Accelerating Insights, Agility, and Value with SAP Data & Analytics

In this episode of the 'Digital Transformation Unleashed PwC and SAP in Action' vodcast series, Hamilton Chock, PwC’s U.S. managing director for alliances, engages with Frank Rinaldi, the head of PwC's data and analytics practice. They delve into the importance and evolution of data analytics in business transformation, focusing on how organizations can leverage SAP tools to stay agile and competitive. Rinaldi shares his extensive experience in ERP-focused transformations, emphasizing the need for agility in analytics to rapidly adapt to changing business queries. The conversation covers the 'Leading with Insights' solution that incorporates SAP's Business Technology Platform (BTP) for advancing data analytics and integrated planning capabilities. They also discuss the application of Generative AI in improving data quality and forecasting, alongside SAP's suite of data analytics products and how they can be effectively utilized in diverse business environments. The podcast concludes with strategic advice on embarking on a data analytics journey, underscoring the significance of selecting the right data sets, platforms, and governance models to ensure the reliability and agility of analytics solutions.

00:00 Welcome and Introduction to the Digital Transformation Unleashed PwC and SAP in Action Series

00:45 Exploring the Role and Evolution of Data Analytics

02:02 The Power of Agility in Data Analytics

03:34 Introducing Leading with Insights: A Data Warehouse Solution

04:14 The Impact of SAP's Business Technology Platform on Analytics

05:59 Harnessing Gen AI for Enhanced Data Insights

08:32 SAP's Comprehensive Suite of Data Analytics Solutions

10:51 Top Considerations for Embarking on a Data Analytics Strategy

12:59 The Value of SAP's Industry-Specific Solutions and Closing Thoughts

#PwC #SAP

Transcript

Accelerating Insights, Agility, and Value with SAP Data & Analytics

​[00:00:00] 

Hamilton Chock: Thank you everybody for joining. This is Hamilton Chock and I serve as a PwC's U. S. managing director responsible for our Alliance here. And we're going to be continuing our vodcast series entitled digital future unlocked with PPC and SAP, where we bring some of the most foremost solutions experts to discuss [00:01:00] a wide array of SAP topics.

As we get into the session here, I'm going to be introducing our special guest, Frank Rinaldi, who leads our data and analytics team. Practice. And so we're going to be talking a little bit about data and analytics today. Frank I'm going to ask you a couple of questions during this vodcast series.

And I'd like to just kind of get into it. So, again, thanks again for joining. Frank first and foremost for, for everybody who's listening or viewing today's session let's talk about your role and responsibility here at PWC.

Frank Rinaldi: Sure. Thank you, Hamilton. So, you know, I have been in the data analytics space now, mostly centered on ERP focused transformations for 23 years. I've been at the firm for 15. I've worked for SAP. I've worked for clients. So typically I love to bring different viewpoints as we, as we work on different engagements and I've worked for very small companies doing transformation projects and hundreds of millions that work for very [00:02:00] large companies and hundreds of billions in revenue.

So I love to bring those viewpoints from a data analytics standpoint. As you know, Hamilton, this area continues to evolve every couple years right? It feels like if you take your eye off and come back to it you know, the entire space has changed in terms of the technology in terms of how businesses are trying to gain a competitive advantage.

So looking forward to talk to you about that today, especially in the mid market where I think companies are particularly challenged in terms of Trying to stay working with standard SAP tools from data analytics perspective, but also staying there, also be agile and trying to be continual innovators and leaders in their space so they can compete and grow.

You

Hamilton Chock: Yeah, and in fact, one of the things that we want to talk about today, because you talked about competitive advantage. And you often hear that word agility and the role that plays in giving organizations that competitive advantage. So let's talk about bringing it back home to analytics. How does [00:03:00] analytics enable in your mind agility?

Frank Rinaldi: know, I, I think that it's, it's funny a lot of times when I do these transformation programs, you know, we do a reporting strategy and I think we're going to have the answer at the end of that strategy. The reality is for most companies, when you talk to their executives, It's really their questions.

They're asking are changing quarter by quarter, right? You know, is my demand forecast? Correct? How is my demand for my products changing? What are the products that give me the best margin? I think that the key to a strong analytic solution is being able to. rapidly change the question you're asking and get results quickly and accurately.

So I think as we work with customers in the space and we work for transforming their organizations we really look to figure out not just what do they answer the questions are typically asking 80 percent of the time, but for the 20 percent that are unknown, how do we build a solution that makes it quicker and faster to get results for questions we may not have [00:04:00] anticipated.

Hamilton Chock: And so when you, when you think about getting answered to those questions, I know we promote a lot of different topics in the market, especially right analytics, but there's a specific offering that we have today. You know, leading with insights, you want to talk about it at a high level, what that is.

