Flexso SAP Analytics Vision

Transcription

1 Flexso SAP Analytics Vision

2 Flexso Analytics Vision Operational Analytics: back home Hybrid Analytics: Extend with cloud Advanced Analytics: start the journey

3 Flexso Analytics Vision Operational Analytics: coming home Hybrid Analytics: Extend with cloud Advanced Analytics: start the journey

4 Embedded Analytics versus Strategic Analytics Strategic Analytics All analytics use cases All applications and data Embedded Analytics BI, planning & predictive Operational BI (!!) Instant insight to action SAP Applications Part of the application experience

5 SAP Operational Analytics Today? Delays in operational decision making process

6 Key Differentiators of S/4 HANA Embedded Analytics Faster operational decision making Real-Time Visual analytics - Dedicated analytics apps Fiori - unified user experience

7 SAP S/4 HANA Embedded Analytics Portfolio Offering per Type of User FIORI Launchpad Publish & Share SAP Analytics Portfolio End-User Apps: Analyze the data and act according to insights! Analytical Fiori Apps, Query Browser, Smart Business KPIs, Key-User: Enable the end user! Query Designer, KPI & Report Modeler SAP Analytics Cloud SAP Business Intelligence ( Analysis for Office, ) IT User: Provide the single source of truth in one semantic layer Virtual Data Model Maintenance (Eclipse)

8 How to get Started with S/4 HANA Embedded Analytics? End-User Adoption Key User Enablement Standard Virtual Data Models Standard Analytical Apps Identify Operational Reports

9 Business case Embedded Analytics Follow-up Tool

10 Cloostermans Industrial Machines Engineer-to-order business Project driven Mechanical Engineering Electrical Engineering Manufacturing Assembly Integration/Testing S/4 HANA greenfield implementation

11 Business case Follow-up Tool Context? Quotation Sales Department Sales Order? Project Electrical Engineering Mechanical Engineering?? Electrical engineer(s) Mechanical engineer(s)?? Project Manager Responsible electrical engineering Responsible mechanical engineering

12 How did we approach this? S/ > no default app for project follow-up Virtual Data Models Standard Delivered Virtual Datamodel of Sales Extended with quotation details (custom quotation builder) Custom Virtual Data Model for Projects Combined Query View on Sales & Projects Enable the key user Train & support in KPI modeler

13 Demo Follow-up Tool Number of Projects Electrical Engineering & Engineer assignment Open Fiori Launchpad Navigate to Tile Review hours performed on projects Navigate in drill-down views to Assigned Engineers View Launch Project Builder

14 Demo

15 Demo Follow-up Tool Number of Projects Electrical Engineering & Engineer assignment Graphical overview on project status (Actual hours / Planned Hours / Estimated Hours Quotation) Validation of engineer assignment Contextual jump to project maintenance Real-time update in analytical app

16 Business Benefits of Embedded Analytics Follow-up Cloostermans Operational Reporting in integrated in transactional system Stay in same interface (fiori) for insights (analytics) & actions (transactions) One Datamodel serves multiple perspectives: Responsible View Project Manager View Engineer View

17 Flexso Analytics Vision Operational Analytics: coming home Hybrid Analytics: Extend with cloud Advanced Analytics: start the journey

18 Challenges Traditional Reporting Solutions? Business challenges Self-service dashboarding/story building capabilities required Easy access of data residing in different sources Collaboration & Mobility IT Challenges Struggle in deployment of local clients (interdependencies) Investment in upgrades and dependencies with ongoing projects Complexity in set-up mobile reporting/dashboarding

19 Hybrid analytics in a bimodal context Run Traditional Analytics IT driven process Reliability Governance & security Standardized SAP Analytics Hub Bi Modal Analytics SAP Analytics Cloud Business Driven Process Rapid Delivery Less Governance Exploration Freedom SAP Business Intelligence Innovate Agile Analytics Data Foundation (cloud & on premise applications or databases)

20 SAP Analytics Cloud (SAC) Business Autonomy Publish and Collaborate End-User Stories: Make Agile Visualizations to Respond to Business Questions Use the User-Friendly UI to build Agile Analytics Key-User: Enable the end user! Standard Content: Install, Link and Enhance / Custom Content: Build and Link new Models IT User: Connect the Various Source Systems for SAC Setup the Connections and the authentications

21 How to get started with Cloud Analytics? Story Building, Publishing and Collaboration Build / Enhance Models and connect to DataSources Connect Standard Models to DataSources Examine SAC Standard Content Identify DataSources and Setup Connections

22 Hybrid Data Access for cloud analytics Blending on premise and cloud data Cloud Datasources (SFSF, C4C, SCP, SalesForce, ) SAP Datasources (BW, ECC, HANA, ) Data Acquisition Live Data Connection SAP SCP SAP HANA SAP BW (incl. S/4 HANA) SAP Universes SDA SDI All Data (incl Big Data stores) SDA SDI Other Datasources (SQL, )

23 Leverage SAC Standard Content For Line of Business and Industry Solutions Lines of Business Industry Solutions Health Care Utilities Retail Implementation acceleration via predelivered models & stories! Public Sector Insurance Embedded SAC on roadmap! Higher Education & Research

24 Self-service capabilities Respond Fast to Emerging Business Questions in an User-Friendly Interface Collaboration Make your own Calculations GEO Spatial Analysis Variance Analysis Use Embedded Machine Learning for Quick Insights Data Preparation and Cleansing

