This document provides information about eCapital Advisors, a performance management and business analytics consulting firm. It discusses eCapital's founding, headquarters location, number of customers, employees, and service offerings such as strategic assessments, implementations, upgrades, training, and managed services across various industries. The document then outlines an agenda for discussing advanced allocations and actual efficiency through density and sparsity in Essbase.

1. Advanced Allocations
Jon Keskitalo
eCapital Advisors

3.  Founded in 2001 – Headquartered in
Minneapolis
 Performance Management & Business
Analytics consulting firm
 Over 250 customers
 eCapital Advisors employees
• Dedicated to Enterprise Performance Management
and Business Analytics, enabling clients to make
better business decisions
• Proven customer satisfaction and experience across
a variety of industries
• Advisory services, strategic assessments,
implementations, upgrades, training, customer
enablement and managed services
eCapital Advisors Overview

4. eCapital Service Offerings
 Strategic Assessments
• AgriBank, Children’s Hospital
 Implementations
• Ecolab, General Mills, Medtronic, Thomson Reuters
 Upgrades
• Ameriprise, Hormel Foods, Merrill Corporation
 Managed Services
• Prime Therapeutics, HB Fuller
 System Architecture and Infrastructure
• Every client
 Training
• Hyperion
• Oracle BI
• Oracle University Reseller

5. I believe in allocations

7. Agenda
Part 1 Believing in Allocations
Part 2 Actual, Real Efficiency

8. Agenda
Part 1 Believing in Allocations

9. What are allocations?

10. What are allocations?

11. What are allocations?

12. What are allocations?
W&W
Corporation

13. What are allocations?
W&W
Corporation

14. What are allocations?
W&W
Corporation

15. What are allocations?

16. What are allocations?

18. As-is Allocations

19. As-is Allocations
?

20. Result

21. Result

22. Result

23. Result: Lock it down

24. Result

26. Result: common issues
Boardroom confusion: “what is it?”
• “I may not be able to change it, I just want to know what it is”
Monolithic “Lower cost” driver
• The cheapest isn’t always the best
Uncontrolled costs
• No one is ‘technically’ responsible

27. What if

28. ?
?
What if
• Share of total
• Amount of total
• Details of total

29. ?
?
What if
• Share of total
• Amount of total
• Details of total

30. Result
• Share of total
• Amount of total
• Details of total

31. Result
• Share of total
• Amount of total
• Details of total

32. Result

34. Why does the black box happen?
• Inadequate Technology/Process
• Same issue as budgets/planning:
conventional tools are too slow and
static
• Pandora’s Box
• If you are going to open the box, you
need a tool you can address it
dynamically with (Inserting yourself into the
boardroom discussion)

35. I also believe in EPM
Flexible, Powerful,
Integrated, Elegant
Dynamic,
user-driven
allocations
Out of the box
functionality
Configuration,
Support
Configuration,
Support
New Technology,
Cost,
(lack of) Flexibility
Why
Why
Not
Essbase Planning HPCM*
*Hyperion Profitability and Cost Management
+

36. Part 2 Actual, Real Efficiency
How density and sparsity works in
Essbase
Density vs Sparsity

37. Into the mothership..
Density vs Sparsity

38. "Can you explain what sparse
and dense mean?"
Density vs Sparsity
- everybody

39. Totally Dense Totally Sparse
Density vs Sparsity

40. Density vs Sparsity

41. Classic Dimension Balance
Dense Dimensions Sparse
Dimensions
Period
Account
Division
Entity

42. ‘Classic’ Dense v Sparse Logic
Per01 Per02 Per03 Per04
District 1
District 2
District 3
District 4 485,257.11 77,834.50 77,834.50
District 5
District 6 266,486.93 24,341.23 24,341.23
District 7 344,691.25 31,179.95 31,179.95
District 8
District 9
District 10 244,573.50 244,573.50 18,748.54 18,748.54
District 11
District 12 8,074.79 8,074.79 840.35 840.35
District 13 261,755.20 261,755.20 24,586.03 24,586.03
District 14 48,025.70 48,025.70 5,894.05
District 15 476,684.45 476,684.45 45,825.66
District 16 172,732.59 172,732.59 18,555.22 18,555.22
District 17 15,903.22 15,903.22 1,691.53 1,691.53
District 18
District 19
District 20
District 21 461,529.89 461,529.89 70,084.34 70,084.34
Not so
dense
Pretty
dense

