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So with that, I'll move forward. And and this is, remember, this is very high level AI implementation, what it would look like for a sales order entry road map starting first though with the use cases versus effort, this is what it would really look like. And again, this is really highlighting those three to five. I have the sales order entry one bolded here, but it's really listing out what are the different use cases you're looking at. So here I've listed sales order entry, prevent machine downtime and financial digital assistant. And what you're going to see is a quick description of what you're, what you're really trying to accomplish there. And then the ultimate goal is also in that third column. And now I try to categorize these. So a few things which categorizes like a quick win, which we stress a lot about our AI journey is it's a quick win to get executive buy in or upper level management buy in or even lower management buy in just to get AI into your business to produce quick ROI. That's one.
But then as you can see, that third one's a financial digital system. It takes a lot more heavy lifting, a lot more strategic investments, maybe more discovery calls, maybe more data and security things that might need to go on there. It just really depends on, on the use case of how we kind of categorize those. And then lastly, you'll just see a quick little bar of just the value versus level of effort. So we're gonna focus on that first one because obviously document sales order entry from PDF and the JD Edwards is, is a big, big value add as we've heard a lot from customers and the effort's pretty low. If you've seen there's actually a a session we did yesterday on document understanding and if you definitely check that out because if you can see how seamless it is, especially using OCI services out of that that information in. So anyways, we're gonna move forward with that one. Just wanted to give some background on, you know, the sales order entry as that will be the example throughout the whole presentation here.

Phase Approach

So moving forward, just looking at a high level like phase approach, what it would look like. So for example, we start with and really this is going back to what's the future? What would the future look like? So we'll start with that top 1. So that's really phase one, the document extraction. So converting unstructured PDFs in the JD Edwards data, so actually uploading those PDFs in the JD Edwards, that's phase one. That's the automation piece predicting patterns. So document understanding will start to understand product availability, discounts from customers, right? Maybe some price breaks, some different things might change. So it will start to understand the customer's history and what not and start to make insights off of that and provide some predictability there after automation. And then lastly, again, it's just eventually where we want to go. So we want to give you guys an end to end order entry, right? Real time communication with customers such as order confirmation, order status. So having the ability to do that extended out to a customer or even building out a digital assistant. Again, we want to build off of these AI solutions. They only just have one centralized thing. You don't just need to build a document understanding tool. We can start to connect these different things. But again, just really just showing an implementation road map where we want to take it. It's not just a one-time solution here. So just wanted to highlight that for the phase approach.

Milestones

Next we'll go in the milestones. So with the milestones, again, it would be a more in-depth timeline when we build out an implementation road map, but really broke it down to these three things. So really the planning, right? So the ability to train the existing sales order documents, hammering PDF, whatnot, whatever you send in the implementation, still automate the reading extraction of a few. So with a few, then move on to more and then get feedback from the initial end users. So this is the human in the loop. This is when we start to bring end users into the solution and that's when we start permitting that change management as well and then eventually scale. So roll out more document automation to other departments. You saw the milestone phases before we focused distinctly on document on the sales order entry. But with the scaling, we could even start to scale if we want to just stick with automation, the different, you know, upload contracts to a database, expense reports, invoices, stuff like that. So, yeah, so that's, that's the milestones again, will be more detailed in the implementation, but you'll get a good understanding of what it would look like here and what we would provide as well.

Data Readiness 

With that, we're moving the data readiness. And before I really get into this one, it's very high level.
I wanted to reference getting your data AI ready, preparing JD Edwards Master Data for success was a session that was presented yesterday by Manuel Naira and Mo Shujaat. And I encourage you guys to go watch that one because that's really the beginning of this. I don't have enough time to go over it at the highest level. So I want you guys to really 'cause that's kind of your starting point for the data readiness where you're at with implementing a certain process AI solution that we're talking about today. But going back to the slide here, so just quick example, current sales order entry. So 80% would come in from a standard PDF form. In this example, 15% handwritten written 5% just come in, in the e-mail, just detailed e-mail unstructured the current sales order attributes and, and there would be more, but those are the current ones that would be listed. Just give an example, we've listed the attributes that would be involved in this.  And then historical sales orders in the P4210 believe data cleansing valid. So this is what you know with the customer. We checked the data. We've, we've done the data cleanse and data validation of the, the sales order entry. And we believe that data validation and cleansing may need to be done 'cause this will enhance future predictability for customers that we talked about in that Phase 2 when we were talking about the phase approaches. So again, just an example of what potentially may come up in that section.

Security Readiness 

Next is security readiness. And again, there's too many. We have a whole security track during AI week. I encourage you guys to go back, rewatch those. Those are very important because security is a big question that comes up when we talk about AI week. So I encourage you guys to go back, watch those sessions. But this is a high level just kind of how it works for a sales order entry. You'll have JD Edwards role-based security for them that was already set up. Most users are trained on current manual sales orders. I'll be with the document understanding security. The OCI side need to set up secure data transfer from CSR e-mail folder to OCI storage buckets. That's just where they house. We would house the the sales orders that would come in and then create and then encryption to transfer sales order information from OCI document understanding. So again, and then encryption's important mixing OCI with JD Edwards. So talk about that and, and, and what we need to do is probably that security readiness before implementing a solution.

