Transcript Business Analysis

Business Analytics
for Decision Support
10/16/08
ModelSheet and the ModelSheet logo are registered trademarks of ModelSheet Software, LLC.
Copyright © 2009 by ModelSheet Software, LLC
Principal Consultant in Business Analytics
Howard I. Cannon, Chairman and CTO, Founder
While working on the MIT Research Staff, Howard invented Flavors, the first non-hierarchical objectoriented programming system. He co-founded Symbolics, where he engineered major pieces of the
company's hardware and software, founded and ran the successful Graphics Division, and as VP of
Product Marketing managed the introduction of several key products. He was VP of Development at
Macsyma, where he led a small team that produced review-winning technology when matched against
much larger competitors. Howard founded Groton NeoChem, where he led the development and marketing
of revolutionary Web-based data management software for drug discovery. The company was sold to
SciQuest. He has been an executive in a number of other companies, where he led development and made
numerous technical innovations. Howard did undergraduate work at MIT.
Richard J. Petti, President, Founder
As a marketing executive at MathWorks, a $400 million software company, Dick introduced revolutionary
business analytics that directly impacted overall revenue and profitability, contributed on all 11
management boards for commercial businesses, and restructured strategic planning to enable project
champions and executives to better evaluate opportunities. As Division GM at Symbolics, he turned around
the Macsyma business and raised funding to spin it off as Macsyma Inc., which he ran until its acquisition
by a defense contractor. Dick served as a consultant at McKinsey, where he received top ratings for his
financial analysis, operations analysis, and troubleshooting in R&D management. Dick has worked or
consulted in 8 businesses in Fortune 100 companies, including GE HQ and two other GE locations. MBA U
Chicago, PhD Berkeley, BS MIT.
®
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Experience includes diverse industries and functions.
Industries
Functions
Software
General
Management
Macsyma, Inc.
Symbolics
Armstrong Computing
Marketing,
Bus. Planning
MathWorks
Macsyma
Symbolics
Hasbro Interactive
Alphatech
Groton Neochem
Insightful
SciComp
Manufacturing
& Computer
Operations
Product
Development
Macsyma
Symbolics
Intellivid
Manufacturing
Consulting
GE HQ
McKesson
GE Wireless Communications
AT&T
Exxon Nuclear
McKinsey
GE Lighting
Boeing
American Express
GE Lighting
Xerox
Pilgrim Telephone
®
Industry and Functional Background
Service
Booz, Allen &
Hamilton
Return
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Outline
Introduction
• Background
• Strategy & analytics
Business
Development
• Project selection
o Business planning
o Business cases
Finance
o Project cost accounting
o ModelSheet models
– Business financial plan
– Investment project analysis
Key:
• Included in main presentation
o Excluded from main presentation
Marketing
Programs
• Program profitability
o Pricing analysis
o Data mining
o ModelSheet Model
Sales Planning
& Resources
• Sales planning
• Sales force
organization
Sales
Analysis
(Program profitability)
•
•
•
•
Product
Programs
Operations
Analysis
• Product profitability
o Software quality
o ModelSheet model
o Manufacturing
o Distribution
o Computer operations
o ModelSheet model
(Product profitability)
(Process flow analysis)
®
In-depth sales analysis
Color maps
Market basket analysis
Customer x product
profitability
Summary &
Next Steps
Copyright © 2009 ModelSheet Software, LLC.
4
Effective use of information is an increasing source
of advantage in non-information industries.
“Is a supermarket a business that sells food,
or is it a business that exploits knowledge
about customer preferences, geographical biases, supply chain logistics,
product life cycle, many kinds of sales information
to optimize its operations
delivery, inventory, pricing, product placement, promotion
to grow and increase margin?
The answer to that question may determine
your company’s long-term viability in the Information Age.”
Source: Business Intelligence,
by David Loshin, page 11
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Strategy and analytics
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Business Intelligence
transforms data into actions in three stages.
Extract information from data.
Analytic information means trends and patterns in data.
Example of information: Sales of product A are lower in German Auto industry
and higher in Japan than in overall Auto markets.
Create knowledge from analytic information and business context.
Knowledge means placing information in a business context, including
causes, effects, interrelationships.
Example: Product A sells more in Germany and less in Japan because it use
used in electronics pioneered in Germany that Japan has not adopted.
Create plans and actions from knowledge to improve results.
– Create tactical plans the serve the existing strategy.
– Alter strategy for serving customers and generating value.
®
Strategy and analytics
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Business intelligence can transform data into actions
in many parts of a business.
Domain
Sales analysis: analyze patterns of
strength and weakness
Benefits
Sales plans: produce consistent,
detailed sales plans
Yields better decisions than ad-hoc
opinions
Allocate resources better, build
consensus behind targets
Marketing programs: measure
revenue generation, profit
Let marketing ROI drive most
marketing programs
Product and channel profitability
Take account of profitability, but
don’t let it dominate planning.
Investment project evaluation:
score candidate projects
Scoring systems and tools aid
very complex decisions.
Operations analysis: quantify costs,
margins in manufacturing, distribution, service, admin processes
Translate objectives into
operational metrics and goals.
Return
®
Strategy and analytics
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Outline
Introduction
• Background
• Strategy & analytics
Business
Development
• Project selection
o Business planning
o Business cases
Finance
o Project cost accounting
o ModelSheet models
– Business financial plan
– Investment project analysis
Key:
• Included in main presentation
o Excluded from main presentation
Marketing
Programs
• Program profitability
o Pricing analysis
o Data mining
o ModelSheet Model
Sales Planning
& Resources
• Sales planning
• Sales force
organization
Sales
Analysis
(Program profitability)
•
•
•
•
Product
Programs
Operations
Analysis
• Product profitability
o Software quality
o ModelSheet model
o Manufacturing
o Distribution
o Computer operations
o ModelSheet model
(Product profitability)
(Process flow analysis)
®
In-depth sales analysis
Color maps
Market basket analysis
Customer x product
profitability
Summary &
Next Steps
Copyright © 2009 ModelSheet Software, LLC.
8
Challenge: Identify high and low-performing
marketing programs.
• What does 'success' mean for a marketing program?
• Revenue-generation metrics are often misleading.
– How do you allocate credit among marketing programs that touched a
customer?
• Lead generation metrics are often misleading.
– Lead-to-order conversion rates and average order sizes vary across
segments.
Most companies can’t adequately measure
effectiveness of Marketing and Sales programs.
®
Marketing programs evaluation
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Solution: Evaluate programs mostly on
revenue generation and contribution margin.
• Key Assumptions / Methods
–
–
–
–
The customer is the site, not the person who purchases.
Each lead event declines in effectiveness over time.
Program event types have different levels of impact.
Allocate revenues to marketing programs.
• Measures of Effectiveness
– Generation of leads / new leads / or highly qualified leads
– Generation of revenue / new customer revenue
– Contribution margin is generally the best metric.
• How to use the Metrics
– Compare programs by program type and at several levels of hierarchy.
– Compare programs for each market segment.
– Combine metrics with field knowledge.
®
Marketing programs evaluation
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10
Marketing program analysis shows leads,
imputed revenue, contribution margin $ and %.
Marketing Program Analysis
Pgm Cluster
Sector
Pgm Bud Office
Pgm Grp
Pgm Ind Grp
Pgm Ind Fam
Unprod_Ld?
