Analytics &
Management Information

Faisal Haneef
Business Intelligence - SAP UKI
What do business managers want from IT?



               Reduced operational cost and improved efficiency from
          ...
SAP BI (Business Warehouse)


          An integrated end-to-end Data Warehouse solution

                                ...
SAP Reporting & Analysis

           Analytical                                                                Reporting &...
Business Content



                                                +11,000 InfoObjects

                                 ...
Content based on Market Requirements

                                           Content based on
                        ...
SAP BI - Reporting and Analysis For All User Types


                                                Authors and Analysts
...
Information Delivery

                                                       BUSINESS INTELLIGENCE SUITE
                 ...
Authors & Analysts




 SAP AG 2004, Title of Presentation / Speaker Name / 9
Knowledge Workers
                                                        Targeted




                                   ...
Executives




 SAP AG 2002, Title of Presentation, Speaker Name 11
Alerts – pushing information to depots & users




 SAP AG 2002, Title of Presentation, Speaker Name 12
SAP NetWeaver - BI Architecture




 SAP AG 2002, Title of Presentation, Speaker Name 13
Not So Long Ago … What Will the Future Bring?

                                                                           ...
Limit the Costs of Growth

    Increasing awareness about                                          Enterprise Data
       ...
Multi-Layer SAP BI based on EDW Functions

                                                                             En...
Advance Functionality




                    Data Mining                         Planning         Balanced      Reporting...
Advance Functionality




                    Data Mining                         Planning         Balanced      Reporting...
Planning cycles



           Strategic Planning and                          Operational Planning and Budgeting
         ...
Business planning & simulation

                                                        BPS
                              ...
SAP BI Planning Architecture
                                                                  User Interaction

         ...
 SAP AG 2002, Title of Presentation, Speaker Name 22
 SAP AG 2002, Title of Presentation, Speaker Name 23
Advance Functionality




                    Data Mining                         Planning         Balanced      Reporting...
Data Mining – Why?

                                         Analyze                      Data Mining
            Customer...
Analytical Process Designer

                  Graphical modeling (drag&drop) to build analytical processes that feed
    ...
Data Mining Methods - Explorative


   Clustering




    ABC                                  A          B   C           ...
Data Mining Methods - Predictive
Regression




Decision Trees
                                                           ...
Composite Scenarios: Customer Retention

               Decision Trees                                ABC Classification  ...
Audi Retail – Example of integrated application


                              Automized lead qualification              ...
Advance Functionality




                    Data Mining                         Planning         Balanced      Reporting...
 SAP AG 2002, Title of Presentation, Speaker Name 32
Scenario-based Analytics using the Visual Composer

            Modeling of BI-Applications using the BI Kit of   Scenario...
Visual Composer Model




 SAP AG 2002, Title of Presentation, Speaker Name 34
 SAP AG 2002, Title of Presentation, Speaker Name 35
 SAP AG 2002, Title of Presentation, Speaker Name 36
 SAP AG 2002, Title of Presentation, Speaker Name 37
Business Scenarios

  Business          Enterprise Asset Management
   Process             Emission Management
  Exception...
Scenario 1: Business Process Exception Management

                        Monitoring, Management and Analysis of dialog- ...
Scenario 2: Unbilled Revenue Reporting

                        Individual contract based calculation of the Balanced Shee...
Scenario 3: Intercompany Data Exchange

                        Regulatory requirements (Settlement Analysis, Payment Proc...
Scenario 4: Enterprise Asset Management

                        Monitoring, Management and Analysis of company KPI‘s (MTT...
Scenario 5: Energy Data Management

                        Combine meter reading data and customer master data to analyze...
Scenario 6: Integrated Sales Planning and Analysis

                        Calculation of contribution margin on customer...
Scenario 7: Customer Analytics

                        Customer Segmentation (based on Margin, Consumption, Amount, Socia...
Scenario 8: Financial Analytics

                        Automation of data transfer, consolidation, integrated planning, ...
The different BI Layers


                              Access                                                        Busi...
Upcoming SlideShare
Loading in...5
×

Analytics

1,108

Published on

0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
1,108
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
67
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide

