Video: Fix It: Turn Insights into Better Standards | Duration: 1192s | Summary: Fix It: Turn Insights into Better Standards

Transcript for "Fix It: Turn Insights into Better Standards": Alright. Hello, everyone. We'll give it another thirty seconds or so so folks can join, and I'll kick things off. Alright. I think we can jump into things now. This will be recorded so you can go back and watch it on demand for anything you do miss. But to start off, I'm Marissa. I'm on the product marketing team here at Agiloft, and I'm excited to bring to you part two of our, webinar series, find it, fix it, scale it. So today, our focus is fix it. So if you're here for us with us for part one, it was focused on find it. So we went and dug into our contracts. We had two primary questions in there. The first was, hey. Do any of my contracts have some auto renewing terms? Help us understand, where those are, how frequently it's potentially coming up in our contracts, and, potentially learn from that as well. And then the other one, very hot topic right now around allowing AI models to train on your data. And so we ask our contracts if any of our, if any of them allow for third parties to train on, customer data. And so given those insights now, we have the opportunity to jump into fix it. And so once you've gone through and actually gotten to, understand, hey. What are those risks in our contracts? What are the gotchas that keep coming up? You wanna figure out how do I fix it going forward? And so today, we'll focus on how do we actually implement that, into our standards. So that way going forward, we catch it before we accept auto renewing and something auto renews that we didn't want to, or we stop anyone from potentially training on our customers' data in our, terms there. And then stay tuned also for the next series, next part of the series, Scale It. You will see the registration in the chat there where we will focus on how you actually make this scale for your organization. How do you make sure redlining a review is something you can scale across the organization, scale getting these insights. So that way it's not just, hey, a one off request, but getting those insights ongoing within there. And so jumping into things just to give background, similar to what we did in the last one. Again, contracts have two moments that really matter. Right? There's the pre signature. Hey. Teams wanna make sure when they're in negotiations that they're applying the standards. They wanna make sure that, hey. Is this actually something I can approve? But reviews can become a little slow, a little inconsistent. Hey. This time we accepted this, and this person did this. So, thinking about how do we make it consistent, when we're negotiating and keep deals moving along. And then the other side, your contracts have really valuable insight. And so teams need to understand what's in their contracts, both to learn from, but also to execute on the contract and and get things done from there. So making sure that you're able to make decisions with complete information. And that's where ASHA comes along. That's where you put that AI to work, helping the team before and after signature, understand, hey. What's in my, contracts? How do I understand, what I can learn from them, what we've done in the past with them, and apply that to future ones to make every contract better. And, specifically, looking at that, today, we're gonna focus on applying those insights to your standards. How do we build screens that make us better at applying those standards consistently, applying those learnings, and making sure we learn from them? And then, again, we'll follow-up in the next, part of the series to dig into more post signature. What does that look like, continuing to learn and drive those insights there? And with that, I will pass things off to my colleague, Tanya, who will drive us through on the fix it side. And, also, while I jump off here, I will be in the q and a answering any questions. Feel free to put them in the chat as we go along here, and we will whatever we don't get to in the chat, we will, follow-up with after the call. Alright, Tanya. Off to you. Right. Thank you, Marissa. Okay. So today, we're going to look at how we can take our contract knowledge and and preferred positions and turn them into playbooks that help guide our negotiations. And this really builds on what we saw in our last session. Last time, we used Astra to look across our existing contracts and identify where risk already existed. Today, we're gonna take what we learned from that exercise and move upstream. So we're moving from finding the risk in the active contracts to now building the tool that will help prevent that risk in the contracts we're negotiating today. So let's get started by creating a new screen or playbook within Astra. Here under our screens tab, I have access to all the screens that are available to my team that we can currently use. Now creating a new screen, we have a variety of different options on how we can start that process. So we can build one from scratch. We can also copy from a community screen, which we'll see a little later today. We can also generate from a contract. So say we have a golden contract that exists that we've already negotiated. It has the preferred language that we want to use moving forward. We can take that and create a playbook out of it. So I have an example here today of a services agreement of a playbook that we have taken from a contract we previously negotiated. So within this agreement, all I need to do is highlight which pieces of the language I consider a standard. So you can see that there's square brackets around certain language within the document. Now those are standards that I want Astra to create, so I can use those in a playbook moving forward. And now once I've completed going through and highlighting each item that's important for us, I can upload that document into Astra. It's going to then create that playbook based off those important standards. Now we'll also be able to define which side which party are we within the documents. We can give it extra guidance on where we're coming from in those negotiations. So for this example, we're the client, so I can add that in. Now while Astra's generating the playbook, what's happening here is really about accelerating that first step. So instead of starting with a blank page and manually defining every standard, we're giving Astra a contract that represents language we've already reviewed and are comfortable with. So Astra can use that agreement as a starting point to identify the positions, the language that all become standards in our playbook now. And, what's important is this isn't about removing the human in the process. Once this playbook is generated, we can review what Astra has created and then refine or add standards based on our preference or based on how our contracts and negotiating are evolving over time. So here we can see our playbook that's been generated. It's generated the title for us that I can go ahead and change. Now this title is gonna be what our users see later on when they're accessing the playbook. So it's clear to give it a distinct title so they know what they're what to expect with the playbook. Now each play or each item within the document that I uploaded is now created as a standard. So we have access to review all of these, and I can see the specifics behind it. So each standard is more than just the text that came in from the document. We're giving Astra extra guidance on how we want it to work with the contracts that it's negotiating. We can also give extra user guidance so our users are confident when using our playbooks. Now looking back at what Jack found with the risk within our current contracts, I wanna create a standard based off that information that he found. So up here, I can add