Time to Bite the Hand that Feeds You?
Don Woodlock
www.systemdynamics101.com
540 W. Northwest Hwy
Barrington IL 60010
1.847.277.5515
dwoodlock@ alum.mit.edu
Abstract
The average life expectancy of a company is sadly only 40-50 years. You would
think that a company lifetime could easily surpass our lifetimes because many
generations can work at a company and pass down it’s products, brands, know-how,
competencies, customer base, etc. to successive generations. But ultimately
companies die because they fail to adapt and change. One area of adaption that is the
most difficult to navigate is when to start investing in new markets and de-investing in
the traditional markets that initially built the company. Too many companies get
themselves caught in a trap of continual investment in their ‘core’ markets, which are no
longer growing and missing out on growth adjacencies that can fuel the company’s next
generation of growth. This paper will explore the reinforcing feedback loops and
systemic delays that cause most companies to invest too much and too long in their
traditional market and recommends a new R&D investment rule of thumb that breaks
this cycle. A significant mindset change from looking at R&D allocation as a % of sales
and instead adopting R&D as a % of future market size is proposed.
Introduction
One of the most vexing problems in business today is how to grow a company
over the long run when markets change. Most successful companies are able to
capitalize on a market segment that is appealing and is a good fit the company’s
offerings and strategies and this success may last 20 years. But many markets go
through multiple waves of technology adoption and rarely are companies able to
successfully ride more than their one wave. Why is that? Because there are powerful
reinforcing feedback loops that encourage a company to sit in one segment for too long
and cause their leadership teams to have difficulty seeing that their core business is
running out of oxygen. This paper evaluates this reinforcing cycle and explores
alternative policy choices to move from one wave in the market to the next with
success.
There is a wealth of literature around the topic of business strategy and the
challenges with corporate inertia. The reasons for corporate inertia have been
articulated long ago (Hannan and Freeman, 1984) and because of this challenge, we
generally see a Darwinian natural selection process across companies in an industry
where the ones best suited to the current environment replace the ones that were best
suited only to the past. One study (Noda and Bower, 1996) shows a good example
where reinforcing feedback loops caused one company (BellSouth) to escalate
commitment to a promising future business (wireless) while a peer company (US West)
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faced some early disappointments and their reinforcing loop caused a de-escalation to
their wireless business until it was too late to take advantages of this new growing
market. But the best case for a company is an evolutionary internal selection process
where resource allocation and reallocation shed old businesses and span new ones as
Intel did by successfully moving from their DRAM core business to microprocessors
(Burgelman, 1996). Though the strategy literature highlights that adaption is critical,
there is little development of simple rules of thumb that top management can use to
overcome the strong forces of inertia and ensure that their organizations are always
adapting and investing in the new future. This paper proposes one.
This is an extremely simple model by any System Dynamics standards.
However it is very powerful in a few respects. First the portfolio management of R&D
dollars is an extremely important problem in the corporate world. The conceptual
roadblocks that cause a company to invest too long in today’s markets are worth
illuminating as mistakes of this type are made in nearly every boardroom in the world.
And secondly the System Dynamics model covered here, properly calibrated, can also
provide a tool for organizations to use in their R&D allocation process.
The Business Scenario
My domain is Healthcare Information Technology like electronic medical records
(EMRs), billing and scheduling systems for physicians and hospitals, etc. The adoption
of IT technology in our industry always looks the same. In the beginning of the market,
it is the largest and most sophisticated healthcare organizations that move from a
paper-based process to an IT-based process first. For example, large hospital systems
and academic medical centers adopted EMRs about 10 years ago at least in some
form. The software vendors in this space built expensive, sophisticated IT systems to
handle large complex organizations. The vendors built implementation and service
approaches and teams that were comfortable taking 12 months to install an IT system
and perform important but expensive workflow redesign services as part of the
technology adoption. These initial sets of companies were successful, made money,
and served the market well. We'll call this the L-Group Vendors. (L standing for Large
Customers)
Then the next wave of customers adopt IT technology and they represent the
midsize hospitals and midsize physician groups. This new wave is being serviced by a
new set of companies since the original companies are unable to retool their products
and process to fit this midsize market. In fact they don’t even want to. For the most
part, the L-Group Vendors pooh-pooh this market as small, unsophisticated, and
‘beneath’ them. So naturally since there is a market to be served, new vendors that
don’t have these biases crop up and serve the market well. We'll call this group the S-
Group Vendors. (S standing for Small Customers)
Eventually the L-Group vendors run into a growth problem. The large hospitals
have finished adopting the Health IT technology and move into maintenance mode and
move their money elsewhere — building new hospitals, buying diagnostic imaging
equipment, etc. So the L-Group Vendors find themselves serving a market that is not
growing anymore. They see that the midsize customer market is big now, higher
growth, and seems like an adjacency that they should be able to enter. They may have
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this sinking feeling that they should have been investing in this midsize market years
ago, or maybe not. But now they start investing in this new high growth market — most
certainly too late as the S-Group Vendors are fully entrenched and serving the market
well.
Why did this happen?
What can companies do to prevent getting caught in this trap?
Causal Loop Diagram
Lets start with why this happened. We are going to take the perspective of a
successful L-Group company. The Causal Loop Diagram can be drawn like this as in
Figure 1:
Success (market-
share) with Large
(— Customers (L-Group)
Investment
in Product R Revenue / Profits
Features &
Complexity
YO Preference for and
Better Understanding of
Large Customers
Figure 1. Causal Loop Diagram for L-Group Success
Success with this particular segment of customers brings you revenue and
profits. Because these customers are your source of revenue and profits, you spend a
lot of time with them, you understand their needs better, you have a natural desire to
help them be more successful, and you have plenty of ideas on how you might continue
to serve your sweet-spot customers. You receive frankly less to no feedback from
customers from other markets. This increased customer understanding and motivation
to serve and add value causes you to invest in features/complexity in your product to
continue to serve these customers better. And naturally as you continue to improve your
product for this segment, you will continue to gain market share in this segment. There
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are other reasons that companies seem to have an up-market bias — bigger deals, more
prestigious customer names, more noteworthy press releases, etc. which have been left
out of this model but certainly compound this issue.
This story isn’t necessarily bad. This cannot be characterized as a vicious cycle
ora virtuous cycle just yet. Most successful businesses revolve around a core segment
that they serve extremely well. But it can be bad if the segment no longer grows and
you haven't built any adjacent markets to fuel your next wave of growth.
What gives in this model? Other segments. In Figure 2, the CLD is fleshed outa
little more.
Success (market-
a share) with
Large Customers
a (L-Group) oS
®
Investment in. Revenue / Profits
Product Features &
Complexity Rl
Preference for and Better
Understanding of Large
Customers
Success with Smaller
Customers (S-Group) »)
Revenue / Profits R2 invest ovans
ae! in Simplicity f=
/ Lower Cost
Solutions
Preference for/ S
Understanding of
Smaller Customers
R1 = L-Group Success
R2 = S-Group Success
Figure 2. Causal Loop Diagram for Investment Choices in Two Markets
In this model, the smaller customer segment does not desire features and
complexity. These customers desire simplicity and have a lower target cost. The S-
Group vendors are sitting in the other reinforcing loop continuing to refine their product
for this midsize market. All vendors face a limited R&D budget. The more they invest in
features and complexity, the less they will invest in simplicity and lower cost. So if they
are in the midsize market at all, they will loose market share overtime as they favor the
large customer market over the mid-size customer market.
Again so far this isn’t necessarily bad. The L-Group Vendors are digging into
their market; the S-Group Vendors are digging into their market. And if you think this is
a theoretical scenario, | can give you a dozen different Healthcare IT markets and can
point out the L-Group and the S-Group vendors and | imagine this is replicated in many
markets and many verticals around the globe.
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OK. So now let us introduce the problem. The growth in the large market slows,
the growth in the smaller market continues, and eventually the small customer market is
larger than the L-Group market and the L-Group vendors stop growing and desire to
move into the S-Group market. When and how should you make the move to invest in
this new high growth market? What policies should you use to always be on your toes
when your markets are changing?
System Dynamics Model Version 1
Here is a very basic model to test out some different policies on how a company
should manage its R&D investment portfolio.
Here is the scenario that was modeled:
e The L-Group Market has an annual revenue size of $1B/year. Its growth rate
(Average Annual Growth Rate, AAGR) is 0%, and the beginning market share of
our company is 25%. Our company’s beginning revenue from this market is
250M/year (25% * $1B).
e The S-Group Market has an annual revenue size of 250M/year — only % the size
of the L-Group market. But its growth rate is +20% and the beginning market
share of our company is 25% as well. Our company’s beginning revenue from
this market is 62.5M/year.
. There is a concept of market affection, which is basically your degree of
attractiveness to one or the other market on a scale from 0%-100%. If you prefer
a market, you will invest more R&D as a % of sales into building products that
that market prefers. And the more products you have for a particular market, the
higher your market share in that market. And the converse is true — the fewer
products, the less market share.
. In the beginning you have an equal preference for each market — your market
affection is 50%/50%. As you become attracted to one market, your affection will
only move at 5% per year. For example in year 1, if you prefer the L-Group
market, the affect to move to 55%/45% L-Group vs. S-Group. The assumption
here is that there is gradualness typical in companies when they are moving
away from a market that has been important to them. These shifts take time
because of legacy, customer base demands, unwinding verbal and contractual
commitments, retooling employee skill sets and biases, etc.
. Lastly the cycle time to build new products and have them impact your market
share is 3 years. Though software schedules can typically be a faster — 12 to 18
months lets say, it takes another 18-24 to have new products make a substantial
contribution to a company’s financials and market share.
In Figure 3 you can see a slightly simplified version of the model.
Page 5
L-Group Section
L-Products Released
O—— L-Market size
WIP L-Products
Building L- Releasing /
Products L-Products 4
Revenue from
L-Market share ————+
L-Market
R&D for
L-Market
Affection for (| $52) Total
L-Market Changing Revenue
S-Group Section # Affection i
R&D for Revenue from
a S-Market S-Market share ————” _$-Market
Building S- “ai
Products
S-Products ——s Released
O—S—— S-Market size
WIP S-Products
Releasing
S-Products
Figure 3. Stock and Flow Diagram for Investing in Two Markets
Starting in the center you can see the Affection for the L-Market stock. This will
drive R&D for both the L-Market and the S-Market. Obviously more Affection for the L-
Market will mean more R&D for the L-Market. R&D will drive product development,
which as mentioned takes an average of 3 years to get to released products. The
number of released products for the respective markets will drive the market share in
those markets. This market share, combined with the size of the total market for that
segment, will drive the revenue for that segment.