43. ‘Classic’ Dense v Sparse Logic
Per01 Per02 Per03 Per04
District 1
District 2
District 3
District 4 485,257.11 77,834.50 77,834.50
District 5
District 6 266,486.93 24,341.23 24,341.23
District 7 344,691.25 31,179.95 31,179.95
District 8
District 9
District 10 244,573.50 244,573.50 18,748.54 18,748.54
District 11
District 12 8,074.79 8,074.79 840.35 840.35
District 13 261,755.20 261,755.20 24,586.03 24,586.03
District 14 48,025.70 48,025.70 5,894.05
District 15 476,684.45 476,684.45 45,825.66
District 16 172,732.59 172,732.59 18,555.22 18,555.22
District 17 15,903.22 15,903.22 1,691.53 1,691.53
District 18
District 19
District 20
District 21 461,529.89 461,529.89 70,084.34 70,084.34
Sparse dim Dense dim
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block

44. ‘Classic’ Dense v Sparse Logic
District 4 485,257.11 77,834.50 77,834.50
District 6 266,486.93 24,341.23 24,341.23
District 7 344,691.25 31,179.95 31,179.95
District 10 244,573.50 244,573.50 18,748.54 18,748.54
District 12 8,074.79 8,074.79 840.35 840.35
District 13 261,755.20 261,755.20 24,586.03 24,586.03
District 14 48,025.70 48,025.70 5,894.05
District 15 476,684.45 476,684.45 45,825.66
District 16 172,732.59 172,732.59 18,555.22 18,555.22
District 17 15,903.22 15,903.22 1,691.53 1,691.53
District 21 461,529.89 461,529.89 70,084.34 70,084.34
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block

45. ‘Classic’ Dense v Sparse Logic
District 4 485,257.11 77,834.50 77,834.50
District 6 266,486.93 24,341.23 24,341.23
District 7 344,691.25 31,179.95 31,179.95
District 10 244,573.50 244,573.50 18,748.54 18,748.54
District 12 8,074.79 8,074.79 840.35 840.35
District 13 261,755.20 261,755.20 24,586.03 24,586.03
District 14 48,025.70 48,025.70 5,894.05
District 15 476,684.45 476,684.45 45,825.66
District 16 172,732.59 172,732.59 18,555.22 18,555.22
District 17 15,903.22 15,903.22 1,691.53 1,691.53
District 21 461,529.89 461,529.89 70,084.34 70,084.34
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
index

46. From the “Database Administrators Guide”

47. From the “Database Administrators Guide”
“If a database has 10 existing blocks and 100
potential blocks, the overhead is as much as ten
times what it would be without the complex
formula… as many as 90 extra blocks to read and
potentially write to”

48. District 4 485,257.11 77,834.50 77,834.50
District 6 266,486.93 24,341.23 24,341.23
District 7 344,691.25 31,179.95 31,179.95
District 10 244,573.50 244,573.50 18,748.54 18,748.54
District 12 8,074.79 8,074.79 840.35 840.35
District 13 261,755.20 261,755.20 24,586.03 24,586.03
District 14 48,025.70 48,025.70 5,894.05
District 15 476,684.45 476,684.45 45,825.66
District 16 172,732.59 172,732.59 18,555.22 18,555.22
District 17 15,903.22 15,903.22 1,691.53 1,691.53
District 21 461,529.89 461,529.89 70,084.34 70,084.34
District 1
Has to create
all potential
blocks for
District 1
Fix(“Per01”)
“District 1”=“District 4”;
Endfix;
Fix(“District 14”)
“Per04”=“Per01”;
Endfix;
The Cost of Calculation