Cmpgn Attend
Pgm Family
Acct Region
(All)
(All)
(All)
(Multiple Items)
(All)
(All)
(All)
(All)
(All)
(All)
Pgm Type
Seminar
Pgm Sub-Type
Private Seminar
Specify country
and industry
Specify year,
quarter of event
Pgm
FR - Paris - 2005Jan15
FR - Rouen - 2005Jan26
Private Seminar Total
Public Seminar
FR- Platform Lille - 2005Mar12
Public Seminar Total
Seminar Total
Specify type of
lead event
Cmpgn
Sales Tier
Acct Location
Acct Ind Grp
New/Old
Opty/Order
Lead Qtr
Lead Yr
Rev_Ev_Yr
Data
Win $
9,073
630
9,703
330
330
10,033
All reports contain illustrative data
®
Marketing programs evaluation
(All)
(All)
France
Auto
(All)
(All)
Q1
2005
(All)
CM $
7,855
470
8,325
337
337
8,662
CM %
93.8%
33.9%
85.8%
96.9%
96.9%
86.4%
Program Event
with very low
CM %
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11
Client Impact: Marketing Program Analysis
had a strong impact at MathWorks.
• Sales VP: “Revenues are below plan. I want more promotional
spending in every area.”
• CEO: “I won’t spend more until I know where and how effective
are the millions we now spend.”
• 1-2 years later: Marketing uses new metrics to identify individual
program events to improve or eliminate.
• 3 years later: Director of Marketing Programs gets ovation
during presentation in German office for quantitatively linking
strong/weak product-industry segments, customer sites, and
marketing programs.
®
Marketing programs evaluation
Copyright © 2009 ModelSheet Software, LLC.
12
Outline
Introduction
• Background
• Strategy & analytics
Business
Development
• Project selection
o Business planning
o Business cases
Finance
o Project cost accounting
o ModelSheet models
– Business financial plan
– Investment project analysis
Key:
• Included in main presentation
o Excluded from main presentation
Marketing
Programs
• Program profitability
o Pricing analysis
o Data mining
o ModelSheet Model
Sales Planning
& Resources
• Sales planning
• Sales force
organization
Sales
Analysis
(Program profitability)
•
•
•
•
Product
Programs
Operations
Analysis
• Product profitability
o Software quality
o ModelSheet model
o Manufacturing
o Distribution
o Computer operations
o ModelSheet model
(Product profitability)
(Process flow analysis)
®
In-depth sales analysis
Color maps
Market basket analysis
Customer x product
profitability
Summary &
Next Steps
Copyright © 2009 ModelSheet Software, LLC.
13
Challenge: Forecast sales for a business
with thousands of segments.
Segments defined by
products, channels, customer industries/sectors, product options, revenue
categories and interrelated interdependencies between segments.
Managers can not humanly track thousands of segments
Managers must have final say on high-level targets
But cannot humanly deal with excessive detail
®
Sales planning
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14
Solution: Let managers' judgment control the
overall plan and let historical data provide detail.
Our tools:
Base plan on managers' targets for larger segments
• By revenue categories, product, location/channel, license option, customer industry
and sector.
• Use hierarchies of products, locations/channels and industries.
Use historical data to plan detailed segments
Use centrally-planned estimates of macro-effects
Ensuring consistent macro-assumptions across the company and freeing segment
managers from this burden.
Set up performance metrics that are independent of macro-effects.
Your segment managers can predict growth relative to overall company plan in a more
straightforward way.
®
Sales planning
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15
Manager’s targets control the plan;
historical data provides background detail.
Managers' Inputs to Sales Plan - Locations (Channels)
Locations
Perpetual License Revenue
Support Revenue
Mgr
Location
Region
Mgr
Mgr
Target
Target
Perp Rev
Perp Rev
($K)
Grow %
Mgr
Target
Plan
(Fcst-Mgr
Plan Perp
(Fcst-Mgr
Target
Support
Plan
Support
Target)
Plan Perp
Rev Grow
Target)
Support
Rev Grow
Support
Rev Grow
Support
Rev ($K)
%
Perp Δ%
Rev ($K)
%
Rev ($K)
%
Δ%
NA-National
NA
19,890
19,907
7.2%
0.1%
53,980
53,063
26.1%
-2.2%
NA-Regional
NA
14,890
14,901
7.4%
0.1%
30,208
30,990
29.0%
3.3%
NA-Other
NA
24
24
9.9%
0.2%
34
35
32.2%
3.2%
France
EMEA
3,058
3,059
28.1%
0.0%
10,780
10,819
40.2%
0.5%
Germany
EMEA
6,450
6,452
16.1%
0.0%
15,900
16,014
28.7%
0.9%
Nordic
EMEA
2,240
2,241
27.5%
0.0%
7,984
7,966
34.4%
-0.3%
UK
EMEA
2,570
2,571
5.8%
0.0%
7,670
7,672
26.5%
0.0%
EMEA-Other
EMEA
5,989
5,992
6.1%
0.1%
14,985
14,889
34.8%
-0.9%
Japan
APLA
7,193
7,197
5.5%
0.1%
11,856
11,463
11.6%
-3.8%
APLA-Other
APLA
5,090
5,094
5.8%
0.1%
6,977
6,382
4.6%
-9.8%
67,439
9.0%
0.1%
160,374
159,292
26.7%
-0.9%
Total
67,394
Managers’
revenue
targets
8.9%
Green indicates
plan matches
targets well.
Managers’
revenue
targets
®
Sales planning
27.6%
Red indicates plan
doesn’t matches
targets so well.
Copyright © 2009 ModelSheet Software, LLC.
16
Usually allow manager’s location targets
to dominate over industry targets.
Inputs to Sales Plan - Industries
Industries
Perpetual License Revenue
Support Revenue
(Plan - Mgr
Mgr Target Mgr Target
I_Family
I_Group
Rev ($K)
Growth %
Plan
Plan
Trgt)
Rev ($K)
Growth %
Δ%
(Plan - Mgr
Mgr Target Mgr Target
Rev ($K)
Growth %
Plan
Plan
Trgt)
Rev ($K)
Growth %
Δ%
Aero Defense Aero Defense
10.0%
25,112
7.7%
-2.3%
64,178
21.6%
0.0%
Auto-OEM
Auto
10.0%
8,787
9.4%
-0.6%
22,614
23.0%
0.0%
Auto-Parts
Auto
12.0%
2,290
13.2%
1.2%
4,434
41.2%
0.0%
Comms
Electronics
12.0%
5,939
10.4%
-1.6%
14,091
26.3%
0.0%
Computers
Electronics
14.0%
3,147
10.0%
-4.0%
6,403
30.7%
0.0%
Boards
Electronics
13.0%
3,135
10.4%
-2.6%
6,648
26.2%
0.0%
Semicond
Electronics
14.0%
4,254
11.9%
-2.1%
11,588
67.4%
0.0%
Ind Equip
Ind Equip
12.0%
4,630
9.7%
-2.3%
8,651
23.4%
0.0%
Instruments
Tier 2
12.0%
3,024
9.7%
-2.3%
5,277
31.3%
0.0%
Medical
Tier 2
10.0%
2,321
7.1%
-2.9%
4,714
31.9%
0.0%
Process Ind
Tier 2
8.0%
4,800
6.9%
-1.1%
10,694
25.3%
0.0%
10.9%
67,439
9.0%
-1.9%
159,292
26.7%
0.0%
68,620
Managers’ revenue
growth targets
Yellow indicates
plan matches
targets fairly well.
159,292
No
managers’
targets
®
Sales planning
26.7%
Copyright © 2009 ModelSheet Software, LLC.
17
Sales plan shows detail similar to that in sales analyses.