You can see that the part of the model that is not filled out is: what drives the
Changing Affection? Here we will explore several different policy options.
The goals for the company are as follows:
e Maximize the total cumulative revenue over the time horizon. In particular the
Accumulated Incremental Revenue over the company’s starting revenue will be
compared across the policy options.
e Grow faster than the overall market is growing.
The question is — how do you decide what market segment you should favor? Invest
in your current revenue stream, invest in the highest growth market, the biggest market,
something else?
Page 6
| examined the following five policy options that | thought were typically chosen
by companies, consciously or not. They are listed here along with the popular
management expressions justifying each of them:
1. Favor the segment that gives you the most revenue. Invest in your ‘core’.
2. Favor the segment that is the largest (market size). Fish in the biggest pond.
3. Favor the segment that is growing the most. Go for growth — even if it’s small
today.
4. Don’t favor either segment — stick with 50/50 no matter what. A balanced
portfolio across your core segments while investing in growth.
5). Favor the segment that will be the largest in 3 years. Go where the puck is going
to be.
When | do this exercise with a management team, | ask which method is used
most often. | always get the answer Policy 1 — Invest based on current revenue. Bigger
businesses deserve bigger R&D budgets right? Fair is fair. In fact the most common
metric around R&D investment is R&D as a % of sales, which basically encourages that
behavior. More sales means more R&D. Smaller revenue means less R&D. Plus it’s a
common rule of thumb to not bite the hand that feeds you.
However | modeled these 5 policies under the scenario above to determine the
best policy regardless of what was most common.
Policy 1: Favor the Segment that gives you the Most Revenue
If you go with Policy #1, favoring the segment with the most revenue, you get the
following outcomes:
e 3.014B in Accumulated Incremental Revenue.
e Company grows more than the market 50% of the time.
Figure 4 shows the results of this policy.
Your revenue grows from both markets. In the L-Group market, you are growing
because you are investing there and gaining market share. In the S-Group market, you
are growing because the market is growing at 20%; You are loosing market share but
the rising tide is helping you enough so there is some growth.
Because the L-Group market is giving you more revenue, you become more and
more attracted to that market. You are investing there and become less and less
attracted to the S-Group market. By year 10, you are all-in in the L-Group Market and
no longer investing anything in the S-Group Market.
Your L-Group market share grows over time because you are investing there
reaching over 50% by the end of the simulation. Conversely your S-Group market
share ends at 13%.
Page 7
Quarterly Revenue
Affection by Market
350 80%
2 300 Y
S
2 250
= 8 50% a
g 0 40%
* 150 30% =
100
20%
50 10% ee
0 0%
o 12 3 4 5 6 7 8 9 10 11 12 0 12 3 4 5 6 7 8 9 1 1 12
Years Years
—#—L-Group Revenue —=—S-Group Revenue Total Revenue —# Affection for L-Group Market —=— Affection for S-Group Market
Market-share by Market Growth Rate Comparison
60% 16%
yy 14% wrod
50%
a 12% eS ae
40% 10% A Wall ae
g eee « 3%
&% 3 6% Es
20%
10%
0%
4%
2%
| Uh
i
0%
ji 23 4 5
2%
ry
Years
[-2=L-Group Marketshare —*—S-Group Marketshare |
4%
Years
—eTotal MarketAAGR —*— Our AAGR
Figure 4. Results from Policy 1 - Prefer the
segment that gives you the Most Revenue
Lastly you are able to beat the growth rate of the overall market about half the
time.
Your over-investment in the bigger L-Group market has paid off for the first
several years of this simulation. However, sadly at the end of the simulation, you are
growing way behind the market. The total market growth rate is now driven by the S-
Group market which you are not much
years following this simulation.
of a player in the out years and certain in the
Policy 2: Favor the Segment that is the Largest.
You have the following outcomes by following this policy:
policy #1.
3.166B in accumulated incremental revenue. 5% better than policy #1.
Company grows more than the market 52% of the time.
2 points better than
Page 8
Figure 5 shows the results of this policy.
Quarterly Revenue Affection by Market
450
400
350
g 300
2 250 .
: x
_ 200
w 150
100
50
0
o 12 3 4 5 6 7 8 9 0 1 12
Years Years
—L-Group Revenue —=—S-Group Revenue Total Revenue —e Affection for L-Group Market —>— Affection for S-Group Market
Market-share by Market Growth Rate Comparison
50% 16%
45% 14% Pre ad
40% Pian 12% rcs al
35% Pl 10% 4
30% en
H naan ey
& 2% Spend ah ae ee 2 6%
15% vis
2%
10% Yi
% 0%
° Pll 2 3 4 5 6 7 8 9 10 1 12
0% Fs
Years
[-2=L-Group Marketshare —s— S-Group Marketshare |
-4%
—#—Total MarketAAGR —=*—Our AAGR
Figure 5. Results from Policy 2 - Favor the segment that is the largest market
This seems like a smart move. Invest in the L-Group segment for a while. Once
the S-Group segment becomes big enough to matter, you start investing here.
This policy performs better than the first one. In year 7 (see below) the S-Group
market becomes larger than the L-Group market. You begin to be attracted to the S-
Group market when that happens and start to trend in that direction with your R&D
spending.
Page 9
Quarterly Market Sizes
800
700 =
600 ri
500 rd
400
300
|O90000000000000 OOo sees renee OOOO
200 =
0
o 1 2 3 4 5 6 7 8 9 10 11 12
Years
$ in Millions
—e—L-Group Marketsize —=s— S-Group Marketsize
You can see in the Affection graph, that you spend your first seven years
investing in the L-Group market. Than at year seven, you gradually start to favor the S-
Group market. Not a bad policy. You've lost market share in the S-Group market but
start to regain it at the end of the cycle.
Though you have only beaten the growth rate of the market in 52% of the
quarters, you are clearly headed in the right direction at the end of the simulation. If
carried forward for 10 more years, this will probably make this policy look even better.
Policy 3: Favor the Segment that is Growing the Most - Go for Growth
You have the following outcomes by following this policy:
e 4.296B in accumulated incremental revenue. 43% better than policy #1.
e Your company grows more than the market 86% of the time. 36 points better
than policy #1.
Figure 6 shows the results of this policy.
Page 10
Quarterly Revenue
Affection by Market
100%
90% pos
80% a
10% eal
60% —- —
S 50%
40% [Bee
30% ee,
20%
A 0%
10% +
Years
—+L-Group Revenue —=—S-Group Revenue» Total Revenue
Years
—e— Affection for L-Group Market —=— Affection for S-Group Market
Market-share by Market
60%
Growth Rate Comparison
50%
25%
20%
40%
30%
15%
Share
20%
10%
AAGR
10%
5%
0%
0%
Years
[-e—L-Group Marketshare —s— S-Group Marketshare |
5%
Years
Total MarketAAGR —=—Our AAGR
Figure 6. Results from Policy 3 - Favor the segment that is the highest growth.
Clearly this is a big improvement.
You can see that the revenue growth is very
strong driven by the rise in your S-Group Revenues.
By basing your decisions on growth rate alone, you end up playing the opposite
of policy #1. All your affection from the beginning to the end is given to the S-Group
Market. You are building products for the S-Group Market alone so your market share
keeps rising in that market.
share.
So you have the high growth market + a rising market
Lastly you consistently outperform the market.
Page 11
Policy 4: Don’t favor either segment — stick with 50/50 no matter what. Hedge
your bets.
This is the balanced policy. Partially feed your current markets while investing in
your growth markets. This balanced perspective
companies try to use.
is also a very popular strategy that
You have the following outcomes by following this policy:
e 3.655B in accumulated incremental revenue
. 21% better than policy #1.
e Your company grows more than the market 88% of the time. 38 points better
than policy #1.
Figure 7 shows the results of this policy.
$in millions
Quarterly Revenue
100%
Affection by Market
90%
80%
70%
60%
%
50%
40%
mae 30%
20%
i 10%
0%
Years
—#L-Group Revenue —=—S-Group Revenue Total Revenue
—#— Affection for L-Group Market —=— Affection for S-Group Market
Share
35%
30%
25%
20%
15%
10%
5%
0%
Market-share by Market
20%
Growth Rate Comparison
paneeserroeerret
geen 15%
10%
AAGR
5%
2
haw
0%
o 1 2 3 4 5 6 7 8 9 10 iL 12 5%
Jio2 3 4 5 6 7 8 9 10 li i
Years
[== L-Group Marketshare —s—S-Group Marketshare |
Years
Total MarketAAGR —=— Our AAGR
Figure 7. Results from Policy 4 - Don't favor either segment. Keep it 50/50.
Page 12
This looks pretty good but not as good as policy 3. Your affection has stayed steady
at 50/50. Your revenue has growth nicely with a balance from each market. Your
market share is the same in both markets — the rise driving by new products. And lastly
you typically outperform the market with this strategy
Your growth gap to the market is closing because you are an average player in
both markets and will eventually grow at the average. Your inability to make tough
choices have given you balance but if the simulation was carried out another 10 years,
rather ordinary performance.
Policy 5: Favor the segment that will be the largest in 3 years. Go where the puck
is going to be.
This was my guess as to the winner. You take 3 years to develop products,
therefore point to the larger segment by the time the products are out.
You have the following outcomes by following this policy:
e 3.507B in accumulated incremental revenue. 16% better than policy #1.
e Your company grows more than the market 88% of the time. 38 points better
than policy #1.
This was good performance but strangely not the best performance. Your
market affection starts in the L-Group market but in year 4 switches to the S-Group
market. As predicted, 3 years earlier than policy #2 which waits until year 7 when the S-
Group market is actually bigger. But because you spent 3 years getting more and more
attracted to the L-Group market (up to 71%) and the gradualness of your ability to move
R&D dollars from once place to another (the 5% per year in the model), it actually takes
until year 8 before you are truly spending more on the S-Group market. This, plus the
3-year delay in product development, adds up to a significant delay between
recognizing the attractiveness of a segment, driving change in your organization, and
truly making a difference in that new segment.
