Six Qualities of the Best Pricing Software

Pricing Toolbox - overview
•

Developed by professionals for professionals … pragmatic & operational

•

Functionalities
–
–
–
–

•

Data management (Transactional data, CRM, Market research, competitive Intelligence, …)
Sophisticated analytics & modeling
Flexible & intuitive reporting / data visibility
Supports all aspects of pricing & Value management

Platform & integration
–
–
–
–

Based On Microsoft’s Power BI Platform
‘portable’ SQL + Office + Add ons toolbox for rapid implementation
Connectablility to your info sources (ERP / Oracle / Data warehouse..)
Tools can be ‘transported’ to your platform if & when necessary

Page 2

Pricing Toolbox
What it is not
A

What it is
•Effective support to Pricing Performance

panacea that will by itself get your company improvement in companies
to higher levels of pricing performance … it

takes expertise & changing your ways of
working
An

off the shelf readymade solution to your
pricing analytics & management needs… we

believe nobody can offer that
A

‘black box’ that will take charge & manage
your pricing for you… we believe that your

expertise is key to making any pricing tool
relevant & effective and that you should stay in
charge

•An Integrated set of tools that can be adapted to
your situation to effectively support all aspect of
Pricing
–
–
–
–
–

Data Collection management
Pricing & Value Analysis & insights
Monitoring & reporting
Modeling, simulation & Decision support
Implementation support

•A flexible set of Tools based on SQL & office tools
supplemented by statiscal & modeling add-ons to
support sophisticated analysis & modeling

Page 3

Level 3
Pricing & Customer Value
reporting & Pricing Toolbox
Control
Reporting Analysis
P& L Reports

Traffic Lights
Performance Touring Handling AS
Price
Change

PRODUCT LEVEL PRICING TRAFFIC LIGHTS

Share
Growth

% Rel Share % Premium
vs Ref.
vs Ref.
Value
Win / Loss Elasticity
Comp
Comp Positioning Indicator Measure

#E440

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215/45R17 BW Z BRIDGESTONE TURANZA EL400-02

#E402


#E329

P215/45R17 BW W BRIDGESTONE TURANZA EL400-02

#G432

13%

0

1

8%

9

16%

0

1

8%

GM %

Action
Overall Required

Fullfilment

13%

1,5

61%

94%

0,60024934

7

20%

1,5

60%

85%

0,57732634

107

16%

0

1

8%

7

15%

2,0

54%

85%

0,53853075

77

BRIDGEST ONE POT ENZA RE92A AS
215/45R18 BW W BRIDGESTONE POTENZA RE92A AS

Discount
Change

97
115

BRIDGEST ONE

12%

0

1

8%

9

8%

1,9

59%

97%

0,59126945

59%
54%
59%

19%

0

1

8%

7

7%

1,9

59%

92%

0,58842208

58%

82

11%

0

1

8%

7

6%

1,2

41%

86%

0,40759921

40%

103

8%

0

2

8%

7

8%

0,9

53%

85%

0,53514842

8%

0

1

8%

9

7%

1,0

59%

87%

0,60924063

60%

#C193

117

5%

0

1

8%

9

4%

1,2

58%

98%

0,59778409

60%

P235/50R18 BW V BRIDGESTONE TURANZA EL42

0,46415437

46%

0,59362246

Y

52%

109

P235/45R17 BW W BRIDGESTONE TURANZA EL42

58%

BRIDGEST ONE T URANZA EL42

#E445

123

5%

0

1

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7

7%

1,6

45%

101%

P235/60R18 BW H BRIDGESTONE TURANZA EL42

#C010

82

3%

0

1

8%

7

8%

1,6

59%

84%


#G447

137

1%

0

1

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9

6%

1,1

45%

205/55R16 BW H BRIDGESTONE TURANZA EL42 RFT

85%

0,45843948

X
X

45%

95

1%

0

1

8%

9

4%

1,7

42%

99%

0,43203873

43%

#7334

94

1%

0

1

8%

8

2%

1,0

37%

101%

0,36211277

36%

Y
Y

BRIDGEST ONE T URANZA EL42 RFT


#E446

119

2%

0

1

8%

9

3%

1,2

40%

85%

0,38266467

38%


#7335

98

3%

0

1

8%

9

1%

1,6

37%

101%

0,37233824

37%


#E330

78

5%

0

0

8%

7

1%

2,3

41%

88%

0,40485926

40%

86

6%

0

0

8%

9

1%

3,3

57%

100%

0,56939127

56%

BRIDGEST ONE T URANZA ER30
205/45R16 BW W BRIDGESTONE TURANZA ER30

#7271

105

7%

0

0

8%

7

0%

4,9

55%

99%

0,53339714

54%


#7272

118

10%

0

0

8%

7

0%

6,8

58%

101%

0,59676541

59%


#7270

78

6%

0

0

8%

7

0%

4,9

59%

98%

0,60021896

60%


#7273

99

9%

0

0

8%

8

0%

4,3

39%

91%

0,39917475

40%


#7275

103

7%

0

0

8%

9

0%

2,7

53%

90%

0,51685851

51%


#C195

128

8%

0

0

8%

9

0%

3,5

54%

93%

0,53413606

53%

255/55R18XL BW Y BRIDGESTONE TURANZA ER30

#7269

116

7%

0

0

8%

7

0%

5,0

40%

85%

0,40320361

40%


Fin . Reports

Y

58%

73

#7274

75

8%

0

0

8%

7

0%

4,2

46%

85%

0,45598798

46%

Corridors

X
Y

Select Subject

Normal Screen
Select SBU
P1

Full Screen

S

P

Key Tools
Transactional Analysis
 Price evolutions
Objectives vs. Realized  Price Evolutions
Waterfall
Pricing & Value Waterfalls
 Price dispersion mapping
 Detailed variance analyses
 Time series
 Elasticities / Pricing
dynamics analyses
Exceptions Mngmt
Elasticities
Time Series
Revenue Variance

(UnitPrice T2 * UnitVolume T2 ) - (UnitPrice T1 * UnitVolume T2 )

Price Variance
(Unit PriceT2 - Unit PriceT1) * Unit VolumeT2

Menu-Tier Variance
(MenuTier(T2)_OldUnitPrice x VolumeT2) - (UnitPriceT1 x VolumeT2)

Item-Price Variance
(UnitPriceT2 x VolumeT2) - (MenuTier(T2)_OldUnitPrice x VolumeT2)

Promotional Item Price Variance
tbd - will be a special component of item-price

Client Conditions & Discount Variance

Volume Variance
(Unit VolumeT2 - Unit Volume T1) * Unit PriceT1

Mix Variance
(Unit VolumeT2 - (Unit Mix%T1 * Total VolumeT2)) * Unit PriceT1

Quantity Variance
((Unit Mix%T1 * Total VolumeT2)-Unit VolumeT1) * Unit PriceT1

Marketing & Sales support

Value Analysis

Reporting tools tools to help monitor, control & Ana.
Share Evolutions
Peer Pricing
PortFolio
manage Pricing & support effective implementation
of pricing policies

5

EVC / EVIU

Value Maps / curves

Pricing & Value
Leakages Management
Key Tools
 Pricing & Value Waterfalls
 Time series
 Elasticities / Pricing
dynamics analysesC

Transaction analysis tools to help monitor, control
& manage Pricing Performance & identify
opportunities for improvement

6

ns

Open Scenario
Save as
Insights, Budgeting & simulation tools
Stats & Simulations
Pricing Simulators

Portfolio Simulator

Network Simulator

D & R Savings

Segm. & Clusters

Regressions & stats

Pricing Process Performance
Analytical & simulation tools to help support
Strategic Decision making on Pricing & Value
Pricing BSC
Pricing Diagnostic
Pricing RACI
Strategies & implementation
7

Key Tools
 Pricing & Value modeling &
simulation
 Portfolio simulation
 Network simulation &
optimization
 Simulation of impact of
alternative Pricing or D&R
 Segmrentation & clustering
tools
 Regression & statiistical
tools

Benchmarking
Key Tools
 Share & competitive
performance monitoring
 Peer Pricing & Value selling
support
 Portfolio analyses
 Analyses of performance on
key Value attributes
 Campaign effectivenes
measurement & modeling
 Competitive & Pricing
Intelligence tools

Tools to help support Strategic Marketing
& Sales with a value focus & Marketing
effectiveness improvements

8

.

Item-Price Variance



Value analysis & measurement Tools

Volume Variance


Mix Variance


Quantity Variance

Value Analysis
EVC / EVIU

Value Maps / curves

Win / Loss


Elasticities

Key Tools
 Economic Value Modeling
Pricing BSC
Pricing Diagnostic
 Value Map & Curves
 Choices Based Conjoint
Modeling & simulation
 Win / Loss analyses
 Elasticities nalyses &
simulation
Pricing Price Points / Pricing Alignment
Thought Proc.

Psycholgical
Pricing analyses

CBC / Perceptions

Price Points
Product price occurence
(in comparable sales situation)
9
8
7
6
5
4
3
2

1
0
80

85

90

95

100

105

110

115

Occurrences

Tools to help Measure Value Perception &
Willingness to pay & elasticities & to use Value as a
base for Pricing

9

P

Ind

Process Performance tools

ns

Pricing Diagnostic

Pricing RACI

Pricing Thought Proc.

110

Pricing BSC

Pricing Alignment

Industry Pricing

115

Tools to help follow monitor, control & gradually
improve the strategic Pricing & Value management
capabilities of the company

10

Key Tools
 Pricing Balanced Score Card
 Pricing Diagnostics &
Improvement Roadmap
 Pricing Processes & RACI
 Pricing Thought Process
 Pricing Alignment reports
 Industry Pricing analyses &
decision support

Data Capabilities

Security and Data Privacy

Data Storage and Management
Functionality

Data Capabilities
Security and Data Privacy

• Secured environment
– All data is stored as necessary in a completely secured environment
• Microsoft Business Intelligence solutions
• MS SQL Server 2012 engine
• Sharepoint Server 2012, Powerpivot 2013

– Only project related personnel has access to data:
• Account Director
• Project Manager
• IS personnel 100% dedicated to project

• Data Privacy
– All Data kept confidential and Private
– Completely private space from other ongoing projects
• Server and Database
• Internal Network space and resources

Data Capabilities
Data Storage and Management

• MS Windows Server and SQL server technology fully adapted to
meet customer/account needs:
– Large data storage capability
• Able to adapt to any large size database

– Fully managed server environment with daily backups
• Data protection and restore services to previous versions

– Adaptable core processing power and internal memory
• Server Power adapted to size of database to match processing needs

– Fully dedicated server to customer / account

Data Capabilities
Functionality

Connectivity and Data Integration
Multiple Platform Support:
•Connection to nearly any data
source, from traditional relational
sources including like Oracle, SQL
Server, Sybase, DB2, Teradata,
Access, and any ODBC-compliant
platform.
•Connection to non-database sources
(including Excel and SharePoint) and
non-SQL systems (including
Salesforce.com, Business Objects,
and Oracle Business Intelligence
platforms).
•Run SQL queries against any of
these sources.
•Import Export Functionality

Data Capabilities
Functionality

Data Automation
•Scheduled Data downloads and
Uploads:



Download new data
Upload modified data

•Automation of tasks:
•

Calculations
 Applied logics and formulas
to data.

•

Data checks
 Data consistency

•

Transports
 Transport to any other linked
system for further analysis.

Data Capabilities
Functionality

Sync Validation
Scheduled synchronization:
•

Compare and synchronize data
between different data sources
to ensuring consistency and
validity.

•

Internal quality process
 Automated
 Manual

•

Rules validation
 Automated checks
 Reporting

Data Capabilities
Functionality

Advanced Analytics
•

Pre-build functionality for
speedy data analysis
 SQL queries
 Server Jobs

•

Automated queries to perform
cubed based data analysis
 Immediately available
reporting based on identified
needs.

•

Mathematical and Statistical
functions through SQL
services
 Capability to add or update
records on the go

Data Capabilities
Functionality

Data Cleansing
•

Identify and correct data
inconsistencies:





Format
Grouping
Relationships
Calculations

•

Maintain original data on
backup database for future
queries

•

Programmable cleansing
procedures to always perform
same actions once identified.

