PegaWorld iNspire 2024: Supercharging Digital Transformation with Intelligent Master Data Automation

Join Infosys and Mondelez to know about how we harnessed the Pega systems to streamline and standardize Mondelez’s master data management (MDM) across various regions. Discover how Mondelez and Infosys jointly composed a Pega Cloud-based MDM platform, aptly named “Mozart”, which elevates operational efficiency to unprecedented levels by ensuring data quality, consistency, and governance across multiple domains.

Transcript:

- Good morning. Alright, my name is Sachin Batra and welcome to the breakout session on Supercharging Digital Transformation with Intelligent Master Data Automation. With me today, I have Srini.

- Thank you, Sachin. Good morning everyone. Thank you for joining our session today. I'm Srini Rajagiri. I'm the Director of Data Management Solutions at Mondelez International. We are excited to share our transformational journey today and how our solution integrated Infosys and Pega Systems helped us to achieve our goal.

- Thank you, Srini. All right, so let's get started for, I did not want to be between you and the lunch. Okay, so for starters, allow me to introduce who we are. We are Infosys, a leader in next-gen digital services. We are a company with $18.6 billion revenue with more than 300,000 employees worldwide from 56-plus nationalities, serving, give or take, about 2000 customers worldwide. In more than 40 plus years of our existence, we have had repeat business of about 95.1%, and we pride ourselves to be your champion. You heard yesterday about customer love, and it is a reflection of that love that you see here with 95% and more repeat business. Now, in 40-plus years of existence that I talked about, we have been consistently rated high, on the higher quadrants of best companies to work for, best employer, most valued IT services, brand, et cetera, so on and so forth, and also rated high in the sustainability initiatives and our ethics and values. I will quickly move on to our Pega practice. Now, our Pega practice formed about 16, 17 years ago is a dedicated team of about 3000 individuals. Consultants, architects, working closely with you on some of your projects, working for some of your projects. We have delivered collectively about 50-plus programs, large programs successfully. And you should shortly hear about one such program from Srini. Our Pega practice has been rated equally well by Pega itself and by the industry analysts, the latest being an award for customer service that we got yesterday, that was announced yesterday by Pega, and by industry analysts like Average, for example, last quarter, rated us as a leader in their peak service metrics. Now, as we work with Pega globally, as well as locally, what we realized is the customers like you all over the world, are wanting to do more with less. So at Infosys, at our DPA practice, we have a fluid DPA approach. The fluid DPA approach allows us to work with you and help you deliver four things: Speed, agility, scale, and using the features that we have called sense, analyze, respond, evolve. Now when we are delivering this to you, and you should again hear shortly from Srini, how we helped them achieve not only success, but at the cost of operational efficiency. How did you benefit in your operational efficiency as well as amplify your customer experience? So Srini, over to you.