You can see that your market share in the S-Group doesn’t increase much until
the end of the simulation period. But your growth rate is strong throughout and will no
doubt outperform in the next 10 years.
So what would sound like the best option was not, because of the severe time
delays, much longer than the 3 years of product development.
Page 13
Quarterly Revenue Affection by Market
450 100%
400 90%
350 80%
300 Us ae
Js a
3 %
lea ax | me
a ea 30% i eee.
100 esses eeeeeeee® 20%
50 | elena eee 10%
0 0%
o 1 2 3 4 5 6 7 8 9 0 n 12 o 12 3 4 5 6 7 8 9 ll 12
Years Years
=e L-Group Revenue —-—S-Group Revenue Total Revenue = Affection for L-Group Market —=— Affection for S-Group Market
Market-share by Market Growth Rate Comparison
40% 20%
35% a
30% ee 15%
25% ees ea
g . va 10%
B 20% §
° a
15% 5%
10% ;
5% 0%
yi23 45 67 8 9 0 1 2
0%
o 12 3 4 5 6 7 8 9 10 nl 12 5%
Years Years
[-2=L-Group Marketshare —=—S-Group Marketshare | —eTotal MarketAAGR —=s—Our AAGR
Figure 8. Results from Policy 5 - Favor the segment that will be the largest in 3 years.
The net of version 1.0 of this model was that Policy #3, going for the highest
growth market from the beginning, was the winner. Here are the results:
Accumulated Improvement Qtrs >
Policy Incremental |% overPolicy| Market
Revenue 1 AAGR
l-Most Revenue 3,014 0% 50%
2-Largest Market 3,166 5% 52%
3-Highest Growth 4,296 43% 86%
4-Invest in both 3,655 21% 88%
5-Largest in 3yrs 3,507 [16% 88%
Page 14
$in Millions
300 di, |—+— Policy 1
250 —= Policy 2
> Policy 3
—— Policy 4
150 —* Policy 5
Revenue Comparison
A few important notes on these results:
What is most remarkable about these results is how they compare with
reality. | mentioned that the most prevalent policy in business today is
actually Policy #1. And this performed the worst by a large margin. How
much more efficient could we make R&D investments if company’s really
understood this major disconnect?
In this scenario it worked, but always favoring the Highest Growth segment is
probably not always the best policy. In this case it was even though the
highest growth was only % the size of the large segment. For example if you
make the highest growth segment tiny in size, than its high growth nature
really doesn’t matter. The next section will more robustly test the policy
choices.
Monte Carlo Analysis
This research is using a generic model to apply to many company situations and
| was concerned that the initial model parameters have significantly influenced the
outcome of Policy 3 being the winner. So | ran a Monte Carlo analysis using 10,000
trials and a variety of market sizes and growth rates. Specifically:
Initial Market Sizes for both L-Group and S-Group markets were randomly
selected from $0 — $1000M / year.
Initial Growth Rates were randomly selected from -20% to 20% for both markets
and then were held constant through the simulation timeframe.
Page 15
The results of this analysis were that Policy 5 was the winning policy across this
broader arrange of company situations. Here were the results:
Accumulated Revenue
Improvement | % Time Best
Policy Mean Median % Policy*
Policy 1-Most Revenue 5,867 4,309 0% 22%
Policy 2-Largest Market 5,889 4,326 0% 23%
Policy 3-Highest Growth 5,886 4,356 1% 30%
Policy 4-Invest in Both 5,104 3,907 -9% 0%
Policy 5-Largest in 3yrs 7,501 5,560 29% 68%
*The reason these add to more than 100%, is that in the case of a tie for best policy, each of the
winner policies is given credit.
This histograms that compare Policy 3 to Policy 5 are as follows:
Policy 3 Median = $4,356M
1600 ~
1400 ~
1200 ~
1000 ~
800 -
600 ~
400 -
200 +
o 4
SH FP GF _ GH GH HF GF GF GF HF _ SF GF gF
SS SS NS SS Ss
SO LX LS SS S S SS
FKP PHP KH LHP HHP wh
Policy 5 Median = $5,560M
2000
1800
1600
1400
1200 +
1000 -
800 +
600 ~
400 +
200
10)
2 $ $ 6 $
FFFFFLEFE SF SOG
Version 2.0 of the Model
After presenting this model to leadership teams throughout my company, a few
common questions came up:
1. Maybe the problem with Policy #5, with those initial parameters, was that the
time horizon was not optimized. Given this scenario, would 5 years or 7 years
perform better?
2. What would be the impact if we could change the organization faster?
example what if we could move our Affection by 10% per year instead of the 5%
per year in the model.
3. Lastly what if we could develop products faster? For example what results could
we obtain with a 2-year development timeframe instead of 3 years?
| modified the model in a few ways to try out some of these new hypotheses in the
following ways:
- The simulation time of the model was expanded to 20 years instead of 12
to give more time for decisions to play out.
- The L-Group segment was modified to start at 1.2B/year and still be at 0%
growth.
- To prevent the S-Group segment from become unrealistically big, | started
it’s size at 100M/year, it’s initial growth rate at 24% and slowed its growth
rate to eventually hit 3% in year 20.
- | hardwired the model to Policy #5 from version 1.0.
To illustrate this here are the respective market sizes for the simulation. You can
see that the S-Group market becomes bigger in year 12.
500
450
400
350
300
250
200
150
100
50
$in Millions
Quarterly Market Sizes
ra
=
ae
01 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Years
—¢— L-Group Marketsize —*— S-Group Marketsize
Page 17
Evaluating the Time Horizon
Here | evaluated different time horizons associated with the Policy ‘Favor the
market that is the largest in X years’. Here were the results of some selected time
horizons:
Accumulated
[Time Incremental
Horizon Revenue Improvement %
6,043 }2%
6,136 0%
6,362 4%
6,565 [7%
6,641 [8%
6,469 5%
6,387 4%
Wleloln{ufwle
1
i.
You can see that 9 years seems to be the best time horizon for these parameters
and results in an 8% improvement over the original 3 years. This also matches the
commentary from above. You have delays because of investing in the other market,
delays changing an organization, and product development delays that roughly add up
to this timeframe. To further illustrate the 9-year time horizon, you can see the results
of this change in Figure 9.
This is a good example of navigating appropriately through both markets. In year
3 the switch is made to start to favor the S-Group market even though it won’t be larger
for another 9 years. That allows you to reap the rewards of the today’s market (L-
Group) while investing and eventually reaping the rewards of tomorrow's market (S-
Group).
Page 18
Quarterly Revenue
Affection by Market
350
0% a
300 20% ee
250 10% a
4 60% pa
200
2 & 50%
é eA
€ 150 40%
+ 30%
100 4
20%
50 10%
0 a 0% oe
‘ y
0123 45 67 8 9 101112131415 1617 18 19 20 SUSE UR RB BT RE BARR MRR Mo
Years Years
=e L-Group Revenue —-—S-Group Revenue Total Revenue a= Afecton for Group Market —=— Affection for S-Group Market
Market Share by Market Growth Rate Comparison
70% 10%
60% 8% jana
50% | 6% i
40% Pee 4% Mi
§
i «
5 aoe gm
20% 0%
pyro eset soe oo ooo EDS OD
10% 2%
OS TIRST OATS OMNIS HS ON SLD
6%
Years Years
[-e=CGioup Marcetshare —=— 5 Group Marcethare]
—o— Total MarketWAGR —=— Our AAGR,
Figure 9. Results from investing using Future Market Size with a 9 year time horizon.
Evaluating the Timeframe required for Organization Change
Next we evaluate the benefits of moving the organization faster from one market
to another. Specifically in the original model, the affection % could only move by 5%
per year. This is because of the difficultly in moving away from a market as spending
shifts take time because of legacy, customer base demands, unwinding existing
commitments, etc. But what if you could figure out ways to do this faster?
Page 19
The results are in the following table:
Improvement %
Accumulated over 5%/year
Affection Rate} Incremental Affection Rate
Speed Revenue Change
5.0% 6,136 0%
7.5% 6,340 3%
10.0% 6,523 6%
12.5% 6,677 9%
15.0% 6,799 [11%
If you could move at 10% per year instead for example, that would be a 6%
improvement over just the original pace of driving organizational change. In the model
itself, the faster you can make this move, the better the improvement gets.
Evaluating the Timeframe required for Product Development
Lastly we take a look at the benefits of having a 2-year R&D timeframe instead of
the model's original 3 years. Remember R&D does not just consist of building and
releasing the products but also any time delays in making an impact in the market
share. For some industries there maybe delays due to building market awareness,
launch scheduling, market perception, building reference sites, etc. Here are the
results:
Accumulated Improvement %
R&D Incremental | over 3 year R&D
Timeframe Revenue Timeframe
5 4,861 |-21%
4 5,482 511%
3 6,136 0%
2 6,810 [11%
1 7,503 [22%
You can see that dropping down to a 2 year timeframe will yield an 11%
improvement in accumulated incremental revenue relative to the 3 years. I’ve put ina
few other data points to illustrate that basically the faster the better. It allows you to
build up your market share in your chosen market faster.
Putting it all together
Lastly | looked at having a longer time horizon (7 years instead of 3 years) plus
faster ability to change (i.e. 10% Affection Movement instead of 5%) plus faster R&D (2
years instead of 3 years) relative to the original parameters. Here are the results:
Page 20
Accumulated Improvement %
Incremental over Original
Improvements Revenue Policy 5
(Original Policy 5 6,136 |0%
All Three
llmprovements 7,676 |25%
Driving all three of these changes, gives you a staggering 25% increase from the
original parameters of the model. (N.B. | changed the new time horizon from 9 years to
7 years because it turns out given the faster R&D timeframe and the faster ability to
change, 7 years becomes the optimal time horizon — not 9 as with the original
parameter values.)
You can see that better policies plus increased knowledge of the dynamics of the
situation driving other improvements yield a very different future for the company.