•

Reports availability for data
comparisons

Transactional Analyses
Key Tools
 Pricing & Value Waterfalls
 Time series
 Elasticities / Pricing dynamics
analysesC

Transaction analysis tools to help monitor, control
& manage Pricing Performance & identify
opportunities for improvement
22

Tool 1: Price Evolutions(Illustrative)
Plant Name
Industry Name
Custo Rev Segment Name
Product Family Code
Product Grp Code
Prod Rev Segment Name

(All)
(All)
5_VL
(All)
(All)
(All)

Pricing

Normal

Full Screen

64,00

SKU Unit Prices ($)

What it is:
Analyses Prices (or D&R)
Go to Product Pivot over time
evolutions
Go toMay be used for a single
Price Evolution
product or a group of products,
Go to SKU Elasticity
globally or by client segments /
Go to Product Elasticityby account manager.
channel, or
Go to Financial Pivot

32,00
Ac1
Ac10

16,00

Ac11

Ac12
Ac13

8,00

Ac14
Ac15
4,00

Ac16

Ac17
Ac18
2,00

1,00
nov.-07

juin-08

déc.-08

juil.-09

janv.-10

août-10

févr.-11

Go to Customer Elasticity

What it does:
provide visibility and insights
on evolutions to identify trends /
changes in dynamics or
correlations & opportunities &
threats that they represent

sept.-11

Tme Series (Weeks)

Corrective actions it may lead to:
Improved / more rational pricing on objectives.
Industry pricing actions to influence pricing dynamics
Price structure rebalancing
The stakes:
Together with other aspect of transactional analyses, typically results in bottom line improvement of up 4
% of sales in the first year
Page 23

Flexible tool integrated in Transactional
analysis

24

Tool 2: Dynamic Price Waterfall
(Illustrative)

Dynamic Waterfall Analysis

What it is:
Detailed analyses of
leakages (by type) that take
place between List price &
Pocket Margin.
May be used at Product,
Client, Segment or Market
level

100%
90%
80%
70%
60%
List Price
Results

Price
Concession

100%

Invoice
Price

Options

Warranty $ Financing

Prompt
Pay

92.7%

Margin/
COGS
14.1%

Leakages

7.3%

0.9%

1.0%

4.6%

1.4%

Series1

93%

92%

91%

86%

70.6%

85%

What it does:
provide visibility and control
of ‘hidden’ discounts and
costs to clarify the
contribution margin on a
given deal.

Rationalization of discount & client conditions policies.
Improved control & exceptions management on Discounts & Client Conditions
Sales force support & Monitoring
The stakes:
Together with Price dispersion analyses, typically results in 2 to 4 % ROS improvement in first year
Level 2 Tools

Page 25
Page 25

Pricing

FULL

Dynamic Waterfall

USUAL

100%

ADJUST
COLUM

80%

60%
aa

40%

A Profile Selection

aa
aa
aa
aa
aa
aa
aa

20%

B Profile Selection

0%

6,5%

4,5%

13,6%

Fiscal Year

2009

10,4%

6,4%

4,5%

13,9%

Fiscal Month

(All)

Region Name

(All)

A-B

0,2%

0,0%

-0,3%

0,0%

0,0%

-0,6%

0,0%

0,0%

0,0%

0,0%

1,0%

-1,0%

0,0%

0,0%

0,2%

0,1%

0,0%

-0,3%

Region Name

(All)

Acct Mngr Name

(All)

aa

Acct Mngr Name

(All)

Customer Name

(All)

aa

Customer Name

(All)

Industry Name

(All)

aa

Industry Name

(All)


(All)

aa


(All)

Material GrP Name

(All)

aa

Material GrP Name

(All)

Product Name

(All)

aa

Product Name

(All)


(All)

aa


(All)

Plant Name

(All)

aa

Plant Name

(All)

26

NET NET MARGIN

10,5%

0,0%

Other Mktg Costs

0,0%

0,0%

Client Recruiting
Costs

0,0%

-40,1%

Client Mngmt
Costs

-41,2%

75,3%

Gross Margin

76,3%

2,0%

Client Technical
Costs

2,0%

2,0%

Cost of Goods
Sold

1,9%

7,0%

Net Sales

7,1%

0,0%

Unbilled
Guarrantees

0,0%

5,8%

Unbilled Services

5,2%

0,0%

Total Rebates

0,0%

0,9%

Invoiced Sales

0,9%

8,4%

Discretionary

8,1%

0,0%

Other Discounts

0,0%

100,0%

Full Truck
Discount

100,0%

102,6%

Early Payment
Discount

102,8%

B Profile

Volume Discount

A Profile

(All)

Sales Gross
Revenues

(All)

Fiscal Month

Theoretical
Revenues

Fiscal Year

Tool 3: Price Dispersion (Illustrative)
National
40%

What it is:
Analysis of discounts given as
a function of size of accounts.
May be used for a single
channel, or by account manager.

Lack of control &
discipline

Large discounts
given to small
accounts
/ not taken away
from reduced

Avg Discount

Average discount

30%

20%

What it does:
provide visibility and control of
actual logic & discipline in the
implementation of Client
conditions & discounts.

Standard volume discount
Large accounts put
at risk by unfair
treatment

10%

0%
0

50,000

100,000

150,000

Size of account (Yearly revenues €)

Rationalization of discount & client conditions policies.
Improved control & exceptions management on Discounts & Client Conditions
Sales force support & Monitoring
The stakes:
Together with Price dispersion analyses, typically results in bottom line improvement of up 4 % of sales
in the first year
Page 27

Price Dispersion Tool
All

Disc. & Reb. Selection

Selected
Selected

List to Max Price Disc.

Selected

Early Payment Discount

Selected

Full truck Discount

Selected

Discretionary Discount

Selected

Rebates
Unbilled Services

Selected

Unbilled guarrantees

Selected

Client Management Costs

Selected

Recruiting Costs Alloc

Selected

Marketing Costs Alloc

Selected

Max to Client Price Disc.

Selected

USUAL
SCREEN

ADJUST AXES

AUTO
AXES

Selected

10

Dynamic Dispersion Map
Map Options

StdVolume Discount

0

Y: Disc. & Reb. (% Gross Sales) Map - Y:
Dynamic Dispersion

X: Gross Sales
Bubbles: Gross Profit

-10
-20

30

Apply Zoom
Y MAX

-40
-50

220% Speed

Detected

-30
Manual & Auto Zoom

Unexplained Disc

FULL
SCREEN

MAP
Dynamic Dispersion Map - Y: Disc. & Reb. (% Gross Sales) , X: Gross Sales

Pricing

0% Apply

Y MIN

-140% Speed
1 Speed

1

12 911 Apply
-90 Speed

10

Apply
X MAX

2 000

X MAX
X MIN
Detected

-60
-4 000

Customer Name

(All)

Market Name

(All)

Market Segment Name

(All)

Customer Breath Name

(All)


(All)

Material GrP Name

(All)

Product Family Name

(All)

Product Grp Name

(All)

Plant Name
Prod Hier Name

(All)
(All)
(All)

a
a
a

100%

Manual Y MIN

X MIN

Profile B

D&R & Other Mktg. (% (% Net Sales) Profit (% Net Sales)
COGS Gro
Gross
Gross Sales

D&R & Other Mktg. (% (% Net Sales
COGS Gro
Gross Profit

Code

Gross Profit (%
Net Sales)

(All)

16 000

COGS (% Net
Sales)

Acct Mngr Name

a
a
a
a
a
a
a
a
a
a

14 000

D&R & Other
Mktg. (% Gross
Sales)

(All)

12 000

Gross Sales

Region Name

Profile A

10 000

Gross Profit (%
Net Sales)

a

Gross Sales

Top Ten

DATA TABLE

B

8 000

COGS (% Net
Sales)

(All)

6 000

D&R & Other
Mktg. (% Gross
Sales)

Industry Name

4 000

Gross Sales

(All)

2 000

Auto Graph Nº

2009

Fiscal Month

0

A

Manual Graph Nº

Fiscal Year

a
a
a
a
a

Manual Y MAX

-2 000

Region Name

(All)

22

West

West

2_S

12 752

-47,51%

52,43%

47,57%

12 911

-5,06%

54,21%

45,79%

Acct Mngr Name

(All)

23

West

West

3_M

11 197

-45,09%

53,40%

46,60%

10 842

-3,96%

54,54%

45,46%

Customer Name

(All)

2

Central

Central

2_S

9 752

-54,42%

57,84%

42,16%

9 476

-4,18%

58,45%

41,55%

Market Name

(All)

3

Central

Central

3_M

9 106

-53,63%

60,02%

39,98%

8 766

-3,78%

60,78%

39,22%

Market Segment Name

(All)

12

North

North

2_S

8 683

-55,21%

59,48%

40,52%

8 822

-4,00%

60,60%

39,40%


(All)

17

South

South

2_S

7 717

-49,86%

53,82%

46,18%

7 260

-2,98%

53,93%

46,07%


(All)

13

North

North

3_M

7 518

-50,55%

57,43%

42,57%

7 246

-2,92%

57,01%

42,99%

Material GrP Name

(All)

18

South

South

3_M

6 956

-46,67%

55,16%

44,84%

6 596

-2,57%

56,50%

43,50%

Product Family Name

(All)

7

East

East

2_S

6 904

-56,40%

59,16%

40,84%

6 835

-3,18%

60,83%

39,17%

Product Grp Name

(All)

8
24
4

East
West
Central

East
West
Central

3_M
4_L
4_L

6 356
3 291
3 022

-56,01%
-44,08%
28
-50,53%

63,09%
57,92%
62,25%

36,91%
42,08%
37,75%

6 160
3 415
2 706

-2,82%
-1,14%
-1,04%

63,28%
55,29%
61,17%

36,72%
44,71%
38,83%

Plant Name
Prod Hier Name

(All)

Change Type
of Analysis 1

Change Type of
Analysis 2

Region

Custo Rev S

Region

Custo Rev
Segment

10%

-43% Apply

Detected

Detected

10%

Fiscal Year

2010

Fiscal Month

(All)

Industry Name

(All)

(All)
(All)

-90

Consistency Concept
Levers
-

Discounts
Rebates
Sales Costs
Mktg. Costs
(Others Costs)

Different levels of Levers
delivering the same result:
Inconsistent

Results

Results

Market
-

Sales
Margin
SoW & MS
Value Perception
Customer Satisfaction
(Others Results)

Levers correlated to
Results: Consistent

Levers

Levers

Using the Pricing Toolbox, we measure The
impact of Pricing Levers on Performance:
Are they consistent?

Results

Efficiency Concept
Using the Pricing Toolbox, we measure The Pricing
Levers’ Efficiency:

Do they provide a positive ROI?

Results

Market

Levers

More Levers /
Less Results:
Black Hole

-

- Levers /
-- Results:
Inefficient

Evolution
of Levers

+

-- Levers
-Results:
Efficient

++ Levers /
+ Results:

+ Levers /
++ Results:

Inefficient
Evolution
of Results

/

-

Efficient

+

Less Levers /
More Results:
Managers’ Dream

Improving efficiency drives TOP LINE impact

Effectiveness Concept
Using the Pricing Toolbox, we measure Levers
Level Effectiveness:
Are we hitting the soft spot?

Levers
-

Discounts
Rebates
Sales Costs
Mktg. Costs
(Others Costs)

Ineffective
Implementation zones

-

Sales
Margin
SoW & MS
Value Perception
Customer Satisfaction
(Others Results)

Effective
Implementation zone
P=1

Sales

SoW

P=1

SoW

Results

Market

Tool 5: Variance Analysis
Revenue Variance

Price Variance

Menu-Tier Variance

Item-Price Variance



What it is:
Analysis of variance in sales revenues.
Price variance
Volume variance
With additional detail on demand
May be used for a single product or a
group of products, by Sales rep or by client
segments / channel.


