Salesforce, Inc. (CRM) Earnings Call Transcript & Summary

First manufacturing webinar on AI-Powered Transformation: Unlocking Manufacturing Excellence with Tableau. To introduce myself, I'm Ruchira Chakraborty. I'm a Senior Account Executive managing the Tableau manufacturing in the West. And I have with me Prashant Keshri, who is an SME from the Solution Engineering team. Quickly to take you through the agenda for today. Number one, we are going to delve deeper into what is the importance of analytics in manufacturing and what are some of the key industry trends that are driving this. Number two would be looking at a product demonstration and the relevant businesses use cases. So what is Industry 4.0? So steam propelled the first original industrial revolution. Electricity powered the second. And preliminary automation and machinery engineered the third. Now cyber physical systems or intelligent computers are now shaping the fourth industrial revolution. So there are 4 foundational types of disruptive technologies that can be applied all along the value chain for Industry 4.0. Number one in this list is Connectivity, Data and Computational Power. Number two, Analytics and Intelligence. The third is Human Machine Interaction, which includes your Robotics and Automation. The fourth is Advanced Engineering, which includes additive manufacturing such as 3D Printing, Renewable Energy and Nanoparticles. So while 39% of the industry have implemented a nerve center and 25% are fast-tracking certain automation programs, what is hindering the widespread adoption of Industry 4.0? You've seen that 45% mentioned that they struggle with sudden material shortages. 41% face a lot of fluctuation in demand with steep drops. And 30% have also witnessed worker unavailability or the unavailability of skilled labor. So let me take you through something which is the World Economic Forum's Global Lighthouse Network. This is inspiring manufacturers to leverage Industry 4.0 and develop, replicate and scale innovations in manufacturing. So lighthouses can be built practically anywhere by small or big companies in both developed and developing economies and greenfield and brownfield locations. While we have 21 new manufacturers who have joined the network in late 2023, a total of 153 factories are now engaged in this network. And they have all implemented advanced manufacturing technologies that result in a boost in productivity, sustainability and supply chain resiliency. In this list from India, you will see companies such as Dr. Reddy's Laboratories and CEAT who are also invested with us, leading this journey. And I would love to take you through how they have achieved this or what are some of the key areas where they have seen growth. So coming to Dr. Reddy's Laboratories. They were facing severe business challenges from price erosion. And this is a 25-year-old site in Hyderabad that embarked on this large-scale digitalization project. They were wanting to grow and sustain in the generics pharma market. So this site deployed over 40 fourth industrial revolution use cases by operating in garage mode and leveraging IIoT and democratized the platform for advanced analytics. So if you look at on the right side, there are a couple of very significant use cases that can be relevant to most of us. Number one is, they faced a drop of 52% in their overall quality deviations by implementing an IoT-enabled manufacturing quality management. They also looked at lowering their energy consumption by 20% with real-time asset performance monitoring and visualization. Some of the other use cases are also here for you to see. And these double-digit improvements is what landed them in the World Economic Forum Lighthouse list. The second customer that I'd love to talk about is CEAT with their Halol plant in Indore. Here again, some of the key things that they were looking at is reducing their overall cycle time, which was a huge bottleneck, and they did this with a cycle time optimization at their mixer. The second thing that they also looked at is reducing their overall total scrap by 46% and reducing their wastage thereby. This is with a digitally enabled scrap monitoring with in-built root cause analyzers. So some of these are definitely very inspirational and tell the story of how analytics can really change the game when it comes to Industry 4.0. Now coming to one more area, which is how is business differentiating itself today in terms of the customer experience. So there is a huge shift in the industry from a product-centric to a customer-centric business model. And many of the manufacturers today are differentiating this based on customer experience as opposed to what was earlier mainly product differentiation. So what are some of the key things that govern the shift? So product-centric organizations invest significant resources in continuously improving their ability to build, develop and innovate on their products. They focus on internal operations, the customer relationship is primarily owned by the distributors, and sales is very transactional with minimal customer engagement. And product connectivity is also something that has been known to be limited. While it is still something that would continue to stay relevant and important, operational excellence has now become table stakes in the market. As a result, now, to differentiate themselves in today's marketplace, manufacturers must also put the customer at the center of what they do and focus on continuously improving the complete end-to-end customer experience. So what are some of the key characteristics of customer-focused organizations? They focus on the entire holistic customer experience. And this customer relationship now has joint ownership amongst all the stakeholders in this relationship. Sales teams don't just look at sales transactionally anymore, but they look to maximize the lifetime customer value that is portrayed. And customer engagement is no more just at the time of sale, but it's an ongoing relationship. And the product and operations have now deeply connected them ever. So Salesforce has been working with manufacturing customers for over 22 years, and we are very proud of some of the trusted relationships that we've built over time. Today, I'd like to introduce to you some of the top solutions we have for manufacturers. And we are going to cover a range of topics that help solve some of these top-of-the-mind challenges that we see in the industry. For example, how do I manage my distributor, customer and end customer marketing and communications? How can I plan my volume, my pricing and my delivery execution? Can I get insight into my demand forecasting? Can I get insights into how my raw material prices will fluctuate? And how will that ultimately impact every other aspect of my manufacturing downstream processes? How can I maximize my ability to sell my products online? Which are my most profitable products? Which are not doing so well? And how can I improve my agility with data? I'm sure some of these questions deeply resonate with you, if not all. And in your business, you must be facing some or more such questions. Which of these are the highest priority for you, we would love to have a discussion at some point. And you are not alone. Now I'd like to hand this over to my distinguished colleague, Prashant Keshri, who is an engineering -- Solution Engineering Specialist. And he will take you through the nitty gritty of how Tableau can steer you forward in this journey.