Frank Rinaldi: Yeah, absolutely. You know, leading with insights is a data warehouse focused solution where, we're giving you a reporting solution with Pre packaged extractors and content both considering your old investment legacy systems, as well as your new investment in S4 and packing that up so that you have the data and the models to ask, not just those 80 percent of questions, you know.

Ideally, so that you can quickly get to the other 20 percent of information. We have it there in the package solution. You can quickly pull it and form that up and get answers to those questions quickly.

Hamilton Chock: One of the things that I always think about when I think of analytics, we always think about the role analytics plays, especially when you're looking [00:05:00] at SAP BTP or the business technology platform. So talk to me about some of the more detailed, maybe integrated planning analytics that are incorporated into the offering today.

Frank Rinaldi: Sure. You know, our leading with insights platform is all built on BTP. Whether that's HANA or data sphere underneath and SAC on top it's an integrated solution all enabled by BTP. And again that, if you're, even if, The great thing there is that when you go live and your S4 system is focused on processing transaction and making sure your company is run efficiently, that BTP platform is there so you can more easily customize it without worrying about impacting the S4 system.

And also giving you tools. that are integrating and implementing some of the latest and greatest. You talked about integrated planning Hamilton, that's one of the great things about BTP is that you can grab data from all over the place, right? If you're creating an integrated plan between your finance and supply chain, some of your supply chain may not be fully on SAP.[00:06:00] 

BTP is a place where you can pull that information together and then, as all of us are looking at the new tools out there, especially as SAP and other vendors are embedding AI into the tool sets, you can look to use some of the latest AI tools. Through S. A. C. To come up with those integrated plans and also create forward looking demand forecasts.

And adjust those as you want to play with different variables in that demand forecasting cycle again, that's something that A. I. Is evolving in that space is the models of all that. That's something that we're seeing our clients do more and more as you're trying to get the value of A. I. Into those integrated plans with multiple data sets.

Hamilton Chock: I'm smiling as you bring that up because Jenny, I is buzzword now that you're here everywhere, right? You can't engage in a conversation, any conversation without hearing Jenny. I'm so frank, tell me about how can clients leverage Jenny in your mind to make sense of their data? And gain to gain these valuable insights that you've been referring to.[00:07:00] 

Frank Rinaldi: Well, I wish I had all the answers and hopefully I would have bought all these AI companies years a year ago and been a billionaire now. But I would tell you that everyone is rapidly experimenting. And in a PwC, I think we do a lot of our experiments by line of business. To better understand what worked for different parts of the business landscape I know in data analytics, that's how we look at things.

And if I think about, for SAP customers, very often the line business we most focus on is this is the CFO, right? You mentioned integrated planning. We look a lot at, Where can, where are the inefficiencies in the planning process in terms of where is there bad data quality and how do we better detect that?

How do we look at easier ways to plan without having to go through the manual process of asking people what they think and then integrating that into an improved plan going forward? I think that those areas of actually looking at data quality and actually generating the plan automatically are the two places that we are looking to use Gen [00:08:00] AI more and more.

Data quality is a place where, as you look at how these large language models are being used to learn, or even again, people are lumping down machine learning into AI, but I see as another piece of it they're looking at using those different types of models to better look at the data quality coming in, more proactively identifying where there's errors, and then either or.

Direct noting those errors and making sure that executives who are looking at the results of data sets with those errors understand them or proactively trying to fix it based on previous information fixes that have come into the system. And that takes model training and better prompting. We are working on that.

On the other side, in terms of generating that plan, as I mentioned before, a lot of the tools SAP is using is actually will automatically generate the demand curve whether that's, or that planning curve and then you can actually prompt the Gen AI tool, in this case, I think SAP calls it, to change what it comes up with based on different variables, right?

So I think those are [00:09:00] something that, especially in this space, this office of CFO, are things that we're testing out and trying to prove out more as the models get more sophisticated and more accurate in their predictions. Absolutely.

Hamilton Chock: And so Frank, you talked about the tools that SAP is using. So we all know, that SAP has a pretty robust suite of data analytics products, talk to me about those those solutions and how clients can. Really capture the value of those solutions in their own environments today.

And then as they think about us for how they can really tap into those benefits even further.

Frank Rinaldi: Absolutely. I think a common misperception one of the things challenges clients have is when they do their S4 projects, they want to make their system as efficient as possible. And a lot of times they try to get everything out of S4. The reality of the world is though S4 is not going to have everything.

Typically you'll have a separate HR system. You'll have a separate corporate planning system from the FPA department at a minimum. And then many times you may have multiple [00:10:00] ERP solutions. Not just that you might be trying to consolidate maybe small instances of S. A. P. And so you need one place to bring all that data together.

