Financial models are widely used in a variety of business applications from financial reporting to capital budgeting to valuing and structuring mergers and acquisitions. The purpose of this chapter is to discuss the basics of applying financial modeling methods to firm valuation and to assist the reader in understanding the power (and limitations) of models in analyzing real world situations. The model discussed in this chapter is relatively simple consisting of four Microsoft Excel worksheets and is applied to the valuation of a single firm. This chapter discusses commonly used model data requirements, the impact of the 2017 Tax Cuts and Jobs Act, accounting linkages within models, suggestions on how models should be managed, using models in a low interest rate environment, model balancing mechanisms, and provides a detailed illustration of how to calculate a firm’s cost of capital.
Financial models; M&A valuation; Merger and acquisition valuation; Merger valuation; Acquisition valuation; Discount rates; Cost of capital; Cost of equity; Normalized cash flow; Cash flow projections; Synergy; Sources of value; Destroyers of value; Restructuring; Pro forma accounting; GAAP; Financial statements; Valuation; Analyzing financial statements; Betas; Credit ratios; Income statement; Balance sheet; Cash flow statement; International accounting standards; Financial modeling; M&A modeling; M&A models; Building financial models; Model balancing mechanisms; Terminal values; WAAC; CAPM
There are two kinds of forecasters: the ones who don’t know and the ones who don’t know they don’t know.
John Kenneth Galbraith
Valuing the target’s cash flow typically involves identifying the key determinants of cash flow, projecting pro forma financial statements, and converting projected cash flows to a present value. This provides a baseline standalone value for the target and theoretically represents the minimum price a buyer can expect to pay for the target. Estimates of synergy plus the minimum price denotes the maximum value the acquirer should pay for the target. The actual purchase price paid falls within this range and is determined largely by the relative negotiating leverage of buyer and seller.
What happens when something occurs that could reduce significantly the baseline standalone value of the target firm? M&A agreements of purchase and sale try to account for the unexpected by including so-called material adverse change clauses. If triggered, such clauses allow the buyer to renegotiate the contract or to walk away from the deal. Adverse changes could include events having a negative impact on the target’s operating and financial condition or the ability of the seller to close the deal. What follows is a discussion of a recent example of how such a clause was used to compensate a buyer for the perceived reduction in the value of the target firm due to events not revealed during due diligence.
After more than a decade of mismanagement, Yahoo Inc. announced that it had reached an agreement on July 25, 2016 to sell its core internet operating assets to wireless telecom giant Verizon Inc. for $4.8 billion in cash. What remained of Yahoo was renamed Altaba, which owned $40 billion worth of assets in Chinese e-commerce firm Alibaba, another $9.6 billion in Yahoo Japan, and certain patents not included in the sale to Verizon.
Closing the deal was hampered by the discovery in November 2016 of several breaches or hacks of more than one billion Yahoo email users’ private accounts which had occurred in 2013 and 2014 and the potential reduction in the firm’s value resulting from these incidents. Further complicating the process, the SEC initiated an investigation of Yahoo’s failure to make public sooner these potentially material events in late December 2016.
Both firms were under considerable pressure to close the deal. The Yahoo board wanted to exit the firm’s internet assets so that it could focus on the eventual sale of its stake in Alibaba and Yahoo Japan. Verizon wanted to gain control of Yahoo internet operations so that it could implement its digital media strategy to compete against Facebook and Alphabet’s Google in digital advertising. What was not known at the end of 2016 is the extent of the potential damage to the value of Yahoo internet assets due to the data breaches.
Verizon’s executives and board weighed the relative cost of acquiring damaged Yahoo assets compared to the lost time in implementing its planned digital media strategy. The options were clear: walk away; wait to assess the extent of the damage and negotiate a price reduction; or close the deal and merge Yahoo into AOL (which Verizon acquired in 2015) and begin to build their digital media businesses. How could they measure the dollar cost of each option?
Walking away from the purchase of the Yahoo assets would mean that Verizon would have to either find another firm to acquire similar assets (and there weren’t any) or incur the cost of building similar assets. Closing immediately ran the risk of acquiring assets which could come with substantial liabilities from consumer and SEC lawsuits and a substantial loss in Yahoo’s user base. Postponing closing until they had greater clarity over the issues would mean that they would lose valuable time in implementing their digital media strategy. Verizon could calculate the net present value of each option by varying the magnitude and timing of expected cash flows and then choose the option with the highest NPV.
