SAP is making its pitch for the future of so-called intelligent applications leveraging technologies such as machine learning, blockchain, analytics and the Internet of Things (IoT) in an offering called Leonardo, a brand previously associated only with the company's IoT efforts.

SAP Leonardo is a set of industry accelerators – short and relatively low-cost professional services engagements coupled with licenses to SAP cloud-based or on-premises software – that the company hopes will change the way it engages with customers, both current and future ones.

The 451 Take

Having launched Leonardo as its IoT brand only in January, this is a quick pivot for SAP's branding strategy but one it hopes will broaden the opportunities while avoiding too much branding confusion. The machine-learning approach – starting with applications, then gradually opening up the platform – makes sense, given its strength is in the application. Frankly, the battle for developer's hearts and minds in terms of machine learning is a fierce one, where SAP is up against not only its usual rival Oracle (and Microsoft) but also some of its partners, including Google and IBM.


Although SAP has made some large acquisitions in the past – Ariba, BusinessObjects, Hybris, SuccessFactors and Sybase among them – it's not that prolific an acquirer given its size and age and unlike its great rival Oracle, SAP tends to buy technology it needs rather than buy market share. CEO Bill McDermott said during SapphireNow that the company's growth trajectory is organic and will largely remain so, pointing out that the last large-scale M&A move was two years ago, when it paid $8.3bn for employee travel and expense manager Concur Technologies. In that deal – the largest acquisition in SAP's history – it had to pay 12.4 times trailing 12-month revenues for the SaaS company, which proved it will go the mat if it needs to, as far as acquisitions are concerned.

The migration of SAP's entire application portfolio to the HANA in-memory database platform continues; SuccessFactors will all be ported to HANA during 2017, Ariba is about halfway there and Concur is at an earlier stage.


SAP's tagline for the new Leonardo is 'intelligently connecting people, things and businesses.' The 'intelligently' refers to technologies such as machine learning, 'connecting' includes APIs, while 'people, things and businesses' refers to a variety of technologies and approaches including collaboration, mobile, speech recognition, IoT and microservices.

SAP pitches Leonardo as a shared-risk scenario with its clients because the engagements are in the €50,000-350,000 range, including cloud-based (or on-premises) software and fixed-price services. The aim is to get application-ready within eight weeks.

Machine learning and analytics

SAP is relatively late to machine learning compared with the likes of IBM, Google and Microsoft, although not when compared with its main rival Oracle.

One of its key advantages is the masses of business data it has in is systems including all the transaction data generated by Ariba.

SAP's machine-learning group numbers about 160 people now, rising to 300 by year-end under the leadership of Markus Noga, part of the group run by the company's chief innovation officer Juergen Mueller. The group, which is spread across SAP centers in Germany, Israel, Singapore and the US, has identified more than 300 use cases already for machine learning. SAP believes there's a lot that can be done automating what are tedious processes for humans such as document matching or extracting information from invoices or classifying help desk tickets into categories – all this can be done using machine learning.

SAP is taking a slightly different approach from that of companies such as Amazon Web Services, Google and IBM. It is taking an application-led approach at the outset, figuring that there are more users of SAP applications than there are developers. And so SAP has launched – or is the process of launching – a set of machine-learning business services wrapped in APIs for customers to use in their applications. And it plans to have about 50 'intelligent' applications of its own launched by the end of the year, according to chairman Hasso Plattner.

And there are also more SAP developers than machine-learning specialists so SAP is offering the use of its pre-trained models to customers via APIs. The last step will be enabling developers to train their own models. However, it's all going to happen quickly, with the company opening up its machine-learning technology to partners and customers in the second half of 2017. All they will need to get started is an SAP Cloud Platform account.

It's early yet for machine-learning customers; about 15-20 companies have systems in production, but that's to be expected at this stage.

CoPilot is a chatbot UI and framework for building conversational interfaces for any SAP application. It can also be integrated into other applications as well as hooking into other chat-oriented applications such as Slack. SAP is building a set of conversational interfaces for use cases in areas such as procurement, service and support and the vision is that any SAP application will be accessible via CoPilot. SAP will eventually open up CoPilot to partners and customers to build their own bots.

SAP had toyed with the brand name Clea for its machine-learning technology, but although it may still show up on some customer invoices, the official name is now SAP Leonardo Machine Learning.

SAP has undertaken a broad rebranding exercise in its BI and analytics portfolio and has left the BusinessObjects brand solely for BI tools and mainly on-premises applications. This reverses a rebrand a year ago when SAP Analytics Cloud became BusinessObjects Cloud; that has changed back, so SAP BusinessObjects is now called SAP Analytics Cloud, among any other name changes.

In terms of new products, SAP has announced version 2.0 of Lumira, which brings together Lumira visualization and Lumira Designer (formerly known as SAP BusinessObjects Design Studio). And SAP partner Zoomdata enables Lumira users to connect to many more data sources.

A new product called Analytics Hub has also been launched. It grew out of work by SAP's own IT department, to meet a user need to pull together a catalog of analytic content across an enterprise. The data stays within whatever analytics tool it comes from, be it an SAP or third-party product – but the Analytics Hub creates a single index so users can personalize what they see.


With Leonardo containing a significant professional services element, SAP was at pains to point out that its systems integrator and other partners backed the idea, with Deloitte identified as the main launch partner. SAP says partners such as Deloitte will be able to come up with their own accelerators based on Leonardo, the hope being that these small engagements – whether delivered via partners or directly by SAP – will lead to considerably larger ones, which partners will lead. Other partners of different stripes include Google, Intel and NVIDIA.


Oracle remains SAP's principal competitor and then the SaaS vendors Salesforce on the CRM front and Workday for ERP. On the analytics front, it goes up against the likes of IBM, SAS Institute, Oracle and Microsoft most often.

Machine learning and the quest to get more developers seeing SAP as a machine-learning platform opens it up to new competition from Google and Amazon Web Services, in addition to the likes of IBM and Microsoft.

SWOT Analysis


One of SAP's main strengths is the mass of business-critical data contained within its myriad applications, which is essential feedstock for machine learning.


SAP's developer community needs to be beefed up, but it is hoping machine learning can be a catalyst for that. There is a short-term risk of branding confusion as the meaning of what is SAP Leonardo changes.


Securing its rightful place as the go-to machine-learning vendor for its vast customer base should keep the company busy for some time.


Companies – and often partners – such as Google and Amazon represent new competitors for SAP, along with its traditional rivals as the battle for developers' attention heats up.
Nick Patience
Research Vice President, Software

Nick Patience leads 451 Research’s coverage in two key areas: digital transformation and artificial intelligence/machine learning. Nick is a cofounder of 451 Research and Research Vice President, Software. He oversees the company’s coverage of the software industry spanning four research channels: Customer Experience and Commerce, Workforce Productivity and Compliance, Data Platforms and Analytics, and Development, DevOps and ITOps.

Patrick Daly
Senior Research Associate, Information Security

As a Senior Research Associate in 451 Research’s Information Security Channel, Patrick Daly covers emerging technologies in Internet of Things (IoT) security. His research focuses on different industrial disciplines of IoT security, including the protection of critical infrastructure, transportation and medical devices. In addition, Patrick’s coverage spans technological domains, including security for IoT devices, applications, platforms and networks.

Keith Dawson
Principal Analyst

Keith Dawson is a principal analyst in 451 Research's Customer Experience & Commerce practice, primarily covering marketing technology. Keith has been covering the intersection of communications and enterprise software for 25 years, mainly looking at how to influence and optimize the customer experience.

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