Analytics

  1. 1. Analytics & Management Information Faisal Haneef Business Intelligence - SAP UKI
  2. 2. What do business managers want from IT? Reduced operational cost and improved efficiency from automated and streamlined business processes. Tools to manage the business: Business analysis – revenue, profitability, pipeline….. Planning & Forecasting tools – bring x-business data together High-level, single version of the truth drilling down to detail Pro-active management tools – alerts, exception reporting…  SAP AG 2002, Title of Presentation, Speaker Name 2
  3. 3. SAP BI (Business Warehouse) An integrated end-to-end Data Warehouse solution Powerful Information Analysis Innovative, intuitive user interface Powerful OLAP analysis Web & MS Excel based front-ends Easy integration with Portal Information Management ‘Best of breed’ technologies Rich Business Content -pre-configured Information models, reports, KPI’s and extractors Industry Specific Business Content Business Planning & Simulation Configurable to specific requirements Data Extraction Built on the SAP Entity Model SAP and non-SAP data extraction Powerful Data Maintenance and Administration  SAP AG 2002, Title of Presentation, Speaker Name 3
  4. 4. SAP Reporting & Analysis Analytical Reporting & Applications Interactive Analysis Business Content SAP Business Intelligence SAP Business Intelligence e-Billing HR Finance & Market Other Other Costs CRM  SAP AG 2002, Title of Presentation, Speaker Name 4
  5. 5. Business Content +11,000 InfoObjects SAP delivers “Best Practice” data models & reports. +340 ODS Objects These are based on the entity model supporting the whole SAP solution. +650 InfoCubes It means customers can deploy quickly with the assurance of a +120 MultiProviders robust data model. +3,200 Queries +1,900 Workbooks +800 Roles  SAP AG 2002, Title of Presentation, Speaker Name 5
  6. 6. Content based on Market Requirements Content based on Content based on Market Requirements Market Requirements 40 Query ed liz na so r Pe MultiProvider 5 InfoCube 61 s rd da ODS an 51 St Contract Contract 574 characteristics InfoObject Open item Open item 146 key figures 336, coming from 266 Text and attributes (master data) Extractor 70 transactional data  SAP AG 2002, Title of Presentation, Speaker Name 6
  7. 7. SAP BI - Reporting and Analysis For All User Types Authors and Analysts Need to dig into the data – explore & find trends Business Managers Need personalized information specific to their function Summary – but with the ability to drill down to the detail Executives High level analysis (dashboards) - alert to key business issues & actions  SAP AG 2002, Title of Presentation, Speaker Name 7
  8. 8. Information Delivery BUSINESS INTELLIGENCE SUITE AUTHORING Query Design Data Web Formatted Application Mining Design Reports Desktop Ad-hoc Tabular Mobile Query REPORTING Reports & ANALYSIS OLAP Dash- Analysis boards Enterprise Web Portal Broadcasting AUTHORS AND EXECUTIVES AND KNOWLEDGE WORKERS ANALYSTS INFORMATION CONSUMERS BUSINESS INTELLIGENCE USERS  SAP AG 2002, Title of Presentation, Speaker Name 8
  9. 9. Authors & Analysts  SAP AG 2004, Title of Presentation / Speaker Name / 9
  10. 10. Knowledge Workers Targeted Emailed Alert Driven  SAP AG 2002, Title of Presentation, Speaker Name 10
  11. 11. Executives  SAP AG 2002, Title of Presentation, Speaker Name 11
  12. 12. Alerts – pushing information to depots & users  SAP AG 2002, Title of Presentation, Speaker Name 12
  13. 13. SAP NetWeaver - BI Architecture  SAP AG 2002, Title of Presentation, Speaker Name 13
  14. 14. Not So Long Ago … What Will the Future Bring? Scenario Models Scenario-based Scenario-based SAP BI Content Content Enterprise Data Enterprise Data Warehouse Layer Warehouse Layer Performance Performance Content based on Content based on Market Requirements Market Requirements Reporting Models  SAP AG 2002, Title of Presentation, Speaker Name 14
  15. 15. Limit the Costs of Growth Increasing awareness about Enterprise Data Enterprise Data the relation between an SAP BW Warehouse Layer Warehouse Layer infrastructure, growth and costs Customer investments for an adequate SAP BW infrastructure Activities run under the title ‘Enterprise Data Warehouse’ Most common to all activities is the concept of a layered architecture SAP NetWeaver BI Architected Data Marts With Business Content DWH Bus Architecture - Administration, Solution centric Maintenance Cost – SAP NetWeaver BI with Layered Architecture – Corporate Information Factory (CIF) No of Application Scenarios (Data Marts)/ Volume  SAP AG 2002, Title of Presentation, Speaker Name 15