Verizon considered the data breach disclosed at the end of 2016 as triggering the material adverse change clause in the contract and tried to change the terms of the deal. After conducting additional due diligence to size potential future liabilities stemming from the hack, Verizon demanded a reduction in the purchase price of $925 million. Yahoo countered with data showing that the impact of the hacks on usage of its services appeared to be small.
The deal finally closed on June 13, 2017 with Verizon paying $350 million less and the two firms agreeing to split any future costs related to the data breaches. Verizon gave up its right to sue over any allegations that Yahoo had covered up the data breaches. Altaba would retain any liability for the SEC investigation and any related shareholder lawsuits.
The purpose of this chapter is to discuss the basics of applying financial modeling methods to firm valuation and to assist the reader in understanding the power (and limitations) of models in analyzing real world situations. Building upon the basics of financial modeling outlined in this chapter, Chapter 14 will discuss the important role such models play in valuing and structuring mergers and acquisitions using a substantially more complex, interactive model.
This chapter begins with an overview of what financial modeling entails, why it is important, the data requirements of such models, and common financial model linkages. The chapter then illustrates a simplified methodology for using a financial model to value a firm and discusses where to find data required by the model. The case study at the end of the chapter entitled “Life Technologies Undertakes a Strategic Review” illustrates how financial models can be used to estimate firm value, identify the key determinants of firm value, and to simulate alternative outcomes to facilitate management decision making.
The spreadsheets and formulas for the model described in this chapter are available in a Microsoft Excel file entitled “Target Firm Valuation Model” on the companion site to this book https://www.elsevier.com/books-and-journals/book-companion/9780128150757). A review of this chapter is available in the file folder entitled “Student Study Guide” on the companion accompanying this book.
Financial modeling refers to the creation of a mathematical representation or model of the financial and operational characteristics of a business. Applications involving financial modeling include business valuation, management decision making, capital budgeting, financial statement analysis, and determining the firm’s cost of capital. Such models are at best a simplistic illustration of how the firm actually creates value for its shareholders. Their real value comes from forcing the model builder to think about the important relationships among the firm’s financial statements and to focus on the key determinants of value creation and the assumptions underlying forecasts. Often referred to as “simulation,” financial models provide a useful means of assessing alternative options and associated risks and of identifying how firm value is affected by different economic events. To estimate firm value, financial modeling requires that the analyst forecast cash flow. How this may be done and the accompanying challenges are addressed next.
The quality of a model’s output is dependent on the reliability of data used to build the model and the credibility of the assumptions underlying cash flow projections. Consequently, analysts must understand on what basis numbers are collected and reported. That is, are they based on GAAP or pro forma financial statements?
US public companies prepare their financial statements in accordance with generally accepted accounting principles (GAAP). GAAP financial statements are those prepared in agreement with guidelines established by the Financial Accounting Standards Board (FASB). GAAP is a rules-based system, giving explicit instructions for every situation that the FASB has anticipated. In contrast, international accounting standards (IAS) are a principles-based system, with more generalized standards. GAAP and IAS currently exhibit significant differences. When and the extent to which GAAP and IAS systems converge are open questions. While the way financial data is recorded often differs by country, GAAP-based reporting is used throughout this book.
In 2017, the US Securities and Exchange Commission announced that it was investigating allowing public companies to supplement their GAAP financial statements with information prepared according to international accounting standards. The supplemental information is used by US companies seeking to purchase foreign firms to see what the firms’ consolidated financial statements might look like if they two firms were to merge.
A firm’s financial statements typically consist of an income statement, balance sheet, and cash flow statement. The income statement measures a firm’s financial performance over a specific time period: month, quarter, or year. The statement displays revenue and expenses generated from both operating and non-operating activities. Operating revenues and expenses are derived from the firm’s normal operations; non-operating revenues and expenses result from activities such as the sale of assets or employee termination expenses associated with a facility closure. Such events are not a regular part of a firm’s normal operations.
The balance sheet provides data on what a firm owns (i.e., its assets), what it owes (i.e., its liabilities), and its value to its shareholders (i.e., shareholders’ equity) at a moment in time. Assets are resources that generate future cash flows for shareholders. Liabilities are obligations to parties outside of the firm. Shareholders’ equity is the value of the business to its owners after all obligations to external parties have been satisfied.