Output of Revenue Plan
P_Family (All)
Product
(All)
Pr_Mgr
(All)
Rev Class P_Group
Perp
PL
Add-ons
Perp Total
Support
PL
Add-ons
Support Total
Grand Total
Region
Location
I_Group
Data
2002
32,427
19,593
52,020
33,852
17,377
51,228
103,248
2003
31,188
18,320
49,508
33,203
16,513
49,717
99,224
(All)
(All)
(All)
2004
35,948
21,278
57,226
36,405
20,348
56,753
113,979
Sales history,
4 years
I_Family
Option
2005
39,458
22,425
61,882
40,526
20,775
61,301
123,183
(All)
(All)
Can filter plan like
sales reports
2006
Var 2006 GR 2003 GR 2004 GR 2005 GR 2006
42,830
3,372
-3.8%
15.3%
9.8%
8.5%
24,609
2,184
-6.5%
16.1%
5.4%
9.7%
67,439
5,556
-4.8%
15.6%
8.1%
9.0%
55,400
14,874
-1.9%
9.6%
11.3%
36.7%
35,902
15,126
-5.0%
23.2%
2.1%
72.8%
91,302
30,001
-3.0%
14.2%
8.0%
48.9%
158,740
35,557
-3.9%
14.9%
8.1%
28.9%
Planned
revenue
Growth history,
3 years
®
Sales planning
Planned
growth
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18
Client Impact: Sales Planning Tools improve segment
detail, credibility and consensus around sales plans.
• Product, industry managers have stronger voice in sales plan.
• Plans can track detail variances in reviews.
• Centralized forecasting of overall sales improves sales plan.
• Sales plan has greater buy-in from executives and managers.
Return
®
Sales planning
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19
Challenge: Help sales reps to sell solutions
in second-tier customer industries.
Geographic sales reps are too diversified to learn industry
problems and solutions.
• Second-tier industries suffer most: communications, electronics, financial
services, biotech-pharmaceutical, industrial equipment.
• Smaller customers in major industries, served by Geo reps, suffer too.
– National account sales has focus needed to sell solutions in largest industries:
aero-defense, automotive.
Previous attempt to organize by industry caused “a train wreck.”
• Must assign new accounts to right industry in real time.
• Commission squabbles
• Sales management highly valued administrative simplicity.
®
Sales force organization
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20
Solution: Reorganize global sales by industry,
but flexibly.
Explore the facts.
• Solicit opinions of industry and SBU marketing managers and sales reps.
• Compare specialization by industry with rep productivity.
– Use ‘Gini’ specialization indices by industry and sales channel.
Design methods, build support.
• Initiate discussion with geographic sales management.
• Promote flexible industry assignment to senior management.
– 80:20 rule is OK. Fix account assignments gradually over several years.
– Discuss relative value of simple sales admin and selling effectiveness.
• Follow up with matrixed multifunctional industry teams.
Expand to global sales force.
• Implement in U.S. and largest foreign markets.
• Implement across national borders in selected situations.
®
Sales force organization
Copyright © 2009 ModelSheet Software, LLC.
21
Client Impact: Worldwide sales force enabled
to sell solutions in secondary industries.
• Marketers and sales reps in secondary industries thrilled by
opportunity to learn problems and sell solutions.
• Project that was resisted at top three levels of management
becomes an unqualified success.
Return
®
Sales force organization
Copyright © 2009 ModelSheet Software, LLC.
22
Outline
Introduction
• Background
• Strategy & analytics
Business
Development
• Project Selection
o Business planning
o Business cases
Finance
o Project cost accounting
o ModelSheet models
– Business Financial plan
– Investment project analysis
Key:
• Included in main presentation
o Excluded from main presentation
Marketing
Programs
• Program profitability
o Pricing analysis
o Data mining
o ModelSheet Model
Sales Planning
& Resources
• Sales planning
• Sales force
organization
Sales
Analysis
(Program profitability)
•
•
•
•
Product
Programs
Operations
Analysis
• Product profitability
o Software quality
o ModelSheet model
o Manufacturing
o Distribution
o Computer operations
o ModelSheet model
(Product profitability)
(Process flow analysis)
®
In-depth sales analysis
Color maps
Market basket analysis
Customer x product
profitability
Summary &
Next Steps
Copyright © 2009 ModelSheet Software, LLC.
23
Challenge: Managers find it hard to cut through data
complexity to reveal detailed sales trends.
First, adjust sales for distortions
in revenue
Due to currency exchange rates, geographic differences in actual prices, channel
or customer discounts, price changes over time, purchase of distributor, trade-ins,
upgrades
in unit sales
Due to product options, trade-ins and upgrades.
due to timing
from seasonality, random large orders, prepayments.
Detect and analyze trends in secondary segments.
– Growth trends in smaller segments often signal emerging opportunities.
– Define segments by products, locations, industries, revenue categories.
®
Sales analysis
Copyright © 2009 ModelSheet Software, LLC.
24
Solution: Highlight broad and detailed trends by segment
and adjust for the most common distortions.
Our tools:
Enable fine segmentation and roll-up of company sales.
• By revenue category, product, product option, location/channel, customer industry
and sector, and application.
• We use hierarchies of products, locations/channels and industries to deliver
appropriate granularity for each situation.
Adjust for structural changes to focus on market effects.
• Adjust revenue for exchange rates and, optionally, by normalizing for price
differences due to geographic location, sales channel, volume discounts, and price
changes over time.
• We also adjust unit sales by defining 'virtual unit' across product options and
accrue for trade-ins and upgrades.
Adjust for timing and noise.
• Report de-seasonalized sales for most purposes.
• Recommend using a good revenue recognition policy for early service orders.
®
Sales analysis
Copyright © 2009 ModelSheet Software, LLC.
25
Pivot reports provide overview and drill-down to detail.
Choose
• revenue
• unit sales
• normalized revenue
Revenue classes
• product sales
• support
• leases
5-levels of
products &
options
Roll-up to
company total
4 levels of
locations
Pivot Table of Revenue - High-Level Overview
Rev-or-Units
Rev Class
P Family
Product
Options
Rev
(All)
(All)
(All)
(All)
Prod Group
Platform A
A Add-ons
Platform B
B Add-ons
Grand Total
Data
2001
67,604
51,201
29,595
36,605
185,004
D-Options
Region
Location-1
Location-2
Location-3
2002
74,819
58,882
34,960
45,287
213,949
2003
77,709
60,367
36,084
48,162
222,321
(All)
(All)
(All)
(All)
(All)
2004
91,393
75,570
42,127
62,487
271,577
Sales history,
5 years
I Group
I Family
Industry
Prod Year
Prod Mgr
Prod intro year
measures
innovation
2005
GR 2002 GR 2003 GR 2004 GR 2005
106,008
10.7%
3.9%
17.6%
16.0%
92,199
15.0%
2.5%
25.2%
22.0%
46,444
18.1%
3.2%
16.7%
10.2%
70,518
23.7%
6.3%
29.7%
12.9%
315,169
15.6%
3.9%
22.2%
16.1%
Product
manager for
convenience
®
Sales analysis
(All)
(All)
(All)
(All)
(All)
3 levels of
industries
Growth history,
4 years
Copyright © 2009 ModelSheet Software, LLC.
26
Use fineness appropriate for each management level.
