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
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.
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
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.
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
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.
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.
Plan is 92k – which is way to high! I’m ¾ into the third quarte and I know that my last quarter was 79k (already a big increase). Q3 should be more with Q2. Take a look at Road Bikes – they are 3 times what they were in Q2 and 4 times what they were in Q1. I could adjust the number to be 120 for instance.
Plan is 92k – which is way to high! I’m ¾ into the third quarte and I know that my last quarter was 79k (already a big increase). Q3 should be more with Q2. Take a look at Road Bikes – they are 3 times what they were in Q2 and 4 times what they were in Q1. I could adjust the number to be 120 for instance.
Gives me an objective of 470 quantities and 65k – much better.Now if I did that I just affect my road bikes. What happens if I want to run spreading – i.e I don’t know the details of quantities by bike type but I know that my target quantities should be no more than 210. I can use spreading.
