Session attendees learned the strategies and techniques of an ideal project example to modernizing finance analytics capabilities using a business-led and technology enabled approach.

1. 1
840 US radio stations
175MM+ downloads
241MM listeners (all radio)

2. 2
750K+ displays
over 50 countries
more than just billboards
multi-platform reach

3. 3
modernizing clear channel
time to modernize finance
at clear channel

4. 4
The dogmas of the
quiet past are inadequate
to the stormy present.
The occasion is piled high
with difficulty, and we
must rise with the
occasion. As our case is
new, so we must think
anew and act anew…
“
“

5. 5
more
transparency
escaping the vortex
…and begin to release the
potential to create new value
Catalyst Strategist
Steward Operator

6. 6
how we’re shifting from…
vortex valueto
we strive for balance
Finance
Analytics

7. 7
people were compensating for
deficiencies
Finance
Analytics
we gain efficiencies though modernization of
technology and process
Finance
Analytics

8. 8
and gain effectiveness though modernization
of people and information
Finance
Analytics
to elaborate,
we are…

9. 9
Inconsistent
business logic
Unstructured,
unrepeatable
data * ComputerWorld
90% of spreadsheets
contain at least 1 error*
Offline data
removing the duct tape!
simplifying the Rube Goldberg
machines

10. 10
modernizing the role of
finance, too
http://youtu.be/3EadrFE2o3E
mindful of the effects
How we perceive
what we build
How others perceive
what we build

11. 11
current overall solution
BI
Summary
Financial Data
(Actual, Budget,
Forecast)
GL Detail
from MS
AX
Countries
Summary
Data from
Non-MS AX
GLs
CCOA and
CCME
Summary
Financial Data
(Actual)
Business Viewpoint
(Mappings and Hierarchies)
FSR
Controller
(CCUS)
TM1
Close
Analytics
TM1
Plan, Budget,
Forecast
IBM Cognos
Products
Other Vendor
Products
Operational Data Store and EDW Controller (CCI)
Feeder Systems:
PeopleSoft and Other GL Systems,
BoB, Ratings, Rates, Occupancy, etc.