Awesome. Thank you, Ruchira, for sharing those insightful details around Industry 4.0, the Lighthouse Network concept and the critical role of data analysis in driving productivity in the manufacturing industry. Well, these are extremely important changes, which are coming very fast in the manufacturing industry as a whole. Now let's deep dive with the product specifics and in the world of Tableau and explore how others in the industry leverage data. We will examine a supply chain use case to illustrate this in action. With that, let me switch my screen real quick and walk you through that. Well, now I'm in a role of our supply chain leader named Rahul. Rahul starts his day by keeping a track of his business on Tableau mobile application, which is accessible on Android and iOS, which also has Tableau Pulse that AI engine deployed on top of it. Well, what is Tableau Pulse? Tableau Pulse is an reimagining data experience built on Tableau platform that involves every user with intelligent, personalized and contextual insights delivered in the flow of work actually. It is -- well, in this case, Rahul starts his day by heading through the quick summary, which is generated by the generative AI component of Tableau Pulse. The generative AI actually highlights the -- surfaces the key insights in plain, simple-to-read English language. In this case, product shortages has taken a steep spike in the range of about 35%. The CSATs has fallen down by somewhere around 3.3% and the product shortages remain constant. Now imagine all of these insights are available but on multiple screens. By using Tableau Pulse, these insights actually comes as a very quick data summary or data bulletin, exactly how you see your newspaper for how to consume it easily and then proceed with this analysis. On top of it, Tableau Pulse also allows Rahul to keep focused on the specific KPIs, which is important for him in the form of metrics. Now these are the metrics which Rahul is mostly interested in. In this case, the sales number. How is sales performing? How has been the trend over a period of time? What is contributing towards that sales performance? These set of insights are actually surfaced by Tableau Pulse. At the same time, the product shortage situation, the CSAT score. What is happening with delivery cost? What is our product shortages amount? Now in this case, product shortages amount is spiking up, which is not favorable to the business. Therefore, Rahul can do a deep dive of it on his mobile screen. The moment he does that, Tableau Pulse does a very quick time series comparison, helps him get more perspective towards the performance compared to last time period. In this case, previous month of previous year very quick. Pretty useful and important information for Rahul to start his day. At the same time, Tableau Pulse also builds pretty clear line trend for Rahul to understand how has been the product shortage over the period of time. In this case, it has spiked up in the last few weeks of the month of October. At the same time, Rahul will have more questions. Which products are falling short? Or which has got less inventory? In that case, the moment he clicks on inventory, he gets the list of product categories which is falling short in inventory. At the same time, the individual product SKUs, which has the least inventory available. While Rahul is doing all of it, Tableau Pulse actually scans the data and then surfaces more insights in the form of those start-up questions, which is which product has increased the most with respect to product shortages. Which product category has the highest product shortages amount? At the same time, Rahul has a conversational box deployed on Tableau Pulse, available on Tableau mobile application for him to interact more with this data. In this case, when he just types a very -- I mean, a keyword called product, Tableau Pulse actually builds that question on top of it and then allows Rahul to interact with it. In this case, which product has decreased the most. The moment he clicks on it, he gets to understand that the fly fighter, Trica or Roland are the set of products which has increased the most in a favorable scenario in the line of business. Well, imagine all of this was -- Rahul was able to do it on his mobile application. Pretty handy, pretty useful for Rahul to start his day. At the same time, Rahul lands up on Tableau screen with Tableau dashboard, which brings data from multiple sources, multiple applications, helps him correlate various different business factors. Now in this case, what is the sales performance? What is happening to shortages? What has been the fill rate, broken at the individual SKU level? At the same time, since it belongs to the supply chain vertical, it is extremely important for Rahul to keep a track of product shortages and the product type level. He can very quickly glance through products such as desk or products such as health care are seeing maximum shortages in the near future. Therefore, Rahul will have a question now. How can he fix the situation? And that's where the AI engine of Tableau comes into action. It recommends to Rahul, in this case, that desk accessories has a maximum product shortages. It is because of these specific factors, and then it further recommends to Rahul to change the supplier. The current product shortage is in the range of 76%. And the engine says that the -- AI engine, which is the Einstein engine, recommends to Rahul to change the supplier. Therefore, Rahul can now do an impact analysis to switch the supplier for desk accessories from supplier B to supplier D, in this case. The moment he does that, he can wait to see the impact which can happen in the business. The moment he does that, the AI engine reruns for based on the business selection, which Rahul did just now and now the product shortages actually falls