For the final points, | rebuilt version 2.0 of the model to run under the original
Policy 1 which was the most popular way that companies allocate R&D dollars — by their
current revenue streams and compared it with the new recommended way that
companies make decisions based on this paper — Invest by Future Market Size (Policy
5), have a long-time horizon, change quickly when moving into new markets, and speed
up your R&D cycle. To illustrate just how different these 2 companies are at the end, |
offer the following comparison graphs in Figure 10.
The company on the left is all about digging into the L-Group market. They've
got a great share of the market, but they are no longer growing their revenues. They
had a great run when they outperformed the market but those days are long gone.
They continue to invest into their core and gradually ignore other markets. This makes
things easy but it’s a company without much of a future.
In contrast the company on the right has grown its revenues and they are still
growing. Their growth rate did underperform the market somewhat while they retooled
their product line for the growth markets. And it's paid off — they are now consistently
growing faster than the market. Lastly they have invested in the L-Group while that
market was hot, now they are investing in the S-Group and growing their market share
nicely there. And with these policies they will be continually reinventing themselves
when the next growth market comes along. The company on the right is all about smart
change and moving quickly to the future.
Page 21
The Typical Company
The New Company
$in millions
Quarterly Revenue
AR €
Quarters
—s—L-Group Revenue —=_ S-Group Revenue __ Total Revenue
Quarterly Revenue
$in millions
a
Quarters
—s_L-Group Revenue = S-Group Revenue Total Revenue
—o—-Group Marketshare —®— S-Group Marketshare ]
Growth Rate Comparison Growth Rate Comparison
15% 14%
1% — =
10%
& a, oe A,
$ 54 Loe
q 6%
4%
Ue
0%
10% An OomnaAHOMKR A HAMH oan GD
AANRARESSHRSCEERR G
Quarters Quarters
—+ Total MarketAGR —2—Our AAGR —+Total MarketAAGR —=-Our AAGR
Market Share by Market Market Share by Market
70% 60%
60% 50%
50% 40%
§ 40%
30%
& 30% é .
20% ah
10% 10%
0% 0%
cease ake aes SaRkSERLR B sO ge aRaRe SRRSERR GB
Quarters Quarters
[-#= Group Marketshare —S— S-Group Markets hare ]
Figure 10. Comparison of a typical company using R&D as a % of Sales with a
new company using R&D as a % of Future Market Size, a long planning horizon,
faster organization change, and faster R&D.
Page 22
Conclusion
The thinking and the tools that companies use today do not encourage them to
change and adapt to the markets around them. There are strong biases that pull a
company more and more toward its original market and inhibit its ability to invest in new
upcoming growth markets. Today’s leaders especially don’t understand the large time
delays that come with recognizing an interesting market, turning the ship around to
invest in a new market, and then having the products out that truly impact market share
and revenue. Today's methods of R&D investing are based on each business getting a
% of its revenue that it can invest in R&D. This methodology, though fair and easy to
understand and administer, is the epitome of this misunderstanding and it leads to
significant underperformance, stagnation, and early unnecessary death of a company.
The System Dynamics model built to examine this situation clearly shows the
trap that R&D as a flat % of sales can ensnare a company. Of all the logical choices of
R&D portfolio management, this method often performs the worse despite being the
most popular. Basing your R&D dollars on your current performance (e.g. revenue) can
lead a company into a self-fulfilling prophecy. You are doing poorly in a market, so you
invest less, which causes you to be even worse in that market. And this approach can
lock a company into a market and a strategy that inhibits change. This paper concludes
that basing your R&D investment on your Future Market Size is actually the wisest
investment philosophy and allows your company to be continuously investing in where
the future growth is. It also highlights the enormous benefits to decreasing the delays
that are inherent in the system around organization change and product development
timeframes. | hope with this work that R&D as a % of Future Market Size becomes the
new standard in the industry.
References
Hannon, M. T. and J. H. Freeman (1984), “Structural inertia and organizational
change.”, American Sociological Review, 49(2): 149-64
Noda, T., and J. L. Bower. 1996. “Strategy making as iterated processes of resource
allocation.”, Strategic Management Journal Summer Special Issue 17: 159-192.
Burgelman, R. A. 1996 “A process model of strategic business exit: Implications for an
evolutionary perspective on strategy”, Strategic Management Journal 17: 193-214
Biography
Don Woodlock is presently Senior Vice President and General Manager for GE
Healthcare IT and is responsible for the business unit that builds IT systems for hospital
departments. This $800 million business, headquartered outside of Chicago IL, is the
market share leader and serves 3,000 customers in 50 countries with over 1,500
employees across the globe.
Page 23
Don’s work in System Dynamics consists of using SD tools to aid in decision making at
GE Healthcare around R&D investment, headcount planning, balanced scorecards and
performance, and leadership development. Don is also a leading video producer on
System Dynamics with his video series Introduction to System Dynamics at
www.systemdynamics101.com — with over 5,000 viewers. Lastly Don is pioneering the
mainstream adoption of SD tools through the use of Excel as a modeling tool to
facilitate broader use of the discipline.
Don holds a_ Bachelor of Science in Electrical Engineering from the
Massachusetts Institute of Technology. He currently lives in the Chicago area with his
wife and two children. His hobbies include running, playing guitar and spending time
with his family.
Page 24
L-Group Growth Rate
S-Group Growth Rate
Products per R&D % per year
Average R&D Time
Average Product Age
Increase in Affection to Favorite Segment
Initial L-Group Marketsize
Initial S-Group Marketsize
Policy
Quarters
L-Group Products
Affection for L-Group Market
R&D as a % of sales for L-Group Market
Building L-Group Products
Releasing L-Group Products
L-Group Products WIP
Aging L-Group Products
Released L-Group Products
S-Group Products
Affection for S-Group Market
R&D as a % of sales for S-Group Market
Building S-Group Products
Releasing S-Group Products
S-Group Products WIP
Aging S-Group Products
Released S-Group Products
L-Group Market
L-Group Marketsize
L-Group Marketshare
S-Group Market
S-Group Marketsize
S-Group Marketshare
Affection Shift
Change to L-Group Affection
Favorite Segment
Policy #1: By Larger Revenue
Policy #2: By Larger Market
Policy #3: By Higher Growth
0%
20%
1
3 Years
5 Years
5%
1,000 per year
250 per year
5 Change on Control1 page
0 0.25 0.5
50% 51%
7%
53%
7%
1.79375
0.83
10 10.96042
1.8375
0.91
11.88455
1.25
25 24.58333
1.229167
24.26753
49%
7%
48%
7%
1.70625
0.83
10 10.87292
1.6625
0.91
11.62934
1.25
25 24.58333
1.229167
24.26024
250 250
25%
250
24%
63 65.625
25%
68.90625
24%
1.3% 1.3%
an>D>
>
o>>
0.75
54%
8%
1.88125
0.99
12.77542
1.213377
24.04454
46%
6%
1.61875
0.97
12.27898
1.213012
24.01634
250
24%
72.35156
24%
1.3%
55%
8%
1.925
1.06
13.6358
1.202227
23.90693
45%
6%
1.575
1.02
12.83073
1.200817
23.83877
250
24%
75.96914
aD>y>
24%
1.3%
1.25
56%
8%
1.96875
1.14
14.46823
1.195346
23.8479
44%
6%
1.53125
1.07
13.29275
1.191939
23.71606
wo>op>
250
24%
79.7676
24%
1.3%
Policy #4: Stick with 50/50
Policy #5: Largest in 3 years
Which Policy to Use
Output Variables
L-Group Revenue
S-Group Revenue
Total Revenue
Total Marketsize
Total MarketAAGR
Our AAGR
Beat Market?
Incremental Revenue
A
5A
61
16
78.125 78
312.5 315.625
4%
-3%
0
1
61
17
77
318.9063
4%
-1%
(0)
-1
17
7
322.3516
4%
1%
0
-1
60
18
78
325.9691
4%
2%
0
0
60
19
79
329.7676
1.5
58%
8%
2.0125
1.21
15.27505
1.192395
23.86119
43%
6%
1.4875
1.11
13.67252
1.185803
23.63799
250
24%
83.75598
24%
1.3%
an>D>
1.75
59%
8%
2.05625
1.27
16.05838
1.19306
23.94105
41%
6%
1.44375
1.14
13.9769
1.181899
23.59547
250
24%
87.94378
an>>
24%
1.3%
60%
8%
2m
1.34
16.82018
1.197053
24.0822
40%
6%
14
1.16
14.21216
1.179773
23.58043
250
24%
92.34097
wo>y>
24%
1.3%
2.25
61%
9%
2.14375
1.40
17.56225
1.20411
24.27977
39%
5%
1.35625
1.18
14.38406
1.179022
23.58576
250
24%
96.95801
D>y>
24%
1.3%
2.5
63%
9%
2.1875
1.46
18.28623
1.213988
24.5293
38%
5%
1.3125
1.20
14.49789
1.179288
23.60514
250
25%
101.8059
orp
24%
1.3%
2.75
64%
9%
2.23125
1.52
18.99362
1.226465
24.82669
36%
5%
1.26875
1.21
14.55848
1.180257
23.63304
250
25%
106.8962
wo>rD>
24%
1.3%
65%
9%
2.275
1.58
19.68582
1.241334
25.16816
35%
5%
1.225
4:21.