A cash flow statement summarizes the firm’s cash inflows and outflows from operating, investing, and financing activities. Cash flows from operations arise from the firm’s normal operations such as revenues and actual cash expenses after taxes. Cash from investing activities arises from the acquisition or disposition of current or fixed assets. Finally, cash inflows from financing activities include the issuance of additional shares or new borrowing; cash outflows include share repurchases, principal repayments, and dividend payouts.
Pro forma financial statements (also referred to as adjusted financial statements) present financial data in a way that may describe more accurately a firm’s current or projected performance. Because there are no accepted standards, pro forma statements may deviate substantially from GAAP statements. In 2015, 5.7% of US Standard & Poor’s companies reported their financial statements using GAAP accounting standards exclusively.1 Most public firms supplement their GAAP statements with pro forma statements which are “adjusted” to reflect factors that firms will argue more accurately represent their business. Pro forma statements are used to show what an acquirer’s and target’s combined financial performance would look like if they were merged.
The US Security and Exchange Commission’s Regulation G (introduced in 2003) requires public firms disclosing non-GAAP measures to the public to also present comparable GAAP financial measures and to reconcile the GAAP and non-GAAP metrics. In 2010, the SEC in an effort to clarify the implementation of Regulation G issued new Compliance and Disclosure Interpretations (C&DIs) giving firms more discretion in how they adjust for non-GAAP financial indicators, somewhat offsetting the rigor introduced by Regulation G. However, the net effect of Regulation G and the C&DIs has been to reduce the extent to which firms have manipulated reported earnings to beat analysts’ earnings projections.2
Although pro forma statements serve a useful purpose, such liberal accounting can easily hide a company’s poor performance. Exhibit 9.1 suggests some ways in which an analyst can tell if a firm is engaging in inappropriate accounting practices.
The failure to adequately review a firm’s financial statements can have disastrous results for acquiring firm shareholders. Firms may manipulate earnings upward prior to a bid in an effort to get a higher offer price. Earnings manipulation tends to occur more commonly with respect to overstating net sales rather than mishandling accruals, since the latter may be more easily detected during acquirer due diligence.3 Furthermore, earnings manipulation reflects on the target firm’s managerial competence and integrity, with substantial earnings management indicative of less competent and honest managers. 4
Valeant Pharmaceutical International Inc., a Canadian based company, found itself at the center of a firestorm generated by alleged accounting irregularities. In late 2016, the firm was accused of understating its normal operating expenses by burying a portion of such expenses among one-time acquisition related write-offs and inflating sales by “channel stuffing.”5 The firm publishes both a GAAP based EPS and proforma (adjusted) cash flow based EPS. The latter made its performance look much better than the standard method of calculating EPS.
US IPOs are not allowed to provide earnings projections at the time of listing but those in the United Kingdom are permitted to do so. Most large IPOs in the UK generally provide earnings forecasts in their prospectuses. Using data on UK IPOs, earnings manipulation has been found to be lower for large IPOs that provide earnings forecasts than for those that do not. The risk to firms providing earnings forecasts that are too optimistic is that they may lose public trust with investors. Furthermore, those that provide forecasts tend to outperform those that do not in the long-run. This suggests that earnings forecasts for modeling and valuing IPOs may contain useful information for analysts.6
A financial model creates a set of projections about the future of a business in terms of the businesses’ income statement, balance sheet, and cash flow statement. Each statement is linked in such a way that changing assumptions about one factor can result in changes in other financial statements. Let us examine these linkages in more detail.
The income statement, balance sheet and cash flow statements are interrelated (see Fig. 9.1). All items on the income statement from revenue through taxes affect the calculation of net income which measures how well the assets and liabilities listed on the balance sheet were used. Net income flows from the income statement to retained earnings (i.e., cumulative income or losses since the firm’s inception) on the balance sheet and also is shown as the first line of the cash flow statement. The cash flow statement shows cash from operating, investing, and financing activities. It describes the source of cash inflows and the uses for cash outflows and the amount of cash the firm reports on its balance sheet at the end of an accounting period. That is, the cash flow statement begins with net income from the income statement and concludes with the firm’s ending cash balance, which is also shown at the top of the asset side of the firm’s balance sheet.
Firms maintain minimum cash balances to meet short term working capital needs such as payroll. Cash from operating and investing activities above that required to maintain the firm’s desired minimum cash balance may be used to repay any outstanding debt. Consequently, the firm’s year ending debt balance is reduced by the amount of excess cash used to repay debt.