Coarse and Fine Segmentation by Location
Rev-or-Vseat
Rev Class
P Group
P Family
Region
EMEA
EMEA Total
V-Units
(All)
(All)
(All)
Product
Options
I Group
I Family
(All)
(All)
(All)
(All)
Data
Location-1
Location-2
Location-3
2002
France
18,924
Germany
32,077
Nordic
8,868
UK
28,758
EMEA-Tier 2 Benelux
15,706
Israel
5,512
Italy
5,186
Spain
15,768
Switzerland
17,337
EMEA-Other Czech Republic
6,142
Greece
15,084
Hungary
-6,499
Poland
-11,251
Russia
-10,434
S Africa
-7,036
Turkey
14,639
EMEA-Remainder
15,349
EMEA-Other Total
15,993
EMEA-Tier 2 Total
75,503
164,129
®
Sales analysis
2003
31,789
43,970
23,509
22,718
-3,284
20,296
4,794
9,587
13,304
3,282
1,248
1,252
15,902
8,432
345
-1,298
10,239
39,403
84,099
206,086
2004
45,331
47,089
3,280
27,321
15,045
-1,364
21,493
1,603
8,484
-6,382
-8,695
9,135
-1,053
-8,189
-11,253
2,848
9,295
-14,294
30,966
153,989
2005
35,634
48,574
28,703
44,693
11,273
23,076
4,208
11,524
13,490
-9,105
-11,381
5,142
14,851
-7,157
3,578
2,833
-1,363
-2,602
60,968
218,573
Copyright © 2009 ModelSheet Software, LLC.
28
Probe why similar customer sites
have different product attach rates.
Order Attach Rates by Customer Site
2-levels of
customer
organization
Rev-or-Units V-Units
Rev Class Perp
Options
(All)
P Group
(All)
P Family
(All)
Prod Mgr
Prod Year
Region
Location-1
Location-2
(All)
(All)
(All)
(All)
(All)
I Group
(All)
I Family (All)
Site Age (All)
CoState (All)
CoSalesTeam
(All)
Product Data
Platform 1 Platform 2
Parent
Company
Intel Corp
CompanySite
Intel R&D
Intel Corp India
Intel Corp
Intel Corp UK Ltd
Intel Corp Salem, Oregon
ZAO Intel A/O
Intel Electronics 74 Ltd
Intel Products M Sdn Bhd
Intel Corp Total
2005
170
29
13
22
1
1
1
1
237
2005
25
0
4
0
0
0
1
0
30
Site age probes how well
you attract new customers.
Product A
2005
%P1
14.7%
0.0%
31.9%
0.0%
0.0%
0.0%
157.7%
0.0%
12.6%
2005
103
5
13
10
0
0
1
0
132
Product B
2005
%P1
60.7%
17.0%
103.7%
45.5%
0.0%
0.0%
157.7%
0.0%
55.6%
2005
71
1
6
16
0
0
1
0
95
2005
%P1
41.8%
3.4%
47.9%
72.9%
0.0%
0.0%
157.7%
0.0%
40.0%
Attach rates relative to
product Platform 1.
®
Sales analysis
Copyright © 2009 ModelSheet Software, LLC.
29
Color Maps help spot segments
with above- and below-average performance.
Color Map of Product Attach Rates
Auto Total
Automotive Industry
North
America
Total
France
European Countries
Germany
Nordic
UK
Europe
Total
Asia
Total
Other
Product Family
Product
Platform Product
Platform
%
%
%
%
%
%
%
%
%
Product family 1
Add-on #1
%
%
%
%
%
%
%
%
Add-on #2
%
%
%
%
%
%
%
%
Add-on #3
%
%
%
%
%
%
%
%
Add-on #4
%
%
%
%
%
%
%
%
%
%
%
%
%
%
%
Product family 1 Total
%
%
%
%
%
%
%
%
Product family 2 Total
%
%
%
%
%
%
%
%
Product family 3 Total
%
%
%
%
%
%
%
%
Key:
= product attach rate significantly higher than global industry average
= product attach rate significantly lower than global industry average
=product sales are too low to consider attach rate
France has above-average
sales of Platform product
in Auto industry.
France has below-average
sales of two add-on families
in Auto industry.
Sales analysis
UK does not have
significant above-average
sales of any add-on
product in this family.
UK has below-average
sales of Platform product
in Auto industry.
UK has above-average
sales of two add-on
families in Auto industry.
®
Copyright © 2009 ModelSheet Software, LLC.
30
“Market basket analysis” shows which products are
purchased and used together, and how often.
Definition: “Market basket analysis” computes which products
occur together, and how often.
• Analyze orders to determine what products sell together well
• Analyze installed base to determine what products are used together
Typical Uses:
• Advise sales reps to focus on best product combos for each segment.
Design sales training modules to cover co-use products together.
• Feature most popular product combos in sales & marketing programs.
• Adjust product plans based on how customers use products together.
• Design product suites.
The term “market basket analysis” comes from grocery marketing.
“How many people buy both beer and diapers on Thursdays?”
®
Sales analysis
Copyright © 2009 ModelSheet Software, LLC.
31
Client Impact: Sales Analysis Tools
revolutionized business planning at MathWorks.
• Product managers spend 2-3 hours on each sales review
(not 2-3 weeks).
• Reviews waste little time guessing which trends are real and
which are artifacts (instead of half the time).
• Improves resource allocations in Marketing and Development.
• Depth and clarity of conclusions in reviews takes a great leap.
– Accurately scope and diagnose areas of strength and weakness.
– Detect irrational pricing or other policies buried in the system.
– Provides market feedback from small and medium customers.
Return
®
Sales analysis
Copyright © 2009 ModelSheet Software, LLC.
32
Challenge: Manage low-margin business
with huge diversity of product-customer segments.
Business segments are too numerous to manage by feel.
• 60+ wholesale locations
• 500-3,000 customers per location
• 300-2,000 products per location
Profits are often concentrated.
• ~20% of customers generate 80% of profits.
• ~20% of customers generate losses.
• Some product or service lines generate losses.
This problem is common in low-margin businesses with many product or
service offerings.
• Wholesale and retail distribution
• Retail financial services
• Health care institutions
®
Product & customer profitability
Copyright © 2009 ModelSheet Software, LLC.
33
Solution: Estimate profitability of products,
customers and product x customer segments.
Compute gross margin from prices and COGS.
Allocate selling costs to customers and to products.
Use activity-based costing to create detailed cost models.
X
• Warehousing and delivery costs
• Order admin costs
Actions: Alter prices for some products and customers.
• Drop some products. Consider joint ordering and usage.
• Alter prices for some customers, with intent to lose some customers
®
Product & customer profitability
Copyright © 2009 ModelSheet Software, LLC.
34
Client Impact: Customer x product profitability metrics
improved profits at chemical distributor.
• Repriced money-losing customers and took chance they walk.
– Top 20% of customers generate half of profit. 10% cause losses.
• Repriced or eliminated unprofitable product lines at some
locations.
• Raised profitability significantly at test locations.
– Largest branches had 5-15% unprofitable customers.
– Smaller branches had less unprofitable business.
• Client added customer and product profitability as a permanent
utility.
Return
®
Product & customer profitability
Copyright © 2009 ModelSheet Software, LLC.
35
Outline
Introduction
• Background
• Strategy & analytics
Business
Development
• Project selection
o Business planning
o Business cases
Finance
o Project cost accounting
o ModelSheet models
– Business financial plan
– Investment project analysis
Key:
• Included in main presentation
o Excluded from main presentation
Marketing
Programs
• Program profitability
o Pricing analysis
o Data mining
o ModelSheet Model
Sales Planning
& Resources
• Sales planning
• Sales force
organization
Sales
Analysis
(Program profitability)
•
•
•
•
Product
Programs
Operations
Analysis
• Product profitability
o Software quality
o ModelSheet model
o Manufacturing
o Distribution
o Computer operations
o ModelSheet model
(Product profitability)
(Process flow analysis)
®
In-depth sales analysis
Color maps
Market basket analysis
Customer x product
profitability
Summary &
Next Steps
Copyright © 2009 ModelSheet Software, LLC.