in the well acceptable range of 12%. Now at the same time, while he was keeping a focus on desk accessories, now he can move his focus on other high-value product, which is going to be health care. The moment he does that, the whole model runs in real time, and it runs for that specific selection again, and then helps Rahul towards more recommendations. In this case, health care as a product line has a potential of a product shortages of somewhere around 10%, highlights the top reason which is contributing that situation. Also recommends Rahul to stop the product marketing -- to stop marketing of this specific product line. Therefore, now he can do an impact analysis further by switching off the marketing campaign and then see or observe what can be the potential output in this case. So now Rahul can very quickly understand that if he stops the marketing from a specific product line, the product shortages can fall well below the [indiscernible] range of 2%. Now imagine all of it is happening in just a user click and Rahul is able to control the business scenario and situation fairly better and fairly controlled. Now, what more? For that, let me switch back to my screen and walk you through other use cases. But there are many more use cases you can build on Tableau. Here is a short list of use cases, which a lot of organizations have deployed on Tableau to reap the benefits of data. These are Tableau Accelerators, plug-and-play dashboards. It helps you instantly deploy business use cases on the fly without the need to develop it from the scratch. It saves time immensely. Therefore, let's say, if you come from financial vertical, you will have use cases such as financial statement, budget controlling, ESG benchmark, we have those plug-and-play dashboards available. If you want to understand more about sales analytics, well, you have use cases such as sales pipeline, sales and margin, sales process quota to understand more about your sales performance. If you come from a supply chain and you want to analyze more of your data to optimize the supply chain collectively, be it from a perspective of shipment, how best you can deliver your products. When you are in the production line, can you control your scrap inventory? If you are at a distributor level or let's say, when you are delivering your products or keeping an inventory of your products, what is the status of your products? Which products are falling short of the required threshold inventory values? All of those use cases are available for you in a form of Tableau Accelerators. And just like I said, these are plug-and-play dashboards. Well, to take this conversation forward, let's take an example of a CEO Cockpit. What is CEO Cockpit? It is a view for MDs and company promoters and the head of the organization to get a quick glance of the business. Let's see how. Now for that, what you see on the screen is a consolidated view of data flowing from various different verticals, sales, finance, HRMS systems, your feedback management systems, all brought together in 1 single interface makes a user life easier and helps in correlating a lot of business factors at advance. In evaluating our operations performance, we start with finance on the right-hand side, right, accessing both the financial health and profitability to understand the core strength of our bottom line. Moving to sales on the left-hand side, we can closely examine the sales performance and sustainable and pipeline quality ensuring we are not -- we are just not only meeting and actively -- and also actively generating sustainable revenue streams. In case of supply chain, we focus more on meeting customer demand and on-time delivery. Speaking of customers, we can also bring in sourcing data from all the feedback which is generated across different platforms. In case of human resources also plays a really key role in sustaining growth of -- by retaining talent, I mean, a critical component for driving innovation and maintaining operational stability across the board. Together, these dimensions give a holistic view of automation's current standing and potential growth -- for growth, right? It helps a business leader to correlate a lot of business factors and then quickly come to a conclusion. Therefore, it makes the decision-making cycle fairly easy and faster and more confident in. Now all of it is powered by Tableau, right? Now to -- I mean, to do a call back of what we discussed today, if we learn just one thing over the last past few minutes, it is that the pace of digital transformation has just not only accelerated. I mean those companies that are not going digital are being left behind. I'd like to say that digital transformation is a data transformation, by the way. And Tableau is modernizing the analytics tech stack. It is more about -- it is just not about building visualization. It is also about reaping the benefit out of the data into the workflows that enhanced your augmented AI and built on a flexible, composable infrastructure that empowers every employee at every company to drive their digital transformation with the data. We start by helping you truly harness the full value of your data wherever it resides, so you can seamlessly launch your analytics. At the same time, they are enhancing your analytics with artificial intelligence. So whether it is pulling trends into natural language or generating predictions and recommended actions based on those trends, we can help everyone in your organization make smarter and faster decisions. And all of it is done in the flow of work with contextual and actionable insights for every user. Well, with this, I want to say thank you. I want to say thank you for giving us your attention, giving us your time. I hope this session was useful and insightful to you. But see you on the next episode of Tableau-Powered AI webinar. Thank you.