May 10, 2021
•6 minute read
SAP Analytics
SAP Analytics focuses on how organizations use enterprise data to generate insight, support better decisions, and automate parts of day-to-day decision-making across SAP environments. The topic spans business intelligence, machine learning, artificial intelligence, SAP HANA, the Predictive Analytics Library, SAP Data Intelligence, SAP Analytics Cloud, and SAP AI offerings embedded across business processes.
Analytics connects business users, data scientists, ML engineers, finance leaders, supply chain teams, and IT organizations around a shared goal: turning SAP data into operational insight, predictive capability, and business process intelligence.
What is SAP Analytics?
SAP Analytics is the use of SAP data, analytics platforms, and embedded intelligence to understand business performance, identify patterns, predict outcomes, and guide decisions inside enterprise processes. It includes descriptive analytics through BI, advanced machine learning models that learn from changing data, and AI capabilities that support problem-solving and decision-making.
SAP Analytics focuses on how organizations use enterprise data to generate insight, support better decisions, and automate parts of day-to-day decision-making across SAP environments. The topic spans business intelligence, machine learning, artificial intelligence, SAP HANA, the Predictive Analytics Library, SAP Data Intelligence, SAP Analytics Cloud, and SAP AI offerings embedded across business processes.
Analytics connects business users, data scientists, ML engineers, finance leaders, supply chain teams, and IT organizations around a shared goal: turning SAP data into operational insight, predictive capability, and business process intelligence.
What is SAP Analytics?
SAP Analytics is the use of SAP data, analytics platforms, and embedded intelligence to understand business performance, identify patterns, predict outcomes, and guide decisions inside enterprise processes. It includes descriptive analytics through BI, advanced machine learning models that learn from changing data, and AI capabilities that support problem-solving and decision-making.
The end-to-end process of BI involves analyzing the data generated by businesses, transforming the data into insights, and leveraging those insights to make optimal decisions. BI tools primarily leverage “descriptive analytics,” because these tools traditionally focus on analyzing current and historical performance based on data generated by the enterprise.
In practice, SAP Analytics helps organizations use tools such as SAP Analytics Cloud, SAP HANA, SAP Data Intelligence, and SAP AI capabilities to support reporting, planning, predictive analytics, automation, and business process improvement.
What are some SAP Analytics use cases?
Business intelligence and reporting
Teams use BI tools to analyze current and historical enterprise performance, transform business data into insights, and support decisions based on descriptive analytics.
Predictive analytics
Organizations use machine learning algorithms and SAP HANA’s Predictive Analytics Library to build models that learn from input data and support predictive use cases.
Self-service analytics
SAP Analytics Cloud supports business users with intuitive, AI-guided analytics capabilities, helping functional managers work with analytics without needing to be data scientists or technical managers.
Enterprise planning
SAP Analytics Cloud combines planning, predictive analytics, reporting, and BI, allowing organizations to use it as a collaborative enterprise planning tool.
Business process intelligence
SAP AI offerings are positioned to infuse intelligence into lead to cash, design to operate, source to pay, and recruit to retire processes.
Data science and ML development
SAP applications support data scientists and ML engineers building advanced ML models and solutions, while also helping end users perform advanced analytics with minimal technical proficiency.
What does SAPinsider research say about SAP Analytics?
SAPinsider research shows that analytics maturity increasingly depends on cloud-based platforms, self-service access, and cross-functional data models. SAP Analytics Cloud reflects this shift by combining planning, predictive analytics, reporting, BI, and AI-guided analytics for business users.
The SAP Business Data Cloud benchmark shows that data foundations remain a major constraint. Only 3% of organizations have a unified governed data layer, while 38% remain siloed, limiting progress toward real-time analytics and AI-driven decision-making. Still, investment momentum is building. SAPinsider found analytics modernization was a top SAP BDC driver at 28%, followed by AI and agent-based use cases at 26%.