  16. 16. Multi-Layer SAP BI based on EDW Functions Enterprise Data Enterprise Data Warehouse Layer Warehouse Layer BI Suite NW BI Analytical Reporting Layer Reporting Data Warehouse Integration Layer Integrated Reporting Layer – Detail DataSource Merge Process & mySAP CRM Data Propagation Layer - Detail Plan DataSource based, Partitioned, granular SAP APO Data Warehouse Data Acquisition & Abstraction Layer Receive by DataSource and distribute OLTP Layer SAP ERP / Non-SAP OLTPs / eBusiness / Mainframe / Utilities  SAP AG 2002, Title of Presentation, Speaker Name 16
  17. 17. Advance Functionality Data Mining Planning Balanced Reporting Analytical Scorecards Applications Business Business Warehouse Content (BW) e-Billing HR Finance & 3rd Party Other Other CRM Projects  SAP AG 2002, Title of Presentation, Speaker Name 17
  18. 18. Advance Functionality Data Mining Planning Balanced Reporting Analytical Scorecards Applications Business Business Warehouse Content (BW) e-Billing HR Finance & 3rd Party Other Other CRM Projects  SAP AG 2002, Title of Presentation, Speaker Name 18
  19. 19. Planning cycles Strategic Planning and Operational Planning and Budgeting Plan evaluation Target setting on group level in the business units Reconciliation of operational plans with strategic Store Planning targets Assortment Planning Operational Planning Sales planning Marketing planning Strategic Targets (Operating Profit + 4%, Market share+10%) Strategic Planning August December  SAP AG 2002, Title of Presentation, Speaker Name 19
  20. 20. Business planning & simulation BPS SAP’s standard planning tool Integrated to BW, SAP’s data warehouse It is independent from SAP’s core transactional system, yet fully integrated Planning of SAP & Non SAP data across all functional areas is supported All levels of detail are supported by BPS Supports multiple planning methodologies, functions & interfaces  SAP AG 2002, Title of Presentation, Speaker Name 20
  21. 21. SAP BI Planning Architecture User Interaction Presentation Planning Front Ends Portal based HTML in GUI Excel Inplace Excel Client ALV Grid Open Interface and Web Services Business Logic Planning Framework Modeling Manual Planning/ Automatic Process Analysis Planning control Common Read / Write Interface Access / Storage DWH Layer Dimensional Master Data Granular Data Data Data Acquisition  SAP AG 2002, Title of Presentation, Speaker Name 21
  22. 22.  SAP AG 2002, Title of Presentation, Speaker Name 22
  23. 23.  SAP AG 2002, Title of Presentation, Speaker Name 23
  24. 24. Advance Functionality Data Mining Planning Balanced Reporting Analytical Scorecards Applications Business Business Warehouse Content (BW) e-Billing HR Finance & 3rd Party Other Other CRM Projects  SAP AG 2002, Title of Presentation, Speaker Name 24
  25. 25. Data Mining – Why? Analyze Data Mining Customers with a certain rate, Does this payment behavior happen by payment method, and consumption accident or is it representative? don‘t pay well. Is the payment method the main driver? Customers in a certain segment Is this link confident? with budget billing plan are very Are there any customer in this segment profitable. left that don‘t have a budget billing plan? Should we start a marketing campaign? More than 50% of the customers are Can‘t we cluster (A,B,C) our customer profitable. better?  SAP AG 2002, Title of Presentation, Speaker Name 25
  26. 26. Analytical Process Designer Graphical modeling (drag&drop) to build analytical processes that feed back into the business process Processes are automated and can be self-learning  SAP AG 2002, Title of Presentation, Speaker Name 26
  27. 27. Data Mining Methods - Explorative Clustering ABC A B C 20% of customers Classification generate 60% of sales Association Analysis Weight Weighted Score Tables Customer Age Gender Income Score … … … … … … … … … …  SAP AG 2002, Title of Presentation, Speaker Name 27
  28. 28. Data Mining Methods - Predictive Regression Decision Trees Complaints <=4 >4 Complaints No ? Age No Gender Gender Buy F M Sales Income Yes Income Yes # of Products <=30 k >30 k No Yes  SAP AG 2002, Title of Presentation, Speaker Name 28
  29. 29. Composite Scenarios: Customer Retention Decision Trees ABC Classification Clustering A B C At Risk B A Loyal C Goal: Reduce Customer Churn Association Analysis Transfer Cross-Selling Knowledge Rules Marketing Campaign  SAP AG 2002, Title of Presentation, Speaker Name 29