In building financial models, the previously described linkages among the financial statements introduce circular logic known as circular references in spreadsheet software programs. Circular references are a series of cell references in which the last cell reference refers to the first resulting in a closed loop. For example, increases in interest expense reduce net income, which decreases cash flow to repay borrowing resulting in higher debt outstanding and higher interest expense. Fig. 9.2 illustrates this circularity.
Such circular references could result in the financial model becoming unstable with Microsoft’s Excel software showing any of the following error messages: REF!, #Value, or Div/0!. To resolve circular references using Microsoft’s Excel, turn on the iteration command for Windows 7, 8, or 10 as follows:
An alternative means of resolving circular references is to use “toggle buttons” which indicate a state such as yes/no or on/off. “Toggle buttons” are used in the models accompanying this textbook on the income statement (interest income and expense rows) and debt repayment (revolving credit facility row) worksheets. Such buttons are triggered by switching the interest income/expense or revolving credit “toggle button” on and off and on (i.e., from 1 to 0 to 1 and may be expressed as 1 >> enter 0 >> enter 1). This often restores model stability just as turning a wireless modem on and off and on can restore an internet connection. “Toggle buttons” are displayed on the worksheets as follows:
The Tax Cuts and Jobs Act of 2017 capped net interest expense deductions at 30% of earnings before interest, taxes, depreciation, and amortization (EBITDA) through 2022 and earnings before interest and taxes (EBIT) thereafter. Fig. 9.3 illustrates the decision rule that determines the extent to which net interest expense can be deducted for tax purposes based on EBIT.7 If net interest expense is less than or equal to 30% of EBIT, 100% of net interest expense is deductible; otherwise, only the amount of net interest expense equal to 30% of EBIT is deductible. EBT and i are earnings before taxes and net interest expense, respectively.
See Eq. (9.1) for the Excel formula for modeling this decision rule.
The modeling process used to value a firm consists of a series of steps. First, analyze the target firm’s historical statements to identify the primary determinants of cash flow. Second, project three-to-five years (or more) of annual pro forma financial statements. This period is called the planning period. Third, estimate the present value of the projected pro forma cash flows, including the terminal value. These steps are discussed in detail in the following sections.
Understanding how a firm made money historically is helpful in determining how it may do so in the future. Once the firm’s historical financial data has been collected,8 the analyst should look for relationships or correlation between line items on financial statements and the firm’s free cash flows. Variables exhibiting strong historical correlation with operating cash flows and in turn firm value often are referred to as value drivers. Value drivers are variables which exert the greatest impact on firm value. For nonfinancial firms, they generally include the rate of growth in sales, the cost of sales as a percent of sales, S, G, & A as a percent of sales, the WACC assumed during the annual cash flow growth period, and the WACC and sustainable cash flow growth rate assumed during the terminal period.9
Equal to the difference between sales and cost of sales as a percent of sales, gross margin per dollar of sales summarizes a firm’s ability to create value. A simple diagram plot of a firm’s gross margin over at least one full business cycle (usually 5–7 years) provides useful insight into how the firm was able to create value historically. An increase in the ratio over time indicates that the firm has been able to reduce its costs compared to sales, raise prices on items sold, or a combination. A declining ratio reflects deterioration in the firm’s ability to control costs, raise prices, or both. However, gross margin may show considerable variation from 1 year to the next. How we deal with this issue is addressed next.
To ensure historical relationships can be accurately defined, normalize the data by removing nonrecurring changes and questionable accounting practices in order to identify longer-term trends in the data. Such data often is easily recognized because it represents an outlier in the data series. Cash flow may be adjusted by adding back large increases in reserves10 or deducting large decreases in reserves from free cash flow to the firm. Similar adjustments can be made for significant nonrecurring gains on the sale of assets or losses due to nonrecurring expenses, such as those associated with the settlement of a lawsuit or warranty claim.