49. US District 4 485,257.11 77,834.50 77,834.50
US District 6 266,486.93 24,341.23 24,341.23
US District 7 344,691.25 31,179.95 31,179.95
US District 10 244,573.50 244,573.50 18,748.54 18,748.54
US District 12 8,074.79 8,074.79 840.35 840.35
US District 13 261,755.20 261,755.20 24,586.03 24,586.03
US District 14 48,025.70 48,025.70 5,894.05
US District 15 476,684.45 476,684.45 45,825.66
US District 16 172,732.59 172,732.59 18,555.22 18,555.22
US District 17 15,903.22 15,903.22 1,691.53 1,691.53
US District 21 461,529.89 461,529.89 70,084.34 70,084.34
US District 1
Canada District 1
Mexico District 1
Brazil District 1
Honduras District 1
Guatemala District 1
Argentina District 1
… District 1
Fix(“Per01”)
“District 1”=“District 4”;
Endfix;
Fix(“District 14”)
“Per04”=“Per01”;
Endfix;
The Cost of Calculation
Has to create
all potential
blocks for
District 1

50. Has to create
all potential
blocks for
District 1
The Cost of Calculation
Fix(“District 14”)
“Per04”=“Per01”;
Endfix;
Fix(“Per01”)
“District 1”=“District 4”;
Endfix;

51. ‘Existing Block’
overhead
‘Potential Block’
overhead
The Cost of Calculation

52. The Cost of Calculation
P&L
Allocation
Calc
Footprint

53. Dense Dimensions
Accounts
Periods
Countries, Divisions
Calc
Footprint

54. As-is Approach
P&L
Allocation

55. New Approach
P&L
Alllocation
Calc
Footprint

56. Dense Dimensions
Accounts
Periods
Countries, Divisions
Calc
Footprint

57. ?
?
Black box way
Transparent way
An example

58. ‘Classic’ to ‘Allocation’
US Canada Mexico Panama Brazil Argentina
Gross Revenue 500,000 200,000
Sales Allowances 100,000 50,000
Net Revenue 400,000 150,000
std labor 50,000 10,000
std material 55,000 12,000
Standard Cost 105,000 22,000
Standard Contribution 295,000 128,000
Plant Variance 18,000 8,000
Gross Margin 277,000 120,000
Selling 30,000 10,000
G&A 33,000 8,000
SG&A 63,000 18,000
Operating Profit 214,000 102,000
Allocations
OP with Allocations 214,000 102,000
Pretty
dense
Not so
dense

59. US Canada Mexico Panama Brazil Argentina
Gross Revenue 500,000 200,000
Sales Allowances 100,000 50,000
Net Revenue 400,000 150,000
std labor 50,000 10,000
std material 55,000 12,000
Standard Cost 105,000 22,000
Standard Contribution 295,000 128,000
Plant Variance 18,000 8,000
Gross Margin 277,000 120,000
Selling 30,000 10,000
G&A 33,000 8,000
SG&A 63,000 18,000
Operating Profit 214,000 102,000
Allocations
OP with Allocations 214,000 102,000
Dense dim Sparse dim
‘Classic’ to ‘Allocation’

60. US Canada
Gross Revenue 500,000 200,000
Sales Allowances 100,000 50,000
Net Revenue 400,000 150,000
std labor 50,000 10,000
std material 55,000 12,000
Standard Cost 105,000 22,000
Standard Contribution 295,000 128,000
Plant Variance 18,000 8,000
Gross Margin 277,000 120,000
Selling 30,000 10,000
G&A 33,000 8,000
SG&A 63,000 18,000
Operating Profit 214,000 102,000
Allocations
OP with Allocations 214,000 102,000
Dense dim Sparse dim
BlockBlock
‘Classic’ to ‘Allocation’
Block Block

61. US Canada
Gross Revenue 500,000 200,000
Sales Allowances 100,000 50,000
Net Revenue 400,000 150,000
std labor 50,000 10,000
std material 55,000 12,000
Standard Cost 105,000 22,000
Standard Contribution 295,000 128,000
Plant Variance 18,000 8,000
Gross Margin 277,000 120,000
Selling 30,000 10,000
G&A 33,000 8,000
SG&A 63,000 18,000
Operating Profit 214,000 102,000
Allocations
OP with Allocations 214,000 102,000
Dense dim Sparse dim
BlockBlock
‘Classic’ to ‘Allocation’