36
Challenge: Consider product profitability
in investment decisions.
What is the role of profitability in investment decisions?
• How does a company combine financial metrics with human judgment?
• How can a company avoid letting financial metrics stifle the vision and judgment
needed for innovation in many situations?
How do you estimate profitability of products?
•
•
•
•
How do you account for long-term development investments?
Which costs do you include?
How do you allocate costs to products?
How do you treat technical and market dependencies among products?
®
Product profitability
Copyright © 2009 ModelSheet Software, LLC.
37
Solution: Let the role of product profitability metrics in
investment decisions vary across businesses.
Our tool:
Fosters an environment for proper use of financial information in
investment decisions that values qualitative factors and expert
opinion.
Uses product profitability metrics to help build consensus around
potentially contentious resource decisions.
Computes product profitability
By using appropriate time horizons for product development investments;
including product-specific marketing, selling, and supports costs; and using
cost drivers for activity-based costing.
®
Product profitability
Copyright © 2009 ModelSheet Software, LLC.
38
Client Impact: Product profitability metrics improve
process and results for investments in product.
• Product CM becomes key input for engineering headcount
decisions at MathWorks.
– Even long-time executives discovered patterns they did not fully realize.
• Product CM helps build consensus around contentious
decisions.
– Product CM prevents some weaker resource requests from surfacing.
Return
®
Product profitability
Copyright © 2009 ModelSheet Software, LLC.
39
Outline
Introduction
• Background
• Strategy & analytics
Business
Development
• Project selection
o Business planning
o Business cases
– Enter embryonic bio market
– Turnaround small business
– Large business in trouble
Finance
Marketing
Programs
• Program profitability
o Pricing analysis
o Data mining
o ModelSheet Model
– Financial plan
– Investment project
• Sales planning
• Sales force
organization
Sales
Analysis
(program profitability)
•
•
•
•
Product
Programs
Operations
Analysis
• Product profitability
o Software quality
o ModelSheet model
o Manufacturing
o Distribution
o Computer operations
o ModelSheet model
(Product profitability)
o Project cost accounting
o ModelSheet models
Sales Planning
& Resources
(Process flow analysis)
®
In-depth sales analysis
Color maps
Market basket analysis
Customer x product
profitability
Summary &
Next Steps
Copyright © 2009 ModelSheet Software, LLC.
40
Challenge: Allocate resources
among scores of candidate projects.
Dozens of projects compete for resources each year.
Conditions vary widely across business units and segments.
•
•
•
•
•
High/medium market growth rates
Unchallenged market leader or competitor with <5% share.
Varying market synergies with company’s market-leading products
Varying synergies with company’s existing products and expertise.
Varying expertise in distribution and in support compared to leader.
Some engineering managers believe no need to plan: “Throw 1-2
engineers at each opportunity; add/subtract based on early results.”
®
Project selection
Copyright © 2009 ModelSheet Software, LLC.
41
Solution: Quantify strategic concepts
with linear decision models.
Introduce standard strategic concepts.
• Market attractiveness (Market growth is often the best simply proxy.)
• Relative competitive strength (Relative market share is best simple proxy.)
Score each project on key dimensions.
• Market attractiveness: growth, appropriate size, competitive intensity
• Competitive position
- Products and technology
- Relative market share, synergies with other products
- Distribution and support
Estimate costs and payoffs.
• 5-year revenue estimates and risks
• Development costs and risks
• Business model difficulties and risks
Assemble into portfolio view.
®
Project selection
Copyright © 2009 ModelSheet Software, LLC.
42
Client Impact: Investment project evaluation tool
brought discipline and buy-in to resource decisions.
• Eliminated backlog of unevaluated investment proposals.
– Scored two dozen projects in first year methods used.
• Trained managers in how to think about project evaluation.
– Engineers particularly liked the rational and thorough process.
• Managers who got adverse resource decisions knew reasons.
Return
®
Project selection
Copyright © 2009 ModelSheet Software, LLC.
43
Implemented Investment Project Financial Analysis
as a ModelSheet Model
• ModelSheet model and Excel workbook for
investment project financial analysis
Link
• ModelSheet model has advantages over Excel.
•
•
•
•
•
Named variables, readable symbolic formulas (and fewer formulas)
Segmentation dimensions, time series
Separates model logic from sheet layouts
Generates Excel workbooks
Learn about ModelSheet
Link
Return
®
Investment project analysis
Copyright © 2009 ModelSheet Software, LLC.
44
Outline
Introduction
• Background
• Strategy & analytics
Business
Development
• Project Selection
o Business planning
o Business cases
Finance
o Project cost accounting
o ModelSheet models
– Business Financial plan
– Investment project analysis
Key:
• Included in main presentation
o Excluded from main presentation
Marketing
Programs
• Program profitability
o Pricing analysis
o Data mining
o ModelSheet model
Sales Planning
& Resources
• Sales planning
• Sales force
organization
Sales
Analysis
(Program profitability)
•
•
•
•
Product
Programs
Operations
Analysis
• Product profitability
o Software quality
o ModelSheet model
o Manufacturing
o Computer operations
o Distribution
o Computer operations
(Product profitability)
(Process flow analysis)
®
In-depth sales analysis
Color maps
Market basket analysis
Customer x product
profitability
Summary &
Next Steps
Copyright © 2009 ModelSheet Software, LLC.
45
Summary: Operational Data
Contains Information That Can Improve Decisions.
Operational data contains organic information that can inform and
improve decision-making.
Organic reports help manage many aspects of a business.
A company needs certain assets to implement organic reports.
• Relevant operational data
• Information systems infrastructure
• Strategic – analytic expertise
®
Summary and next steps
Copyright © 2009 ModelSheet Software, LLC.
46
Suggested Next Steps
Identify likely opportunities for impact of strategic assessment
and business analytics.
• Business Development
• Finance
• Marketing Programs
• Sales Planning and Resources
• Product Programs
• Operations Analysis
• Sales Analysis
Return
®
Summary and next steps
Copyright © 2009 ModelSheet Software, LLC.
47
Appendix
The appendix includes topics excluded from the flow of the
default presentation in order to save time.
®
Copyright © 2009 ModelSheet Software, LLC.
48
Find the right prices and where to compete.
Case 1: Optimize Educational prices for technical software
• Do controlled test on a few products in large product line.
• Analyze why price elasticities vary by product type.
• Estimate revenue and unit sales impact of price changes.
Case 2: Telecom PBX equipment
•
•
•
•
Segments include small/large PBX, buy/lease, premium options.
Revenue includes up-front charges and annual fees.
Customer preferences differ for current cash and NPV.
Can vendor be competitive across the board?
®
Pricing
Copyright © 2009 ModelSheet Software, LLC.
49
Client Impact: Pricing analysis has helped clients
to manage profits and market share.
• MathWorks Education Marketing has firm basis for deciding
which prices to adjust.
• AT&T identified areas of mis-pricing that lost PBX orders.
Return
®
Pricing
Copyright © 2009 ModelSheet Software, LLC.
50
Definition of “Data Mining”
Data mining means finding hidden patterns in customer behavior that
lead to more effective actions.
Found in in large, high-dimensional data sets
Data mining focuses on differentiating impact of marketing and sales
activities by individual customers.
• Instead of impact on market segments.
• This is a critical activity in building a customer-centric business.
• Two basic types of data mining differ.