12. 12
automate
standardize
control

13. 13
Cognos TM1
from g/l to financial statements
automate
Financial
Statements
(Internal &
External Views)
Variance
Commentary
control
0
2
4
6
Analysis
standardize
Source Summary
Trial Balances
MONTHLY INCOME
STATEMENT TEMPLATE
Fiscal Year
2013
Period
Apr
Business Unit
808 - LOS ANGELES
MARKET
Currency
USD - Constant
Collapse / Expand
Collapse All
CM Act Adj vs
CM Act Adj vs
CM Act Adj vs
CM Act Adj vs
CM Act Adj vs
CM Act Adj vs
CM Fcst
CM Fcst %
CM Bdgt
CM Bdgt %
PYSM
Act Adj
PYSM Act Adj %
4110 - POSTING/PREMIER
REVENUE
POSTING REVENUE
1,357,834
1,357,834
0
0.0%
Variance due to higher than anticipated occupancies.
1,193,425
164,409
13.8% Variance due to a 12% higher than
1,083,697
274,136
25.3% Variance due to both higher blended
4110 - POSTING/PREMIER
REVENUE
PREMIER
PANEL REVENUE
648,308
648,308
0
0.0%
Variance due to higher than anticipated occupancies. New
624,435
23,873
3.8%
643,769
4,539
0.7%
4130 - BULLETIN REVENUE
BULLETIN REVENUE
3,522,704
3,522,704
0
0.0%
3,487,083
35,621
1.0%
3,446,694
76,010
2.2%
4140 - WALLSCAPE/SPECTAC
ULAR/SCAFFLWALLSCAPE/SPECTACULAR/SCAFFLD
324,286
324,286
0
0.0%
270,000
54,286
20.1% While
rate remained relatively flat to budget,
261,880
62,406
23.8% Our strongest driver was Occupancy
4150 - DIGITAL SIGN REVENUE
DIGITAL SIGN REVENUE
1,392,576
1,392,576
0
0.0%
Digital Losses from LACity Decision
3,298,735
(1,906,159)
(57.8%) Decrease due to LACityDecision to force LA
2,989,708
(1,597,132)
(53.4%) Decrease due to LACityDecision to
4180 - SHELTER
REVENUE
SHELTER
REVENUE
520,550
520,550
0
0.0%
455,891
64,659
14.2%
Increases due to better packaging
of shelter
430,555
89,995
20.9%
Strongest Drivers here were
4200 - EMBELLISHMENT/SS/PRODUCTION EMBELLISHMENT/SS/PRODUCTION
80,066
80,066
0
0.0%
Since
we've
been trending high on production revenue we
203,646
(123,580)
(60.7%) Since we've been trending high on
276,223
(196,157)
(71.0%) Losses of production revenue from
4270 - OTHER REVENUE
OTHER REVENUE
2,711
2,711
0
0.0%
4,081
(1,370)
(33.6%)
617
2,095
339.6%
NET REVENUE
+ REVENUE
7,849,035
7,849,035
0
0.0%
9,537,296
(1,688,260)
(17.7%)
9,133,144
(1,284,108)
(14.1%)
5101
- POSTING
OPERATING EXPENSE
74,450
74,450
0
0.0%
70,851
(3,599)
(5.1%)
66,943
(7,507)
(11.2%)
5201 - BULLETIN DIRECT
OPERATING EXPENSE
20,688
20,688
0
0.0%
Variance due to vinyl we produced for Panda Expense that was
10,472
(10,216)
(97.6%) Variance due to vinyl we produced for Panda
10,390
(10,298)
(99.1%) Variance due to vinyl we produced for
5204 - EMBELLISHMENTS
OPERATING EXPENSE
5,463
5,463
0
0.0%
5,076
(387)
(7.6%)
4,070
(1,393)
(34.2%)
5205 - ROTATE
OPERATING EXPENSE
145,888
145,888
0
0.0%
Variance due to high wage/premium
wages due to higher
117,401
(28,488)
(24.3%) Variance due to high premium wages of $17
104,956
(40,933)
(39.0%) Variance due to high premium wages
5206 - WALLSCAPE/SPECTAC
ULAR/SCAFFOOPERATING EXPENSE
24,768
24,768
0
0.0%
Variance due to timing of Utah Tourism Campaign. We had
46,554
21,786
46.8% Variance due to timing of Utah Tourism
86,236
61,468
71.3% Variance due to timing of Utah
5250 - TRANSIT
OPERATING EXPENSE
0
0
0
0.0%
0
0
0.0%
1,423
1,423
100.0%
5251 - SHELTER
OPERATING EXPENSE
92,389
92,389
0
0.0% Variance due to savings in outside services as we train our
103,047
10,658
10.3%
Variance due to savings in outside services
105,364
12,975
12.3%
Variance due to savings in outside
5254 - DIGITAL SIGNS
OPERATING EXPENSE
26,030
26,030
0
0.0%
28,118
2,089
7.4%
27,778
1,748
6.3%
5260 - SIGN SHOP
OPERATING EXPENSE
30,691