Volume Variance

Mix Variance

Quantity Variance

What it does:
provide visibility of key evolutions of
revenues and drivers for variance.
Helps monitor & manage pricing strategy
, campaigns & discounting policies


Price adjustments.
Launch of campaigns & reactive actions
Competitive actions
The stakes:
Strong monitoring of Price & volume performance at any level – key driver to discipline & change
management

Variance Analysis tool – Impact Summary

Pricing

Contribution to Revenue Variance

REVENUE
PRICING
TIER
PRICE
PROMO

VOLUME
PRODUCT MIX
QUANTITY
QTY PER CUSTOMER
TRAFFIC VOLUME
NEW/CLOSED STORES
CUSTOMERS/STORE

$172 212
$394 409
$361 927
$32 482

-$222 197
$135 047
-$357 244
-$54 482
-$302 761
$196 605
-$499 366

Normal Screen
34

Full Screen

Variance Analysis tool – flexible analyses
KEY PRICING INDICATORS (KPI) SUMMARY
Menu-Tier Variance
Change
+$361 927
+3,0%
Item-Price Variance

Price Variance
+$394 409
+3,3%

+$32 482
+0,3%

Dine-In (Net)

AREA
REGION
T1
T2

+$172 212
+1,4%

# Menu Items
BE Total
0,41 per Cust 2,37
0,41 per Cust

+$1 252 523

2,36
Product Mix Variance

Qty Per Cust. Var

Advertising index
Brand Loyalty Index (BLI)

(sample)

+$135 047
+1,1%

Volume Variance

-$54 482
-0,5%

Quantity Variance

-$222 197
-1,8%

+$196 605
+1,6%

Customer Count Var

-$357 244
-3,0%

Cust. per Store Var

Controllable Factors

-$302 761
-2,5%

Opening/Closing Var

CPR Index

Uncontrollable Factors
Weather Index
Competitive Index
Total Hours of Operation
Loc. Accessibility Index
Comp. Rev Changes

-$499 366
-4,1%

Daypart: All
Cust. Count (total)
T1
9 608 658
T2
9 402 908
Difference (#)
-205 750
Difference (%)
-2,14%

BER Total
9 608 658
9 402 908
-205 750
-2,14%

Total (Net)

%
######
######

SD
1,9%
1,9%
-0,0%

35

Carry Out (Net)
+$1 080 311

Beverage Incidence Rates (Daypart = All)
CD
Hot Mlk/Jce Kids Other Total BE Total Impact / Mnth
2,5% 7,7% 1,4% 1,0% 0,3% 14,7% 86,0%
-$156 008
2,5% 7,4% 1,4% 1,0% 0,3% 14,5% 85,0%
+0,0% -0,3% -0,0% -0,0% +0,0% -0,3% -1,0%

Tool 5: Time Series (Illustrative)
Plant Name
Industry Name
Product Family Code
Product Grp Code

(All)
(All)
5_VL
(All)
(All)
(All)

Pricing

Normal

Full Screen

64,00

SKU Unit Prices ($)

What it is:
Analyses Prices (or D&R)
Go to Product Pivot over time
evolutions
Go toMay be used for a single
Price Evolution
Go to SKU Elasticity
Go to Product Elasticityby account manager.
channel, or
Go to Financial Pivot

32,00
Ac1
Ac10

16,00

Ac11

Ac12
Ac13

8,00

Ac14
Ac15
4,00

Ac16

Ac17
Ac18
2,00

1,00
nov.-07

juin-08

déc.-08

juil.-09

janv.-10

août-10

févr.-11

Go to Customer Elasticity

What it does:
provide visibility and insights
on evolutions to identify trends /
changes in dynamics or
correlations & opportunities &
threats that they represent

sept.-11

Tme Series (Weeks)

Improved / more rational pricing onbjectives.
Industry pricing actions to influence pricing dynamics
Price structure revbalancing
The stakes:
Together with other aspect of transactional analyses, typically results in bottom line improvement of up 4
% of sales in the first year
Page 36

Flexible tool integrated in Transactional
analysis
Selected
Selected
Selected
Selected
Selected
Selected
Selected
Selected
Selected
Selected
Selected
Selected
Selected

FULL
SCREEN

0

Pricing

-50

3000

-100

2500

Lines in Rigth Axe: Rebates
Columns in Left Axe: Gross Sales

-150

Apply Zoom
Lines MAX

-200
1500
-250
1000

-300

500

-350

0

-400

Detected

Lines MIN
Detected

Col. MAX
Detected

Col. MIN
Detected

Manual Lines MAX

Industry Name

(All)

Market Name

(All)

Market Segment Name

(All)

Product Name

(All)

Glob SoW Name

(All)

Customer Name

(All)

1
1
1
2
2
2
3
3
3
4
4
4
5
5
5
6
6
6
7
7
7
8
8
8
9
9
9
10
10
10
11
11
11
12
12
12
TOTAL LOOK AT
TOTAL PROFILE
TOTAL LOOK AT/TOTAL PROFILE

Week Name

7

Gross Sales Rebates

1 249
3 138
3 229
3 077
2 065
2 232
2 067
2 117
1 583
2 633
2 792
2 638
28 820
114 594
25,1%

Rebates

A-Z

6

Gross Sales

Manual
Calendar
Auto
Graph
Week Calendar
Graph Nº
Nº
Code

5

-140
-340
-358
-347
-235
-247
-232
-242
-172
-300
-315
-289
-3 217
-12 636
37
25,5%

8

9

10

11

Disc. & Reb. (% Gross Sale Gross Sales) Rebates
Gross Profit (% Net Sales

12
Net Sales

Manual Lines MIN

230 Speed
-64 Apply
-60 Speed
-434 Apply
21 335 Speed
3 852 Apply
-90 Speed
589 Apply
1 Col. MAX
0 Col. MIN

Gross Sal

Gross Sales
(% Total)

(All)

Data Table

4

Net Sales

(All)

Acct Mngr Name

3

Rebates

Region Name

2

Gross Sales

(All)

1

Gross Profit
(% Net Sales)

2009

Month

a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a

Disc. & Reb.
(% Gross
Sales)

Year

USUAL
SCREEN

Dynamic Disband Graph

2000
Manual & Auto Zoom

Unexplained Disc
StdVolume Discount
Full truck Discount
Rebates
Unbilled Services

Time Series - (Lines in Rigth Axe: Rebates-Columns in Left Axe: Gross Sales)

3500

Map Options

All

Levers Selection

-30,16%
-28,15%
-29,74%
-28,58%
-28,55%
-29,57%
-30,65%
-30,12%
-28,97%
-29,80%
-28,95%
-29,82%
-11,16%
-11,03%
101,2%

41,02%
44,12%
41,12%
44,01%
45,85%
43,42%
40,30%
42,64%
44,14%
43,15%
43,49%
43,50%
43,13%
63,85%
67,5%

1 249
3 138
3 229
3 077
2 065
2 232
2 067
2 117
1 583
2 633
2 792
2 638
28 820
114 594
25,1%

-140
-340
-358
-347
-235
-247
-232
-242
-172
-300
-315
-289
-3 217
-12 636
25,5%

872
2 254
2 269
2 197
1 475
1 572
1 434
1 480
1 124
1 849
1 984
1 852
20 361
127 229
16,0%

1,09%
2,74%
2,82%
2,68%
1,80%
1,95%
1,80%
1,85%
1,38%
2,30%
2,44%
2,30%
25,15%
100,00%
25,1%

Year
Month

2009
(All)

Region Name

(All)

Acct Mngr Name

(All)

Industry Name

(All)

Market Name

(All)

Market Segment Name

(All)

Product Name

(All)

Glob SoW Name

(All)

Customer Name

(All)

10
10
17
10
500
0

Tool 6: Dynamic evolutions & elasticity

(Illustrative)
All
Selected
Selected
Selected

Change in Price (%)

Selected

14
Map Options

Selected

FULL
SCREEN

MAP
Dynamic Evolution Map - Y: Net Price , X: Volume (Units)

Pricing

12
10

Selected
Selected

8

Selected
Selected

6

Selected
Selected

Manual & Auto Zoom

4

Selected
Selected

2
0

Y MIN

Detected

X MAX
Detected

X MIN

Manual Y MAX

-1

3
B

Profile A

4

5

6

Manual Y MIN

0% Speed

What it does:
200% Speed
1000%
5% Apply
10000%
-90% Speed
actual dynamics & relationships
0% Apply
between 200% components &
price
100% X MAX
X MIN
performance
-90%

COGS (% Net
Sales)

Gross Profit (%
Net Sales)

Gross Sales

D&R & Other
Mktg. (% Gross
Sales)

1 708

-40,08%

56,70%

43,30%

1 513

-0,43%

Gross Profit (%
Net Sales)

D&R & Other Mktg. (% (% Net Sales Profit
COGS Gro
Gross

Gross Sales

54,25%

45,75%

Acct Mngr Name

(All)

44,20%

Customer Name

(All)

Fiscal Year
Corrective Change Type
actions Change Type of lead to:
it may
Analysis 2
of Analysis 1
Fiscal Month
Improved Pricing & client conditions policies.
Code
Industry Name
Earlier identificationCusto Revcompetitive threats & changes in industry dynamics
of
Region
Region Name
Segment
Targeted price adjustment based on expected impact
20

South

South

5_VL

10000%

-11% Apply

COGS (% Net
Sales)

COGS Gro
Gross
Gross Sales

D&R & Other
Mktg. (% Gross
Sales)

Change in Volume (%)
Top Ten

DATA TABLE

AUTO
AXES

Profile B

Gross Sales

a
a
a
a
a
a
a

2

Auto Graph Nº

a

1

A

Manual Graph Nº

a
a
a
a
a

0

ADJUST AXES

What it is:
Dynamic Evolution Map
Analysis of evolution of Price
Y: Net Price
Dynamic Evolution
- Y: Net Price , X:
(and – orMapD&R)Volume (Units) how they
and
X: Volume (Units)
Impact Volumes or Margins.
30
May be used for a single
Apply Zoom
globally 10000% client segments /
or by
Y MAX
100% Speed
Detected
11% Apply
channel, or by account manager.

Detected

-2

USUAL
SCREEN

The stakes:
15
North North
5_VL
1 241
-41,13%
55,04%
44,96%
1 102
-0,34%
55,80%
19
4_L
1 808
-44,50%
57,28%
KeySouth South price adjustments & improved 42,72% 1realization56,90%
to finer
price 580 -0,52%

2010
(All)
(All)
(All)

43,10%

Market Name

(All)

18

South

South

3_M

6 956

-46,67%

55,16%

44,84%

6 596

-2,57%

56,50%

43,50%

Market Segment Name

(All)

14

North

North

4_L

2 204

-48,10%

57,27%

42,73%

1 992

-0,75%

58,24%

41,76%


(All)

17

South

South

2_S

7 717

-49,86%

53,82%

46,18%

7 260

-2,98%

53,93%

46,07%


(All)

Page 38

Dynamic Evolution / elasticity Tool
All

Disc. & Reb. Selection

Selected


Selected


Selected

Full truck Discount

Selected


Selected

Rebates

Selected

Unbilled Services

Selected


Selected


Selected


Selected


Selected


Selected

USUAL
SCREEN

ADJUST AXES

AUTO
AXES

Dynamic Evolution Map

14
Map Options

Selected

StdVolume Discount

12
10

Y: Net Price

Dynamic Evolution Map - Y: N

X: Volume (Units)

30

8

Apply Zoom
Y MAX

4
2
0

100% Speed

Detected

6
Manual & Auto Zoom

Unexplained Disc

FULL
SCREEN

MAP
Dynamic Evolution Map - Y: Net Price , X: Volume (Units)

Pricing

11% Apply

Y MIN

0% Speed
-11% Apply

X MAX

200% Speed

1000%

Detected

5% Apply
-90% Speed

10000%

0% Apply
X MAX

200%

X MIN

-90%

X MIN

Manual Y MAX

-1

Customer Name

(All)

Market Name

(All)

Market Segment Name

(All)


(All)


(All)

Material GrP Name

(All)

Product Family Name

(All)

Product Grp Name

(All)

Plant Name

(All)

a

D&R & Other Mktg. (% (% Net Sales
COGS Gro
Gross Profit

Code

Gross Profit (%
Net Sales)

(All)

COGS Gro
Gross
Gross Sales

COGS (% Net
Sales)

Acct Mngr Name

a
a
a
a
a
a
a
a
a
a

Profile B

D&R & Other
Mktg. (% Gross
Sales)

(All)

100%

Manual Y MIN

Gross Sales

Region Name

6

Gross Profit (%
Net Sales)

a

Profile A

5

COGS (% Net
Sales)

(All)

Gross Sales

Top Ten

DATA TABLE

B

4

D&R & Other
Mktg. (% Gross
Sales)

Industry Name

3

Gross Sales

(All)

2

Auto Graph Nº

2009

Fiscal Month

1

A

Manual Graph Nº

Fiscal Year

a
a
a
a
a

0

Region Name

(All)

20

South

South

5_VL

1 708

-40,08%

56,70%

43,30%

1 513

-0,43%

54,25%

45,75%

Acct Mngr Name

(All)

15

North

North

5_VL

1 241

-41,13%

55,04%

44,96%

1 102

-0,34%

55,80%

44,20%

Customer Name

(All)

19

South

South

4_L

1 808

-44,50%

57,28%

42,72%

1 580

-0,52%

56,90%

43,10%

Market Name

(All)

18

South

South

3_M

6 956

-46,67%

55,16%

44,84%

6 596

-2,57%

56,50%

43,50%

Market Segment Name

(All)

14

North

North

4_L

2 204

-48,10%

57,27%

42,73%

1 992

-0,75%

58,24%

41,76%


(All)

17

South

South

2_S

7 717

-49,86%

53,82%

46,18%

7 260

-2,98%

53,93%

46,07%


(All)

4

0

4_L

3 022

-50,53%

62,25%

37,75%

2 706

-1,04%

61,17%

38,83%

Material GrP Name

(All)

21

West

West

1_VS

2 044

-51,31%

50,96%

49,04%

1 932

-0,81%

51,62%

48,38%

Product Family Name

(All)

9

East

East

4_L

1 974

-54,95%

64,78%

35,22%

1 718

-0,73%

63,79%

36,21%

Product Grp Name

(All)

1

0

1_VS

1 759

-59,30%

55,62%

44,38%

1 568

-0,77%

57,77%

42,23%

Plant Name

(All)

Change Type
of Analysis 1

Region

Change Type of
Analysis 2

Custo Rev
Segment

39

10000%

Detected

Detected

-2

10000%

Fiscal Year

2010

Fiscal Month

(All)

Industry Name

(All)


Volume Variance

Value analysis & measurement Tools


Mix Variance


Quantity Variance


Value Analysis
EVC / EVIU

Value Maps / curves

Win / Loss

Pricing Process Performan

Elasticities

Key Tools
 Economic Value Modeling
Pricing BSC
Pricing Diagnostic
 Value Map & Curves
 Choices Based Conjoint
Modeling & simulation
 Win / Loss analyses
 Elasticities nalyses &
simulation
Pricing Price Points / Psycholgical
Thought Proc. Pricing Alignment

Pricing analyses

CBC / Perceptions

Price Points
9
8
7
6
5
4
3
2

1
0
80

85

90

95

100

105

110

115

Occurrences

Tools to help Measure Value Perception &
Willingness to pay & elasticities & to use Value as a
base for Pricing

40

Client Value
Logic / Approach

– “Rational”
• Financial Value Measurement (FVM) /
Expected value in use (EVIU)
• Cost to customer without product minus
cost to customer with product

– “Emotional”
• Price elasticity
• Perceived value of ‘qualitative’ attributes

Analysis / Tools
FVM/EVIU
Simulation of client
level impact

Transactional analysis
/ observed elasticities
Discount / Rebates
elasticities
Win / Loss analyses
Key Buying Factors
Choice based conjoint/
Perceived price/value

Tool 7: Economic Value to Clients

(Illustrative)

Total
Value
€2029 !