- Thank you, Sachin. So before I go into digital transformation journey, I wanna quickly go through a test of who we are. Mondelez International is one of the largest snack companies in the world with a global net revenue of $36 billion in 2023. We have a total of 91,000 diverse and talented employees across the world. We have operations in 80 plus countries, and our delicious products are sold in more than 150 countries. 39% of the revenues of 2023 coming from emerging markets. And we do have like more than $55-plus million in charitable contributions in local communities. So if you see on the right side, net revenues based on the category, biscuit is about 49%, chocolate, 30%. We have gum and candy, 12%. Other category, 9%. The same thing why, geography where you have like all the regions that shows clearly our presence globally. And we do have some awards, prestigious awards from some companies. So we are a global snacking leader. We hold the number one global portion in biscuits, cookies, and crackers with a total net revenue of $17.6 billion in 2023, and with chocolate, $10.6 billion in 2023. And we are at number three, cakes and pastries and snack bars. We do have an iconic $1 billion brand such as Oreo, Milka, Cadbury, Reese's, Chips Ahoy!, and Clif. So Mondelez International, our purpose is to empower people to snack right. So we'll lead the future of snacking around the world by offering the right snack for the right moment, made the right way. That means like we are delivering a wide range of delicious products made with sustainable ingredients and packaging that consumers can feel good about. So our digital transformation journey, why it is important, right, why we had to start this. Four years ago, we did the ethos assessment, which is basically reviewing our all master data processes from end to end, from idea to market and what we call like seven steps of master data at Mondelez International, which is basically covering from product initiation all the way through product publication. And it involves lot of systems, lot of manual processes. As part of the assessment, what we learned, there was a value leak. Apart from value leak, we had data quality issues, data governance issues, and our processes are not harmonized across the regions, and as well as the technology was different in every region. So we had an opportunity to automate all this process and that was our main business case. And apart from that, as part of our mission 2030, we have a growth strategy. So we wanna increase our business, how we can streamline and automate our processes to our users. So we looked at different options, what can be done. We looked at the solutions that we have at Mondelez internally, and we decided to go ahead with Pega as it gives like a lot of options, not just the complex workflows and complex business rules, it comes with APIs and integrations. So our main scenario was orchestrating or connecting to multiple systems using Pega as an orchestration layer. So as part of this whole journey, what we did, we started with data collection process as phase one. We want to get everything at one place and start doing that data collection in Pega for different data domains across all the regions. And we wanna address standardization, harmonization, data quality issues, right? And streamline the operations and as well as address the data governance. Whenever the attribute is changing, we wanna make sure like right business person comes into the picture and approves that before it goes into that. So our Mosaic journey, we named our project as Mosaic, we started with, once we decided with Pega, we started with a proof of concept in Q1, 2021, and we picked the scenario, a complex scenario and we wanna make sure like Pega is the right solution and we wanna approve. So we picked the product creation scenario as well as the integrations with multiple systems in that proof of concept. So it took about three months to build that small application and give some contents to our business stakeholders. And we kept the users in that POC to make sure like what they're going to get in this, right? So we proved the POC and then we moved to Q2 2022. This is where Infosys comes into the picture. We shared our scope, this is what we wanna do, like this is the timeframe. Infosys came back with the overall legacy timeline, what works for us. in the next one year, right, from 2022. So during the first half of 2022, we took the opportunity to harmonize our processes across the regions. This is where we help Pega Business Consulting also consider the picture, and they helped us with process before Infosys takes that and delivers a complete project. So we started with two selective data domains, our customer and then vendors in a complex region where we had like different functions comes into the picture for that. So we strategically pick the data domains and we categorize all the data domains based on the complexity into different releases. So release one, release two, and release three. Release one, we kept all the complex ones and that gives a platform to roll out for the future ones quickly. So if you see in Q1 2023, we had three data domains go live. One is customer and the other one is product, which are very complex ones. And then Q3 we scaled up with a few other data domains, and Q4, I'm sorry, in Q3 you see like 18 go-lives, right? So release one, release two week, build a platform in such a way we can scale up and rollouts can happen quickly. So all these go-lives are, 24 go-lives, right, across all the four regions and talking about eight data domains. And Infosys also came up with a POD approach, project-oriented delivery approach where we could scale up or scale down the resources. There was a situation where we did, where we needed more resources to support the go-live. So that worked out very nicely with that approach. So a high-level view of Mondelez' application on Pega, I'm sure like everybody knows about layer cake approach here. So we build a Mondelez enterprise layer on the foundation layer and then we have our project Mosaic layer. Mondelez layer, we kept single sign-on as an example, right? You don't need to do that when we build new applications on top of this. And the Mosaic layer, where we kept like all the data domain, data models, which are specific to this. And then we build the four applications, implementation layer based on the region. And then we have data domains sitting on each region. So we see we have so many data domains sitting on this region, each region, and all these data domains in these regions, we did everything within the one-year-off timeline. All the goal was, so some of them are parallel, and in our scenario it's a global. We have resources, participated, the core team participated from 26 countries. So we are complex and our resources has spread across multiple regions. And apart from the data domains, so we did all this as part of Mosaic. If you see we have DocuSign and then customer end-to-end process. After that initial digital transformation journey, we continue to extend our process like end-to-end. We wanna make sure like sales comes into the picture. So this is where you could add the value real quick because you already have the application built layer cake. So for the end-to-end customer example, we onboarded all the pre-sales process into the process which we built like as part of Mosaic. And that overall process reduced the overall timeline for the sales from 16 days to six days in this scenario, which is about like 62% of improvement in the overall process. The other example I'm gonna give, MROs, which is maintenance, repair and operations. So we started using Pega, in fact we started this project in February this year. We went live with MROs globally about seven plans yesterday. We were able to quickly do this, unlock the business value in four months because we have this layer cake and data models, reusability functionality is there, right? So we delivered this within the four months of MRO solution. So how did we do this? So foundations build the future. So in order to deliver this huge transformation journey, we came up with our own teams, internal teams, how we structured the teams. product owners based on the region. It's not just enabling the product owners. We provided Pega trainings and the certification. They got the enough knowledge to support our transformation journey in the Pega. And then we have process owners who controls all the processes. That's again like regional-wise and global based on the data domains. And we do have regional semis who own the processes. They work closely with our business users and we have business users as well. Internal controls, just like any other project, we have internal controls comes into the picture, make sure like whatever we do in the systems implementation, make sure we follow that process. And we did some integrations as part of this digital transmission journey. Initially, the phase one is all about getting all the processes into Pega, data collection process. Not a lot of integration stress SAP systems. In this case we had integrations with DocuSign as an example. We had an ETL tool where we did some integrations for the internal control reports and then we use Pega Robot Manager to connect to external websites to collect some information, automate the process for the customer creation. So that's how we build the team to support this overall journey. And the strategic partnership and governance, you need to have a tight governance, not just internally, you need to have this partnership and the governance with your partners as well. So we have Infosys and Pega as Mondelez. We had regular connects on a monthly basis during this phase of the project. So we talk about like what are the barriers, right? What are the challenges to get the project on time and deliver on time, right? So this worked out very nicely and we do get like new stuff that we have within the Pega, right? All that sessions from Pega systems as well as Infosys. So this model and this governance, strong governance worked very well for us, and we are continuing this for the projects that we are currently doing. And the team that we have in this project, we had about like 230 people involved in this project. So it's a lot of people and these people are like all over the regions, right? So as I mentioned, we had people from 26 countries involved in this project, and partners, a lot of partners, 150-plus partners, resources involved in this journey. The next one, the success story. We deployed all these solutions globally. As I mentioned, we are truly global and our solutions are deployed in about 70 countries. And it's not just English, right? When you go to the certain markets, you need to translate that into the local language. So we use the translator as well to have the application in the local languages. And the adoption rate was like 100%. I have seen personally so many applications users did not like, or the design was not right, or either the change management. In our case, the adoption rate was 100%, obviously giving better experience. And we went live with more than 4,000 users globally for all the data domains, what we had, eight data domains across four regions. And we have improved SLS as well. The overall customer creation, if I take an example for Latin America, it used to take like 24 days for the data collection, all the processes, in the manual process, what they used to do. Now it's taking 10 days. It's a quite big improvement, which is about like 58% of improvement in the overall process. So there are some key benefits in the value, what you can unlock within the short time using the Pega, you know, Pega platform, what we had. So the journey ahead. So we did all this work, data collection process, within the Pega with limited integrations. What we're gonna be doing, we are gonna integrate with our ERP system and non-ERP system. There are some opportunities where we can orchestrate better, and do the integrations and remove some back office manual tasks. It's complete end to end, right, connecting to multiple systems. And we wanna look at the rules-based data quality and automation. So we did like, as part of the phase one, we did, but we wanna enhance more and automate furthermore when it comes to the business data quality rules. And the process mining is one thing. We started looking into that. So we build this, we've been using the system for the last 18 months. We wanna get better and we wanna see what opportunities we can implement and what else can, process mining, help us in this journey. So I think with this, it's my last slide. So I have a three minutes video that we put together after the last year's project. We'll play that please.