SAPinsider’s AI maturity research reinforces the importance of trusted analytics foundations. While 91% of respondents report some AI use, 79% cite access to high-quality, trusted data as a requirement for successful AI strategies.
The Role of Analytics in Business Process Intelligence: A RISE with SAP PerspectiveIncreasingly, businesses are shifting their focus to accommodate the new digital reality. Technology is a key enabler in this aim, but businesses also need to consider what needs to change within their enterprises, including their processes and organizational design. Business transformation has become the front-and-center strategic priority that helps organizations adapt to the digital world and ultimately deliver value to customers.
The business process intelligence (BPI) component of RISE with SAP enables businesses to become intelligent enterprises by providing best-in-class processes, process management, and process intelligence capabilities. When linked with analytics capabilities, BPI serves as a foundational component for driving business transformation because it extensively leverages all three key ingredients involved in the journey: people, process, and technology.
In this article, Kumar Singh, Research Director, Data & Analytics, Supply Chain Management, SAPinsider, explains how analytics-powered BPI establishes process foundations that drive and undergird the success of a business transformation journey.
Read this article and learn:
• The role of analytics in supporting four critical BPI sub-components: Monitor and Analyze, Design, Simulate and Improve, Model and Manage, and Benchmarking.
• The value of an effective and robust data collection and data management infrastructure to eliminate data latency, quality, and integrity.
• About the importance of good data to drive process improvements, process re-design, and process optimization in business transformation initiatives.
• How strategic and thoughtful KPIs help improve processes continuously while serving as a benchmark against the best in your class.
• Why investing in people – an analytics talent pool dedicated to BPI and BPM – is essential to enhance analytics capabilities and drive business transformation success.
Enterprise Artificial Intelligence – Embedded AIIf your company has not begun building an artificial intelligence (AI) strategy, it may risk falling behind competitors. That could mean lagging in areas of innovation that AI can enable, including improved or new products, reduced risks, and a better bottom line. There is good news for SAP customers: SAP has already begun embedding AI into its offerings, intending to make them ready to use. Additionally, SAP provides development platforms with AI capabilities that will enable customers and partners to enhance SAP systems with AI innovations. How can SAP customers incorporate SAP’s AI work into their own strategy?
In an exclusive piece for SAPinsider, Dr. Feiyu Xu, Senior Vice President, Global Head of Artificial Intelligence at SAP teams up with Maximilian Herrmann, Project Consultant and Storyteller at SAP, to detail SAP’s plan for AI both within and complementary to its products, as well as what the vendor and its customers have already achieved in the AI space.
Read this column and discover:
- The growing market and demand for AI across many industries and the common roadblocks to adoption that companies are facing;
- How SAP embeds AI into processes and applications, and how it develops ready-to-use AI functionalities with its internal “AI Factory” approach;
- The AI-powered products and services that SAP currently offers and how customers can use them; and
- An embedded AI use case for increasing efficiency around supplier invoice processing already in use by more than 100 small business and medium enterprise (SME) SAP customers.
May 4, 2021
•9 minute read
The journey from Strategy to an Analytics Algorithm : A Marketing Analytics exampleEvery Analytics algorithm that you use in your teams should tie to your Corporate strategy goals. However, very few resources currently clearly highlight how. Closing this link, in my mind, is one of the ingredients to the secret sauce to developing analytical products that will work, in a sustainable way (not a blip that goes […]
Feb 6, 2021
•1 minute read
Maximize Your Investment in SAP and Azure Synapse to Create a Cost-Effective Data Analytics StrategyBusinesses across the globe are struggling as they attempt to wrangle multiple data sources into a cohesive data analytics strategy. Bringing together SAP and non-SAP data is complex and requires significant technical resources. In this session, learn from experts about how you can leverage IBM to help you bring this data together in a data fabric that maximizes your investment in SAP combined with Azure Synapse creating a cost-effective data analytics strategy and […]
Feb 1, 2021
•1 minute read
Impact on Analytics and VisibilitySAP S/4HANA, for many organizations, is the single sources of truth for finance and business functions. As organizations conduct their SAP S/4HANA transition projects, they are consolidating data from multiple systems across the enterprise. This has an impact on the business capabilities of making critical decisions, conducting analysis, and understanding the direction of the business as well as building tools that can help make better decisions. This track will focus on how you can utilize your SAP HANA database, discuss the analytics capabilities of SAP S/4HANA, and how customers can move forward with analytics both inside and outside SAP S/4HANA.