14.57027
1.181652
aD>yD
23.6646
250
25%
112.241
24%
1.3%
3.25
66%
9%
2.31875
1.64
20.36409
1.258408
25.55023
34%
5%
1.18125
1.21
14.53733
1.18323
23.69556
250
26%
117.8531
wo>y>
24%
1.3%
3.5
68%
9%
2.3625
1.70
21.02958
1.277512
25.96973
33%
5%
1.1375
1.21
14.46339
1.184778
23.72222
250
26%
123.7457
wo>ry>
24%
1.3%
3.75
69%
10%
2.40625
1.75
21.68337
1.298486
26.42371
31%
4%
1.09375
1.21
14.35186
1.186111
23.74139
D>y>
250
26%
129.933
24%
1.3%
A A A A A A A A A
60 60 60 61 61 62 63 64 65 66
20 21 22 23 24 25 27 28 29 31
79 81 82 84 85 87 89 92 94 97
333.756 337.9438 342.341 346.958 351.8059 356.8962 362.241 367.8531 373.7457 379.933
5% 5% 5% 5% 6% 6% 6% 6% 6% 7%
5% 6% 7% 8% 9% 9% 10% 10% 11% 11%
0 £ EE 1 1 1 1 1 di, LE
1 2 4 5 i 9 11 14 16 19
70%
10%
2.45
1.81
22.32642
1.321185
26.90947
30%
4%
1.05
1.20
14.20587
1.18707
23.75031
250
27%
136.4297
24%
1.3%
an>D>
4.25
71%
10%
2.49375
1.86
22.95963
1.345473
27.42453
29%
4%
1.00625
1.18
14.0283
1.187516
23.74662
250
27%
143.2511
an>>
24%
1.3%
45
70%
10%
2.45
191
23.49633
1.371227
27.96661
30%
4%
1.05
1.17
13.90927
1.187331
23.72831
250
28%
150.4137
24%
-1.3%
A
A
B
4.75
69%
10%
2.40625
1.96
23.94455
1.39833
28.5263
31%
4%
1.09375
1.16
13.84392
1.186416
23.701
250
29%
157.9344
D>y>
24%
-1.3%
68%
9%
2.3625
2.00
24.31167
1.426315
29.09537
33%
5%
1.1375
1.15
13.82776
1.18505
23.66961
250
29%
165.8311
orp
24%
-1.3%
5.25
66%
9%
2.31875
2.03
24.60445
1.454768
29.66657
34%
5%
1.18125
1.15
13.85669
1.183481
23.63845
250
30%
174.1227
wo>rD>
24%
-1.3%
5.5
65%
9%
2.275
2.05
24.82908
1.483329
30.23361
35%
5%
1.225
1.15
13.92697
1.181922
23.61125
250
30%
182.8288
24%
-1.3%
A
A
B
5.75
64%
9%
2.23125
2.07
24.99124
1.511681
30.79102
36%
5%
1.26875
1.16
14.03514
1.180562
23.59127
250
31%
191.9702
wo>y>
24%
-1.3%
63%
9%
2.1875
2.08
25.09614
1.539551
31.33408
38%
5%
1.3125
1.17
14.17804
1.179563
23.5813
250
31%
201.5687
wo>ry>
24%
-1.3%
6.25
61%
9%
2.14375
2.09
25.14854
1.566704
31.85872
39%
5%
1.35625
1.18
14.35279
1.179065
23.58374
250
32%
211.6472
D>y>
24%
-1.3%
67
32
100
386.4297
7%
11%
1
22
69
34
103
393.2511
7%
12%
£
24
70
36
106
400.4137
7%
12%
EE
27
109
407.9344
8%
12%
1
31
112
415.8311
8%
12%
1
34
74
41
115
424.1227
8%
12%
1
37
76
43
119
432.8288
8%
12%
1
41
77
45
122
441.9702
8%
12%
1
44
78
48
126
451.5687
9%
12%
di,
48
80
50
130
461.6472
9%
12%
LE
51
6.5
60%
8%
21
2.10
25.15283
1.592936
32.36149
40%
6%
1.4
1.20
14.55672
1.179187
23.60062
250
32%
222.2295
24%
-1.3%
A
A
B
6.75
59%
8%
2.05625
2.10
25.11301
1.618075
32.83949
41%
6%
1.44375
1.21
14.78741
1.180031
23.63364
an>>
250
33%
233.341
24%
-1.3%
58%
8%
2.0125
2.09
25.03276
1.641974
33.29026
43%
6%
1.4875
1.23
15.04263
1.181682
23.68425
250
33%
245.0081
wo>y>
24%
-1.3%
7.25
56%
8%
1.96875
2.09
24.91545
1.664513
33.71181
44%
6%
1.53125
1.25
15.32033
1.184212
23.75359
250
34%
257.2585
24%
-1.3%
7.5
55%
8%
1.925
2.08
24.76416
1.685591
34.10251
45%
6%
1.575
1.28
15.61863
1.187679
23.8426
250
34%
270.1214
noy>
24%
-1.3%
7.75
54%
8%
1.88125
2.06
24.58173
1.705126
34.46107
46%
6%
1.61875
1.30
15.93583
1.19213
23.95202
250
34%
283.6275
24%
-1.3%
53%
7%
1.8375
2.05
24.37075
1.723053
34.78649
48%
7%
1.6625
1.33
16.27034
1.197601
24.08241
250
35%
297.8088
24%
-1.3%
8.25
51%
7%
1.79375
2.03
24.13361
1.739324
35.07806
49%
7%
1.70625
1.36
16.62073
1.20412
24.23415
250
35%
312.6993
24%
-1.3%
8.5
50%
7%
1.75
2.01
23.87247
1.753903
35.33529
50%
7%
1.75
1.39
16.98567
1.211708
24.4075
250
35%
328.3342
24%
-1.3%
8.75
49%
7%
1.70625
1.99
23.58935
1.766765
35.5579
51%
7%
1.79375
1.42
17.36395
1.220375
24.6026
250
36%
344.751
25%
-1.3%
81
52
133
472.2295
9%
12%
1
55
82
55
137
483.341
9%
12%
1
59
83
58
141
495.0081
10%
12%
EE
63
84
61
145
507.2585
10%
12%
1
67
85
64
150
520.1214
10%
12%
1
72
154
533.6275
10%
12%
1
76
87
72
159
547.8088
11%
12%
1
81
88
76
163
562.6993
11%
12%
1
85
88
80
168
578.3342
11%
12%
di,
90
89
85
174
594.751
11%
12%
i,
96
48%
7%
1.6625
1.97
23.28607
1.777895
35.74578
53%
7%
1.8375
1.45
17.75445
1.23013
24.81947
250
36%
361.9885
25%
-1.3%
9.25
46%
6%
1.61875
1.94
22.96431
1.787289
35.899
54%
8%
1.88125
1.48
18.15617
1.240973
25.05803
250
36%
380.0879
25%
-1.3%
9.5
45%
6%
1.575
1.91
22.62562
1.79495
36.01774
55%
8%
1.925
151
18.56815
1.252902
25.31814
250
36%
399.0923
25%
-1.3%
9.75
44%
6%
1.53125
1.89
22.2714
1.800887
36.10232
56%
8%
1.96875
1.55
18.98956
1.265907
25.59958
250
36%
419.0469
26%
-1.3%
10
43%
6%
1.4875
1.86
21.90295
1.805116
36.15316
58%
8%
2.0125
1.58
19.41959
1.279979
25.90207
250
36%
439.9993
26%
-1.3%
10.25
41%
6%
1.44375
1.83
21.52146
1.807658
36.17075
59%
8%
2.05625
1.62
19.85754
1.295103
26.22526
250
36%
461.9993
26%
-1.3%
10.5
40%
6%
1.4
1.79
21.128
1.808537
36.15566
60%
8%
21
1.65
20.30275
1.311263
26.56879
250
36%
485.0992
27%
-1.3%
10.75
39%
5%
1.35625
1.76
20.72359
1.807783
36.10855
61%
9%
2.14375
1.69
20.7546
1.32844
26.93225
250
36%
509.3542
27%
-1.3%
11
38%
5%
1.3125
1.73
20.30912
1.805427
36.03009
63%
9%
2.1875
1.73
21.21255
1.346613
27.31519
250
36%
534.8219
27%
-1.3%
11.25
36%
5%
1.26875
1.69
19.88544
1.801504
35.92101
64%
9%
2.23125
1.77
21.67609
1.365759
27.71714
250
36%
561.563
28%
-1.3%
179
611.9885
12%
13%
1
101
185
630.0879
12%
13%
£
107
191
649.0923
12%
13%
a
113
90
107
198
669.0469
12%
13%
1
119
90
114
204
689.9993
13%
14%
1
126
90
121
212
711.9993
13%
14%
1
133
90
129
219
735.0992
13%
15%
1
141
90
137
227
759.3542
13%
15%
1
149
90
146
236
784.8219
13%
15%
di,
158
90
156
245
811.563
14%
16%
1
167
11.5
35%
5%
1.225
1.66
19.45332
1.79605
35.78208
65%
9%
2.275
1.81
22.14475
1.385857
28.13762
250
36%
589.6411
28%
-1.3%
11.75
34%
5%
1.18125
1.62
19.01346
1.789104
35.61408
66%
9%
2.31875
1.85
22.6181
1.406881
28.57614
250
36%
619.1232
29%
-1.3%
33%
5%
1.1375
1.58
18.56651
1.780704
35.41784
68%
9%
2.3625
1.88
23.09576
1.428807
29.03217
250
35%
650.0794
29%
-1.3%
12.25
31%
4%
1.09375
1.55
18.11305
1.770892
35.19415
69%
10%
2.40625
1.92
23.57736
1.451609
29.50521
250
35%
682.5833
30%
-1.3%
12.5
30%
4%
1.05
1.51
17.65363
1.759708
34.94387
70%
10%
2.45
1.96
24.06258
1.475261
29.99473
250
35%
716.7125
30%
-1.3%
B
B
B
89
166
255
839.6411
14%
16%
1
177
89
177
266
869.1232
14%
17%
£
188
89
189
277
900.0794
14%
17%
a
199
88
201
289
932.5833
14%
17%
1
211
87
215
302
966.7125
15%
18%
1
224
Affection for A-Group Market
Equation
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
110%
120%
130%
140%
150%
160%
R&D as a % of Sales
0.0%
14%
2.8%
4.2%
5.6%
7.0%
8.4%
9.8%
11.2%
12.6%
14.0%
14.0%
14.0%
14.0%
14.0%
14.0%
14.0%
R&D=(7%/50%)*Affection
R&D as a % of Sales
16.0% 4
14.0% 4
12.0% 5
10.0% +
8.0% 5
6.0% 4
4.0% 5
2.0% 4
0.0%
0%
10% 20% 30%
R&D Transfer Function