- [Narrator] There is no doubt that our Mondelez Vision 2030 is bold, and our Mondelez digital services organization embraces these aspirations through initiatives that bring tools, processes, and solutions to support growth for the future. Project Mozart is one of our MDS global initiatives launched during Q3 in 2022, focusing on data management orchestration processes. It aims to simplify the process of master data records creation such as customers, products, pricing and discounts. These processes are core to our daily operations and having these records created effectively and in timely manner is critical for our organization. We recently concluded Project Mozart phase one and a little over 4,000 active users in all four regions are launching data requests in a global standard platform called Pega. Pega offers realtime reporting, traceability, and rules to simplify data management processes. As we look back on our journey so far, we celebrate the accomplishments that can only be attributed to strong partnerships between business units and functions across Mondelez. It also highlights the importance of a laser focused approach to our objectives and the committed team working behind the scenes. The project was guided by principles of agile methodology and its behaviors which helped us to adapt and steer through the complexities to organizing close to 30 go-lives ranging across multiple data domains and regions within the agreed timeline. As we continue to stabilize our solution, we're starting to see tangible results. We have launched and processed thousand of requests, maintained our service level agreements, and business continuity has been kept throughout the rollouts. We have also garnered positive feedback from a substantial number of end users as well as identifying improvement opportunities that will keep us enhancing our solution. With over 1000 Bravos recognizing different functional participants across the team, it shows that although the journey was not easy, Project Mozart, phase one is delivering positive results. We are very humbled with the results and what Project Mozart has accomplished in this phase. We brought a solution to Mondelez that will continue to support our aspiration to digitize our processes. Overall, Project Mozart serves as a testament of Mondelez' commitment to innovation, strong data management, and its vision for the future. It reflects the company's readiness to embrace more challenges and opportunities on the horizon. In MDS, we're excited about the future as we seek to drive initiatives in the data management space that help to shape the future of Mondelez. We're ready for more.