• Supervised learning
Directed: seeks to answer a pre-formed question, validate a hypothesis.
• Unsupervised learning
Undirected: seeks useful patterns in data that were not previously known.
“unsupervised learning”
®
Data mining
Copyright © 2009 ModelSheet Software, LLC.
51
Challenge: Predict which customers will buy
which products with what probabilities.
Types of Information Used to Predict Customer Purchases
• Installed base of products
• Purchase history by product / service
• Seminars and other marketing program events attended
– E.g. webinars, product trials.
• Web pages visited
• ‘Opportunities’ (very highly qualified leads)
• Number and types of support requests
– Including recommendation of support engineers for new purchases.
®
Data mining
Copyright © 2009 ModelSheet Software, LLC.
52
Solution: Various approaches can
predict purchases and probabilities.
Some Algorithmic Methods for Data Mining
• Neural networks
• Maximum likelihood methods
– with parameterized model
• Bayesian networks
Return
®
Data mining
Copyright © 2009 ModelSheet Software, LLC.
53
Implemented Marketing Program Contribution Margin
Analysis as a ModelSheet Model.
• ModelSheet model and Excel workbook for
marketing program contribution margin analysis
Link
• Allocate revenue to marketing programs to compute contribution margin
• ModelSheet model has advantages over Excel
•
•
•
•
•
Named variables, readable symbolic formulas (and fewer formulas)
Segmentation dimensions, time series
Separates model logic from sheet layouts
Generates Excel workbooks
Learn about ModelSheet
Link
Return
®
Data mining
Copyright © 2009 ModelSheet Software, LLC.
54
Challenge: Assure high level of software quality.
What does quality mean?
How organize for quality?
How balance repairing defects with new features?
How test code?
How use up-front design and reviews?
Use coding standards?
®
Software quality
Copyright © 2009 ModelSheet Software, LLC.
55
Solution: Reorganize software development
to focus on quality over new features.
• Adjust the meaning of quality to different applications.
– Use different blends of reliability, features, performance, memory footprint, usability I different
situations.
• SW developers have primary responsibility for quality.
– One or two developers have primary responsibility for quality of each SW module. Developers
write and perform tests, write draft documentation.
– Keep ratio of QE to developers low.
• Use short design-test-fix cycle.
– Clear all defects in overnight testing. Exceptions require approvals.
• Use 4 kinds of testers and 5 kinds of tests.
– Testers: primary developers, domain experts, idiosyncratic users, aesthetes
– Tests: feature tests, interaction tests, application tests, off-course tests, stress tests.
– Include algorithms, user interface, on-line help and documentation.
• Do up front external design reviews and code reviews.
– Document semantics, usage procedures, programmer interfaces. Use up-front project plan and
standard project management variance metrics. Adapt reviews to seniority of developers.
• Enforce code standards.
– Modularity, abstraction, object ontology, naming, code layout, comments, executable tests and
demos, user documentation, user interface and help systems. Little non-source documentation
®
Software quality
Copyright © 2009 ModelSheet Software, LLC.
56
Challenge: Track defects
for maximum impact on quality.
• Classify defects by impact on users.
– impact per encounter, and frequency of encounters.
• Defect repair process is very complex.
–
–
–
–
What products are affected
Who is responsible
Current status in the process
Schedule and rate of progress
• Show each user what he needs without burying him in detail.
®
Software quality
Copyright © 2009 ModelSheet Software, LLC.
57
Solution: Show patterns of defect inventory and process
with flexible level of detail.
Key Features of Defect Reports
• Reflect differences in priority of defects.
– Severity of each occurrence affects priority.
– Frequency of occurrence affects priority.
• Report inventory and flow-through of defects.
– Current status
– Schedule information
• Show appropriate information to each user.
– Present different views for different user groups.
– Use hierarchies of product components, teams, status.
®
Software quality
Copyright © 2009 ModelSheet Software, LLC.
58
Defect reports show
appropriate information to each user.
5 levels of
ownership
Owner Div
Owner Dept
Owner Mgr
Component
2 levels of
defect status
3 levels of
product
components
(All)
(All)
(All)
(All)
Sub Comp
Severity
Frequency
Status
Sum of Total
Owner Group
Accessories
Owner
Conrad B
Michelle S
S_Comp
Priority
Core
1 High
3 Low
Optical instruments 1 High
2 Medium
3 Low
Core
2 Medium
3 Low
Optical instruments 1 High
2 Medium
3 Low
2 factors in priority
(All)
(All)
(All)
(All)
Timing
information
Create Date yr-mo
(All)
Last Mod Date
(All)
yr-mo
Last Mod By (All)
S_Status
All Dev
Open
All QE
Open
1
4
2
3
6
1
1
2
1
3
Closed
1
2
Grand
Total
1
4
2
4
6
1
1
2
3
3
3 levels pf priority
®
Copyright © 2009 ModelSheet Software, LLC.
59
Client Impact: MathWorks is growing rapidly
in huge production code markets.
• MathWorks is growing from maker of design tools to a leading
maker of tools for programming embedded microprocessors.
– Automatically programming the world’s microprocessors is a huge growth
market.
• Leading embedded system vendors are adopting new releases
of MathWorks software.
– This is a critical decision point for key customers.
• This program implemented the most radical and disruptive
changes in MathWorks development practices in many years.
– President made software quality his top priority for two years.
Return
®
Software quality
Copyright © 2009 ModelSheet Software, LLC.
60
Implemented Product Profitability Analysis
as a ModelSheet Model.
• ModelSheet model and Excel workbook for
Business Unit Financial Plan
Link
• Revenue less costs of goods, development, marketing, support
• ModelSheet model has advantages over Excel
•
•
•
•
•
Named variables, readable symbolic formulas (and fewer formulas)
Segmentation dimensions, time series
Separates model logic from sheet layouts
Generates Excel workbooks
Learn about ModelSheet
Link
Return
®
Software quality
Copyright © 2009 ModelSheet Software, LLC.
61
Outline
Introduction
• Background
• Strategy & analytics
Business
Development
• Project selection
o Business planning
o Business cases
Finance
o Project cost accounting
o ModelSheet models
– Financial plan
– Investment project analysis
Key:
• Included in main presentation
o Excluded from main presentation
Marketing
Programs
• Program profitability
o Pricing analysis
o Data mining
o ModelSheet Model
Sales Planning
& Resources
• Sales planning
• Sales force
organization
Sales
Analysis
(program profitability)
•
•
•
•
Product
Programs
Operations
Analysis
• Product profitability
o Software quality
o ModelSheet model
o Manufacturing
o Distribution
o Computer operations
o ModelSheet model
(Product profitability)
(Process flow analysis)
®
In-depth sales analysis
Color maps
Market basket analysis
Customer x product
profitability
Summary &
Next Steps
Copyright © 2009 ModelSheet Software, LLC.
62
Challenge: Cost accounting systems misguide
business decisions at regulated company.
Capital and expense cost accounting maximizes regulated profits
but distorts business decisions.
Competitors’ rule of thumb: “price 10% below market leader and
make large profits.
Market leader cannot adopt competitors’ pricing because
accounting system says this would generate losses.
• Is the leader a cost laggard?
• How does the accounting system affect profit metrics?
- Timing of revenues and costs
- Building book value as basis for regulated profits
®
Cost accounting
Copyright © 2009 ModelSheet Software, LLC.
63
Solution: Adopt cost accounting methods
of investment bankers.
Capitalize expenditures not recouped from initial cash flows.
Do not capitalize at-risk expenditures that support future earnings,
such as installation costs on leased systems.
