think well all of these are going to help the leadership make better decisions because I have 20 kpis and now these firms are being measured against a lot of kpis in reality a lot of the kpis were not updatable we couldn't really there there was a lot of subjectivity happening there was a lot of you know interpretation around it so in order to set up a good kpi we have to do a few things you have to identify kpi so we really want to talk about we need to set some relevant kpis that go against your performance or the questions you're trying to answer you want to also create some kind of tool dashboard pivot table something that that flushes out the data that shows you the performance of those kpis um if you cannot see what's happening on a regular basis and you cannot keep them if you cannot measure these on a continuous basis how do you know what's performing and what's not how do you know if you're moving in the right direction then you have to evaluate them um how are you going to be able to achieve your business goals off these kpis are they going to be helping leadership make decisions and sometimes when we evaluate them we decide to change them and say you know what the maybe we started off with 20 but we really only need to focus in on five these five really make a difference in how we behave and that's where you go into the assessment right do you do they still align with the goals of the business the goals of your corporation the goals of your Law Department because a lot of the times our kpis you know started off with good intentions but they really didn't do my for for our actions that happen later um in a practical sense and when we're thinking about data-driven decisions and practice um sometimes we focus on one thing too much right so looking at you know working in any legal department whether you're on the corporate side or the law firm side spend is a big big kpi that is the most important that's the one everyone's looking at that is the number everyone's talking about how much money do you spend how big is your budget how much are corporate clients paying us for this work that spin number becomes that finish line and sometimes that's the one kpi everyone focuses on when in reality sometimes that does not change Behavior knowing the number you spend does not ultimately change Behavior so focusing in on just the Finish Line we're missing the milestones in between right the little stops along the way where you stop and get some water because you need those in order to keep going so looking at the same kpi with no and not changing it not assessing it not reevaluating it and then expecting Behavior to change over time it's not going to happen one of the things that we have to do is take a step back and say what else can we look at and one of the examples I have is we were looking at diversity spend of our suppliers you know how much of the day of the spend was actually going to suppliers on a quarterly basis it started off quarterly basis just on spend and every quarter we were showing the number and the percentage was staying the same quarter or a quarter we went to monthly and you know so then the second the second time you show the number your month the same month so then now we took a step back and said well let's look at the actions that are happening at the beginning how many times are diverse suppliers being invited to submit bids on tinders or rfps and the percentage was exactly the same as the outcome of the percentage of spend which then you start to you know to say well if they're not even being invited how are we going to increase spend overall and that change actually started to move the needle because people started thinking about it on something that they could make difference in an action now that the lawyers could take and if the lawyers can take that action then there's going to be a change in behavior and there's going to be a change in the output and again what is the problem we're trying to solve um that always we always go back to that when I'm looking at all this data and the data is being put in front of our lawyers instead of giving them homework I'm trying to give them options with the data and say if you go through door a this is the possibility if you go through tour B this is the other possibility so when they make their ultimate decision they know that you know but there could be a dud behind door B and then how does change happen one of the most important things about change is really thinking about it in a holistic way right um sometimes when things aren't going well we are quick to assume that people do not know what they are doing and they're not following the procedures but sometimes there's pieces missing of that puzzle and in our path we are missing you know if the process is not clearly defined or outlined where we know that we need to take steps forwards or sometimes even take a step back because it's clear steps are required throughout our process people will fail any technology can do many things and as we're talking about all this new technology that's out there especially with the very hot topic of AI and you know using a lot of these great platforms that are out there they can do many great things but if they're not incorporated into the process of everyday working and people do not know how to use them and the training is not there the technology will also fail so these three these three things are extremely important for us to incorporate change into any of our departments whether we're on the corporate or the law firm side that's such a such a wonderful examples as you were saying that telling that story he just reminded me a few years ago I was working um at a at an insurance law department for folks who are familiar but not familiar with the insurance insurance typically has three different legal teams a a corporate legal teams that works on the day-to-day legal corporate litigation matters a staff Council which is sort of an in-house capital law firm and a retained Council team it just sends out matters that they can't adjudicate internally the internal teams they have to send out and we're preparing for these preferred provider annual reviews the