3 40% 50% 60% 70% 80% 90% 100 110 120 130 140 150 160
oH HH H H NW
Affection for Group
Policy
Accumulated
Incremental Revenue
(AIR) 3507
Base Case 3014
AIR Improvement % 16%
Qtrs>Market V 88%
Accumulated
Policy Incremental
Revenue
1-Most Revenue 3,014
2-Largest Market 3,166
3-Highest Growth 4,296
4-Invest in both 3,655
5-Largest in 3yrs 3,507
Quarterly Revenue
300
Quarters
= L-Group Revenue —ii— S-Group Revenue *
100%
Affection by Market
80%
60% 4
40%
20%
0%
Quarters
[—— Affection for L-Group Market —ii— Affection for S:
Improvement
%
0%
5%
43%
21%
16%
800 ——
700 ~—
600 +~—
Qtrs >
Market 500 7—
on
AAGR = 400 -—
50% g
52% = 300 +
86% < 4
88% @ 200 7—
Comparison Table
Policy 1
Policy 2
Policy 3
Policy 4
Policy 5
77.591145833 77.38566054
77.591145833 77.38566054
77.591145833 77.37245578
77.591145833 77.37905816
77.591145833 77.38566054
77.48754
77.48754
77.43745,
77.4625
77.48754
77.87743
77.87743
7.75882
77.81813
77.87743
78.53748
78.53748
78.31305
78.42527
78.53748
Revenue Comparison
Growth Rate Comparison
o
Oo
<
<
“‘Trrttttttrri{ty
Pe
Quarters
Total Revenue —¢— Total MarketAAGR —m— Our AAGR
Market-share by Market
40%
35% mart setS os een
| 30%
—_| o 2% ) Oe? 1A anil
20%
ieee Seerecesl GH 15%
10%
5%
Sort 0% Tt
RRS
Quarters
-Group Market —¢— L-Group Marketshare —ai- S-Group Marketshare
Quarterly Market Sizes
2.9 2 % 0 9 6 © 049 20 2
SPA PP we GV OM APY TOM OP Y
Years
x
-@ L-Group Marketsize —m— S-Group Marketsize
79.4512 80.60337
79.4512 80.60337
79.08015 80.04333
79.26567 80.32335
79.4512 80.60337
81.97989 83.5677
81.97989 83.5677
81.18882 82.50558
81.58436 83.03664
81.97989 83.5677
—?— Policy 1
—l- Policy 2
~~ Policy 3
—< Policy 4
—#— Policy 5
85.35468
85.35468
83.98514
84.66991
85.35468
87.32955
87.32955
85.6214
86.47547
87.32955
89.48177
89.48177
87.41049
88.44613
89.48177
91.80152
91.80152
89.35063
90.57608
91.80152
94.27956
94.27956
91.44199
92.86077
94.27956
96.90718
96.90718
93.68661
95.29689
96.90718
99.67614
99.67614
96.08828
97.88221
99.67614
102.5786
102.5786
98.6525
100.6156
102.5786
105.6072
105.6072
101.3864
103.4968
105.6072
108.7545
108.7545
104.2986
106.5266
108.7478
112.0137
112.0137
107.3995
109.7066
111.99
115.378
115.378
110.7006
113.0393
115.3263
118.8408
118.8408
114.2153
116.528
118.7522
122.3953
122.3953
117.9582
120.1768
122.2658
126.0351
126.0351
121.9456
123.9903
125.8677
129.7535
129.7535
126.195
127.9743
129.5611
133.544
133.544
130.7256
132.1348
133.3513
137.3997
137.3997
135.5582
136.4789
137.2457
141.3136
141.3136
140.7149
141.0142
141.254
145.2785
145.2785
146.2196
145.7491
145.3877
149.2871
149.2885
152.0979
150.6925
149.6602
153.3314
153.3409
158.3769
155.8541
154.0872
157.4034
157.436
165.0856
161.2445
158.6858
161.4944
161.5771
172.255
166.8747
163.4752
165.5954
165.7702
179.9177
172.7565
168.4764
169.6966
170.0241
188.1085
178.9026
173.7125
173.788
174.3499
196.8644
185.3262
179.2081
177.8584
178.7613
206.2245
192.0415
184.9901
181.8964
183.2743
216.2301
199.0633
191.0871
185.8894
187.9073
226.9253
206.4074
197.5301
189.8242
192.6809
238.3565
214.0903
204.3518
193.6863
197.6182
250.5728
222.1296
211.5874
197.4691
202.7443
263.618
230.5435
219.2742
201.1669
208.087
277.5361
239.3515
227.4519
204.7752
213.6761
292.3724
248.5738
236.1628
208.2904
219.544
308.1733
258.2318
245.4517
211.7096
225.7256
324.9865
268.3481
255.3662
215.0307
232.2581
342.8614
278.9461
265.9567
218.2524
239.1816
361.8489
290.0506
277.2768
221.3736
246.5388
382.0019
301.6877
289.383
224.394
254.3754
403.3755
313.8848
302.3357
L-Group Growth Rate
Products per R&D % per year
Average R&D Time
Average Product Age
Increase in Affection to Favorite Segment
Initial L-Group Marketsize
Initial S-Group Marketsize
Foresight
Quarters
L-Group Products
Affection for L-Group Market
R&D as a % of sales for L-Group Market
Building L-Group Products
Releasing L-Group Products
L-Group Products WIP
Aging L-Group Products
Released L-Group Products
S-Group Products
Affection for S-Group Market
R&D as a % of sales for S-Group Market
Building S-Group Products
Releasing S-Group Products
S-Group Products WIP
Aging S-Group Products
Released S-Group Products
L-Group Market
L-Group Marketsize
L-Group Marketshare
S-Group Market
S-Group Marketsize
S-Group Market AAGR
S-Group Marketshare
Affection Shift
Change to L-Group Affection
Favorite Segment
Policy #1
Policy #5: Largest in 3 years
Which Policy to Use
0%
1
2 Years
5 Years
10%
1,200 per year
100 per year
7 years
(0) 0.25
50% 53%
7%
1.8375
1.25
10 = 10.5875
1.25
25 25
48%
7%
1.6625
1.25
10 = 10.4125
1.25
25 25
300 300
25%
25 26.5
24%
25%
2.5%
A
A
5A
0.5
55%
8%
1.925
1.32
11.18906
1.25
25.07344
45%
6%
1.575
1.30
10.68594
1.25
25.05156
300
25%
28.1
24%
25%
2.5%
>>>
0.75 1
58% 60%
8% 8%
2.0125 2.1
1.40 1.48
11.80293 12.42756
1.253672 1.26092
25.2184 25.43284
43% 40%
6% 6%
1.4875 1.4
1.34 1.35
10.8377 10.88298
1.252578 1.256736
25.13473 25.2327
300 300
25% 25%
29.7 31.5
24% 24%
25% 25%
2.5% 2.5%
A A
A A
A A
1.25
63%
9%
2.1875
1.55
13.06162
1.271642
25.71465
38%
5%
1.3125
1.36
10.83511
1.261635
25.33144
>>>
300
26%
33.3
23%
25%
2.5%
Output Variables
L-Group Revenue
S-Group Revenue
Total Revenue
Total Marketsize
Total MarketAAGR
Our AAGR
Beat Market?
Incremental Revenue
75
7
81.25 82
325 326.4844
2%
2%
ie)
0
75
7
82
328.052
2%
3%
1
1
76
7
83
76
8
84
329.7069 331.4532
2%
4%
1
2
2%
5%
77
8
86
333.2954
2%
6%
4.
4
1.5
65%
9%
2.275
1.63
13.70392
1.285732
26.06162
35%
5%
1.225
1.35
10.70572
1.266572
25.41926
300
26%
35.2
23%
25%
2.5%
>>>
1.75
68%
9%
2.3625
1.71
14.35343
1.303081
26.47153
33%
5%
1.1375
1.34
10.50501
1.270963
25.48651
rP>rP>
300
26%
37.3
23%
25%
2.5%
70%
10%
2.45
1.79
15.00925
1.323576
26.94213
30%
4%
1.05
1.31
10.24188
1.274325
25.52531
>>>
300
27%
39.4
23%
26%
2.5%
2.25
73%
10%
2.5375
1.88
15.67059
1.347106
27.47118
28%
4%
0.9625
1.28
9.924146
1.276265
25.52928
>>>
300
27%
AL7
23%
26%
2.5%
2.5 2.75 3 3.25 3.5
75% 78% 80% 83% 85%
11% 11% 11% 12% 12%
2.625 2.7125 2.8 2.8875 2.975
1.96 2.04 2.13 2.21 2.29
16.33677 17.00717 17.68128 18.35862 19.03879
1.373559 1.402822 1.434786 1.469341 1.506382
28.05644 28.69572 29.38683 30.12765 30.91609
25% 23% 20% 18% 15%
3% 3% 3% 2% 2%
0.875 0.7875 0.7 0.6125 0.525
1.24 1.19 1.14 1.09 1.03
9.558627 9.151299 8.707387 8.231463 7.72753
1.276464 1.274667 1.270675 1.264337 1.255541
25.49333 25.4135 25.28673 25.11082 24.88421
300 300 300 300 300
28% 29% 29% 30% 31%
44.1 46.6 49.3 52.0 54.9
23% 23% 23% 23% 22%
25% 25% 25% 25% 25%
2.5% 2.5% 2.5% 2.5% 2.5%
A A A A A
A A A A A
A A A A A
3.75
88%
12%
3.0625
2.38
19.72144
1.545805
31.75013
13%
2%
0.4375
0.97
7.199089
1.244211
24.60594
>>>
300
32%
58.0
22%
25%
2.5%
78
9
87
335.2378
2%
7%
4.