Client Impact: Large PBX maker adopted
more realistic costing and pricing.
• Two years later, client reduced stated book value by 20%.
• More accurate costing led to more competitive pricing.
Return
®
Cost accounting
Copyright © 2009 ModelSheet Software, LLC.
64
Implemented Business Unit Financial Plan
as a ModelSheet Model.
• ModelSheet model and Excel workbook for
Business Unit Financial Plan
Link
• Generic financial plan with 150+ variables
• ModelSheet model has advantages over Excel
•
•
•
•
•
Named variables, readable symbolic formulas (and fewer formulas)
Segmentation dimensions, time series
Separates model logic from sheet layouts
Generates Excel workbooks
Learn about ModelSheet
Link
Return
®
$1 Billion business in trouble
Copyright © 2009 ModelSheet Software, LLC.
65
Implemented Investment Project Financial Analysis
as a ModelSheet Model.
• ModelSheet model and Excel workbook for
Business Unit Financial Plan
Link
• Investment return metrics based on discounted cash flow
• ModelSheet model has advantages over Excel
•
•
•
•
•
Named variables, readable symbolic formulas (and fewer formulas)
Segmentation dimensions, time series
Separates model logic from sheet layouts
Generates Excel workbooks
Learn about ModelSheet
Link
Return
®
$1 Billion business in trouble
Copyright © 2009 ModelSheet Software, LLC.
66
Strategy drives analysis,
and can drive it in different directions.
Basic
Strategy
Type of Metric
Revenue, growth
Cost,
Productivity
• Time to break even
Asset Utilization
Incubate
• Sales growth by
segment
Grow
• Penetration of key
• Revenue per employee
customers, applications • Revenue / non-labor input
• % sales from new
products
• R&D as % revenue
• Investment as %
revenue
Sustain
• Sales growth by
segment
• Contribution margins
• Cost reduction rates
• Indirect costs / sales
• ROI
• Asset turnover
Harvest
• Market share
• % share of substitutes
• Unit costs
• ROI
• Asset turnover
®
Strategic planning
• Cash flow
Copyright © 2009 ModelSheet Software, LLC.
67
We can help formulate business plans.
Planning at MathWorks
– Served on all 11 management boards for commercial businesses.
• Aerospace, Automotive, Biotech-Pharmaceutical, Communications-ElectronicsSemiconductors, Financial Services, Industrial Automation
• Control Design, Signal & Image Processing, Technical Computing, T&M
– Led planning for several business units.
• Led planning for first two vertical products in a new application
(computational biology)
• Drove new strategy for money-losing low-growth business unit that got it on a
better trajectory.
– Headed annual long-term planning meeting.
– Drove key organizational changes.
• Re-organization of sales force by industry.
• strategic quality initiative in software development.
• I.T. effectiveness issues.
Other companies (next slide)
®
Strategic planning
Copyright © 2009 ModelSheet Software, LLC.
68
We can help formulate business plans.
(continued)
In Fortune 100 (8 businesses for GE, McKinsey, Booz Allen)
– Diagnosed strategic investment issues involving product line,
manufacturing, and distribution for $900 million communications equipment
business. Identified estimated $80 million recurring savings.
– Identified problems in 3,000-man RD&E lab that allowed two $100+ million
project failures to pass reviews.
In small software company
Turned around world-class technical software product.
Return
®
Strategic planning
Copyright © 2009 ModelSheet Software, LLC.
69
Challenge: Enter computational biology markets?
Growth was slowing for core business units.
• Computerization of engineering work flows is maturing.
• 2002 hi-tech bust signaled that execution alone would lead to cul-de-sac.
Highly profitable privately-held company can consider 5-10 year
investments in automating new work flows.
• Consider other aspects of engineering workflows.
More investment in production code generation, EDA system-level design,
validation, verification & test, medical imaging, …
• Consider new technical workflows.
Computational life science, business intelligence, finite elements, …
Engineer-champions of computational biology: “This is the next
big thing in computation; get in now and make a killing.”
®
Strategy in computational biology
Copyright © 2009 ModelSheet Software, LLC.
70
Solution: Get into computational biology now
and lose money for 5-10 years.
Recognize why comp. biology is unique among opportunities.
• More basic life science is converted to engineering than anywhere else.
Analogy: Maxwell’s equations ~1860-1870 started replacement of mechanicaltech by electro-tech at the cutting edge of innovation. Lasted 150 years.
• Applied life science will be the greatest tech growth area in 21st century.
Overcome bad timing for the two best opportunities for entry.
• Late into bioinformatics. Very hard to build unique technology position.
• Systems biology still immature. Can build unique technology position.
Two product strategies both need staying power.
• Bioinformatics: enter with good product, versus very good freeware.
Key fact: many life science researchers using, struggling with MathWorks tools
despite lack of attention to their needs. Fill pot-holes and create a winner.
• Systems biology: Leapfrog the field with groundbreaking technology in
add-on product at low price.
®
Strategy in computational biology
Copyright © 2009 ModelSheet Software, LLC.
71
Client Impact: MathWorks has software and strategy
to become the leader in computational biology.
• MathWorks is in process of losing money for 5-10 years.
• MathWorks is already the leader in computational systems
biology.
• MathWorks has a tough fight against bioinformatics freeware.
• Computational Biology is likely the most explosive technical
computing application in the 21st century.
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Strategy in computational biology
Copyright © 2009 ModelSheet Software, LLC.
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Challenge: T&M business unit has minus 100% ROS,
tiny market share, and low growth.
3% of customers (for platform product) buy key T&M product.
• Market research and business plan projected 50%.
• Attach rate is not growing.
Development, marketing budgets imply faith in strong growth.
• Some marketing budget as large as business units with 50 x revenue.
• Development team meets guidelines for business with 10 x revenue.
Scale economies and standards are important.
• Scale and standards usually critical in established software markets.
• Products and support must handle many hardware boards (scale).
T&M management board meetings are full of assertions.
• Sales force reluctance drives low sales. So fix sales.
• T&M products pulling other products. Give T&M credit for added revenue.
• Seek partnerships with instrument makers to pull T&M products through.
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Strategy in Test & Measurement
Copyright © 2009 ModelSheet Software, LLC.
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Solution: Ask customers.
Reposition T&M as utility function for main products.
Survey 97% of customers who don’t buy and 3% who do.
• Ask a dozen obvious questions about need for T&M function, product
strengths, incumbent products, force of standardization…
• Start with 1-2 dozen interviews to ensure survey captures the key issues.
Private discussions unearthed key problems.
• Serious product deficiencies for the main part of market.
• Incumbency of and standardization on market leader is crucial.
Solution: position T&M products as completing design cycle for
company’s core products in control design etc.
• Avoid head-on competition with entrenched leader in core of market.
Cut marketing programs aiming at direct competition with leader.
• Give time to fix product deficiencies.
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Strategy in Test & Measurement
Copyright © 2009 ModelSheet Software, LLC.
74
Client Impact: T&M business growing fast
with better margins.
• T&M repositioned as part of larger “Model-Based Design” story.
– Not positioned head-to-head with mainstream T&M leaders who have a
different kind of product.
• Some product deficiencies fixed (deployment).
– Refocusing on product needs helped.
• Growth and margins are up.
– Growth increases substantially in two years.
– Resource commitments are scaled to new strategy.
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Strategy in Test & Measurement
Copyright © 2009 ModelSheet Software, LLC.
75
Challenge: Why was $900 million* wireless comms
vendor unprofitable and losing share?
• Solid #2 competitor was now tied with #3 vendor.