the dreaded sort of get all the data in get all the you know conversations set up and preparing from the head of legal Labs have to go do those and this one we were dreading because we promised this firm everybody liked this Farm but we hadn't been able to move so much work to them and our deal was that we'll maybe have to soft battle here make them feel loved so they continue to work with us and give all the benefits that we're getting from them and the head of legal obstacles comes back in 45 minutes and in my mind I was like either this is a very great conversation or this is a very bad conversation that's a very short meeting um but it was interesting I mean the head of the office was like hey I went in there for first 10 minutes I was just confused the the couple of Partners had come in from the law firm and they were so excited they were Thanking us so much and they said we'd love to work more at some points like time out I mean we gotta talk about I am totally lost and what ended up happening was that even though the legal department and the team that had put the panel firms together hadn't given them enough work they apparently were getting three times the work from the retained Council team so you know apparently the law firm thought that they you know uh all all one team was working but internally those two teams had no clue that that was happening and so it's interesting that that whole data Gap or the data story can only tell you um as long as you're looking into it in the right direction okay so I we have a question here I think um we can go around the room kind of talk about what critical data points did you discover in your Journeys that may have not been obvious at the outset or maybe just overlooked I guess what are the learnings as you go along uh some nuggets of wisdom that we can sort of be aware of Greg do you want to kick us off sure I mean I'll just uh kind of say quickly it's about the timing of spend data uh so kind of building on what Heidi talked about managing the budget and what Alex talked about and recognizing what's the right kind of kpi I talked about how when we condense 30 days to three hours and we said okay five million dollars in March well that wasn't really five million dollars of spend in March that was five million dollars of received invoices in March three million of which was from work that was done in December so one of the most critical things was moving to a cruel based accounting and starting it at an annual basis and then on a quarterly basis and now we're still troubled with the fact that invoices come in 30 days after the end of the month so that's 60 days after the work is done so being able to use invoice time entry data from outside Council as a form of project management is incredibly challenging because you can't take action on something that's 30 days late but at least by moving to the accrual we began to gain competency with Finance because Finance has been doing accrual since 1970 right and so now you could begin to say well if we're forcing accruals at the end of June we at least really know what we've spent in the first six months of the year and we can gate that so we're not getting surprise invoices in September so for us it was really the timing of data between when it's received versus when the work is done versus when are you able to see it and actually take action on it whether at a leadership level or a management level I think Cindy has a great point in the chat as well that I think um just that focus on process and improving the process can make a lot of difference as well as she's mentioned there were some emails involved and um you know and if you can improve that that alone can also improve your cycle of data like you're telling about timing and so on Alex from your standpoint anything that you think of that you know just there was a great learning or aha moment for you um there there's a lot of assumptions that are made when the data is not always there for us you know on the client side looking at you know we had many firms saying we're not getting invited to enough work we're not getting enough spending from you and then really being able to flesh that out and show them um in a very concise way instead and saying you were actually invited to this many rfps this in the last month in you know the short timing uh in the last month you declined to due to conflicts you declined to do the capabilities so you know you so when you start to break it down in that way it's not that they weren't invited but the ones that they actually responded to they would actually have a higher percentage than they were assuming they did and sometimes those data points start to show up and I think there was that question regarded critical data points are based on the questions that keep coming up over and over again you want to address those you want to you know you want people to trust in what you're saying and sometimes the only way to do that is by highlighting the activity and you can only know that as you're going through your processes as to what is going to become more critical or more uh something of more pressure at that time more important or significant in that time period honey I'll take some comments from you and then we're gonna close up with some hard thoughts cruels and just my experience too was that Finance what Finance reported and what we reported in our tool were different so we that that was then tricky for my GC right because he didn't have the right number or it seemed like somebody was wrong so this is where the whole thing with accruals and really making sure that process works well that was kind of a surprise to me in fact when I went to Sara Lee Sears had been cash based which is pretty unusual so when I moved to accrual I didn't understand this but I felt that it was my job to figure it out and to make sure that my GC had the right numbers at you know at the big level right and I that's something I still believe really strongly in the GCS don't need all the details that we might need that's I think our job is to understand all the data but the GCS need to know the big numbers and they need to know the numbers that align with finance