a standard in, and I'm just gonna walk through and fill out the information to make sure I'm giving Astra all of the guidance it needs. So the first one we're gonna look at is contracts that auto renew unless terminated ninety days prior. So we flag that as a risk for us, and we wanna make sure that contracts moving forward have at least or move down to a thirty day window instead, giving us extra room. So first, I can put in the standard text. So this would be what really is our core position that we want Astra to evaluate. So this is something that we wanna keep simple and direct. It's ideally gonna be one to two sentences that clearly state what good looks like for us. Now ahead of time, legal has determined what language we wanna use, so we can add that in to this standard. Now the standard details. This is where we can give Astra more context on how to interpret this rule. So we can get really specific on what we're looking for and what it should flag as a risk. Now if this information is not addressed within the document, we can tell Astra what we want it to do. Do we want it to infer? Do we want it to pass this standard? Or do we want it to always fail this and flag this as a risk for us? Now, next, we have the option to put in our preferred language. So this is the actual language that was provided by legal that we may wanna that we do wanna use moving forward. So once we've identified something that just doesn't meet our standard, we can add this language in. And with this language, we can work with what's already in the contract. So we can surgically put this language in, or we can choose to add it in with a heavy approach. Now our default comment. This can be a comment that's external facing. So when we share these this red line change with the counterparty, they can see where we're coming from and why we made this change. Now for the risk configuration. This gives us a way to distinguish between something that's maybe a minor preference or something that represents meaningful legal, financial, operational, or data risk that we need to flag. Next is our user guidance. So I like to think of this as a place where we can capture that institutional knowledge that exists, and it's gonna then help the person reviewing the contract understand how they should negotiate this standard. So we can bring that in. Now when we look at all of these fields together, we're doing much more than creating just a list of clauses that we like or don't like. We're capturing what our standard is and what good looks like, how important it is, and giving both Astra and the reviewer guidance on how to handle it when they see this in contracts. This allows the playbook to take knowledge that may traditionally live in someone's head or in a document somewhere and make it available consistently during that contract review process. Now once I save it, it's gonna be part of this playbook. So moving forward, this risk standard will be available for our contract negotiations and our team to use. Alright. Next, I wanna show you how we can use our community screens to create a playbook. Our community screens are created by industry experts, and they're meant to be there. And in case you don't have a standard or a playbook for this type of contract, so maybe this is something new that you guys are working with, you can look to our community screens and see if there's something there that can help you get this started. All of our community screens are gonna be broken down by the different contract types that it could be working with. We can also pull out obligations. So that's something that maybe we'll cover in another webinar where we can pull data from our contracts and track those obligations in Agiloft. Now sticking with our services agreements, let's go down and take a look at one that can help us with that. So here under services, we have access to Andy's screen. Now each screen is going to give us information on its purpose. So what is this meant to do with these negotiations? It's gonna tell us any limitations or assumptions to expect within the playbook. But almost more importantly, it tells us about who created it. So we understand Andy's experience in the industry. Now if this is a screen that we're interested in using, we can get this screen and have it added to our playbooks. Now at this point, I can really make this screen my own. I can go in and review each, standard within here. I can then edit it as well. So I have that human element in the process. Now I'm gonna show how we can add a standard to this. So jumping back to Jack's webinar, where he found contracts that don't restrict the vendor from using our data to train the AI. And with AI being so prevalent in the world today, that's a huge risk that we need to be aware of. So let's create a standard that focus on that risk item. So we're gonna walk through what we saw with the previous screen where we created that standard. We're just gonna fill out the important information to make sure that Astra has all the guidance needed. So first, our standard text. So this is letting us know that vendors must not use our data to train their AI or machine learning models. And then our details is where we can get really specific on what we're looking for within this language. Now for this item, if this information is not in the contract, we want this flagged as a risk. So if it's not addressed, we want this to always fail because that's gonna let us know that we can put in our preferred language, so then this item is covered in the contract. So with our preferred language, that's making it very clear that vendors cannot use our customer data to train their AI. Now we can choose that redlining approach. So how do we want it to interact with the information that's already in the contract? And then we can add in that default comment, letting the letting the external party know why we flagged this and why we made this change within the document. Now this is gonna be selected as a high risk item, and we can add in our user guidance as well. So making sure our users are confident when they're going in and using this standard within the playbook. Now saving that is gonna add it to the list of standards that already exist in this playbook. And moving forward, your team can use this standard to flag that risk for contracts that we're currently negotiating. So as we wrap up, I wanna connect what we've done today to the broader journey we're taking across these three sessions. So in our first session, find it, we looked at contracts that we had already been executed and negotiated, and we used Astra to then identify the risks that already existed in those contracts. Now today in fix it, we moved upstream. So instead of finding those risks after the fact, we looked at how we can take what we learned and turn it into actionable standards within a playbook. We saw two different ways to do that. So starting with a golden contract that we've already negotiated and then also leveraging a community playbook. Now within both of those, we brought additional standards in and best practices that we wanna adopt based off the risk that we saw during find it. And then that brings us to our next webinar, so scale it. Next time, we'll put a playbook to work on contracts that are actively being negotiated. We'll see how those standards can help identify deviations, surface risk, provide guidance, and help reviewers address those issues while there's still an opportunity to negotiate. Alright. Thank you everyone for joining. Marissa, are there any questions that we should address? I don't see anyone in there. I think you covered it very well. Thank you, Tanya. Alright. Great. Alright. Thank you everyone for joining. And once again, that link to register for part three is in the chat. So go ahead and register, and we'll see you at the third part. Have a great day, everyone.