Technical Requirements 

And then next would just be the technical requirements. So this is just high-level technical requirements, right? So you have the OCI services on the left, you have the JD tools on the right. So again, just talking about OCI buckets. Document understanding autonomous data warehouse is there. You might use it. You might not use it though. So that's not that's not one that that's an iffy one that could be thrown in. It's an optional one. And then JD Edwards tools. So JD Edwards orchestrations form extension Judy OS actually built this out. So again, just an example of what we would show there. And then we would we would also have a technical requirements. Well, and what that would kind of look like. So sales order would come in via an e-mail, it would go to an OCI bucket, and then once it goes to that OCI bucket, it would be sent to document under OCI document understanding to be trained. And then once that has been trained, it would then get the upload into JD Edwards of P4210.

Human in the Loop

And now I wanted to bring back up again the importance of the change management adoption, the human in the loop. So you have the CSR validation as a sales order comes in, they're keeping tracks and notified via e-mail of the process, right? And even when it gets to the JD Edwards, as you start to train the model, we need the help from the CSRS, especially, you know, look at this example, the historical data from this example, it was not up to par yet. We still need them to help validate and train the model and make sure that, you know, it's getting better and better and, and we can make this process more automated. So human in the loop is obviously very important. It will, you know, it'd be a part of a lot of our technical flows when they get built out in the implementation road map roles and responsibilities again, just listed high-level project manager, you know, obviously important for building out, you know, important for keeping track and, and making sure that the ad solutions build out correctly, right customer service Rep, they really help the organization with the sales orders that are being trained. They know what's coming in, what's going out, what's really coming in. So they'll be a part of that. They kind of understand the flow there. And then really the business analyst, if there's someone that's more involved with JD Edwards really understand the whole end-to-end process. It's very important when implementing this specific solution. And then also the JD Edwards developer again at ERP Suites who want to partner with us, we do have JD Edwards developers that will build out the orchestrations and really embed the tool inside of JD Edwards in the P4210 and then the OCI developer. So that's the one who really trains the models right, gets the handwritten models, PD, FS, what have you inside of OCI and actually trains them.
And then that's me on the end. Just the AI advisor, just make sure everything runs smoothly. So I'm just there fly on the wall, but also helping everyone, educating when see fit and, and helping our team as well with the process and understanding the business requirements. So just thought it'd be fun to just add me on the corner there.

Risk Management 

Risk management, again, huge one that comes up. There is definitely going to be more that come up other than these 4, but the big one, right? Data quality. And again, encourage, encourage, encourage you to watch all the data, all the data and infrastructure sessions that have happened today, all the security ones, 'cause there will be more that, that I have not covered here. But really risk management, right? So data quality and, and it's really just about the kind of on the right there.
What you see is, is what we will aim to strive for and it's building robust preprocessing and human in the loop checks throughout the training for different sales order formats and structures. And then you'll see compliance and regulatory as well, right, Continuously monitoring the sales order entry, making sure they're correct, making sure there's role-based security. That's a big one before even implementing the solution, making sure only certain people have access to certain tables, especially when you start to build it out, it's uploading expense reports or other areas of the business that you can think of invoices. It's just very important that securities in line there and, and the compliance there and then the big one, right, security risk and then encryption. You know, we're working with OCI tools going to sorry, OCI tools going straight into JD Edwards, right? OCI has end-to-end encryption. The JD Edwards has its own security. How do those migrate together? How can we? And again, it's, it's something that's why we use OCI services. It's something that happens very seamlessly. But just making sure that's all good is, is another risk management factor.
And then again, continuous training, right? As new data changes, as models update, continuously adding inputs, you know, there might be different forms that come in different structured data.
You know, as we start to implement a solution, we might use a few sales order documents at the beginning. And as we start to make them and we start to add more and they might be different formats, how can we build this out and make it more streamlined and still having that human in the loop as well to help with the training. So there's just a few. Again, encourage you to watch the data and security sessions as well. Those will provide more information.

Change Management and Adoption

And then this is the big one. This is the one I really wanted to get to is, is really change management and adoption because you're going to get the most push back and you might not just depends where your business is with implementing AI. I talked about earlier, you know, you could be, you know, on the cusp of implementing AI, You could just be getting started. Just really depends where you are on your specific AI journey. But change management and adoption, it's really all about just kind of these five phases, right? So the first one's planning and assessment. So really understanding where your users are that change is coming and really telling them you know, how to really plan for it. Who needs to know when they need to know it. Just really telling them how this process will change and how this AI solution, if, especially if they're immediately involved in their day-to-day operations, how this will enhance the jobs and make them better. And then design and prototype and really have the end users and the ones involved in this be a part of the testing and the prototyping and the designing of this solution. Again, I mentioned before, especially the business analysts, a part of the sales order process. They know it in and out. They're going to understand how the process works. So definitely need them to test it, especially if you're working with us to understand the full process of how you how your process works, because not every business is the same. And then throw it again is deployment and testing. Get it in their hands, get in the end users hands, start having them test to be the Super users that we like to call it, right? And communicate, you know, the road map, the timeline again, keep iterating the benefit of solutions, also important. And then definitely the deployment, right? Real-time support. Again, our team would help with the support, obviously will be ongoing support for you guys promoting usability, right?  Even though the solution's in there right away, we've seen it before. Not everyone's going to be accustomed to it. Not everybody's going to be 100% into it. Really try to promote usability, address resistance in in in patterns and how to do that is very important. And then post go live support. So that really references, you know, start to reference the ROI. How's it really helping them start to create their presentations, have those discussions right and continuously check on end users on the solution, send out surveys. Are they really liking the solution? How's it going? And yeah, are they still involved with the process? Are they still do they still feel valued? Do they still feel like the solution was made for them and they can work alongside of it is also very important.