62. Every cost center *
every division *
every country
‘Classic’ to ‘Allocation’

63. US Canada Mexico Panama Brazil Argentina
Gross Revenue 500,000 200,000
Sales Allowances 100,000 50,000
Net Revenue 400,000 150,000
std labor 50,000 10,000
std material 55,000 12,000
Standard Cost 105,000 22,000
Standard Contribution 295,000 128,000
Plant Variance 18,000 8,000
Gross Margin 277,000 120,000
Selling 30,000 10,000
G&A 33,000 8,000
SG&A 63,000 18,000
Operating Profit 214,000 102,000
Allocations
OP with Allocations 214,000 102,000
Sparse dim Dense dim
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
Block
‘Classic’ to ‘Allocation’

65. ‘Classic’ to ‘Allocation’
‘Classic’ configuration
‘Allocation’ configuration

66. ‘Classic’ to ‘Allocation’
‘Classic’ configuration

67. ‘Classic’ to ‘Allocation’

68. ‘Classic’ to ‘Allocation’
fix(@relative(“division”,0),@relative(“country”,0),@relative(“yeartotal”,0)…

69. ‘Classic’ to ‘Allocation’

70. Total Block Created: [6.0032e+006] Blocks (6 Million)
Sparse Calculations: [6.0060e+006] Writes and [2.3598e+007] Reads (30
Million)
Dense Calculations: [0.0000e+000] Writes and [0.0000e+000] Reads
Sparse Calculations: [0.0000e+000] Cells Dense Calculations: [0.0000e+000]
Cells
[2015-09-30T16:43:43.343-21:43] [ALLOC3] [CAL-579] [NOTIFICATION]
[16][] [ecid:1443630732729,0] [tid:19144] Total Calc Elapsed Time for
[alloc.csc] : [234.239] seconds
‘Classic’ to ‘Allocation’

71. ‘Classic’ to ‘Allocation’
‘Allocation’ configuration

72. ‘Classic’ to ‘Allocation’

73. ‘Classic’ to ‘Allocation’
fix(@relative(“division”,0),@relative(“country”,0),@relative(“yeartotal”,0)…

74. ‘Classic’ to ‘Allocation’

75. Total Block Created: [3.6000e+001] Blocks (36)
Sparse Calculations: [1.1500e+002] Writes and [5.3900e+002] Reads (654)
Dense Calculations: [0.0000e+000] Writes and [0.0000e+000] Reads
Sparse Calculations: [0.0000e+000] Cells Dense Calculations: [0.0000e+000]
Cells
[Wed Sep 30 16:48:46 2015]Local/KESKI@AD/11760/Info(1012579)
Total Calc Elapsed Time for [alloc.csc] : [0.468] seconds
‘Classic’ to ‘Allocation’

76. Summary
Total Block Created: [3.6000e+001] Blocks (36)
Sparse Calculations: [1.1500e+002] Writes and [5.3900e+002] Reads (654)
Dense Calculations: [0.0000e+000] Writes and [0.0000e+000] Reads
Sparse Calculations: [0.0000e+000] Cells Dense Calculations: [0.0000e+000]
Cells
[Wed Sep 30 16:48:46 2015]Local/KESKI@AD/11760/Info(1012579)
Total Calc Elapsed Time for [alloc.csc] : [0.468] seconds
Total Block Created: [6.0032e+006] Blocks (6 Million)
Sparse Calculations: [6.0060e+006] Writes and [2.3598e+007] Reads (30
Million)
Dense Calculations: [0.0000e+000] Writes and [0.0000e+000] Reads
Sparse Calculations: [0.0000e+000] Cells Dense Calculations: [0.0000e+000]
Cells
[2015-09-30T16:43:43.343-21:43] [ALLOC3] [CAL-579] [NOTIFICATION]
[16][] [ecid:1443630732729,0] [tid:19144] Total Calc Elapsed Time for
[alloc.csc] : [234.239] seconds
P&L
config
Allocation
config
-VS-

77. Summary: ‘Classic’ config vs ‘Allocation’ config
Usually all periods and accounts have data in
them, so make those dimensions dense…
Classic
Allocation
Account either is not changing, or can be
seeded,
So Account dimension can be sparse

78. Potential use-cases
• Corporate allocations
• IT project tool
• Capex planning

79. Conclusion
• Improved performance for allocations
• FP&A in the middle, coordinating business
discussion
• From boom-bust spikes to more consistent
results

80. Questions