– Share fell from 36% to 16% in 15 years.
– Leader’s share increased from 50% to 65%.
• Growth was good but becoming nil.
• Profitability was sub-standard and becoming nil.
• Entered microprocessor-controlled radios at good time, but
lagging with second generation.
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$1 Billion business in trouble
Copyright © 2009 ModelSheet Software, LLC.
76
Diagnosis: Business in growth industry
was harvested for 15 years.
• Replace 10-year-old core product to exploit chip integration.
– “New” products were repackaged versions of old less integrated products.
– Core product redesign was cancelled yearly to make profit targets.
• Reduce manufacturing costs.
– Install new manufacturing information system.
• WIP choked factory floor, interfered with operations.
• New MPR system cancelled each year to make profit targets.
– Move some manufacturing overseas to improve cost position.
• Asian rivals with small shares depressed price levels.
• Distribution
– Weak product line enabled competitors to penetrate indirect distribution.
– Business had small services business. #1 competitor made as much
money in wireless service business as in equipment.
• Solution: Invest to realize $80M savings; or sell.
®
$1 Billion business in trouble
Copyright © 2009 ModelSheet Software, LLC.
77
Client Impact: GE recovered capital
for refocusing on stronger businesses.
• Wireless communications business was sold.
– Management concludes it is too late to fix past strategic mistakes.
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$1 Billion business in trouble
Copyright © 2009 ModelSheet Software, LLC.
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Outline
Introduction
• Background
• Strategy & analytics
Business
Development
• Project selection
o Business planning
o Business cases
Finance
o Project cost accounting
o ModelSheet models
– Business financial plan
– Investment project analysis
Key:
• Included in main presentation
o Excluded from main presentation
Marketing
Programs
• Program profitability
o Pricing analysis
o Data mining
o ModelSheet model
Sales Planning
& Resources
• Sales planning
Sales
Analysis
(program profitability)
•
•
•
•
Product
Programs
Operations
Analysis
• Product profitability
o Software quality
o ModelSheet model
o Manufacturing
o Distribution
o Computer operations
o ModelSheet model
(Product profitability)
(Process flow analysis)
®
In-depth sales analysis
Color maps
Market basket analysis
Customer x product
profitability
Summary &
Next Steps
Copyright © 2009 ModelSheet Software, LLC.
79
Problems: Estimate impact of
changes in manufacturing operations.
• Analyze manufacturing costs.
–
–
–
–
–
Material, indirect material (fuel), labor, labor overhead, other overhead
Scrap and rework rates
Complex process flow, including rework flows.
Buffer inventory affects inventory costs and process up-times.
Skilled indirect labor affects scrap rates and uptime rates.
• Estimate cost impact of changes in existing manufacturing
processes and equipment.
– Affects technical decision-making.
– Affects labor/automation trade-offs.
– Affects entry/exit decisions in some product segments.
• Estimate manufacturing costs for new products.
– Affects go/no-go decisions and plans for new products.
– Affects choices of designs, processes, pilot versus full production.
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Manufacturing operations analysis
Copyright © 2009 ModelSheet Software, LLC.
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Solution: Model costs based on
manufacturing work flow.
Costs
•
•
•
•
•
Material
Direct Labor
Indirect Labor
Equipment
Overhead
Stage 1
Scrap
Costs
Stage 2
Scrap
Costs
Metrics
Costs
Stage 3
Stage 4
Scrap
Scrap
• Theoretical
factor costs
• Actual factor costs
• Scrap rates
• Rework rates
• Cost impact of
process changes
Rework
Key Differences from Financial Cost Accounting
•
•
•
•
Include benefits and taxes in direct labor.
Often included in
Break out indirect labor with benefits & taxes.
overhead for inventory
tax accounting.
Break out equipment depreciation & maintenance.
Model volume-dependence of costs (e.g. fixed & variable costs).
®
Manufacturing operations analysis
Copyright © 2009 ModelSheet Software, LLC.
81
Client Impact: GE Lighting improved decision support
for manufacturing changes and new products.
• Engineering can make more accurate cost estimates of factory
changes.
– New costing methods reduce allocated OH rates from 600%+ to 20%.
• Manufacturing costing for new lamp products is more accurate.
– Brite Stik® flourescent lamps
– Miniature metal halide lamps
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Manufacturing operations analysis
Copyright © 2009 ModelSheet Software, LLC.
82
Challenge: Estimate costs of distribution function.
• Operational logistics drive warehousing costs.
– Facilities and picking costs vary widely.
• Optimize position in warehouse based on impact on operating costs.
• Operational logistics drive delivery costs.
– Choose cost drivers: Distances, weight and space costs, routing.
– Interactions of high, low profit segments
• Carry some money-losing products for profitable customers.
• Turnover affects inventory carrying costs.
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Distribution analysis
Copyright © 2009 ModelSheet Software, LLC.
83
Solution: Develop operational
model of distribution costs.
• Model warehousing costs.
– Pallet picking model allocates forklift time and costs.
• Location in warehouse affects travel time.
• Container type, partial pallets and bulk or weight determines forklift costs.
– Floor space, turnover determine space costs for each product.
• Distinguish fixed and variable costs in decision to drop a customer or product.
• Model delivery costs.
– Weight or volume determined truck space.
– Length of deliver route and joint deliveries affect costs.
• Model order admin costs.
– Account for asset turnover, EOQ and vendor characteristics.
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Distribution analysis
Copyright © 2009 ModelSheet Software, LLC.
84
Client Impact:
Distributor improved warehouse operations.
• Alter warehouse layout, picking policies, and delivery logistics.
• Distribution analysis was a cornerstone of profitability analysis
that improved division performance.
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Distribution analysis
Copyright © 2009 ModelSheet Software, LLC.
85
Challenge: Do benefits justify
new back-office information system?
• Process many products in same work flow.
– Air and other tickets, hotel and other reservations, travelers checks
• Determine costs and cost drivers of current and new systems.
– Factory-like processing flow with sequence of stages
– Accumulate labor, machinery, overhead costs
Estimate cost savings of new information processing system.
• Determine which parts of the business system confer strategic
advantage over low-cost competitors.
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Computer operations analysis
Copyright © 2009 ModelSheet Software, LLC.
86
Solution: Construct process flow
similar to manufacturing process.
Costs
•
•
•
•
•
Material
Direct Labor
Indirect Labor
Equipment
Overhead
Stage 1
Costs
Metrics
• Theoretical
factor costs
• Actual factor costs
• Scrap rates
• Rework rates
• Cost impact of
process changes
Costs
Costs
Stage 3
Stage 4
Costs
Special Considerations
Stage 2
Special
Processing
Stage 5
• Distinct products share
processing stages.
• Some processes apply only
to exceptional cases.
• Compare costs & capabilities with new system.
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Computer operations analysis
Copyright © 2009 ModelSheet Software, LLC.
87
Client Impact: Client cancels large unjustified I.T. project.
• $40M project by IBM terminated.
• European Division preserves profit margins.
• Control of I.T. returns to team that built in-house system.
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Computer operations analysis
Copyright © 2009 ModelSheet Software, LLC.
88
Implemented Operations Process Flow analysis
as a ModelSheet Model.
• ModelSheet model and Excel workbook for
Operations Process Flow analysis
Link
• Units and cost flow thru manufacturing or business process flow
• ModelSheet model has advantages over Excel
•
•
•
•
•
Named variables, readable symbolic formulas (and fewer formulas)
Segmentation dimensions, time series
Separates model logic from sheet layouts
Generates Excel workbooks
Learn about ModelSheet
Link
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Operations process flow analysis
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