I think that's where, S. A. P. S. Vision. They have their visualization layer. S. A. P. Analytics cloud, which has been out there for almost 10 years now is becoming a very, solid reporting platform is successful business objects. And as a competitor to other tools out there, like power bi or like tableau.

And then on the back end, you've got their data sphere platform, which they have been. It's a cloud first platform, cloud first data warehouse. So competes with the likes of like snowflakes or even data bricks or hyperscalers that are out there to I think one of the best things about using SAP's platform is that it comes with pre delivered connectors and pre delivered content that you can start from that quite honestly their competitors just don't have or not to the depth of industry specificity that clients expect when they implement S4.

So we're seeing a lot of small and mid sized companies really go to buy [00:11:00] that full SAP stack. Again, it's all enabled by BTP. As far as the licensing agreement, it's easy to use and for large enterprise clients. We still see finance still leaning towards using data sphere and SAC is their source of truth for finance, but they may be using other solutions that like SA partners with Databricks, for example where they may have more voluminous enterprise data that they need to merge that SAP data and do it in a separate place.

Hamilton Chock: So I think so thank you. But I think as we start to think about how we guide our clients, Frank what would you say are maybe the top three considerations if a client is looking to embark on a data analytics strategy? What should it be about? Like when you talk to them, Hey, these three things are maybe where you would start, what would that be in your mind?

Frank Rinaldi: And it's a great question, Hamilton. And if I think back to our comments, what we're starting to earlier [00:12:00] about agility, right? I think the end result should be client should be building an actual platform. And to do that one, I think you need to think about the sets of data that you're going to want to be analyzing to answer the questions.

Yes, you've got your standard finance questions around your external financials. So it was like, what was my net sales? What was my gross sales? What was profitability? But you may be also asking very granular questions about who are my top customers? What does that look like across my different order cache systems, for example?

So one, you want to make sure you've got all that you've got, you're pulling the right data in the same place. Two, you want to make sure that you have a consistent platform with, I would say, tool sets that naturally work together and make it easy for your developers to quickly turn around solutions.

And again, that's where we talked about Datasphere and SAC as being a really nice tool set that you can implement using BTP. And then lastly, I would really think about governance around how you're going to put these pieces together and make sure that you're giving a consistent source of truth back to the [00:13:00] business.

That can be a very light touch, but making sure that you have clear custodians who are looking over ensuring that the, the data and the relevant KPIs you're bringing out are correct and continue to be correct going forward. I think does goes a long way to making sure that you're building trust.

And when you ask for those agile answers, you actually trust what you're getting back versus thinking that it's something that's haphazard and that you don't really, it's not worth. The time that people put into it,

Hamilton Chock: Excellent. Excellent. Frank ton of experience. We can certainly tell by your background and the way in which you've answered some of these questions. So thank you so much for being with us here today. If there's that one, maybe aha moment that a client might have after Implement team.

And SAP data analytics solution based on your experience, any feedback or, or any you know, experiences where you might be able to say this is what they, they really kind of gathered from that, that implementation.

Frank Rinaldi: I'll tell you, [00:14:00] Hamilton, you know, I think the business just wants the answers, right? I will tell you from a technical perspective though sometimes our clients, especially those that chose to go the non SAP route, given the explosion of tools out there in the past five to 10 years I think they took for granted a lot of the prebuilt content that SAP put in, whether it's currency conversions, whether it's unit conversions, when you're looking at your different materials.

And looking like in the consumer package industry, right? No one buys an individual candy bar. If you're a candy manufacturer, you back, you buy packages or you buy whole units that you stand up in a in a retail store. Again, a lot of these guys who build these solutions, don't think about that.

When SAP thinks about it, they think about and they look at that catalog and that deep industry expertise and you get that out of the box. I think companies spend a lot of time trying to recreate that in cool developer kits from companies that have a really good marketing budget, but really don't know these companies, industries.

So again, [00:15:00] I think that there's a lot of be value that you get with SA. Industry specific solutions. They do a great job building them through DNA solutions. They don't always do a great job marketing it though. And I think that's definitely something that a lot of times companies, you know, maybe realize after the fact that man, they had, they gone full stack SAP, they would have been really able to accelerate time to value for those SAP generate insights a lot quicker than if they went with a completely custom solution.

Hamilton Chock: Fantastic. All right, Frank. Well, Hey thank you for taking the time out of your day to join us. And for those of you who are viewing today, appreciate you jumping in and listening to us, if you'd like to learn a little bit more information, Please reach out, give us a call, send us an email, or you can take a look at our website at pbc.

com. Thank you, everyone.

Frank Rinaldi: Thanks folks.

Hamilton Chock: Bye bye.