6
79
10
89
337.2849
81
10
91
339.4415
3%
9%
a:
10
82
11
93
341.7121
3%
10%
1
12
84
41
95
344.1016
3%
10%
1
14
86
12
98
346.6148
3%
11%
f
17
88
12
101
349.2567
3%
11%
al
19
90
13
103
352.0319
3%
11%
1
22
93
14
106
354.9455
3%
11%
1
25
95
14
110
358.0022
3%
12%
1
28
90%
13%
3.15
2.47
20.40626
1.587507
32.62781
10%
1%
0.35
0.90
6.649203
1.230297
24.27553
300
33%
61.2
22%
24%
2.5%
>>>
4.25
93%
13%
3.2375
2.55
21.09298
1.63139
33.5472
7%
1%
0.2625
0.83
6.080553
1.213777
rP>rP>
23.8929
300
34%
64.6
22%
24%
2.5%
45
95%
13%
3.325
2.64
21.78136
1.67736
34.50646
5%
1%
0.175
0.76
5.495483
1.194645
23.45833
>>>
300
35%
68.1
22%
23%
2.5%
4.75
98%
14%
3.4125
2.72
22.47119
1.725323
35.50381
2%
0%
0.0875
0.69
4.896048
1.172916
22.97235
>>>
300
36%
71.8
22%
23%
2.5%
100%
14%
3.5
2.81
23.16229
1.77519
36.53752
0.61
4.284042
1.148617
22.43574
bP>P>
300
37%
75.6
21%
22%
2.5%
5.25
98%
14%
3.4125
2.90
23.6795
1.826876
37.60593
3%
0%
0.0875
0.54
3.836037
1.121787
21.84945
300
38%
79.6
21%
22%
-2.5%
5.5
95%
13%
3.325
2.96
24.04456
1.880296
38.68557
5%
1%
0.175
0.48
3.531532
1.092473
21.23649
annmD>
300
39%
83.8
21%
21%
-2.5%
5.75
93%
13%
3.2375
3.01
24.27649
1.934278
39.75686
8%
1%
0.2625
0.44
3.352591
1.061824
ano>
20.6161
300
40%
88.1
21%
21%
-2.5%
90%
13%
3.15
3.03
24.39193
1.987843
40.80358
10%
1%
0.35
0.42
3.283517
1.030805
20.00437
300
41%
92.7
21%
20%
-2.5%
6.25
88%
12%
3.0625
3.05
24.40544
2.040179
41.81239
13%
2%
0.4375
0.41
3.310577
1.000219
19.41459
annmD>
300
42%
97.4
20%
19%
-2.5%
98
15
113
361.2068
4%
12%
4.
31
101
15
116
364.564
4%
12%
1.
35
104
16
119
368.0782
4%
12%
af
38
107
16
123
371.7537
4%
12%
1
42
110
17
127
375.5947
4%
12%
1
45
113
17
130
379.6051
4%
11%
1
49
116
18
134
383.7883
4%
11%
al
53
119
18
137
388.1475
5%
11%
1
56
122
19
141
392.6855
5%
10%
1
60
125
19
144
397.4045
5%
10%
1
63
6.5
85%
12%
2.975
3.05
24.32976
2.09062
42.77245
15%
2%
0.525
0.41
3.421755
0.97073
18.85769
300
43%
102.3
20%
19%
-2.5%
anmD>
6.75
83%
12%
2.8875
3.04
24.17604
2.138623
43.67505
18%
2%
0.6125
0.43
3.606536
0.942884
18.34252
300
44%
107.4
20%
18%
-2.5%
80%
11%
28
3.02
23.95404
2.183752
44.5133
20%
3%
0.7
0.45
3.855719
0.917126
17.87621
300
45%
112.7
20%
18%
-2.5%
7.25
78%
11%
2.7125
2.99
23.67228
2.225665
45.28189
23%
3%
0.7875
0.48
4.161254
0.893811
17.46437
annmD>
300
45%
118.1
19%
17%
-2.5%
7.5
75%
11%
2.625
2.96
23.33825
2.264095
45.97683
25%
4%
0.875
0.52
4.516097
0.873218
17.1113
300
46%
123.8
19%
17%
-2.5%
7.75
73%
10%
2.5375
2.92
22.95847
2.298842
46.59527
28%
4%
0.9625
0.56
4.914085
0.855565
16.82025
300
47%
129.6
19%
17%
-2.5%
70%
10%
2.45
2.87
22.53866
2.329764
47.13532
30%
4%
1.05
0.61
5.349824
0.841013
annmD>
16.5935
300
47%
135.6
19%
17%
-2.5%
8.25
68%
9%
2.3625
2.82
22.08382
2.356766
47.59588
33%
5%
1.1375
0.67
5.818596
0.829675
16.43255
ano>
300
48%
141.8
18%
16%
-2.5%
8.5
65%
9%
2.275
2.76
21.59835
2.379794
47.97657
35%
5%
1.225
0.73
6.316272
0.821628
16.33825
300
48%
148.1
18%
16%
-2.5%
8.75
63%
9%
2.1875
2.70
21.08605
2.398828
48.27753
38%
5%
1.3125
0.79
6.839238
0.816912
16.31087
annmD>
300
48%
154.6
18%
16%
-2.5%
128
19
148
402.3063
5%
9%
4.
66
131
20
151
407.3921
5%
134
20
154
412.6625
5%
8%
ac
72
136
21
156
418.1173
5%
7%
1
75
138
21
159
423.7557
5%
7%
1
78
140
22
162
429.576
5%
6%
1
80
141
22
164
435.5757
6%
6%
a
83
143
23
166
441.7516
6%
5%
0
85
144
24
168
448.0994
6%
5%
0
87
145
25
170
454.6139
6%
5%
ie)
89
60%
8%
21
2.64
20.5503
2.413877
48.49941
40%
6%
1.4
0.85
7.384333
0.815544
16.35023
300
48%
161.3
17%
16%
-2.5%
anmD>
9.25
58%
8%
2.0125
2.57
19.99401
2.424971
48.64323
43%
6%
1.4875
0.92
7.948791
0.817512
16.45576
300
49%
168.1
17%
16%
-2.5%
9.5
55%
8%
1.925
2.50
19.41976
2.432161
48.71032
45%
6%
1.575
0.99
8.530193
0.822788
16.62657
300
49%
175.1
17%
17%
-2.5%
9.75
53%
7%
1.8375
2.43
18.82979
2.435516
48.70227
48%
7%
1.6625
1.07
9.126418
0.831329
16.86152
annmD>
300
49%
182.2
16%
17%
-2.5%
10
50%
7%
1.75
2.35
18.22607
2.435114
48.62088
50%
7%
1.75
1.14
9.735616
0.843076
17.15924
300
49%
189.4
16%
17%
-2.5%
10.25
48%
7%
1.6625
2.28
17.61031
2.431044
48.4681
53%
7%
1.8375
1.22
10.35616
0.857962
17.51823
300
48%
196.8
16%
18%
-2.5%
10.5
45%
6%
1.575
2.20
16.98402
2.423405
48.24598
55%
8%
1.925
1.29
10.98664
0.875912
17.93684
annmD>
300
48%
204.3
15%
18%
-2.5%
10.75
43%
6%
1.4875
2.12
16.34852
2.412299
47.95668
58%
8%
2.0125
1.37
11.62581
0.896842
18.41333
ano>
300
48%
211.8
15%
18%
-2.5%
40%
6%
1.4
2.04
15.70495
2.397834
47.60241
60%
8%
21
1.45
12.27259
0.920667
18.94589
300
48%
219.4
14%
19%
-2.5%
11.25
38%
5%
1.3125
1.96
15.05433
2.380121
47.18541
63%
9%
2.1875
1.53
12.92601
0.947295
19.53267
annmD>
300
47%
227.1
14%
20%
-2.5%
145
26
172
461.2891
6%
4%
0
91
146
28
174
468.1179
175
475.0923
6%
4%
0
94
31
177
482.2034
6%
4%
0
96
146
33
178
489.4414
6%
3%
ie)
97
145
34
180
496.7955
6%
3%
0
99
145
37
181
504.2541
6%
3%
0
100
144
39
183
511.805
6%
3%
ie)
102
143
42
184
519.4352
6%
3%
0
103
142
44
186
527.1309
6%
3%
0
105
11.5
35%
5%
1.225
1.88
14.39754
2.359271
46.70793
65%
9%
2.275
1.62
13.58526
0.976634
20.17179
300
47%
234.9
14%
20%
-2.5%
anmD>
11.75
33%
5%
1.1375
1.80
13.73535
2.335397
46.17223
68%
9%
2.3625
1.70
14.2496
1.008589
20.86136
300
46%
242.7
13%
21%
-2.5%
30%
4%
1.05
1.72
13.06843
2.308611
45.58054
70%
10%
2.45
1.78
14.9184
1.043068
21.59949
300
46%
250.5
13%
22%
-2.5%
12.25
28%
4%
0.9625
1.63
12.39738
2.279027
44.93506
73%
10%
2.5375
1.86
15.5911
1.079974
22.38432
annmD>
300
45%
258.3
12%
22%
-2.5%
12.5
25%
3%
0.875
1.55
11.7227
2.246753
44.23798
75%
11%
2.625
1.95
16.26722
1.119216
23.21399
300
44%
266.1
12%
23%
-2.5%
12.75
23%
3%
0.7875
1.47
11.04487
2.211899
43.49142
78%
11%
2.7125
2.03
16.94631
1.160699
24.08669
300
43%
273.9
12%
24%
-2.5%
13
20%
3%
0.7
1.38
10.36426
2.174571
42.69746
80%
11%
2.8
2.12
17.62802
1.204335
25.00064
annmD>
300
43%
281.6
11%
25%
-2.5%
13.25
18%
2%
0.6125
1.30
9.681226
2.134873
41.85812
83%
12%
2.8875
2.20
18.31202
1.250032
25.95412
ano>
300
42%
289.3
11%
26%
-2.5%
13.5
15%
2%
0.525
1.21
8.996072
2.092906
40.97536
85%
12%
2.975
2.29
18.99802
1.297706
26.94541
300
41%
296.9
11%
27%
-2.5%
13.75
13%
2%
0.4375
1.12
8.309063
2.048768
40.0511
88%
12%
3.0625
2.37
19.68577
1.347271
27.97289
annmD>
300
40%
304.5
10%
28%
-2.5%
140
47
188
534.878
6%
3%
0
106
139
51
189
542.662
137
54
191
550.4677
6%
4%
0
110
135
58
193
558.2802
6%
4%
0)
111
133
62
194
566.0841
6%
4%
ie)
113
130
66
196
573.8643
5%
4%
0
115
128
70
198
581.6056
5%
4%
0
117
126
75
201
589.2932
5%
203
596.9127
5%
5%
0
122
120
85
205
604.4501
5%
5%
ie)
124
14
10%
1%
0.35
1.04
7.62043
2.002555
39.08718
90%
13%
3.15
2.46
20.37505
1.398645
29.03497
300
39%
311.9
10%
29%
-2.5%
anmD>
14.25
7%
1%
0.2625
0.95
6.930377