- All right, so you heard that, 26-plus go-lives. How many data domains did we talk about? Eight?

- Eight data domains.

- Eight data domains. How many countries did you say?

- 70 plus.

- 70 plus countries. I mean you can just only imagine the complexity of it. But the basics don't change and that's the magic of it. So I wanna quickly touch upon some of the best practices. Srini already talked about it, but just to summarize, you remember when he started off, he said there was a clear end goal, not for just the whole big program, every single phase of it, the clear scope with a clear timeline, clear dependencies identified because it's not about us, it's about those 250 people who are involved on the program across so many countries. Everybody had to come together to deliver. And that was the magic. Having the right team, even if all of us have a diverse team across continents, countries, regions, having those right teams, having right governance with them and having those right processes, that's the backbone of the delivery. He already talked about standardizing and harmonizing the processes. That's a given. We have to do it. That's where you start. The thing that I want to touch upon is the digital first approach. Now what digital first approach gave us was at every step of the journey when we were solutionizing, you look at it from technology. How can I leverage technology to cut down the cost? How can I leverage technology to reduce the number of steps? How can I look at technology to eliminate a step? How can I make technology to make it without a user interaction? Do I really have to have my back office agent work on it or can it rules driven process manage it. That was the key. Or even the amount of data we were capturing in the forms from the user, the data collection exercise. Because we're talking about MDA master data. So there's a lot of data intensive work, but how are you capturing what you can capture without dependency on the user? Last but not the least, so many deployments successful only because there was a clear deployment approach with clear AC, clear governance, and very clear expectation setting and following of Pega's best practices, we never had a single rollback-till date. Alright, so I'm gonna end with a clear call out to the partnership that we had with Mondelez over the last 12-plus years that we have been working with Mondelez. This journey did not start yesterday. This journey on Pega was almost 12-plus years when we first started off incidentally with the customer services implementation, the same thing that I talked about for which we got a partner award yesterday, it started off with the customer services implementation and today we are partnering with Mondelez to help them implement some of the latest and the greatest gen AI features. I also want to call out to our Pega COE and CPG industry experts who have helped us become a leader in our Pega practice as well as in the CPG domain. And today because of that we are, we stand as a leader in the industry. I also want to take a moment to thank the Pega practice team that we have because now we have solutions built around ERP implementations and not just ERP implementations. How do you get the maximum benefit out of your ERP implementations? Because Pega can be used to build a surround system around ERP, we call it ERP Surround. And in fact, as we speak on the Pega's marketplace, we have solutions which talk about how you can maximize the benefits. So I encourage you all to go check out the Pega marketplace to see some of those solutions that we have built. With that, I think we'll come to the end of today's presentation. Happy to take any questions or thoughts from anyone in the audience. You may want to use the speaker. Yeah, thank you.

- [Speaker] Yeah, thank you. It is a really nice presentation and a great work. I can imagine like how much efforts it could have been gone behind the scene. So just wondering like, you know, this is, you are using Pega as a presentation layer, like in a, you know, intake process for , it's not a system of records.

- That is good.

- [Speaker] Okay. And then the follow up question, what I have is, you know, this is all, one aspect of digital transformation is you are bringing from a legacy process whatever you might have to, you know, more transparent way and more governance you baked into it, and you know, of course I think on the downstream ERP systems, enterprise systems, it might be consuming those data which is harmonized. But how do you handle the change management from a prospect of master data organization? If you can give little insight, that would be helpful.

- So change management was a big thing for us in this project because of our four regions, so many countries. So what we did, like we had one change manager taking care of everything and we strategically put like different change managers based on the region and based on the data domains, right? So based on the different functions, we have trained the trainers based on the region. This person trained the trainers and they will try. So we had like about 30 plus different training sessions and not to mention the language, local language, right? We had like about nine languages where we need to translate all the material into local language as well. So the change management, you can build any solution, right? If there is no change management, that's where things get dropped. So we did like strategically global and regional and training the trainers and the business can train their people also, right? So that's a model we use for the change management.

- [Speaker] Yeah, thank you. And in the downstream, like do you have the, how many enterprise systems you have? Is it more complex in nature? Like is it one enterprise data system you're dealing with, whatever the harmonized data you're feeding back?