and if there's a reason that it's different or there's like a settlement that gets included somewhere it's important that he or she knows that so I guess that was kind of to answer the question that was in the chat like that was something that it surprised me that there was that difference and I wanted to work really hard to make sure that we were aligned going forward and again that the GC felt comfortable and credible with the numbers is you hit on that topic I've kind of informally said that data is multi-dimensional so when you're just taking a snapshot of data like in a spend tracking that's one dimension when you want to start to compare that with some other attributes of categories or contexts that's two dimensions when you get to the third dimension that's timing and so often like you highlighted the timing of Finance is different than the timing of Ops is different than the timing of the outside Council and now everybody's looking at the same Diamond but they're some are looking at the top and it looks like a circle and some are looking at the side it looks like a triangle and some are looking at the bottom it looks like a DOT they're all looking at the same thing but it's that different dimensional perspective and and realizing that you can get really twisted up and confused if you rush forward into those dimensions that's part of the reason why it is kind of important to really peel it back systematically like uh like Alex highlighted and really understand the process the platform and the different people that are involved in it cool well I think that's really helpful I know we're not going to get to all the questions in the world try to probably answer uh offline uh if any questions are left but just kind of going through like summarizing what we've learned I mean we talked about data being a real differentiator data can really elevate your Law Department and your legal operations function not only within the the legal function itself but also within the company you can be a really you could really go toe-to-toe with other value creation functions in your organizations um just as we leave I mean I think you've heard sort of from a journey perspective what your expectation should be it's not sort of a one-time deal if you treat it as more of a generational Journey it will help you learn from Heidi of what specific tasks you can take to get control of your data and positioning in the organization Alex kind of laid out that people process mechanism that let's not look at it is just looking at the numbers or looking or putting a technology billing technology and let's take it all of it together and get a measure it along as we go and and if needs change then adapt as well so I mean this is again some metrics I mean you see that how much everybody focuses on outside Council spend but like Alex said you know noting down how many rfps and a law firm was invited to or noting down their dni performance as you put together your kpis you really need to think of it as a holistic program and to bring it all together I think if you look at when we're really talking about spend or Enterprise legal management you do need to have some baseline data or systems whether it's an Excel sheet or whether it's truly a system that helps you operationally and e-billing system where you can gather this information outside Council guidelines system process bills build in some reports that can let you figure out what data you're capturing and then you can sort of continue to climb up that strategic decision making uh process right we can create some dashboards that focus on specific kpis we heard about AI supported build review there's a lot of tools out there that can help you as you're reviewing the bill there and then help you figure out how to better review those bills day to day we're all busy I mean not all of us have time to look at the bill in detail or call the law firm of it figure it out so there are Services out there that can sit on top of your AI and e-billing systems where specialized build reviewers can review your bills talk to your law firms I think Greg talked about some external help getting you know making sure uh your relationships are not effective making sure you're not just gonna doing interviewing the bill for the sake of it and then there are other sort of uh leverage you can use as building a preferred panel program um another one that I don't I mean that I see not everybody is very familiar with they are marked excuse me um looks like we might have just lost a Danish there but uh Alex and Heidi maybe giving some parting thoughts I would just like to put an advocation in for diversity uh we really have found at Kaiser that uh diversity is a place for Innovation it can be protected and incubated and what started off as helping to move our diverse timekeepers we were having 50 of our work done by uh females already but when we got it coated properly we found out the majority of work they were doing was administrative and the males were doing the more Mission critical kind of work so when we got it coded properly we were able to get that work balanced better and before you know it aren't we doing legal project management work so just like to say think about how diversity and using data with diversity can help Drive new innovation maybe Alex and Heidi some parting thoughts I would totally agree with that I think we have to start we have to keep pushing on that front um and we can let up just because we've been talking about it for a while but it is a it needs to be a collaborative and United effort from both sides of the you know from everyone involved great and danish we were just filling in with some partying thoughts maybe Heidi absolutely well I think we had a time so I would like to say a thank you to everyone I really appreciate the recording is available uh we can send it out to you or you can request call in and team to send it out uh you've been really a great audience a good great participation hopefully this was helpful thank you that was your great panel crew keep the data analytics music rolling there you go [Music] time for me to go get a drink I want I want that recording you guys put on a