Presenting SAP Leonardo as a System of Innovation

Presenting SAP Leonardo as a System of Innovation

Executive Q&A on the Promise of SAP Leonardo with SAP’s Thomas Ohnemus and Richard Howells

Published: 16/August/2017

Reading time: 8 mins

Q: What does the broadening of SAP Leonardo as an IoT platform to a system of innovation mean for the SAP customer?

Richard Howells: Limiting SAP Leonardo to strictly a platform to extend IoT to the enterprise does it a disservice. From the customer’s perspective, IoT is just one of many technologies that connects to business processes as they evolve into a digital enterprise. Big data, machine learning, blockchain, and analytics are also part of this convergence and all need to add value to solve business problems and drive business process change.

Value is derived when these technologies work together to drive business outcomes. Big data technologies address the IoT challenge of data generation. Machine learning adds intelligence to data, creating action on physical devices. Blockchain automates transactions and addresses cybersecurity, and incorporates analytics to provide end-to-end visibility and decision support.

IoT is a great technology, but only so far as it drives business process change and outcomes. This was the thinking and strategy for broadening the SAP Leonardo scope as a system of innovation that is delivered on SAP Cloud Platform.

Thomas Ohnemus: The strategy aligns with the enormous change happening in business with digital technology radically changing traditional business processes. While this may sound futuristic, it’s real and it’s happening all around us.

In the consumer world, everyone has a smartphone and everything is at their fingertips. Products are becoming digital, where you now have an intelligent physical presence that creates an enormous amount of data and its digital twin. A car, for example, can send real-time performance information back to a system that a user monitors and can take action on to make repairs or optimize performance. But with autonomous cars, it will go a step further, where the car can communicate with its immediate surroundings, whether that’s other cars, pedestrians, traffic lights, and so on.

All these possibilities are driven by data. We’re at the beginning of this data journey — extracting value from all kinds of new information, and managing the impact as business processes and models change. The typical automotive business, for example, is at the onset of a shift toward offering an Uber-like model of transportation as a service. With so much innovation in the automotive industry happening in software, the typical car manufacturer is evolving from traditional product development to becoming a technology company. From including sensors in the design, to relaying real-time performance data back to engineers, there is hardly a single process left unchanged.

These are the challenges and opportunities for the enterprise. Our customers are asking us to guide them on this path to layering business context on top of innovation, and our answer is SAP Leonardo.

Q: Is the importance of becoming intelligent for a digital enterprise a response to external forces such as customer expectations?

Howells: Whether it’s the products we buy, the machines we use on the manufacturing floor, the assets in the business world, the vehicles we drive, or the buildings and homes we work and live in, everything is being connected and everything is becoming intelligent. At its core, SAP Leonardo is about intelligently connecting people, things, and business processes to reflect this changing world and to meet the demand from business and consumers.

We need this intelligence driven into the business through big data, machine learning, and analytics because everything is also in the moment. Customers want individualized products, and they want them when they want them — not next week, or next month. Manufacturing and logistics must become intelligent to meet this demand. Intelligence, connectivity, and everything being in the moment drives the need for business processes to be connected. Getting the data is just the tip of the iceberg; you have to be able to take action based on the data. You can get a lot of data and not be able to do anything with it and that’s probably more frustrating than not having the data in the first place. Leveraging data by putting it into business context is what it means to become a true digital enterprise.

Ohnemus: Companies must understand intelligence in the scope of traditional business processes and a system of record. What does it mean, for example, for placing and executing a sales order, or a planning process? Because intelligence isn’t limited to breathing new life into manufacturing or logistics processes. With real-time data from IoT, analytics, and machine learning, your whole organization can become predictive, where you’re not making forecasts based on historical data, but instead using real-time data to predict the future.

Yes, the SAP Leonardo portfolio is a system of innovation and intelligence, but every company also has a system of record in place with which it runs its business. And how these two systems can work together influences existing business processes to make the company faster, more efficient, more customer-focused, and more flexible.

Q: What advice do you have for companies that might be overwhelmed by becoming an intelligent business?