  30. 30. Audi Retail – Example of integrated application Automized lead qualification operational lead process based on scoring models analytical lead process lead generation lead qualification transfer lead to dealer monitor fulfillment Predictive Analytics feedback lead results Adjustment and Lead Funnel Analysis enhancement of • Channel Efficiency scoring models • Win/Loss  SAP AG 2002, Title of Presentation, Speaker Name 30
  31. 31. Advance Functionality Data Mining Planning Balanced Reporting Analytical Scorecards Applications Business Business Warehouse Content (BW) e-Billing HR Finance & 3rd Party Other Other CRM Projects  SAP AG 2002, Title of Presentation, Speaker Name 31
  32. 32.  SAP AG 2002, Title of Presentation, Speaker Name 32
  33. 33. Scenario-based Analytics using the Visual Composer Modeling of BI-Applications using the BI Kit of Scenario-based Scenario-based the Visual Composer Content Content Enables Business-User to design analytical Content for the Enterprise Portal Facilitates the integration of BW-data (InfoCubes, BEx Queries and Query Views, BEx Web Applications) with heterogeneous Data Sources (inclusive OLAP- and relational data bases)  SAP AG 2002, Title of Presentation, Speaker Name 33
  34. 34. Visual Composer Model  SAP AG 2002, Title of Presentation, Speaker Name 34
  35. 35.  SAP AG 2002, Title of Presentation, Speaker Name 35
  36. 36.  SAP AG 2002, Title of Presentation, Speaker Name 36
  37. 37.  SAP AG 2002, Title of Presentation, Speaker Name 37
  38. 38. Business Scenarios Business Enterprise Asset Management Process Emission Management Exception Mobile Solutions Customer Management Analytics (BPEM) Sales Planning Asset Lifecycle and Resource Management and Analytics Intercompany Data Exchange Energy Data Management Meter Reading Services Billing of Energy and Services Selling of Energy and Services Energy Capital Management Customer Financial Management Collaborative Services & Intercompany Data Exchange  SAP AG 2002, Title of Presentation, Speaker Name 38
  39. 39. Scenario 1: Business Process Exception Management Monitoring, Management and Analysis of dialog- and mass processes in IS-U/CCS, with Exception handling – Process Optimization Central access to process and exceptional information – Cost Reduction Meter Reading Services Billing of Energy and Services What should a Platform do: Data extraction and Process Integration Time between meter Time between invoicing reading and invoicing and payment Analysis Meter Reading Meter reading Meter reading Meter Reading Billing Outsorting Invoice Invoice Exception handling Preparation preparation Performed processed Outsorting Correction correction Meter Read to Billing Meter reading to billing Billing to Invoicing Billing to invoicing Invoicing to Payment Invoicing to payment Start End # Meter readings # Billing errors # Bill correction # Meter reading errors # Outsorted documents Ø Time for bill correction Ø Time for correction Ø Time for processing of outsorted documents Costs = # Processes x Time per process  SAP AG 2002, Title of Presentation, Speaker Name 39
  40. 40. Scenario 2: Unbilled Revenue Reporting Individual contract based calculation of the Balanced Sheet, monthly or quarterly reporting – Flexible reporting Be pro-active and increase revenues by executing campaigns based on extrapolated data – Increased Revenue Billing of Energy and Services 7. Legal or Company 6. unbilled revenue reporting Closed-Loop Reporting Analytical Compare contract value with offering Scenario BW 5. unbilled revenue extrapolation 3. Customer closes contract Access Transfer from CRM to BW IS-U 2. Customer CRM 4. Contract is receives offer replicated to IS-U 8. Execute a Marketing campaign, not only on billed but also on extrapolated data 1. Create Offer for customer (Calculation in CRM)  SAP AG 2002, Title of Presentation, Speaker Name 40
  41. 41. Scenario 3: Intercompany Data Exchange Regulatory requirements (Settlement Analysis, Payment Process Analysis, Supplier Switch Analysis) - Regulatory Compliance Customer service optimization (Supplier Switch Analysis, Payment Process) that you know where the bottleneck is - Process Optimization Collaborative Services and Intercompany Data Exchange What should a Platform do: Consumption, distributor billing, customer and technical Facilitate Electronic data Data Exchange for Supplier Switch Electronic data Payment Processing exchange Settlement Distributor Supplier Change of customer, change to customer data, payment distribution bill, service request Provides the supply Concludes utility grid and associated contract, invoice, services collections Customer  SAP AG 2002, Title of Presentation, Speaker Name 41