Jan 15, 2021
•3 minute read
Advanced Analytics in SAP and Hybrid EnvironmentsAs Business Intelligence and reporting capabilities mature and get commoditized, organizations are increasingly looking to leverage more advanced analytics approaches. Both SAP as well as third party vendors offer a plethora of advanced analytics capabilities that leverage AI and Machine Learning algorithms. These sessions will help you understand how to leverage advanced analytics tools and technologies in a cloud environment. You will also explore how to use advanced analytics going beyond what you using do in these three areas: descriptive, prescriptive and predictive analytics – as well as using machine learning and AI in your analytics strategy.
Jan 15, 2021
•2 minute read
SAP S/4HANA and Embedded AnalyticsEmbedded Analytics is increasingly becoming a significant feature in applications and is a core value proposition in SAP HANA offering. Available offerings in this space extend beyond the SAP ecosystem into third party vendors as well. As users start interfacing more and more with applications with embedded analytics capabilities, they need to have a good grasp of aspects that can help them exploit this feature optimally. This track will explore embedded analytics, various ways in which SAP HANA makes embedded analytics accessible, and how to get the most out of embedded analytics applications.
Jan 15, 2021
•3 minute read
Pairing Analytics and AutomationBy Pierce Owen, VP of Research, SAPinsider Translating Data into Insights As part of their “digital transformation,” 75% of respondents in a recent SAPinsider survey say their organizations use or plan to use self-service analytics for operational performance. Self-service analytics help democratize analytics, allowing the average business user to visualize raw data, identify outliers or […]
Nov 11, 2020
•3 minute read
Breakthru Beverage Group Reaches New Horizon on Journey to Become a Fully Integrated, Data-Driven BusinessModern consumers expect their unique needs to be met at the push of a button, and this expectation includes the food and beverage industry, as evidenced by the rapid increase in grocery pickup and delivery services, for example. Breakthru Beverage Group — which offers restaurants and retailers a portfolio of established and emerging beer, wine, and spirits, along with guidance on marketing the right products — recognized the need to embrace innovation to deliver the information its customers depend on to grow and improve their business performance and relevance. To meet this need, Breakthru set out to implement an enterprise data warehouse strategy and platform that would quickly deliver meaningful and individualized insights for its customers.
In this article, you will learn how the organization:
• Created a centralized source of governed truth by consolidating and simplifying its technology platform using SAP ERP, and by cleansing and conforming its data
• Successfully moved to SAP HANA-based business intelligence for reporting and analytics using a program that helped users get acclimated to the new technology
• Achieved a range of benefits from its improved and integrative reporting capabilities, such as consistent data, operational efficiency, and actionable insights
Nov 3, 2020
•15 minute read
Climbing the FP&A maturity curveWith the advanced of analytics, automation, and intelligent technologies, businesses more than ever have a significant opportunity to significantly improve financial planning and analysis. But with all the choices and opportunities, the first steps and decisions often seem daunting. This session will help you:
•Understand what technologies and solutions stand to have the greatest impact on FP&A and how you need to evaluate them
•Prioritize financial planning and reporting processes that are the best candidates for applying intelligence, analytics, or automation
•Prepare for the change management challenges of applying new technology to traditional planning processes
•Know how you can measure the success and spread the learnings of initial pilot projects
Oct 20, 2020
•1 minute read
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