Total
Benefit

What it is:
Objective evaluation of
economic value to client of our
offering versus next best
competitive alternative.
Developed by target segment
and or for individual clients.
Can be adapted to supply an
interactive sales support tool

€ 123

€ 2 260
€ 2 137

€ 3 00

€ 2 00
Increased Longer Life
Efficiency

Incr
Maint
Cost

Total
Costs

€ 5 00
Conversion
Costs

Total
Prem.
€1760

€369 Best

Alternative

What it does:
Analyses & visualizes the
Value of our offering

Actions it may lead to:
Development of targeted offers (focusing on attributes that create value for clients)
Can provide a very effective support tool for Sales force
Targeted communication & marketing
The stakes:
In period of High pricing turbulence (such as now), typically results in bottom line improvement of up to 4
% through better ability to communicate value to clients
If used in the context pf a new product launch (or revamp), it often results in bottom line improvement of
10% or more through value based pricing

Page 42

EVC Tool – Synthesis table

43

EVC Tool – Value Waterfall

44

EVC Tool – Value Hierarchy

45

EVC Tool – Stakeholders Value Priorities

46

EVC Tool – Value Lever Logic

47

EVC Tool – Value Lever economic Model

48

Tool 8: Segmented Competitive Value Maps
Segmented Customer Value Map
Competitive Value Maps
(Segment X, Market B, 2008)

Relative Price

Value
Disadvantaged

What it is:
Analysis & mapping of competitive.
Prices
Value (perceived or measured)
May be used for a single product or a group of
Dell
products, globally or by client segments /
Compaq/HP
channel.

1.50

Competitor 4
Competitor 1
0.50

Competitor 3
1.00
Competitor 2

Value
Advantaged

1.50

Clone
Toshiba
What
Fair Value Line

it does:
provide visibility and control of Value & Price
positioning of Products by segment.
Helps define effective Value / Pricing
segmentationtegic

0.50

Relative Value (Perceived /measured)
Relative Perceived Value

Improved proved targeting of Price & Value proposition &segmentation
Support to Sales force in Value Selling
The stakes:
Varies considerably. Repositioning/ Retargeting of Value Proposition may often result in double digit price
increases or Volume increases
Page 49

Tool 9: CBC / Perception Analysis

(Illustrative)

What it is:
T he most effective methodology
for measuring ‘Qualitative’ Value
perception & willingness to pay &
developing Price response /
elasticity models
Attributes elasticity not limited to
price but can include other key
factors affecting WTP

More accurate & effective price & value positioning.
Identification & improvement of other levers that influence clients decisions
Improved competitive tactics & positioning

What it does:
Identifies & quantifies key
decision drivers
Model the impact of changes in
price or performance on key
‘attributes’

The stakes:
Performant approach to price optimization in many markets / industries.Typically results in bottom line
improvement of up to 10 %
Page 51

Tool 10: Win / Loss Analysis

(Illustrative)

What it is:
Systematic & regular evaluation
of reasons of Wins & losses (or
significant changes in Share of
Accounts at clients).
Criteria will include our &
competitive prices but also
conditions & buyer profile to
identify drivers
What it does:
Help identify & quantify key
decision drivers
Helps optimize price positioning
More accurate & effective price positioning.
Identification & improvement of other levers that influence clients decisions
The stakes:
Performant approach to price optimization in deal driven B2B environment.Typically results in bottom line
improvement of up to 4 %
Page 52

Win / Loss analysis tool

Detailed modeling of „Win Probability‟ as a function of Discount level
53

Tool 12: Price Points Analysis

(Illustrative)


What it is:
Identification of Psychological
price points from a customers’
perspective & their impact on
demand
Criteria will include our &
competitive prices but also
conditions & buyer profile to
identify impact

9
8
7
6
5
4
3
2

1
0
80

85

90

95

100

105

110

115

Occurrences

More accurate & effective price points positioning.
Improve price alignments along the product range & vis a vis competition

What it does:
Identification & measurement of
price points
Estimated impact of potential
price realignments / price points
optimization

The stakes:
Performant approach to price optimization impulse / image driven product ranges or industries with high
pricing rivalry
Page 54

Marketing & Sales Support Tools
Key Tools
 Share & competitive
performance monitoring
 Peer Pricing & Value selling
support
 Portfolio analyses
 Analyses of performance on
key Value attributes
 Campaign effectivenes
measurement & modeling
 Competitive & Pricing
Intelligence tools

Tools to help support Strategic Marketing
& Sales with a value focus & Marketing
effectiveness improvements
55

Tool 13: Portfolio Pricing Dashboard
AM: John Smith –
Client Portfolio
Client

Client
Rev.
(YTD)

Client Vol. Disc.
Growth Margin Band Vol.
(%)
(YTD) (Ann.) Band

ABC

1.2M€

6%

ACB

8.1M€

32% 28% XL1

XL1

BAC

0.2M€

1%

29% M1

BCA

3.2M€

-12%

21% L2

Total

3.2M€

-2%

29%

31% L1

Control 2
Net Price Check

Control 1
Volume Band
Except. Curr.
(N/Y & Disc
Auth) (%)

L2

Disc.
Ok’d
(%)

Renego.
(previous)

(Illustrative)

Client Conditions
Monthly Monitoring
Report
Renego.
(next)

Incentive
Score
(Sales Rep)

14%

14%

09/07

09/08

25

17%

18%

02/07

02/08

75

M2

18%

11%

06/07

06/08

1

L2

25%

18%

08/07

01/08

-20

17%

18%

On Time

354

YTL

6

Monitoring 5
Calculation of
Salesman‟s incentive

Previous.
year

Control 3
Exception Handling

Monitoring 4
Renegociations

What it is:
Systematic & regular
Dashboard providing
indication of performance &
guidance on Client portfolio.
Criteria used may vary by
sector and based on
strategic priorities
What it does:
Monitoring tool
Support to sales force in
execution of Pricing strategy

Better targeting of pricing actions by sales force.
Identification of Price increase opportunities or imminent price threats
Improved monitoring of portfolio performance
The stakes:
Higher effectiveness in Pricing execution. Typically results in bottom line improvement of up to 2%

Page 56

Tool 14: Peer Pricing (Illustrative)
What it is:
Support to sales force by
providing contextual information
on similar offers (price
conditions, features & outcome).
Key is identification of
comparable deals & collection of
relevant information
What it does:
provide visibility on what is
feasible / reasonable
Provides reassurance & peer
pressure to perform
More effective pricing by sales force (better margins).
Stronger emulation amongst sales force
Elimination of ‘way over-/under- priced offers’
The stakes:
Similar to Win/Loss - approach to price optimization in deal driven B2B environment. Typically results in
bottom line improvement of up to 4 %
Page 57

Tool 15: Portfolio Analysis / Price Structure Mapping

(Illustrative)

Segmented Price Structure Maps
(Segment X, Market B, 2008)

Full Price / Ha (€)

Product4

Product 3
Product 3

Product 2

What it is:
Analysis & mapping of segmented Product
range.
Prices
Product performance
May be used for a group of products, globally or
by client segments / channel.
What it does:
provide visibility and control of coherence of
product Price & Performance positioning.
Can be used competitively to identify
competitive opportunities / threats

Product Performance (Protection index)

Improved proved positioning of Products
Rationalization of product range
The stakes:
Depending on initial state 1 to 3 % improvement in average realized price
Page 59

Tool 16: Rating Performance / Value Curves
Competitors Value Graphs
9,0
8,0
7,0
6,0
ACME

5,0

Comp 1
4,0

Comp 2

3,0

What it is:
Analysis & mapping of competitive.
Value performance
Performance on attributes
May be used for a single product or a group of
products, globally or by client segments /
channel.

2,0
1,0
0,0

Weight

56

1

1

10

13

19

Ship
Complete

Defects

Range

Service

Shipment
Date

Price

What it does:
provide visibility and control of Value positionin
of Products by segment.
Identifies key attributes by segment
Helps define effective Value segmentation

Region: Central
Segment: Price Driven

Value proposition adjustments
Improved targeting of Price & Value proposition &segmentation
Support to Marketing force in product development / Product attributes
The stakes:
Varies considerably. Repositioning/ Retargeting of Value Proposition may often result in double digit price
increases or Volume increases

Market Name
Industry Name
Product Family Code
Product Grp Code

Pricing

(All)
(All)
(All)
(All)
(All)
(All)

Normal Screen

Full Screen

Tool 17: Promotional Performance analysis (Illustrative)
Column Labels

Avg (x)
Price change (y) vs Volume Change Price

(2008-2009 -

Avg Price

2009 2008
2009
Rev 2009 Prod Hier
by Product )
#VALUE! #VALUE! Gross Rev
Product Code
1 695
2,63
2,63
4 181 Ac1
1 572
34,10
34,14
44 413 Ac13
1 170
39,45
39,42
57 360 Ac15
1 363
42,16
42,17
56 952 Ac16
1 460
44,70
44,66
53 414 Ac17
1 331
47,18
47,31
73 339 Ac18
1 534
50,00
49,85
66 983 Ac19
1 408
5,24
5,26
7 604 Ac2
1 248
55,33
55,24
74 468 Ac21
Ac18
1 479
60,46
60,42
84 845 Ac23
1 375
63,08
62,90
88 276 Ac24
1 416 Ac15 70,99
70,84
108 300 Ac27
20%
30%
40%
1 406
78,91
78,88
119 755 Ac30
1 181
81,35
81,36
120 448 Ac31
1 375
84,15
84,17
119 143 Ac32
1 652
87,07
86,69
100 272 Ac33
1 547
89,32
89,10
119 633 Ac34
1 332
92,10
91,75
127 072 Ac35
1 312
94,75
94,53
125 885 Ac36
1 499
97,37
97,11
135 000 Ac37
1 256
99,62
100,07
124 493 Ac38
1 472
102,62
102,63
149 513 Ac39

Discount Offeredc (% List price)

2011 – Promotional Performance analysis

Row Labels
Ac1
Ac1
Ac1
Ac1
Ac1
Ac1
Ac1
Ac2
Ac2
Ac2
Ac2
Ac2
-40%
-30%
Ac3
Ac3
Ac3
Ac3
Ac3
Ac3
Ac3
Ac3
Ac3
Ac3

--

-20%

Product Code
Vol
Ac1
Ac13 1%
Ac15
Ac16
Ac17
Ac18
Ac19 1%
Ac2
Ac2
Ac21
Ac23 Ac1
Ac13
Ac24
Ac16
0%
Ac27
-10%
0%
10%
Ac30
Ac31
Ac19
Ac32
Ac33-1%
Ac34
Ac35
Ac36
Ac37
Ac38-1%
Ac39

++

Vol Gr
-6%
-17%
24%
-1%
-18%
16%
-12%
3%
8%
-5%
2%
8%
8%
25%
3%
-30%
-13%
4%
2%
-7%
-1%
-1%

Apparent
elast

Pr Gr
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%

43,02
159,98
342,24
159,69
-226,76
-62,23
-42,85
-8,74
48,24
-66,91
7,52
36,16
207,86
-1861,22
-216,68
-68,35
-53,16
10,27
6,56
-27,14
2,07
79,69

Go to Financia

Go to Product

Go to Price Ev

What it is:
Analysis or profit & volume to SKU Ela
Go
impact of promotions.
can be used any type ofGo to Product E
promotional / sales animation
action to evaluate ROI ofGo to Customer
action.
What it does:
actual performance of action,
including stock effects &
cannibalization, to provide
improved vision of actual &
relative performance

Sales Impact (% LT Lift)

Re-adust marketing budget to support most effective actions.
Best practice transfer (Test, Learn & generalize)
Improved targeting of promotions
The stakes:
20 to 40% improvement in Marketing ROI
Page 61

Detailed analysis of impact of promotions on
volume & bottom line

Optimization of promotional effectiveness
62

Tool 18: Benchmarking &
Competitive Intelligence
Category xxx - Average Daily Rate Comparison
(as function of rental duration)
90
80
Avis

70

Hertz

60

Europcar

50

What it is:
monitoring & benchmarking of
competitors ‘Sell-In’ & ‘Sell-out’
prices at relevant levels
Key ingredient of Pricing
Intelligence

Easy Rentacar

40

ADA

30

eSixt

20

Budget

10

What it does:
provide ability to react faster &
smarter to competitive price
movements

RentaCar

0
1

3

5

7

9

11

13

15

Better anticipation / faster reaction to changes in competitive prices
Stronger sales pitch
The stakes:
% through better anticipation of - / faster reaction to - price movements
Page 63

Pricing Performance Management tools
Pricing BSC

Pricing Diagnostic

Pricing RACI

Pricing Thought Proc.

