358  Analyzing the Results
model is technically robust—for example, by checking that the balance sheet 
balances in each forecast year. Second, test whether results are consistent with 
industry economics. For instance, do key value drivers, such as return on in-
vested capital (ROIC), change in a way that is consistent with the intensity of 
competition? Next, compare the model’s output with the current share price 
and trading multiples. Can differences be explained by economics, or is an 
error possible? We address each of these tasks next.
Is the Model Technically Robust?
Ensure that all checks and balances in your model are in place. Your model 
should reflect the following fundamental equilibrium relationships:
• In the unadjusted financial statements, the balance sheet should balance 
every year, both historically and in forecast years. Check that net income 
flows correctly through shareholders’ equity.
• In the rearranged financial statements, check that the sum of invested 
capital plus nonoperating assets equals the cumulative sources of fi-
nancing. Is net operating profit after taxes (NOPAT) identical when cal-
culated top down from sales and bottom up from net income? Does net 
income correctly link to retained earnings, dividends, and share issues 
or repurchases in changes to equity?
• Does the change in excess cash and debt line up with the cash flow 
statement?
A good model will automatically compute each check as part of the model. 
A technical change to the model that breaks a check can then be clearly noted. 
To stress-test the model, change a few key inputs in an extreme manner. For 
instance, if gross margin is increased to 99 percent or lowered to 1 percent, 
does the balance sheet still balance?
As a final consistency check, adjust the dividend payout ratio. Since pay-
out will change funding requirements, the company’s capital structure will 
change. Because NOPAT, invested capital, and free cash flow are independent 
of capital structure, these values should not change with variations in the pay-
out ratio. If they do, the model has a mechanical flaw.
Is the Model Economically Consistent?
The next step is to check that your results reflect appropriate value driver eco-
nomics. If the projected returns on invested capital are above the weighted 
average cost of capital (WACC), the value of operations should be above the 
book value of invested capital. Moreover, if revenue growth is high, the value 
of operations should be considerably above book value. If not, a computational 

Validating the Model  359
error has probably occurred. Compare your valuation results with a back-of-
the-envelope value estimate based on the key value driver formula, using long-
term average revenue growth and return on invested capital as key inputs.
Make sure that patterns of key financial and operating ratios are consistent 
with economic logic:
• Are the patterns intended? For example, does invested-capital turnover in-
crease over time for sound economic reasons (economies of scale) or sim-
ply because you modeled future capital expenditures as a fixed percentage 
of revenues? Are future cash tax rates changing dramatically because you 
forecast deferred-tax assets as a percentage of revenues or operating profit?
• Are the patterns reasonable? Avoid large step changes in key assumptions 
from one year to the next, because these will distort key ratios and could 
lead to false interpretations. For example, a large single-year improve-
ment in capital efficiency could make capital expenditures in that year 
negative (the sale of fixed equipment for cash at book value is unlikely), 
leading to an unrealistically high cash flow.
• Are the patterns consistent with industry dynamics? In certain cases, rea-
sonable changes in key inputs can lead to unintended consequences. 
Exhibit 17.1 presents price and cost data for a hypothetical company 
in a competitive industry. To keep pace with inflation, you decide to 
forecast the company’s prices to increase by 3 percent per year. Because 
of cost efficiencies, operating costs are expected to drop by 2 percent 
per year. In isolation, each rate appears innocuous. Computing ROIC 
reveals a significant trend. Between year 1 and year 10, ROIC grows 
from 9.3 to 39.2 percent—unlikely in a competitive industry. Since cost 
advantages are difficult to protect, competitors are likely to mimic pro-
duction and lower prices to capture share. A good model will highlight 
this economic inconsistency.
EXHIBIT 17.1  ROIC Impact of Small Changes: Sample Price and Cost Trends
$
Year 1
Year 2
Year 3
Year 4
Year 5
…
Year 10
Growth, %
Price
50.0
51.5
53.0
54.6
56.3
…
65.2
3.0
Number of units
100.0
103.0
106.1
109.3
112.6
…
130.5
Revenue
5,000.0
5,304.5
5,627.5
5,970.3
6,333.9
…
8,512.2
Cost per unit
43.0
42.1
41.3
40.5
39.7
…
35.9
–2.0
Number of units
100.0
103.0
106.1
109.3
112.6
…
130.5
Cost
4,300.0
4,340.4
4,381.2
4,422.4
4,464.0
…
4,677.8
Operating profit
700.0
964.1
1,246.3
1,547.9
1,869.9
…
3,834.4
Invested capital
7,500.0
7,725.0
7,956.8
8,195.5
8,441.3
…
9,785.8
Pretax ROIC, %
9.3
12.5
15.7
18.9
22.2
…
39.2