30,691
0
0.0%
Variance due to lower embellishment revenue.
19,671
(11,020)
(56.0%) Comment Required
19,489
(11,202)
(57.5%) Comment Required
5310 - MAINTENANCE - CAPITAL
OPERATING EXPENSE
0
0
0
0.0%
0
(0)
0.0%
(0)
(0)
0.0%
5402
- INDIRECT OPERATIONS
OPERATING EXPENSE
98,481
98,481
0
0.0%
100,454
1,973
2.0%
107,619
9,138
8.5%
5403
- GARAGE
OPERATING EXPENSE
67,193
67,193
0
0.0%
Variance due to lower than anticipated repairs on vehicles. We
69,542
2,348
3.4%
64,835
(2,358)
(3.6%)
5410 - SAFETY/ENVIRONMENTAL
OPERATING EXPENSE
9,314
9,314
0
0.0%
7,286
(2,027)
(27.8%)
6,697
(2,616)
(39.1%)
5411 - MAINTENANCE - EXPENSE
OPERATING EXPENSE
109,224
109,224
0
0.0%
Variance due to Daktronics reduction as a result of Digital
115,193
5,969
5.2%
115,669
6,445
5.6%
5412 - ELECTRICAL
OPERATING EXPENSE
168,886
168,886
0
0.0%
Electrical Accrual added back $21K. The remaining variance
205,797
36,911
17.9% Electrical Accrual added back $21K. The
197,905
29,019
14.7% Electrical Accrual added back $21K.
5414 - TAKEDOWNS
OPERATING EXPENSE
11,919
11,919
0
0.0%
10,867
(1,052)
(9.7%
)
3,812
(8,107)
(212.7%)
5510 - SITE LEASE
OPERATING EXPENSE
2,562,127
2,562,127
0
0.0%
2,534,049
(28,078)
(1.1%
)
2,560,123
(2,004)
(0.1%
)
5520 - REAL
ESTATE
OPERATING EXPENSE
45,567
45,567
0
0.0%
44,666
(902)
(2.0%
)
41,932
(3,635)
(8.7%
)
5532 - PUBLIC AFFAIRS
OPERATING EXPENSE
40,630
40,630
0
0.0%
Variance due to un-used contributions as we had to focus
79,442
38,812
48.9%
Variance due to low outside service fees as
85,380
44,750
52.4%
Variance due to reclass of Fiona
5598 - SALES
OPERATING EXPENSE
433,039
433,039
0
0.0%
Variance due mostlyto commission expense in two parts 1)
500,837
67,798
13.5%
Variance due mostlyto comm
ission expense
478,843
45,804
9.6%
Variance due mostly to comm
ission
5599
- MARKETING & PROMOTIONS
OPERATING EXPENSE
27,704
27,704
0
0.0%
Variance due to missed billing from Arbitron from PYwhen
22,093
(5,611)
(25.4%)
23,977
(3,727)
(15.5%)
5731
- G&A
OPERATING EXPENSE
81,430
81,430
0
0.0%
Variance due to an improvement in Bad debt expenses as this
124,520
43,090
34.6% Variance due to an improvement in Bad debt
79,546
(1,884)
(2.4%)
5820 - LEGAL
OPERATING EXPENSE
0
0
0
0.0%
336
336
100.0%
0
0
0.0%
5880 - FACILITY/OFFICE
OPERATING EXPENSE
52,903
52,903
0
0.0%
Variance due to lower telephone expense
57,925
5,023
8.7%
57,515
4,612
8.0%
5890 - INSURANCE
OPERATING EXPENSE
90,819
90,819
0
0.0%
92,280
1,461
1.6%
90,319
(500)
(0.6%)
5891 - TAXES/LICENSES
OPERATING EXPENSE
289,815
289,815
0
0.0%
292,571
2,756
0.9%
283,494
(6,321)
(2.2%
)
OPERATINGEXPENSES
+ OPERATING EXPENSE
4,509,418
4,509,418
0
0.0%
4,659,046
149,628
3.2%
4,624,316
114,898
2.5%
OIBDAN
+ ALL ACCOUNTS
3,339,617
3,339,617
0
0.0%
4,878,250
(1,538,633)
(31.5%)
4,508,827
(1,169,210)
(25.9%)
9110 - DEPRECIATION
OTHER EXPENSE
1,024,373
1,024,373
0
0.0%
1,004,408
(19,965)
(2.0%
)
1,012,578
(11,794)
(1.2%
)
9120 - AMORTIZATION
OTHER EXPENSE
(4,032)
(4,032)
0
0.0%
(4,032)
(0)
0.0%
(4,032)
0
0.0%
DEPRECIATION & AMORTIZATION
+ OTHER EXPENSE
1,020,340
1,020,340
0
0.0%
1,000,375
(19,965)
(2.0%)
1,008,546
(11,794)
(1.2%)
9150
- G/L ON SALE OF OPERATING ASSETOTHER EXPENSE
0
0
0
0.0%
(356)
(356)
100.0%
(356)
(356)
100.0%
OTHER INCOME & EXPENSE
+ OTHER EXPENSE
0
0
0
0.0%
(356)
(356)
100.0%
(356)
(356)
100.0%
NET INCOME
+ ALL ACCOUNTS
2,319,277
2,319,277
0
0.0%
3,878,230
(1,558,953)
(40.2%)
3,500,637
(1,181,359)
(33.7%)
Commentary
CM Bdgt
PYSM
Act Adj
CM Act Adj
CM Fcst
Commentary
Commentary
…capturing the story
behind the numbers
variance commentary…