Pricing Alignment

Industry Pricing

Tools to help follow monitor, control & gradually
improve the strategic Pricing & Value management
capabilities of the company

64

Key Tools
 Pricing Balanced Score Card
 Pricing Diagnostics &
Improvement Roadmap
 Pricing Processes & RACI
 Pricing Thought Process
 Pricing Alignment reports
 Industry Pricing analyses &
decision support

Tool 19: Pricing BSC & Dashboards

(Illustrative)

What it is:
Balanced scorecard – used to
monitor globally performance &
development of pricing strategy.
sector and level of analysis
What it does:
provide visibility & control of
implementation of Pricing
strategy

Better anticipation / faster reaction to changes in Industry Pricing Dynamics.
Better & balanced monitoring & control of performance, faster ability to react
Improved ability to manage change & performance improvement over the longer term
The stakes:
Strong monitoring of Price Strategy performance & change management at any level – key driver to
Global performance
Page 65

Pricing BSC – A key management tool

67

Tool 20: Pricing Diagnostic & Roadmap
(Illustrative)

What it is:
Diagnostic– evaluates current
level of performance vs Best
practices on all aspects of
Pricing management.
Roadmap : identifies key levers
for improvement of pricing
performance improvement &
provides concrete
recommendations & actions
plans to follow to get there
What it does:
Key tool to support sustainable
performance improvement

Clarifies where we are and where we need to go.
Aligns & organizes the company around the required change management effort to achieve improvement
Helps prioritize & organize action for optimal effectiveness
The stakes:
Best approach to achievable sustainable’ performance improvement

Page 68

Tool 21: Pricing Proccess RACI (Illustrative)
What it is:
Defines & organizes participant
roles & responsibilities in all
pricing processes.
Defines calendar & organizes
to ensure effective collaboration
& consensus building

What it does:
provide visibility, coordination
& control of all key pricing
processes

Improved coordination of stakeholders.
Conflict reduction, improved consensus building
Improved prioritization / more rational arbitrage between alternative plans
The stakes:
Effective management of Pricing & Value across the company

Page 73

Pricing RACI – Country/Process detail

75

Tool 22: Pricing Thought Process

(Illustrative)

What it is:
A ‘qualitative’ process to
support more rational / effective
Pricing decision making – when
data availability is insufficient.
A tool to capitalize on
managers collective expertise to
improve decisions & develop
consensus
What it does:
Provide a strong logical
framework to help focus
discussion, rationalize them &
facilitate consensus

Better Decision making.
Improved consistency across divisions and time
Improved consensus
Development of Pricing & Value culture
The stakes:
Improved Pricing management & consensus
Page 76

Tool 23: Pricing Alignment
Category xxx – 1 Day Rental package comparison
(as function of Km driven)

300

100
70
250
60
90
200
150

200
100
85
90
150

300
130
110
90
150

400
160
135
110
150

500
190
160
130
150

600
220
185
150
150

700
250
210
170
150

150

800
280
235
190
150

Variable

Short Trip

What it is:
Visualization of positioning &
attractiveness if alternative
packages as a function of nt
usage
Key ingredient of Pricing
coherence management

Long Trip

100

Illimité

50
0
0

100

200

300

400

500

600

700

What it does:
provide ability to improve
pricing coherence & better
position offers to meet client
usage characteristics

800

Better positioning of packages & prices
Identification of Price increase opportunities
Stronger sales pitch better fit to needs
The stakes:
In segmented markets – with high price visibility, typically results in volume increases improvement of up
to 10 % through better fit of offer to needs
Page 80

Window - Shadow - Shade
Window

5-15%

40-65%

Key, high visibility offers requiring
precision pricing, based on perceived value
(if possible) or on detailed, accurate
competitive & costing info.

Shadow

10-30%

15-25%

Strongly related to window
products in terms of perceived
value & purchasing decision 
margin based pricing driven by
window products

Shade

55-75%

10-45%

incidental, low visibility products with
low impact on perceived value or
buying decision  cost based pricing
with high margin
81

Tool 24: Industry Pricing Dynamics Assessment
(Illustrative)

What it is:
assessment of Industry pricing
Dynamics.
sector and for Commodities vs
specialty

What it does:
provide visibility and
anticipation of industry level
pricing movements

Improved monitoring of industry level indicators

The stakes:
% through better anticipation of price movements
Page 82

Tool 24: Industry Pricing

(Illustrative)

Page 83

Price dynamics assessment
Price Dynamics assessment

Criteria to M onitor

Weighting

Channel Concentration

Customer

7

Channel Alignment with Example Corp (Loyalty)

10

Customers Profitability & Willingness to Pay

Communicatio
n

5
8

Price Followership Likelihood & Reaction Delay

5
4

Competitive Costs Position

Costs

Value Index / Cost to use advantage

Price Premium against best Value Competitor

Competitor

5

Industry Concentration

Consumer

6

Consumers Profitability & Willingness to Pay

7

Forecasted Costs Evolution

10

Communication Leadership

7
10

Free Capacity Relative Position

Capacity

Competitive / Media Signalling

10

Projected Supply / Demand Ratio

6

Channel Inventory Level

10

Chg vs last period

Chg from last Chg

Current Period
Ariston

6 C's Pricing
Drivers

Current Period

Since Last Period
Ariston

Since Last Price Change
Ariston

Score

2,6
2,7
2,8
2,8
4,6
4,0
3,9
5,0
3,4
3,9
4,4
4,4
3,8
2,9
2,9

110
Ariston

Ariston

GT Corn

2,7
3,7
4,2
3,7
4,4
2,6

3,6

Projected M arket Price Evolution

Score

GT Corn

0,0
0,0
0,1
0,6
0,1
0,6
0,0
1,2
-0,1
0,7
-0,1
-0,1
0,3
0,7
0,8

0,02
0,40
0,54
0,37
-0,14
0,42
0,293
7%

Price Change Recommendations
Directional
84
% change proposed

increase recommended
10%

Score

0
-0,4
-0,7
-0
0,2
0,7
1,7
1,2
-0,3
0,8
0,7
1,3
3,8
0,2
0,3

GT Corn
1

-0,26

2
3

0,10

4
5
6

1,08

7
8

0,34
1,05

9
10
9
10
11

1,56

12
13

0,715
18%

Value Sharing analysis & decision support

85

Open Scenario
Save as
Statistics & simulation tools
Stats & Simulations
Pricing Simulators

Portfolio Simulator

Network Simulator

D & R Savings

Segm. & Clusters

Regressions & stats


Analytical & simulation tools to help support
Strategic Decision Pricing Diagnostic
making on Pricing & Value
Pricing BSC
Pricing RACI
Strategies & implementation
86

Key Tools
 Pricing & Value modeling &
simulation
 Portfolio simulation
 Network simulation &
optimization
 Simulation of impact of
alternative Pricing or D&R
 Segmrentation & clustering
tools
 Regression & statiistical tools

Tool 25: Pricing Simulator (Illustrative)

What it is:
assessment of Industry pricing
Dynamics.
sector and for Commodities vs
specialty

What it does:
pricing movements

Improved monitoring of industry level indicators

The stakes:
% through better anticipation of price movements
Page 87

Pricing Simulator – Single product

88

Pricing Simulator – Competitive dynamics

89

Tool 26: Portfolio Pricing Simulator (Illustrative)
Product Selection for analysis

FULL
SCREEN

USUAL
SCREEN

Check / Uncheck All
Accuspray
Hypak Components
SCF
Hypak Bulk Barrels

Hypak Componets
Bulk

Hypak SCF Barrels
Hypak Plunger Rods
Hypoint Needles
Monovial
Preventis

Readifill Barrel

Rdf Components
Rdf Olunger Rods
Uniject
Sterifill Barrels
Sterifill Components

Accuspray barrel
Hyp BSCF/BCF Stopper
Hyp NSCF/NCF Stopper
Hyp TSCF/TCF Stopper
Hypak Comp SCF Other
Hyp Bulk Barrel Luer
Hyp Bulk Barrels Ndl
Hyp Bulk Ndl Shield
Hyp Bulk Plast Comps
Hyp Bulk PRTC
Hyp Bulk RNS
Hyp Bulk Stp/Byp Stp
Hyp Bulk Tip Caps
Hyp SCF Barrel Luer
Hyp SCF Barrel Ndl
Hyp SCF Barrel Ndl Physiolis
Hypak Plunger Rods
Hypoint Needles
Monovial Stopper
Monovial Vials
TS Needle Guard
Preventis
Preventis Other
Rdf Bulk Stopper
Rdf RTS Barrels Luer
Rdf RTS Barrels Ndl
Rdf RTS Stopper
Rdf SCF Barrel Luer
Rdf SCF Barrels Ndl
Rdf Comp Others
Rdf Plunger Rods
Reservoir
S-fill SCF Brrl Luer
Sterifill Plungr Rod
Sterifill Stppr

Run Impact
Analysis

Go to Impact
Analysis

Go to Product
Synthesis

Go to Product
Hypotheses

Go to Prodiuct
Client Detail

What it is:
Decision support tools to
simulate / optimize pricing
across a porfolio of Products or
countries, taking into
consideration elasticities, price
corridors & potential competition
between ranges

Go to Impact
Menu

Go to Main
Menu

What it does:
Optimization & coordination of
pricing across the portfolio

Implementation of price corridors.
Differentiating offers to better serve different markets / optimoize value capture
Targeted Price increases / decreases

The stakes:
% through better optimization & coordination of prices
Page 90

Tool 26: Portfolio Pricing Simulator (Illustrative)
Corridors

Synthesis

Recalc Full Scen

Multi-country pricing optimization - modulated by country €)

Back to Integ
Region

Country
### US
Canada
North America
Germany
UK
France

Country Level Pricing Options
Reimbursement
Price Constraints / Objective
Scenario
TRUE CoPay

Profit Optimization
Profit Optimization
1

Fixed price
#### No Reimb. Fixed price

5

Regional Corridor
#### No Reimb. Regional Corridor
3
Regional Corridor
3
Regional Corridor
3

Scenario constraints

Min PTW Max PTW
28,79 €

32,79 € OptIm

34,00 €

50,00 €

32,00 €

36,00 € OptIm
36,00 € OptIm

50,95 €

32,00 €

82%

37,77 €

33,57 €

36,00 € OptIm
36,00 € OptIm

57,17 €

32,00 €
32,00 €

Sweden

32,00 €

36,00 € OptIm
36,00 € OptIm

Russia

Profit Optimization
#### No Reimb. Profit Optimization
1

16,00 €

192,86 € OptIm

Europe

PTW

Est. Share Profit
Margin % (%)
Index

746,67 € OptIm

32,00 €

Spain

Public
Price

Performance achieved in Scenario

17,00 €

Regional Corridor
3
Regional Corridor
3
Regional Corridor
3

Italy

Per product
results

32,00 €

32,00 €

Revenue
Index

37,03 € 148,10 €

96%

51%

480%

442%

41,34 €

80%

42%

100%

99%

478%

439%

43%

100%

100%

83%

42%

100%

100%

32,00 €

82%

29%

99%

97%

50,56 €

32,00 €

82%

42%

99%

96%

55,55 €

35,58 €

84%

31%

96%

96%

44,57 €

36,00 €

84%

45%

87%

92%

53,59 €

29,77 €

81%

44%

100%

100%

99%

98%

28,79 €

36,00 €

8,13 €

145,52 € OptIm

39,02 €

25,34 €

77%

43%

100%

100%

8,13 €

20,47 € OptIm

22,80 €

20,45 €

83%

38%

97%

99%

### Korea

Profit Optimization
1
Profit Optimization
1
Profit Optimization
1

3,06 €

10,12 € OptIm

12,60 €

10,08 €

65%

44%

63%

79%

### China

Profit Optimization
1

8,13 €

53,15 € OptIm

22,76 €

13,39 €

74%

39%

100%

100%

98%

99%

96%

96%

96%

96%

414%

372%

Australia
### Japan

APAC
Mexico
Brazil
Latin America

Grand Total

16,25 €

Profit Optimization
No Reimb. Profit Optimization
1

12,50 €

1
Profit Optimization

-2,00 €
25,00 €

40,00 €
128,12 € OptIm
OptIm
80,00 €

37,95 €

24,29 €

76%

67%

Tool 27: Retail Network Pricing Simulator (Illustrative)
Teboil

TypFuel

98E

Date

Brand: Teboil Fuel: 98E - ROS vs Share of Choice, by
station
(bubble size proportional to revenues)

04/01/2010

12%

10%

ROS %

Optimization Parameters Optimization Performance
Criteria

ROS
SoC

Weight Constr. (>)

ROS % SoC %

0,10%

Optim.