  42. 42. Scenario 4: Enterprise Asset Management Monitoring, Management and Analysis of company KPI‘s (MTTR, MTBF, Outage) based on asset management strategy - Increased availaility and reduced outage times / frequency Use online production data to determine areas for improvement – Higher Utilization / Lower cost of operation Asset Lifecycle and Resource Management What should a Platform do: Data Extraction and Transmission and Distribution Process Integration Operations Data - Operation sensor data Analytics for - Equipment maintenance log - Reliability data Maintenance Operations Real-time predictive Analytics Data Mining Scoring Engineer Engineer Alerting Planner Planner Technician Technician  SAP AG 2002, Title of Presentation, Speaker Name 42
  43. 43. Scenario 5: Energy Data Management Combine meter reading data and customer master data to analyze usage patterns and to identify the consumption of empty installations – Identify Non-Billed Installations Produce a list of POD (Point of delivery) belonging to a service provider – Regulatory Reporting Advanced Analysis on Customer Movement – „Know Your Customers“ Energy Capital Management What should a Platform do: Data Extraction and Process Integration Enterprise Data Warehousing APD including Data Mining  SAP AG 2002, Title of Presentation, Speaker Name 43
  44. 44. Scenario 6: Integrated Sales Planning and Analysis Calculation of contribution margin on customer level – Customer Profitability Analyze open opportunities, sales orders and sales contracts to compare forecasting vs. actual data – Improve forecast accuracy Analysis for tracking the status of sales documents, expected and actual revenues and backorders – Increase Revenue Selling of Energy and Services What should a Platform do: Sales Pipeline and Funnel Analysis Contract Analysis Sales Planning and Forecasting Sales Quotation and Order Analysis, Activity Analysis Opportunity Analysis  SAP AG 2002, Title of Presentation, Speaker Name 44
  45. 45. Scenario 7: Customer Analytics Customer Segmentation (based on Margin, Consumption, Amount, Social, Payment Behavior) to be used by Marketing Campaigns and Customer Analytics - Retaining and Reacquiring Customers Last change of business partner (consumption, rates, payment type) for Marketing Analysis – „know your customer behavior“- Customer Profitability Selling of Energy and Services What should a Platform do: Perform Advanced Analysis using Data Mining Methods Collect relevant data Enterprise Data in SAP BI Warehousing APD including Data Mining Deploy Results to CRM as Target Group Selection Customer Lifetime Value (CLTV) Analysis Connection to back-end system ”Close the loop” Use Segment Builder in CRM for further refinements Execute Campaign  SAP AG 2002, Title of Presentation, Speaker Name 45
  46. 46. Scenario 8: Financial Analytics Automation of data transfer, consolidation, integrated planning, fleixble and powerful reporting – Reduce monthly closing and budget cycle Transparency, and single version of truth. Reliable and auditable data. Right- time reporting, exception notification and alerts - Reliability, completeness and transparency Analyze open items, Day Sales Outstanding (DSO) - ”Payment Behavior” Customer Financial Management What should a Platform do: Data Extraction and Process Integration Business Consolidation Planning & Simulation Balanced Scorecard Risk Management Tax calculation Link to operational systems  SAP AG 2002, Title of Presentation, Speaker Name 46
  47. 47. The different BI Layers Access Business Logic Presentation Summarized, Business Calculations Drill-Down, Drill- Open Interface and Web Services Dimensional Common Read / Write Interface Business Planning and Through, Drill-Across Data Pivoting Simulation Granular, Exception Scanning What If User Interaction Data Acquisition Volatile Data Slice and Dice Alerting Gallery of ready-to- Master Data Query Pre-Calculation use Web Templates / Caching Items Background Printing Table, Chart RDBMS Data Mining Map Data Alert Monitor Partitioning Context Menu Indexing Parallel Querying DWH Layer OLAP Engine BI Platform BI Suite Database & Mgmt. Analytical Functionality Navigation  SAP AG 2002, Title of Presentation, Speaker Name 47
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×