Howells: This is often the first question customers have: This all sounds great, but what does it mean for my business? Technology should never be deployed for the sake of technology. It must solve business problems, and our customers succeed by identifying their business problems. IoT and SAP Leonardo help solve many problems, and we’re trying to make it simpler for our customers by delivering industry and line-of-business accelerators, as well as design thinking methodology. Customers identify their business challenges, and we support them with standard packages and fixed-time deployments targeted for a specific business problem. This support originated with solutions such as SAP Vehicle Insights, SAP Digital Manufacturing Insights, SAP Connected Goods, SAP Asset Intelligence Network, and SAP Predictive Maintenance because there was a lot of low-hanging fruit in those areas to capture real-time information from assets in the field and leverage that data to protect against an asset’s failure rather than wait for it to break down, for example.

There are many examples and use cases that companies can deploy today. But identifying business challenges and looking for solutions is the way that most customers have started their IoT and digital transformation journey, rather than just saying, “Yes, we need to do a digital transformation.” 

Ohnemus: That’s true. There’s no individual answer like there was in the past, when a manufacturer searched for a manufacturing system and sales searched for a CRM system. Silos are disappearing, which can make the buying decision more difficult. This is why our industry and line-of-business accelerators embrace the design thinking concept to help customers on their digital transformation journey.

In design thinking workshops as part of SAP Leonardo, SAP helps customers identify and target opportunities where digital transformation can help their existing business. Companies can start small by thinking about which business processes are affected when there is an urgent need to deliver custom products within a few days of the order being placed, for example. What do they need to do to bring this flexibility in the design and delivery of an individualized product? The answer to that is different for everyone, and that’s where design thinking can help.

Q: How are SAP customers leveraging SAP Leonardo as a system of innovation to produce results?

Howells: Kaeser Compressors is a well-known example where they’ve made an asset — in this case, an air compressor — intelligent, and by doing so have been able to sell the compressed air produced by the asset as a service. Sensors must not only track usage hours for billing purposes, but also track the unit’s real-time performance to predict failure and ensure no unscheduled downtime. And here we see another way in which traditional siloes are splintering, because this is a case where a maintenance technician becomes a customer service rep. It’s a different way of thinking, and it begins with generating a lot of data.

Trenitalia, the leading rail transport operator in Italy, is putting thousands of sensors on its trains — which carry approximately 2 million passengers each day — to generate about 700 terabytes of data annually. Its objective was to move to a conditional maintenance model rather than a fixed schedule based on time, or miles traveled. By analyzing this data on SAP Cloud Platform, Trenitalia reduced maintenance costs by up to 10%, which translates to an annual savings of roughly $145 million. In addition to the cost savings, Trenitalia can predict when a train will fail and take proactive action to keep it running. Fewer failures means improved reliability and availability, which translates to more services and happier customers.

Ohnemus: Stara, a tractor manufacturer based in Brazil, is another good example of an SAP customer innovating with IoT technologies — in this case by connecting farmers with machines, and machines with farming processes. With one infrared sensor, a Stara tractor can let a farmer know the exact amount of fertilizer to apply to each plant. One farm owner reported that the added efficiency helped him recover his investment in the technology within two years and led to a significant increase in productivity. I loved a comment he made, something to the effect of he wasn’t just buying a tractor, but he was buying a package of services that hosts his data in the cloud.

Howells: McLaren Technology Group, known for its F1 race cars, is another IoT pioneer. On race day, they typically have up to 300 sensors on each race car, tracking everything from tire pressure to G forces on a driver. They can analyze more than 1 trillion points of data in near real time to enhance performance.

Q: Can this sort of intelligence apply to all types of companies and industries?  

Ohnemus: The examples we’ve provided here really only scratch the surface. New technologies that enable this digital transformation present huge opportunities and advantages for every company out there to improve their businesses to be faster, more flexible, and to serve their customers better and match their expectations.

In the near future, there will be even more requirements for manufacturers to produce individualized products, and to deliver them faster. Yes, it starts with the product, but behind the product is an individual and flexible design, individual and flexible manufacturing, individual and flexible service, individual delivery, and perhaps even individual planning. There are significant requirements and opportunities, and the companies that run with these opportunities are the ones that will best satisfy their customers and will be the winners.


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