6 397 €

2,4%

31,9%

50%

18,00%

Initial

4 509 €

2,3%

28%

Station level Data

Optimize MultiStations pricing
Gross

Row Labels Nb Comp
Prev Prc ev Prev Marg
R
VarCost / Ltr Profit Min Pr MaxPr Price
Gr
Profit
Aura
3 ##### 6 682 €
388 € 1,542 €
94 € 1,605 € 1,739 € 1,661 €
118 €
8%
Espoo
6 ##### 37 978 € 2 654 € 1,462 € 1 320 € 1,538 € 1,666 € 1,551 €
1 494 €
Hämeenkyrö
3 ##### 6 434 €
455 € 1,471 €
147 € 1,540 € 1,668 € 1,579 €
151 €
Hämeenlinna
6 ##### 2 772 €
271 € 1,465 €
-37 € 1,535 € 1,663 € 1,543 €
340 €
6%
Heinola
3 ##### 3 233 €
229 € 1,516 €
-22 € 1,569 € 1,700 € 1,602 €
27 €
Helsinki
6 ##### 11 852 €
924 € 1,475 €
-1 € 1,532 € 1,660 € 1,543 €
723 €
Huittinen
2 ##### 5 972 €
426 € 1,448 €
143 € 1,584 € 1,629 € 1,584 €
144 €
4%
Hyvinkää
3 ##### 11 792 €
767 € 1,412 €
397 € 1,491 € 1,616 € 1,544 €
491 €
Kärsämäki
Ilomantsi
3 ##### 5 897 €
414
172
1,581 € 1,713
Kokkola € 1,512 € Espoo € Janakkala Ilomantsi€ 1,626 € Hyvinkää €
Huittinen 170
Heinola
Jämsä
2 ##### 5 095 €
330 € 1,509 €
91 € 1,564 € 1,694 € 1,628 €
95 €
Kauniainen
HämeenkyröAura
Kiiminki
Jämsä
Kaustinen
2%
Helsinki
Juva
Janakkala
4 ##### 6 578 €
548 € 1,478 €
205 € Kaavi € 1,681 € 1,594 €
1,552
205 €
Juva
3 ##### 3 472 € Kerimäki€ 1,493 €
274
54 € 1,547 € 1,676 € 1,591 €
91 €
Kaavi 0%
4 ##### 5 179 €
401 € 1,506 €
101 € 1,579 € 1,710 € 1,612 €
117 €
SoC % €
Kankaanpää
2
334 € 1,518 €
110 € 40% € 1,70450% 1,639 €
1,573
€
113
0%
10%##### 4 914 €
20%
30%
60%
Kärsämäki
4 ##### 1 722 €
149 € 1,463 €
75 € 1,535 € 1,663 € 1,545 €
134 €
Kauniainen
2 ##### 3 636 €
304 € 1,481 €
91 € 1,538 € 1,666 € 1,592 €
107 €
-2%
Kaustinen
4 ##### 4 202 €
413 € 1,494 €
101 € 1,571 € 1,702 € 1,610 €
124 €
Kempele
2 ##### 5 526 €
385 € 1,517 €
139 € 1,573 € 1,704 € 1,639 €
144 €
Kerimäki
3 ##### 1 678 €
154 € 1,519 €
4 € 1,571 € 1,702 € 1,636 €
29 €
-4%
Kiiminki
2 ##### 1 590 €
286 € 0,546 €
35 € 0,639 € 0,692 € 0,666 €
33 €
Kokkola
5 ##### 12 538 €
979 € 1,487 €
388 € 1,561 € 1,691 € 1,626 €
307 €

Profit

50%

Station
Aura
Espoo
Hämeenkyrö
Hämeenlinna
Heinola
Helsinki
Huittinen
Hyvinkää
Ilomantsi
Jämsä
Janakkala
Juva
Kaavi
Kankaanpää
Kärsämäki
Kauniainen
Kaustinen
Kempele
Kerimäki
Kiiminki
Kokkola

Price
1,661 €
1,551 €
1,579 €
1,543 €
1,602 €
1,543 €
1,584 €
1,544 €
1,626 €
1,628 €
1,594 €
1,591 €
1,612 €
1,639 €
1,545 €
1,592 €
1,610 €
1,639 €
1,636 €
0,666 €
1,626 €

Mod
Revenue
5 743 €
49 623 €
6 719 €
12 690 €
5 196 €
37 160 €
4 982 €
10 063 €
5 883 €
4 571 €
7 532 €
5 045 €
6 316 €
4 560 €
3 919 €
4 591 €
6 056 €
5 239 €
2 495 €
1 584 €
10 536 €

SoC

Gross
Profit

ROS %
46,0%
28,5%
39,6%
24,5%
30,0%
21,0%
51,6%
54,2%
42,5%
46,7%
36,8%
36,8%
36,2%
50,5%
25,7%
45,1%
35,3%
51,3%
19,6%
44,7%
17,7%

What it is:
Systematic Daily price
Station Profile Database
Quality optimization in highly price
competitive environments
Station Level Price Impact
Can be used to optimize
Price Share
Station Level Optimization in a network, taking inti
pricing
Station Level Decision
consideration local competition &
Network demand
Optimization
Competitive Pricing DB

2,1%
3,0%
2,2%
2,7%
0,5%
1,9%
2,9%
4,9%
2,9%
2,1%
2,7%
1,8%
1,9%
2,5%
3,4%
2,3%
2,1%
2,7%
1,2%
2,1%
2,9%

118 €
1 494 €
151 €
340 €
27 €
723 €
144 €
491 €
170 €
95 €
205 €
91 €
117 €
113 €
134 €
107 €
124 €
144 €
29 €
33 €
307 €

Navigation

Brand

What it does:
Simulates / optimizes pricing
based on specific competitive
conditions & capitalizing on
historically measured elasticities

-6%

Improved daily pricing to support overall marketing strategy & objectives
Faster reaction / anticipation of competitive moves
The stakes:
1 to 3% improvement in pricing realization… may be key in markets subject to very intense price
competition

Page 92

Network Pricing Simulator – Competitive database
Brand ServQ

Ähtäri
ABC
Ähtäri
Neste
Ahvenanmaa/Åland
Shell
Ahvenanmaa/Åland
St1
Alajärvi
Neste
Alajärvi
Shell
Alavus
ABC
Aura
ABC
Aura
Shell
Aura
Teboil
Espoo
ABC
Espoo
Neste
Espoo
Shell
Espoo
St1
Espoo
Teboil
Espoo
Ysi5
Eura
ABC
Eura
Neste
Forssa
ABC
Forssa
Shell
HämeenkyröABC

LocQ
4
7
2
2
7
7
6
6
5
7
4
7
2
7
5
5
6
7
2
6
8

Est Margin
Fixed Costs
Est Profit
2010
2010
765 446 €
634 141 €
131 306 €
1/1/10 #######
600 348 €
552 411 €
47 937 €
1/1/10 #######
523 166 €
513 961 €
9 205 €
1/1/10 #######

From

7
6
4
5
6
5
5
8
3
8
7
4
7
8
5
5
6
6
6
4
7


to

Navigation

Location

Quality Impact Analysis
Price Share Trade-Off

1/1/10 #######

604 869 €

527 374 €

77 496 €

1/1/10 #######

580 282 €

551 339 €

28 943 €

1/1/10 #######

556 772 €

511 229 €

45 543 €

Station Level Decision Support

1/1/10 #######

1 156 361 €

1 166 020 €

-9 659 €

Network Optimization

1/1/10 #######

606 556 €

552 489 €

54 067 €

1/1/10 #######

379 495 €

355 500 €

23 995 €

1/1/10 #######

698 248 €

665 290 €

32 958 €

1/1/10 #######

2 802 155 €

2 580 634 €

221 521 €

1/1/10 #######

2 789 870 €

2 610 026 €

179 844 €

1/1/10 #######

2 647 168 €

2 150 629 €

496 539 €

1/1/10 #######

5 175 726 €

4 886 357 €

289 370 €

1/1/10 #######

3 062 354 €

2 916 488 €

145 866 €

1/1/10 #######

3 246 528 €

3 165 562 €

80 966 €

1/1/10 #######

533 067 €

480 939 €

52 129 €

1/1/10 #######

597 229 €

586 904 €

10 326 €

1/1/10 #######

565 716 €

533 519 €

32 196 €

1/1/10 #######

564 044 €

552 906 €

11 138 €

1/1/10 #######

928 792 €

868 337 €

60 454 €

93

Station Level Optimization

Select where you want to go


Network Pricing Simulator – Modeling (1)

Full Screen

Teboil

Modeled vs Measured impact of Service & location quality on normalized share
(2010, Brand: Teboil )

Normal

Start Regression

Regression Results


25,0%

Row Labels Qual Shr Impact Ind LocQ Ind Qual Shr Impact
ServQ
ServQ
LocQ
Qual Shr Impact Q Shr Impact
Mod
Aura
5,6%
117%
126% 20,0%
5,6%
116,7%
126,3%
5,6%
5,4%
Espoo
-2,7%
100%
83%
-2,7%
100,0%
83,3%
-2,7%
-2,4%
Hämeenkyrö
-6,5%
80%
71%
-6,5%
80,0%
70,6%
-6,5%
-6,3%
Hämeenlinna
-5,7%
129%
43% 15,0%
-5,7%
128,6%
42,9%
-5,7%
-5,1%
Heinola
-15,9%
43%
33%
-15,9%
42,9%
33,3%
-15,9%
-15,3%
Helsinki
-7,4%
71%
71% 10,0%
-7,4%
70,6%
70,6%
-7,4%
-7,2%
Huittinen
6,4%
123%
127%
6,4%
123,1%
127,3%
6,4%
6,1%

Regression Statistics
Multiple R 0,992269
R Square 0,984598
Adjusted R Square
0,984027
Standard Error
0,008709
Observations
57

Hyvinkää
Ilomantsi

Navigation


ANOVA

7,0%
-1,9%

111%
120%

141%
75%

5,0%
-1,9%

110,5%
120,0%

Jämsä
Janakkala
-20,0%
Juva
Kaavi
Kankaanpää

-10,7%
9,0%
-15,0%
-2,3%
2,7%
-3,3%

40%
108%
-10,0%
117%
145%
108%

67%
171%
-5,0%
60%
84%
67%

-10,7%
9,0%
0,0%
0,0%
-2,3%
2,7%
-5,0%
-3,3%

40,0%
66,7%
-10,7%
-10,9%
107,7%
171,4%
9,0%
10,8%
5,0%
10,0% -2,3% 15,0% -3,9% 20,0%
116,7%
60,0%
145,5%
84,2%
2,7%
2,4%
107,7%
66,7%
-3,3%
-3,9%

Regression
Residual
Total

Kärsämäki
Kauniainen
Kaustinen
Kempele

-7,9%
-3,2%
7,8%
-1,5%

47%
67%
145%
100%

86%
120%
123%
92%

47,1%
66,7%
145,5%
100,0%

85,7%
120,0%
123,1%
92,3%

-7,9%
-3,2%
7,8%
-1,5%

-7,5%
-0,7%
7,9%
-1,1%

Coefficients
Standard Error t Stat
Intercept -0,24419 0,004335 -56,329908
X Variable 10,103344 0,003434 30,094693
X Variable 20,140246 0,003522 39,8241346

Kerimäki

-5,2%

40%

107%

-5,2%

40,0%

107,1%

-5,2%

-5,3%

Kiiminki

-4,8%

40%

100%

-4,8%

40,0%

100,0%

-4,8%

-6,3%

86%

-20,0%
-1,5%

108,7%

86,2%

-1,5%

-1,1%

Kokkola

-1,5%

109%

7,0%

-7,9%
-3,2%
-10,0%
7,8%
-1,5%
-15,0%

141,2%
75,0%

7,0%
-1,9%

6,8%
-1,5%

SUMMARY OUTPUT



df

94


SS
MS
F
Significance F
2 0,261807 0,13090368 1725,99507 1,1608E-49
54 0,004095 7,5842E-05
56 0,265903
P-value
1,1861E-49
2,0088E-35
1,0348E-41

Lower 95%
-0,2528846
0,0964593
0,1331856

Upper 95%
-0,2355021
0,11022865
0,1473065


Brand

62
62

Network Pricing Simulator – Modeling (2)

