Microsoft office Performance Point

1. Microsoft office Performance Point

4. Integrates Business Scorecard Manager 2005 and Proclarity Dashboard Server

5. Understand data through advanced analytic tools and visualizations

6. Augments SQL and Excel with next generation Proclarity capabilities

7. Empower knowledge workers to manage enterprise data and business rules

9. End to End PPS

10. Report Views Analytic Charts /Grids Strategy Maps Excel Services views Sqlserver reporting services

13. Excel Services views

14. PAS views

15. Sqlserver reporting services views

16. Demo

17. KPIs Thresholds Scoring Weighting Properties Custom Indicators

18. Scorecards

19. Dashboards Consolidated Dashboards Rich UI components Business collaboration Diller down capabilities Filtering & manipulation capabilities Enterprise wide view & performance management

20. Advantages A complete and integrated performance management solution Performance management for all business users Monitoring and analyzing across the entire organization Advanced analytic and visualization capabilities Accountability from the individual to the enterprise Cross-enterprise view Built on the Microsoft Business Intelligence platform

21. Demo

22. This CFO uses Microsoft® Office SharePoint™ Server as a thin and personalized interface to her corporate information

23. One type of information that can be managed inside SharePoint is PerformancePoint scorecards.

24. This CFO can now consume very rich analytics And benefit from a full fledge scorecard (built here following the balanced scorecard methodology)

25. This CFO can now interact with very rich analytics

26. And drill into the data

27. As well as get quick information on KPIs by simply hovering over them.

28. In order to make better informed decisions, she needs to review related but unstructured information.

29. She opens the document library that is related to the scorecard in order to get a more complete view of her business.

30. She opens the strategy map that is related to this scorecard in order to understand how KPIs relate to each other.

31. Now, she wants to know if there is anything more she could review in order to complete her analysis.

32. The application suggests to review the finance scorecard

33. The finance scorecard focuses on finance metrics (revenue, cost, profit), across multiple quarters. The scorecard also display owners at the KPI level. She can now assign tasks to resolve issues based on the kpi ownership.

34. If she needs to, she can filter the scorecard.

35. When she does so, the scorecard and all related analysis views will be filtered accordingly, guaranteeing consistency of information.

36. She can also look at the annotations associated to the KPIs. Annotations allow her to gain more context and understand more than ‘just the numbers’.

37. She wants to drill thru the gross profit margin KPI because it currently shows some issues.

38. The following analytical view opens, presenting her with multiple applications to analyze the data. These applications will help her understand complex data much faster.

39. She first opens a ‘performance map’. This application provides a quick view of the data after 2 dimensions. Here the size of the box is determined by ‘sales amt’ and the color of the box represents ‘% Gross Margin’.

40. She understands that North America is selling a lot [their boxes are bigger]. NA doesn’t have margin issues compared to the other geographies [NA’s colors are green] This CFO drills under Europe

41. She can see product categories split across geographies

42. Or geographies spilt across product categories

43. She can drill up and down

44. And decompose the data further moving from the performance map to the decomposition tree.

45. Decomposition tree is a great and flexible way to ask your data very intuitive questions

46. As a first step, she goes down the product hierarchy But then switches to a geographical view to understand who sells the most road bikes, which is the bigger revenue category in bikes.

47. She then drills across to time dimension to understand when certain geos sell road bikes

48. The data can be analyzed across any geo At this point, we are using all available hierarchies in the data (product category, geography and time).

49. We can of course go back to a much simpler view

50. When users perform this type of analysis, they assume that they picked the right metrics to analyze the data by. Switching their analysis to a different metrics is often challenging.

51. Switching their analysis to a different metrics is very easy using the decomposition tree

52. The analysis is now ran the gross profit margin, but the CFO didn’t have to go through all the steps of the previous analytical path.

53. The CFO has now being able to resolve the margin issue. Holland is the country creating the problem in Europe: it was a top 3 in revenue, but the last performance from a margin standpoint The CFO can save and share this view with the rest of the organization.

54. The analysis can also be shared in PowerPoint in a static and dynamic mode.

55. Going back to the analytical view, the CFO notices that the revenue forecast is wrong

56. She collaborates with the owner of the forecast process in real time

57. Who suggests that she checks her email for a sales forecast update notification

58. The assignment opens in excel. Notice that the PerformancePoint™ functionality is available natively in excel. The user benefits from the flexible interface and the PerformancePoint functionality. Users get the right amount of information at the given point in time. Process and security transpire thru to the end-user experience.

59. Notice that the forecast # is the same as the number in the scorecard. The scorecard and the planning experience are integrated.

60. The yellow cells are the cells the user can contribute to. They represent the business drivers that determine the forecast numbers.

61. The CFO decides that the company will only sell 120 road bikes instead of 300.

62. The application then runs centrally stored calculation and logic. A new forecasting # appears.

63. While this model might work when you have a few subcategories, it is not highly scalable if you have many lines to update to show a new forecast.

64. This is when our customers use our ‘spreading’ functionality. Spreading allows end users to set a bottom line # and have rules and logic defined in PerformancePoint run the allocation at the sub-level.

65. Here, the CFO simply updates the total qty of bikes and the calculation engine spreads the result of centrally defined logic. The results could be based on seasonality or any other calculations defined on the server.

66. The CFO can roll up this analysis to the European forecast and include an annotation at the cell level to explain that the new allocation has been spread.

67. Annotations are stored centrally to enforce auditability of the forecast.

68. The form can be shared and submitted.

69. Comments at the assignment level can be added to share more contextual information. Like cell annotations, they are also stored centrally to facilitate auditability.

70. Once refreshed, the new forecast # is reflected in the scorecard.

71. Architecture

72. Data sources