25 Business Case SAP Analytics Cloud Agile Story Building

26 Demo SAP Analytics Cloud Context Global Care Product Manufacturer Data is originating from various SAP and non-sap Systems DWH Solution BW4/HANA Several Cross-Module KPI s are calculated already in the DWH The company is trying to meet the increasing demand in the market with the constraints of the existing Production Capacity

27 Demo SAP Analytics Cloud We have received a large production order. Can we meet the demand? Create a Story based on received business question Add a GEO Spatial Analysis Apply a filter on Product Group and link the Story Components Analyze the Variance between Production Capacity & Produced Qty Share the story & conclusion

28 Demo SAC

29 Demo SAP Analytics Cloud We have received a large production order. We can meet the demand!! Intuitive story building Integrated collaboration Quick answer on business question

30 Hybrid Reporting Portal: SAP Analytics Hub One Point to all Analytics Special Note for Portal Users Business Explorer Web & Portal SAP analytics cloud & SAP analytics Hub Leverage existing investment - Bex Queries can be fully reused Java Stack: end of maintenance 2024!

31 Integration with BPC for Line Of Business Planning Cloud and on-premise solution integration Integrated Planning scenarios Office integration Data aquisition Data export Write to Planning model Read from BI model / Planning model Analysis for office

32 Flexso Analytics Vision Operational Analytics: coming home Hybrid Analytics: Extend with cloud Advanced Analytics: start the journey

33 Advanced Analytics to support the Management Strategy Transform and/or Increase Value Enterprise Data Data-driven decisions Influencers Insights Predictive Models IOT Data, Behavioral Data, Environmental Data ML Algorithms

34 How to get started? Design Thinking Workshops Advanced Analytics System Architecture Feasibility & Added Value

35 INTERCONNECT & ORCHESTRATE DATA How to prepare your system architecture? VISUALISE (STORY BUILDING & DASHBOARDING) Machine Learning FIND PATTERNS (PREDICTIVE MODELS & MACHINE LEARNING) SAP DataHub Pipelines & Vora Predictive Services CLEAN DATA (DATA PREPARATION) SAP DataHub Agile DataPreparation STORE BIG DATA (DATA LAKES) STORE STRUCTURED ENTERPRISE DATA ( MODERN DATAWAREHOUSE SYSTEMS) Big Data Services GET CONNECTED (IOT SENSORS) IOT Services RECORD ENTERPRISE DATA (ERP SYSTEMS)

36 INTERCONNECT & ORCHESTRATE DATA BW/4 HANA as modern datawarehouse VISUALISE (STORY BUILDING & DASHBOARDING) FIND PATTERNS (PREDICTIVE MODELS & MACHINE LEARNING) CLEAN DATA (DATA PREPARATION) STORE BIG DATA (DATA LAKES) STORE STRUCTURED ENTERPRISE DATA ( MODERN DATAWAREHOUSE SYSTEMS) GET CONNECTED (IOT SENSORS) RECORD ENTERPRISE DATA (ERP SYSTEMS)

37 BW/4 HANA migration strategy New System GreenField Classic SAP BW on Any db SAP BW 7.5 Powered by SAP HANA SAP BW 7.5 On SAP HANA + SAP BW/4HANA Starter Add-On SAP BW/4HANA Classic SAP BW on Any db Full System Conversion System Carve Out / Brownfield Classic SAP BW on Any db Accelerated Greenfield Classic SAP BW on Classic Any SAP db BW on Classic Any SAP db BW on Any db System Consolidation

38 INTERCONNECT & ORCHESTRATE DATA Advanced analytics in SAC VISUALISE (STORY BUILDING & DASHBOARDING) FIND PATTERNS (PREDICTIVE MODELS & MACHINE LEARNING) CLEAN DATA (DATA PREPARATION) STORE BIG DATA (DATA LAKES) STORE STRUCTURED ENTERPRISE DATA ( MODERN DATAWAREHOUSE SYSTEMS) GET CONNECTED (IOT SENSORS) RECORD ENTERPRISE DATA (ERP SYSTEMS)

39 Advanced analytics in SAC Smart Insights

40 Advanced analytics in SAC Automated Forecasts

41 Advanced analytics in SAC Smart Discovery

42 Advanced analytics in SAC Smart Predict

43 Business Case Advanced Analytics Coffee Machines & IOT

44 Miko & SAP Advanced analytics based on connected coffee machines Guarantee machine availability ( predictive maintenance ) Optimized maintenance routes ( geospatial analysis ) POC SAP offices in Brussels (Customer experience center) IOT measurement of coffee consumption, waterflowduration, maxflow & waterconsumption Integration with SAP Leonardo Visualised with SAP analytics cloud

45 Demo Advanced Analytics

46 Demo IOT & Coffee Live visualization of connected machines Leveraging connection to SAP Leonardo Optimize maintenance Use trend & forecast to guarantee maximum availability Mobile visualization Maintenance engineers can use this on the road

47 Flexso Analytics Vision Operational Analytics: coming home Hybrid Analytics: Extend with cloud Advanced Analytics: start the journey

48 Analytics as key catalyst for your business S/4 HANA projects Embedded Analytics as one of the key drivers for your implementation Cloud adoption Accelerator for agile self-service analytics based on cloud & on-premise sources Data-driven innovation Advanced analytics to get insights in your data