Full Screen

Impact of relative Price position (X) on relative share (Y)
(2010, Brand: A24, Station: Kouvola)
Row Labels
140%
A24
A24
A24
130%
A24
A24
120%
A24
A24
A24
110%
A24
A24
100%
A24
A24
A24
90%
A24
A24
80%
A24
A24
A24
70%
A2498%
A24

Zone
Kouvola
Kouvola
Kouvola
Kouvola
Kouvola
Kouvola
Kouvola
Kouvola
Kouvola
Kouvola
Kouvola
Kouvola
Kouvola
Kouvola
Kouvola
Kouvola
Kouvola
Kouvola
Kouvola 99%
98%
Kouvola

Regression Results

Date
Average of Rel Share Average of Rel Price Rel Share Rel Price
01/01/2010
64%
100,7%
64%
101%
02/01/2010
48%
101,8%
48%
102%
03/01/2010
58%
101,2%
58%
101%
04/01/2010
52%
101,6%
52%
102%
05/01/2010
91%
99,6%
91%
100%
06/01/2010
88%
99,7%
88%
100%
07/01/2010
76%
100,3%
76%
100%
08/01/2010
51%
101,5%
51%
101%
09/01/2010
50%
101,5%
50%
102%
10/01/2010
87%
99,9%
87%
100%
11/01/2010
68%
100,6%
68%
101%
12/01/2010
81%
99,9%
81%
100%
13/01/2010
95%
99,5%
95%
99%
14/01/2010
90%
99,7%
90%
100%
15/01/2010
75%
100,1%
75%
100%
16/01/2010
56%
101,1%
56%
101%
17/01/2010
107%
99,2%
107%
99%
18/01/2010
72%
100,4%
72%
100%
19/01/2010100%
99%
100% 61%
101%
101%100,9%
102% 61%102% 101%103%
20/01/2010
88%
99,5%
88%
100%

Start Regression

SUMMARY OUTPUT
Regression Statistics
Multiple R 0,977051
R Square 0,954629
Adjusted R Square
0,954504
Standard Error
0,040874
Observations 365

Normal



ANOVA
df
Regression
Residual
Total

SS
MS
F Significance F
1 12,76001 12,76001 7637,68 7E-246
363 0,606452 0,001671
364 13,36647


Coefficients
Standard Errort Stat P-value Lower 95%
Upper 95% 95,0% 95,0%
Lower Upper
Intercept 24,31444 0,2692 90,32125 7E-251 23,7851 24,8438 23,7851 24,8438
X Variable 1-23,4824 0,268696 -87,3938 7E-246 -24,0108 -22,954 -24,0108 -22,954

95


A24 Kouvola
DI

Navigation

Brand Zone
TypFuel

Network Pricing Simulator – Decision support
Station & Date

Optimization Performance
Profit

Optimization parameters

ROS %

Criteria

SoC %

Weight

Constraints

Brand Zone

Teboil Punkalaidun

Optimized

374 €

1,9%

52,8%

ROS

30%

> 1,7%

Date

04/01/2010

Initial

356 €

2,2%

42%

SoC

70%

> 19%

Teboil Punkalaidun - performance by type of fuel

Optimize Station level pricing

12%

ROS %
10%
8%

Full Screen

Normal

6%


DI
95E

98E

0%
0%

10%

20%

30%

40%

50%


SoC %
60%

70%

Navigation

2%

80%

-2%
-4%


-6%

Row Labels
95E
98E
DI
Grand Total


Price

Nb Comp
2
2
2
2

1,541 €
1,532 €
1,254 €

Mod Revenue
7 768 €
3 966 €
8 423 €
20 157 €

Share Index
0,93
1,06
1,18

SoC

Gross
Profit

ROS %
46,3%
52,9%
58,8%

1,2%
1,7%
2,6%

91 €
67 €
215 €

52,8%

1,9%

374 €

96


4%

1,544 €
1,565 €
1,300 €

37,7%
44,6%
52,6%

-9,1%
-8,4%
-0,4%

Network Pricing Simulator – Detailed Simulation
Station : Hämeenlinna - Date: 28 June - Price simulation / Optimization
Competitive Scenario Today

Changes (+ or -) from base scenario

TRUE

TRUE

TRUE

TRUE

TRUE

TRUE

Teboil

ABC

Neste

Seo

Shell

St1

Serv Q Today
6
3
Loc Q Today
2
5
Fuel Prices today Save Prices

7
8

8
4

2
5

Teboil

2
4

ABC

Neste

Seo

Shell

St1

Changes to Serv Q
Changes to Loc Q
Changes to Fuel Prices

95E

1,672 €

1,703 €

1,679 €

1,706 €

1,672 €

1,673 €

95E

-0,010 €

98E

1,706 €

1,782 €

1,773 €

1,724 €

1,756 €

1,706 €

98E

-0,060 €

DI

1,462 €

1,506 €

1,502 €

1,464 €

1,478 €

1,484 €

DI

Day

Share of Choice

Teboil

ABC

Neste

Seo

Shell

St1

95E

11,4%

9,0%

32,1%

20,0%

14,5%

13,1%

98E

16,7%

6,2%

24,6%

27,1%

6,7%

18,8%

DI

14,6%

7,8%

26,0%

30,6%

11,9%

9,1%

Revenues

34 309 €

20 608 €

72 340 €

64 479 €

30 251 €

31 812 €

2 273 €

1 949 €

6 306 €

4 971 €

2 422 €

2 240 €

Fixed Costs

584 €

1 002 €

2 196 €

1 558 €

889 €

623 €

Profit

766 € -

200 €

821 €

1 027 €

204 €

400 €

Margin

ROS
SoC

2,2%
13,6%

-1,0%
8,1%

1,1%
28,5%

1,6%
26,8%

0,7%
12,4%

1,3%
13,9%
97

223

Simulation Parameters

Projected Impact on Performance

28

Month

June 28

Location

Hämeenlinna
Hämeenlinna

Update
June

Optimization parameters

Optimize
_

Criteria
Return on Sales

Weight

Constraints

70%

>

1,0%

Share of Choice

30%

>

10,0%

Simulated Performance
Simulated
Initial

Profit
ROS % SoC %
766 €
2,2%
13,6%
375 €

1,5%

11,5%

Network Pricing Simulator – Network Optimization

Teboil

TypFuel

98E

Date

Brand: Teboil Fuel: 98E - ROS vs Share of Choice, by
station
(bubble size proportional to revenues)

04/01/2010

12%

ROS %

10%

Row Labels Nb Comp
Aura
8%
Espoo
Hämeenkyrö
Hämeenlinna
6%
Heinola
Helsinki
Huittinen
4%
Hyvinkää
Ilomantsi
Jämsä
2%
Janakkala
Juva
Kaavi 0%
Kankaanpää
0%
Kärsämäki
Kauniainen
-2%
Kaustinen
Kempele
Kerimäki
-4%
Kiiminki
Kokkola

Optimization Parameters Optimization Performance
Criteria

ROS
SoC

Weight Constr. (>)
50%

0,10%

Optim.

6 397 €

2,4%

31,9%

50%

18,00%

Initial

4 509 €

2,3%

28%

Gross

-6%

98

ROS % SoC %

Station level Data

Optimize MultiStations pricing

Prev Prc ev Prev Marg
R
VarCost / Ltr Profit Min Pr MaxPr Price
Gr
Profit
3 ##### 6 682 €
388 € 1,542 €
94 € 1,605 € 1,739 € 1,661 €
118 €
6 ##### 37 978 € 2 654 € 1,462 € 1 320 € 1,538 € 1,666 € 1,551 €
1 494 €
3 ##### 6 434 €
455 € 1,471 €
147 € 1,540 € 1,668 € 1,579 €
151 €
6 ##### 2 772 €
271 € 1,465 €
-37 € 1,535 € 1,663 € 1,543 €
340 €
3 ##### 3 233 €
229 € 1,516 €
-22 € 1,569 € 1,700 € 1,602 €
27 €
6 ##### 11 852 €
924 € 1,475 €
-1 € 1,532 € 1,660 € 1,543 €
723 €
2 ##### 5 972 €
426 € 1,448 €
143 € 1,584 € 1,629 € 1,584 €
144 €
3 ##### 11 792 €
767 € 1,412 €
397 € 1,491 € 1,616 € 1,544 €
491 €
Kärsämäki
3 ##### 5 897 €
414
172
1,581 € 1,713
Kokkola € 1,512 € Espoo € Janakkala Ilomantsi€ 1,626 € Hyvinkää €
Huittinen 170
Heinola
2 ##### 5 095 €
330 € 1,509 €
91 € 1,564 € 1,694 € 1,628 €
95 €
Kauniainen
HämeenkyröAura
Kiiminki
Jämsä
Kaustinen
Helsinki
Juva
4 ##### 6 578 €
548 € 1,478 €
205 € Kaavi
1,552 € 1,681 € 1,594 €
205 €
3 ##### 3 472 € Kerimäki€ 1,493 €
274
54 € 1,547 € 1,676 € 1,591 €
91 €
4 ##### 5 179 €
401 € 1,506 €
101 € 1,579 € 1,710 € 1,612 €
117 €
SoC % €
2
4 914 €
334 € 1,518 €
110 € 40%
1,573 € 1,70450% 1,639 €
€
113
10%#####
20%
30%
60%
4 ##### 1 722 €
149 € 1,463 €
75 € 1,535 € 1,663 € 1,545 €
134 €
2 ##### 3 636 €
304 € 1,481 €
91 € 1,538 € 1,666 € 1,592 €
107 €
4 ##### 4 202 €
413 € 1,494 €
101 € 1,571 € 1,702 € 1,610 €
124 €
2 ##### 5 526 €
385 € 1,517 €
139 € 1,573 € 1,704 € 1,639 €
144 €
3 ##### 1 678 €
154 € 1,519 €
4 € 1,571 € 1,702 € 1,636 €
29 €
2 ##### 1 590 €
286 € 0,546 €
35 € 0,639 € 0,692 € 0,666 €
33 €
5 ##### 12 538 €
979 € 1,487 €
388 € 1,561 € 1,691 € 1,626 €
307 €

Profit

Station
Aura
Espoo
Hämeenkyrö
Hämeenlinna
Heinola
Helsinki
Huittinen
Hyvinkää
Ilomantsi
Jämsä
Janakkala
Juva
Kaavi
Kankaanpää
Kärsämäki
Kauniainen
Kaustinen
Kempele
Kerimäki
Kiiminki
Kokkola

Price
1,661 €
1,551 €
1,579 €
1,543 €
1,602 €
1,543 €
1,584 €
1,544 €
1,626 €
1,628 €
1,594 €
1,591 €
1,612 €
1,639 €
1,545 €
1,592 €
1,610 €
1,639 €
1,636 €
0,666 €
1,626 €

Mod
Revenue
5 743 €
49 623 €
6 719 €
12 690 €
5 196 €
37 160 €
4 982 €
10 063 €
5 883 €
4 571 €
7 532 €
5 045 €
6 316 €
4 560 €
3 919 €
4 591 €
6 056 €
5 239 €
2 495 €
1 584 €
10 536 €

SoC

Gross
Profit

ROS %
46,0%
28,5%
39,6%
24,5%
30,0%
21,0%
51,6%
54,2%
42,5%
46,7%
36,8%
36,8%
36,2%
50,5%
25,7%
45,1%
35,3%
51,3%
19,6%
44,7%
17,7%

2,1%
3,0%
2,2%
2,7%
0,5%
1,9%
2,9%
4,9%
2,9%
2,1%
2,7%
1,8%
1,9%
2,5%
3,4%
2,3%
2,1%
2,7%
1,2%
2,1%
2,9%

118 €
1 494 €
151 €
340 €
27 €
723 €
144 €
491 €
170 €
95 €
205 €
91 €
117 €
113 €
134 €
107 €
124 €
144 €
29 €
33 €
307 €

Navigation

Brand

Tool 28: D & R Savings model (Illustrative)

What it is:
Interactive simulation of
potential impact of changes in
D&R policies
Who is affected?
How much?
Potential impact on
 demand & volumes.
Support to sales force in
explaining / implementing price
changes on their portfolio
What it does:
pricing movements
Better planning / evaluation & selection of D&R changes.
Improved & faster implementation
Improved fairness

The stakes:
40 to 8 month delay in Implementation
20 to 60% fewer ‘exceptions’
Page 99

Estimating the impact of new Pricing Policy

Page 100

Evaluating Impact by Customer

15,0%

Year

(All)

Month

(All)

Region Name

(All)

Industry Name

(All)

Acct Mngr Name

(All)

Glob SoW Code

(All)

Market Name

(All)

Discounts and Rebates % of Gross Sales

Max. Disc. &
Rebates %

Pricing

Gross Sales Revenues & D&R Actual vs. Limit

70%
60%

Normal
Screen

50%
Full
Screen

40%
30%

20%
Market Segment Name
Price Driven
10%
Customer Name
(All)
(All)
(All)
Product Name

(All)

Material GrP Name (All)
Product Grp Name

(All)

Prod Hier Name

(All)

0%

-10%
-20

0
20
Cust. Gross Sales Rev

40

(All)

Total D&R
(Current)

Sales Gross D&R % G.S.R.
Rev.
(Current)

Product Family Name(All)

7 139 205

74 082 396

9,6%

60

80
100
120
Customers Gross Sales Revenues

Maximum
D&R %

D&R
Applying
Max %

15,0%

6 165 641

101

140

160

New D&R % Disc. and Reb. Savings NOK
G.S.
8,3%

973 564

180

Tool 29: Segmentation & Clustering
90 000 000
80 000 000
70 000 000
60 000 000
50 000 000
Comp2

40 000 000

Comp1
30 000 000

What it is:
Segmentation of Clients / Consumers,
based on.
Attributes sought
Potential & willingness to pay
May be used for a single product or a
group of products, globally or by channel.