1.954359
38.08538
93%
13%
3.2375
2.55
21.06566
1.451749
30.1301
300
38%
319.2
9%
30%
-2.5%
14.5
5%
1%
0.175
0.87
6.23908
1.904269
37.04741
95%
13%
3.325
2.63
21.75746
1.506505
31.25681
300
37%
326.4
9%
31%
-2.5%
14.75
2%
0%
0.0875
0.78
5.546695
1.85237
35.97492
98%
14%
3.4125
2.72
22.45027
1.56284
32.41365
annmD>
300
36%
333.5
9%
32%
-2.5%
15
0.69
4.853358
1.798746
34.86951
100%
14%
3.5
2.81
23.14399
1.620682
33.59925
300
35%
340.5
8%
34%
-2.5%
15.25
0.61
4.246688
1.743476
33.73271
100%
14%
3.5
2.89
23.75099
1.679962
34.81229
300
34%
347.3
8%
35%
-2.5%
0.53
3.715852
1.686635
32.57691
100%
14%
3.5
2.97
24.28212
1.740614
36.04054
annmD>
300
33%
353.9
8%
36%
-2.5%
0.46
3.251371
1.628845
31.41254
100%
14%
3.5
3.04
24.74685
1.802027
37.27378
ano>
300
31%
360.3
7%
37%
-2.5%
0.41
2.844949
1.570627
30.24834
100%
14%
3.5
3.09
25.1535
1.863689
38.50345
300
30%
366.6
7%
39%
-2.5%
16.25
0.36
2.489331
1.512417
29.09154
100%
14%
3.5
3.14
25.50931
1.925172
39.72246
annmD>
300
29%
372.7
7%
40%
-2.5%
208
611.892
5%
5%
0
127
114
96
210
619.2257
5%
5%
at
129
111
102
213
626.4392
5%
5%
at
132
108
108
216
633.5213
5%
5%
1
135
105
114
219
640.4618
4%
5%
1
138
101
121
222
647.2514
4%
6%
1
141
98
128
225
653.8817
4%
6%
al
144
94
134
229
660.3453
4%
6%
1
147
91
141
232
666.6358
4%
6%
1
151
87
148
235
672.7478
4%
6%
1
154
0.31
2.178164
1.454577
27.94813
100%
14%
3.5
3.19
25.82065
1.986123
40.925
300
28%
378.7
6%
41%
-2.5%
anmD>
0.27
1.905894
1.397406
26.82299
100%
14%
3.5
3.23
26.09306
2.04625
42.10634
300
27%
384.4
6%
42%
-2.5%
0.24
1.667657
1.34115
25.72008
100%
14%
3.5
3.26
26.33143
2.105317
43.26265
300
26%
390.0
6%
43%
-2.5%
17.25
0.21
1.4592
1.286004
24.64253
100%
14%
3.5
3.29
26.54
2.163133
44.39095
annmD>
300
25%
395.3
6%
44%
-2.5%
0.18
1.2768
1.232127
23.59281
100%
14%
3.5
3.32
26.7225
2.219547
45.4889
300
24%
400.5
5%
45%
-2.5%
0.16
1.1172
1.17964
22.57277
100%
14%
3.5
3.34
26.88219
2.274445
46.55477
300
23%
405.5
5%
47%
-2.5%
18
0.14
0.97755
1.128638
21.58378
100%
14%
3.5
3.36
27.02192
2.327738
annmD>
47.5873
300
22%
410.3
5%
48%
-2.5%
18.25
0.12
0.855356
1.079189
20.62678
100%
14%
3.5
3.38
27.14418
2.379365
48.58568
ano>
300
21%
414.9
4%
49%
-2.5%
0.11
0.748437
1.031339
19.70236
100%
14%
3.5
3.39
27.25115
2.429284
49.54942
300
20%
419.3
4%
50%
-2.5%
0.09
0.654882
0.985118
18.8108
100%
14%
3.5
3.41
27.34476
2.477471
50.47834
annmD>
300
19%
423.5
4%
50%
-2.5%
84
155
239
678.6769
4%
6%
4.
158
80
162
242
684.4197
3%
7
169
246
689.9736
3%
6%
a:
165
74
175
249
695.337
3%
6%
1
168
71
182
253
700.5092
3%
6%
4
172
68
189
256
705.49
3%
6%
1
175
65
195
260
710.2804
3%
5%
al
179
62
202
263
714.8817
3%
5%
1
59
208
267
719.2959
2%
5%
1
186
56
214
270
723.5258
2%
5%
1
189
19
0.08
0.573022
0.94054
17.95212
100%
14%
3.5
3.42
27.42667
2.523917
51.37252
300
18%
427.6
4%
51%
-2.5%
anmD>
19.25
0.07
0.501394
0.897606
17.12614
100%
14%
3.5
3.43
27.49833
2.568626
52.23223
300
17%
431.4
4%
52%
-2.5%
0.06
0.43872
0.856307
16.33251
100%
14%
3.5
3.44
27.56104
2.611611
53.05791
300
16%
435.1
3%
53%
-2.5%
0.05
0.38388
0.816625
15.57072
100%
14%
3.5
3.45
27.61591
2.652895
53.85014
annmD>
300
16%
438.7
3%
54%
-2.5%
20
0.05
0.335895
0.778536
14.84017
100%
14%
3.5
3.45
27.66392
2.692507
54.60962
300
15%
442.0
3%
55%
-2.5%
54
220
274
727.5744
2%
5%
1
192
51
225
277
731.4453
2%
49
231
280
735.1425
2%
5%
li
199
47
236
283
738.6703
2%
4%
1
202
45
241
286
742.0332
2%
4%
4
205
Rough Targets
0-100 20%
100-200 10%
200-300 5%
300-500 2.50%
500+ 0%
Equation AAGR=(-20%/400)*Size+25%
Size AAGR
25 23.7500%
50 22.5000%
75 21.2500% Growth Rate Transfer F
100 20.0000% 25.0000%
125 18.7500%
150 17.5000%
175 16.2500%
200 15.0000%
225 13.7500%
250 12.5000%
275 11.2500%
300 10.0000% 15.0000%
325 8.7500%
350 7.5000%
375 6.2500%
400 5.0000%
425 3.7500%
450 2.5000%
475 1.2500%
500 0.0000%
525 0.0000%
550 0.0000%
575 0.0000% 0.0000%
600 0.0000% 25 50 75 10 12 15 17 20 22 25 27 30 32 35
625 0.0000% 05050505050
650 0.0000%
675 0.0000% Market Size
20.0000%
AAGR
10.0000%
5.0000%
‘unction
Foresight
Affection Rate
R&D Timeframe
Policy
AIR
Qtrs>Market V
Time Horizon
ONNWR
Affection Rate
Speed
5.0%
7.5%
10.0%
7,676
88%
Accumulated
Incremental
Revenue
6,043
6,136
6,362
6,565
6,641
6,469
6,387
Accumulated
Incremental
Revenue
6,136
6,340
6,523
Quarterly Revenue
years
per year
years 350
300
250
$in millions
PN
ao
a0
1
Quarters
—¢— L-Group Revenue —i— S-Group Revenu:
Affection by Market
Quarters
—+— Affection for L-Group Market —i— Affectio
Improvement %
-2%
0%
4%
7%
8%
5%
4%
Improvement %
0%
3%
6%
12.5% 6,677 9%
15.0% 6,799 11%
Accumulated
Incremental
R&D Timeframe Revenue Improvement %
5 4,861 -21%
4 5,482 -11%
3 6,136 0%
2 6,810 11%
1 7,503 22%
Growth Rate Comparison
AAGR
2
&
THT TTT TPT TTT TTT O% ETT TTT TTT TTT TTT TTT TTT
Quarters
e ~~ Total Revenue —?— Total MarketAAGR 1—l— Our AAGR
Market Share by Market
60%
50%
40%
30%
Share
20%
10%
, OY TTT TTT TTT TTT TTT TTT TTT TTT TTT TT TT TTT
Quarters
in for S-Group Market —+¢— L-Group Marketshare —i— S-Group Marketshare
Quarterly Market Sizes
500
450
400
350
300
250
200
150
100
50
ETT
DDO OOD OLD AD A DHD9 0 VAD 9D 9 49.9 OO 49,50
YA TN HGP UGE V Gh “NADI Mah SOM OAM Soh
Years
—¢#— L-Group Marketsize —m— S-Group Marketsize
Quarterly Revenue
450 100% +
400 90% | ———_
350 50%
% 4
300 10%
60% 5
ao
zg 50% +4
= & 40% 5
£ 30% |
2 20% ———_
10% +—————_
OT ttt 0% TTT
90.50 90 9 0 00,9 0 90% wo oo «
SP ah PP PLP OP 428 Pwr yr WP at
Years
—颗 L-Group Revenue —i- S-Group Revenue Total Revenue —¢— Affection for L
Market-share by Market iq
y
40% 20% -
35% a
30% a 15% +———_—
25% 5
20% 10% -
o a
3 159 @
6 15% =z
5% 5
10%
5%
0% 5
0% q See
9 © 9 2 % © 9 © 0,9 © 20 o wo ‘ Vv
oO MAP Pa we OM APH ON oy” s
5% +
Years
—¢— L-Group Marketshare —li— S-Group Marketshare +
Figure 7. Results from Policy 4 - Don't favor either segment. Ke
Affection by Market
Years
-Group Market —— Affection for S-Group Market
3rowth Rate Comparison
Years
Total MarketAAGR —i— Our AAGR
3ep it 50/50.
—
a
a
OST
Quarterly Revenue
TH UVPMS OAS AGH ISP YHA POS
Years
—¢— L-Group Revenue —m&- S-Group Revenue Total Revenue
—?— Affection fc
Share
60%
50%
40%
30%
20%
10%
0%
Market Share by Market
AAGR
14%
12% 4
10% 4
8% +
6% +
4% 5
2% +
a
SG AHA 0505 PY ING OG NR 0 OO OO HH CORN O89 SPR LHS GAO NUK 0540 OF}
SSSA
Years
[—#= L-Group Marketshare —s— S-Group Marketshare |
0%
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OX SUE ONE Ee OK
SSddNnas
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Figure 9. Results from investing using Future Market Size with i
Affection by Market
or L-Group Market —i— Affection for S-Group Market
Growth Rate Comparison
— Total MarketAAGR —i— Our AAGR: ]
a 9 year time horizon.