14. 14
BI on TM1…
…oh yes we did!
we keep
building
on the
foundation
balance sheet
forecasting
cash flow
forecasting
CAFÉ
rolling
forecasts
AP and AR
analytics
automated
tie-outs
operational
data
international
localization
taxation dashboards

15. 15
leadership
commitment

16. 16
Business-led, technology-
enabled approach
invest in people,
not just tools

17. 17
take your testing seriously

18. 18
one last thing…
don‘t forget to download

19. 19
Thank You!

20. Vision2013Drive Growth. Manage Risk. Optimize Performance.
May 19-22, 2013 l JW Marriott Grande Lakes, Orlando, Florida
Preliminary Conference Guide

21. 13
ibm.com/software/analytics/vision
Financial and Operational Performance Management
1072
A Gentle Migration from IBM Cognos Planning
to IBM Cognos TM1 at Northrop Grumman
Speaker(s): Geoff Springfield, Northrop Grumman; Christopher
Poll, Northrop Grumman
Northrop Grumman’s Information Systems sector has been using
IBM Cognos products since 2004. In that time, the company has
developed robust planning and forecasting functionality. But as
the data sets and number of contributors grew, the organization
needed to boost performance to answer the demands from
users. However, rather than an immediate swap to IBM Cognos
TM1, Northrop Grumman implemented a gradual migration that
enabled users to reap many of the benefits as quickly as possible.
Users were able to see improved reporting and greater data
visibility before they even knew the words “Cognos TM1.” Attend
this session to learn how users were able to keep the look and
feel they were used to, and achieve the performance they needed.
Session Type: Best Practices
Level: Intermediate
1075
Migrating from IBM Cognos Planning to IBM
Cognos TM1 at Washington University: Tips,
Tricks, and Hurdles
Speaker(s): Jean Shuler, Washington University in St. Louis; Matt
Frederick, eCapital Advisors
Washington University in St. Louis has a very large IBM Cognos
implementation, with over 300 budgeting and 500 reporting
users. The university originally developed it annual budgeting
applications using IBM Cognos Planning. But because of the
large model sizes and the need for more real-time analysis and
reporting, WUSTL decided to migrate its Cognos Planning
applications to IBM Cognos TM1. The migration project was
successful and there were several learning experiences along
the way. Attend this session to hear about the project and see a
live demo of the university’s new Cognos TM1 model and user
analysis capabilities.
Session Type: Tips & Techniques
Level: Introductory
1077
Cooking up Savings
Speaker(s): Tim Dungan, Lone Star Steakhouse|Texas Land
& Cattle Steak House| Firefly Kitchen & Bar; Robert Hardin,
Perficient
As part of the spin-off from Brinker International, Romano’s
Macaroni Grill, with more than 200 locations, was faced with
creating a new analytics environment from scratch. After an initial
success with IBM Cognos Express, Macaroni Grill migrated to
IBM Cognos Business Intelligence and IBM Cognos TM1 to drive
its financial planning and analysis programs. In a competitive
market, it is crucial to get timely operational data to support the
team in the field and determine where to allocate resources to
improve sales and decrease labor costs. In this session, you’ll
learn how the finance team at Macaroni Grill incorporated
operational data to meet the needs of its line-of-business leaders
and bridge the divide between finance and operations.
Session Type: Best Practices
Level: Introductory
1079
Modernizing Finance at Clear Channel
Communications
Speaker(s): Brandon Turner, Clear Channel; Anthony D’Ugo,
Deloitte and Touche LLP
Faced with a processing, data, systems and talent crunch,
executives at Clear Channel Communications charted a path
forward to modernize their finance analytics capabilities.
Too often, organizations fall into a systems-led approach
and constrain their ability to realize true business value even
before they start. At this session, you’ll learn the strategies and
techniques that Clear Channel used to successfully implement
IBM Cognos Business Viewpoint, IBM Cognos TM1, IBM Cognos
Business Intelligence, IBM Cognos Controller, and IBM Cognos
Financial Statement Reporting (FSR). This project is an ideal
example of modernizing finance analytics capabilities using a
business-led and technology enabled approach.
Session Type: Product
Level: Intermediate