ACME

20 000 000

10 000 000
0
Value
Driven

Price
Driven

Delivery
Driven

Service
driven

Speed
Driven

Quality
driven

1

2

3

4

5

What it does:
Helps define effective Value / Pricing
segmentation
Help visualize weights / stakes &
priorities by segment.

6

Development of targeted offers.
Support to targeting by sales force
Targeted communication & marketing
The stakes:
Varies considerably. Segmentation & adaptation of Value Propositions may often result in double digit
price increases or Volume increases

Segmentation & Clustering – Market research
insights

103

Segmentation & Clustering – Behavioral Segmentation

104


105


106

Tool 23: Statistics & Regression Tools (Illustrative)

What it is:
Statistical tools to support in
depth analysis & modeling of
Pricing & Value
Clustering
CBC / Discrete choice
Logit Regressions
..

What it does:
Enables true insights &
sophisticated modeling

Understanding causalities / Identififying trends
Ability to model / predict
Continous improvement based on historical data

The stakes:
Insights / price response modeling is at the root of Price optimization

Page 107

Statistical tools to prodide insights on causality
Share of Wallet vs Rating

Share of Wallet vs Rating - ACME
Customer Value Map

Competitors Value Graphs

(All)
(All)
East
(All)

7,0

1,50

9,0

90 000 000

8,0

80 000 000

Value
Disadvantaged

7,0

Pricing

6,0

Comp 1

4,0

0,50

Comp 2

1,00

Comp 2

3,0

Value
Advantaged

2,0

Value Graph Segment

1,0

Weight

1

1

Ship
Complete

Defects

Range

10

13

Service Shipment
Date

0
Price
Driven

Delivery
Driven

Service
driven

Speed
Driven

Quality
driven

2

3

4

5

6

USUAL
SCREEN

8,0
y = 4,0565e0,7579x
R² = 0,1959

7,5
7,0
6,5
6,0
5,5

5,0
4,5
4,0
3,5
3,0
0%

10%

20%

30%

40%

50%

60%
108

70%

80%

90%

4,5
4,0

4,0
3,5
3,0

3,0
Value
Driven

Price

FULL
SCREEN

5,0

3 311 727

3,5

10 000 000

19

"Share of Wallet (x) vs Rating (y)"

5,5
729 108

1 008 391

4,5

20 000 000

1

0,50
Relative Perceived Value

56

ACME

6,5
6,0

5,0
Comp1

30 000 000

7,0

1 104 148

5,5

Comp2

40 000 000

7,5

996 900

6,0

50 000 000

1,50

Fair Value
Line

Value Map Seg/Reg

0,0

8,0

SoW vs Rtg Clie

SoW vs Ratings

6,5

60 000 000

Comp 1

ACME

5,0

Segment Share

70 000 000

ACME
Relative Price

Segment
SegmentName
Region
Acct Mngr

100%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

0%

10%

20%

30%

40%

50%

60%

7

Level 3
Performance reporting & monitoring
Pricing Toolbox Full Screen
Reporting Analysis
P& L Reports

Traffic Lights
Price
Change


#E440

BRIDGEST ONE T URANZA EL400-02

vs Ref.
vs Ref.
Value
Win / Loss Elasticity
Comp
Comp Positioning Indicator Measure

GM %

Action
Overall Required

Fullfilment

0

1

8%

9

13%

1,5

61%

94%

0,60024934

59%

16%

0

1

8%

7

20%

1,5

60%

85%

0,57732634

58%

107

16%

0

1

8%

7

15%

2,0

54%

85%

0,53853075

54%

12%

0

1

8%

9

8%

1,9

59%

97%

0,59126945

59%


#E402

73

19%


#E329

82

11%


#G432

0

1

8%

7

7%

1,9

59%

92%

0,58842208

58%

0

1

8%

7

6%

1,2

41%

86%

0,40759921

103

0

2

8%

7

8%

0,9

53%

85%

0,53514842

52%

8%

0

1

8%

9

7%

1,0

59%

87%

0,60924063

60%

117

5%

0

1

8%

9

4%

1,2

58%

98%

0,59778409

60%


#E445

123

5%

0

1

8%

7

7%

1,6

45%

101%

0,46415437

46%


#C010

82

3%

0

1

8%

7

8%

1,6

59%

84%

0,59362246

#G447

137

1%

0

1

10%

9

6%

1,1

45%

Y

X

58%



85%

0,45843948

X

45%

95

1%

0

1

8%

9

4%

1,7

42%

99%

0,43203873

43%

#7334

94

1%

0

1

8%

8

2%

1,0

37%

101%

0,36211277

36%

Y
Y

BRIDGEST ONE T URANZA EL42 RFT


#E446

119

2%

0

1

8%

9

3%

1,2

40%

85%

0,38266467

38%


#7335

98

3%

0

1

8%

9

1%

1,6

37%

101%

0,37233824

37%


#E330

78

5%

0

0

8%

7

1%

2,3

41%

88%

0,40485926

40%

86

6%

0

0

8%

9

1%

3,3

57%

100%

0,56939127

56%

#7271

105

7%

0

0

8%

7

0%

4,9

55%

99%

0,53339714

54%

118

BRIDGEST ONE T URANZA ER30

#7272

10%

0

0

8%

7

0%

6,8

58%

101%

0,59676541

59%


#7270

78

6%

0

0

8%

7

0%

4,9

59%

98%

0,60021896

60%


#7273

99

9%

0

0

8%

8

0%

4,3

39%

91%

0,39917475

40%


#7275

103

7%

0

0

8%

9

0%

2,7

53%

90%

0,51685851

51%


#C195

128

8%

0

0

8%

9

0%

3,5

54%

93%

0,53413606

53%


#7269

116

7%

0

0

8%

7

0%

5,0

40%

85%

0,40320361

40%


Fin . Reports

Y

40%

8%

109
#C193

BRIDGEST ONE T URANZA EL42

Share
Growth

13%

77

BRIDGEST ONE POT ENZA RE92A AS

Discount
Change

97
115

BRIDGEST ONE

#7274

75

8%

0

0

8%

7

0%

4,2

46%

85%

0,45598798

46%

Corridors

X
Y

Select SBU
P1

Key Tools
Transactional Ana
Objectives vs. Realized  Pricing & Value Waterfalls
Price Evolutions
Waterfall
 Time series
 Elasticities / Pricing dynamics
analyses
Exceptions Mngmt
Elasticities
Time Series
Revenue Variance


Price Variance

Menu-Tier Variance

Item-Price Variance



Volume Variance

Mix Variance

Quantity Variance

Marketing & Sales support

Value Analysi

Reporting tools tools to help monitor, control & Ana.
Share Evolutions
Peer Pricing
PortFolio
manage Pricing & support effective implementation
of pricing policies
109

EVC / EVIU

Value Maps / curve

Tool 31: Flexible P&L Reporting (Illustrative)
Go to Financial

Pricing

Month
Region Code
Market Name
Industry Name
Product Family Code
Product Grp Code

(All)
(All)
(All)
(All)
(All)
(All)
(All)

Go to Product
Normal

Go to Price

Full Screen

Go to SKU
Go to Product
Go to Customer
2007

2008

2009

2010 % Gr (10/09)

Theoretical Revenues 1)
Unexplained Discount

94 832 963
-2 986 736

92 711 698 117 583 738 113 518 393
-2 790 767 -2 990 030 -2 789 994

-3,5%
-6,7%

Gross Sales

91 846 227

89 920 931 114 593 708 110 728 399

-3,4%

Total Discounts
Invoice Revenues

-13 692 016
78 154 211

-12 291 691 -17 870 605 -15 830 026
77 629 239 96 723 104 94 898 374

-11,4%
-1,9%

Total Rebates & freebees
Net Revenues

-10 396 467
67 757 744

-10 114 566 -13 041 436 -12 537 011
67 514 674 83 681 667 82 361 362

-3,9%
-1,6%

COGS
Total Client & Mktg costs
Other Logistical Costs
Net Margin
Net Margin %
D&R as Pct of Theo Sales

-37 778 327
-21 873 956

-38 043 193 -45 991 374 -45 737 252
-22 296 836 -27 826 188 -28 026 613

-0,6%
0,7%

-13 768 496
-15%
29%

-15 122 192 -17 962 084 -19 429 116
-17%
-16%
-18%
27%
29%
27%

8,2%
11,9%
-4,8%

What it is:
Regular reports ensuring
coherence with Finance &
enabling insights on impact of
pricing on overall financial
performance
Ability to zoom or group flexibly
by product / segment / regions
What it does:
provide visibility accountability
for Pricing performance
Provides early warning of
threats & improved visibility for
opportunities

Better anticipation / faster reaction to changes.
Improved monitoring & control of performance

The stakes:
Improved control & faster reaction

Page 110

Tool 32: Pricing Traffic Lights (Illustrative)
Pricing

Price
Change

BR ID GE S T ON E
BR ID GE S T ON E P OT E N ZA R E 92A AS

#E440

BR ID GE S T ON E T U R AN ZA E L400-02

#E402


#E329


#G432

BR ID GE S T ON E T U R AN ZA E L42

#C193


#E445


#C010


#G447

BR ID GE S T ON E T U R AN ZA E L42 R FT

#7334


#E446


#7335


#E330

BR ID GE S T ON E T U R AN ZA E R 30

#7271


#7272


#7270


#7273


#7275


#C195


#7269


#7274


#F355

Discount
Change

100
115
98
88
69
83
103
98
115
125
83
127
96
100
111
112
85
84
101
121
77
99
107
122
120
77
88
126
83

13%
14%
21%
27%
26%
23%
30%
41%
49%
58%
39%
32%
25%
21%
31%
42%
53%
29%
26%
37%
34%
42%
25%
20%
18%
19%
20%
23%
13%

Share
Growth

vs Ref.
vs Ref.
Value
Win / Loss
Comp
Comp
Positioning Indicator

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

8%
8%
8%
8%
8%
8%
8%
8%
8%
8%
8%
10%
8%
8%
8%
8%
8%
8%
8%
8%
8%
8%
8%
8%
8%
8%
8%
8%
8%

9
9
9
9
9
8
8
7
9
7
7
7
9
7
9
9
8
7
7
8
9
7
8
7
8
9
7
9
7

13%
19%
22%
33%
48%
49%
24%
31%
29%
18%
15%
14%
18%
10%
7%
7%
4%
5%
6%
9%
7%
10%
14%
18%
23%
34%
20%
21%
16%

Elasticity
Measure

GM %

1,5
1,6
1,7
1,0
0,9
1,3
1,9
1,1
1,0
0,8
0,9
1,0
0,9
0,5
0,4
0,4
0,4
0,5
0,7
0,9
1,1
1,4
1,0
1,5
1,1
0,8
0,9
1,0
1,0

60%
58%
58%
58%
45%
37%
50%
58%
60%
60%
58%
59%
39%
37%
46%
51%
59%
59%
45%
43%
40%
37%
47%
59%
42%
37%
39%
58%
59%

94%
101%
89%
87%
85%
99%
84%
99%
102%
84%
95%
85%
101%
102%
100%
86%
98%
83%
98%
102%
101%
84%
93%
99%
99%
84%
100%
102%
101%

Action
Overall Required

Fullfilment
0,6
0,6
0,6
0,6
0,5
0,4
0,5
0,6
0,6
0,6
0,6
0,6
0,4
0,4
0,5
0,5
0,6
0,6
0,5
0,4
0,4
0,4
0,5
0,6
0,4
0,4
0,4
0,6
0,6

60%
58%
59%
60%
46%
38%
51%
57%
60%
58%
59%
60%
38%
37%
47%
51%
58%
58%
46%
44%
39%
37%
46%
60%
43%
37%
40%
59%
58%

X

Y
X

Y

Y
X

What it is:
Systematic & regular review of
pricing performance at detailed
with indicators / early warning
system to identify opportunities &
threats & know where
management attention should
focus.
What it does:
Saves management times by
providing key synthetic info &
warning systems

X
Y

Better anticipation / faster reaction to opportunities & tgreats
Management attention better focused on real issues
Faster &eralier issue resolution

The stakes:
Agility & competitive leadership

Page 111

Six Qualities of the Best Pricing Software

Six Qualities of the Best Pricing Software

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