- So coming to harmonization or basically it goes with the data domain. If you look at the customer as an example, when you create a customer, you look for the duplicate. So that functionality we enable within the Pega, and there is no direct interaction with ERP but there is a manual work-around. like where the users go and check with the back office. So that's where the automation, if somebody finds that customer before they create, it triggers it, it gives an alert, a customer is already there, right? It should not create. So same thing with MROs also. The spare part is already there. You don't want to duplicate that. So we have all that control and all that functionality built within the Pega.

- [Speaker] Got it. Thank you very much.

- And then our ambition to automate that process as we go into the phase two.

- [Speaker] Yeah. One final question.

- Sure, sure.

- [Speaker] I saw that, you know, you have also mentioned, I think it's for vendor master, customer master, one of your slides you use the RPA technology. Is it Pega RPA you used or something else?

- So we use, we have two RPAs in our overall ecosystem, what we used. Once the request has been reviewed and approved within the Pega, the data goes to our back office and they take the data and they create that data in our ERP system. That's a different RPA. That is automation anywhere we use. So they use that, you know, to reduce the manual work within the ERP system, that is one thing. And the other thing, what we did, we used Pega's Robot manager. This is especially collecting the data from external websites. We wanna automate that process. This is part of the customer create presales process, and that's one of the scenarios where we use the Pega one, read some PDFs, get the data, automate, and pass that to a different case as an input.

- [Speaker] Got it. Thank you very much. Thank you sir.

- Thank you.

- [Speaker] Hey, gentlemen, I've got a question about, you had your different domains, you focused on the most complicated one first. How did you identify complicated data and what was your strategy to deal with that?

- So complex data domain, it's not about the data, the functions that get involved and the functions that, so many touch points that we have in that overall data creation. If you see again, the same example, customer depends on the region. We have seven to eight different functions comes into the picture, and we know the criticality, we need to get the customer created in order to get the revenue in-house, right? You need the customers to be set up. That is one complex thing. Another data domain, I would say like product and bill of materials, you need to have the product-ready set up with right pricing, right attributes, and bill of materials also. So it's not purely based on the data, it's about the complexity, and we already have people who know that complexity within our organization, right? So and the volume also, right? If the volume is more, customer creation volume in some of the regions are huge, right? We wanna prioritize that and where we can unlock the value quickly based on the, it's not just a complexity. We wanna see like where we are going to get benefit quickly.

- [Speaker] So based on your recommend experience, right? I know you said about two domains and then probably you're integrating with more, right? So how many like interfacing applications would you recommend for a master data management? What if we have like about just giving a number, 30 or 40, right? So do you recommend that we use Pega integration for that or do you recommend something else?

- So it all depends on case to case, right? If you have, you can have a number of applications, but if you don't have like right governance, right data quality checks at the time of creation, you're gonna end up seeing all these issues later on in other downstream systems, right? If you have those controls there, then you can look at it. If not, this comes as an orchestration layer where you can put all the data workflows, data quality checks, and tie business rules before the data flows into the transom systems.

- [Speaker] But will Pega be the place where you hold the data or do we need to send that data to like a data warehouse or something like that?

- So in our case, Pega is not the source of truth. We use it as an orchestration layer and data collection, all those validations. We have our own ERP system and other non-ERP systems. So the data goes to ERP and we kept the source of growth as ERP system, and we do have some reporting systems where the data flows to those systems for reporting.

- Can I encourage you to, yeah, sure.

- [Speaker] It's a follow up question. So for the reporting, do you guys use BIX or how do you get the data from Pega?

- So we use BIX. Pega is not a reporting tool, right? It's not meant for it. So we had so many requests for the reporting, especially tag turnaround time, where the request is in the overall process. So we use the BIX to extract all the data and send it to Tableau. That's where we have all the reporting.

- [Speaker] Okay, that's fine. Thank you. And you know, you are not sending the data to data lakes or any-

- So that's part of the phase two where we wanna get all the data into our existing data lakes. We have a a Google platform where we have all the data comes into one place for reporting. So there are some opportunities where we can send all this data for reporting. So it's gonna go to any ERP systems. Apart from that, we want keep it in the reporting system as well.

- [Speaker] So once you create the master data onto one of your ERP systems or non-ERP, like you get the feedback from the bot and that's how you close the case?

- Correct. Correct.

- [Speaker] Okay, that makes sense. Thank you.

- You wanna close the loop. Once we get the record created, you wanna make sure like that gets updated in Pega, then we send the data to reporting to .

- [Speaker] Thank you.

- Yeah.

- Okay. Any other questions? Well, thank you all for joining the session. Thank you everyone.