Common-size financial statements are used to uncover data irregularities. These statements may be constructed by calculating the percentage each line item of the income statement, balance sheet, and cash flow statement is of annual sales for each quarter or year for which historical data are available. Common-size statements are useful for comparing businesses of different sizes in the same industry at a specific moment. Called cross-sectional comparisons, such analyses may indicate that the ratio of capital spending to sales for the target firm is much less than for other firms in the industry. This discrepancy may simply reflect “catch-up” spending at the target’s competitors, or it may suggest the target is deferring necessary plant and equipment spending. To determine which is true, it is necessary to calculate common-size statements for the target firm and its primary competitors over a number of consecutive periods. Called a multiperiod comparison, these analyses help confirm whether the target simply has completed a large portion of capital spending that others in the industry are undertaking currently or is behind in making necessary expenditures.11
Financial ratio analysis is the calculation of performance ratios from data in a firm’s financial statements to identify the firm’s financial strengths and weaknesses. Such analysis helps identify potential problems requiring further examination during due diligence. Ratios allow the analyst to compare firms of different sizes. For example, assume we are comparing operating profits (EBIT) of two firms. EBIT for Firm A is $20 million and $6 million for Firm B. It is inappropriate to conclude the Firm A is better managed than Firm B. Firm A may have a larger dollar value of profits only because it is larger. The firms’ profitability should be compared in terms of their margins (i.e., the amount of profit per dollar of sales each firm can keep). If Firm A has sales of $100 million and Firm B has sales of $30 million, the two firms are equally profitable (when measured in this manner) with each earning 20% of each dollar of sales.
Because ratios adjust for firm size, they enable the analyst to compare a firm’s ratios with industry averages to discover if the company is out of line with competitors. A successful competitor’s performance ratios may be used if industry average data12 are not available. Once the historical data has been normalized or smoothed, we need to understand the primary factors that affected changes in gross margin historically. That is, what are the primary determinants of sales growth and profit margins?
A firm’s revenue growth and profitability are determined by a combination of industry specific and firm specific factors. A suggested approach to understanding the determinants of a firm’s revenue growth and profit margins is to evaluate the industry’s attractiveness in terms of the intensity of competition within the industry (and in turn potential profitability) and the firm’s competitive position within the industry.
A convenient means of evaluating industry attractiveness is to apply the Porter Five Forces Model described in Chapter 4. The Porter Model identifies a series of factors that collectively help determine the potential competitiveness and in turn profitability of an industry. Highly competitive industries tend to offer lower potential profitability than less competitive ones. These factors include: the threat of new entrants, bargaining power of suppliers, bargaining power of customers, threat of substitute products, and the degree of competitive rivalry within the industry. Bargaining power refers to the ability of a firm’s customers to influence the prices of the products and services it sells and suppliers to set the prices the firm pays for materials and services that it buys. This influence can extend well beyond price and include transaction payment and delivery terms. Table 9.1 summarizes the factors that determine the significance of each “force” and its implication for potential profitability. These forces can be augmented to include other considerations such as the role of regulation, unions, and government as needed.
Table 9.1
Table 9.2 generalizes the results of the Porter Five Forces Model by summarizing the characteristics of high profit versus low profit industries. In general, highly profitable industries are subject to less competition than lower profit industries. Highly competitive industries tend to experience so called normal profits. That is, a level of profits that compensates firms for the risk they have assumed. Less competitive industries often result in firms earning abnormal profits (i.e., those in excess of the risk assumed). An example of a high profit industry would be soft drinks and a low profit industry would be airlines. The terms weak and strong refer to the bargaining power of suppliers and customers relative to the firm being analyzed.
Table 9.2
High industry profits are associated with: | Low industry profits are associated with: |
---|---|
Weak suppliers | Strong suppliers |
Weak customers | Strong customers |
High entry barriers | Low entry barriers |
Few substitutes | Many substitutes |
Little rivalry/competition | Intense rivalry/competition |
Once factors affecting industry profitability are understood, the analyst can turn to analyzing firm-specific factors determining profit margins: sales and cost of sales.
Sales are the product of price per unit times the number of units sold. The growth in the firm’s sales thus reflects the ability of the firm to raise prices (i.e., pricing power), the firm’s ability to gain market share, and the growth in product demand in the industry. The firm’s capacity to raise prices is a measure of its pricing power. Pricing power tends to be less in highly competitive markets than in less competitive ones. The degree of competitiveness in a market and in turn pricing power is affected by the ease with which new firms can enter a market, the availability of close substitutes for products or services currently offered in the market, the degree of industry concentration, and the amount of excess capacity. Fig. 9.4 provides a framework (the Pricing Power Continuum) for assessing a firm’s pricing power within its served market. Firms in an industry have significant pricing power when barriers to entry are high, there are few close substitutes for its product or service offering, there is little excess capacity, the firm’s market share is high relative to current competitors and government regulation and oversight is limited. An analyst can describe subjectively the degree of a firm’s pricing power by its relative position on the continuum. The further to the right the firm is placed the greater its perceived pricing power.
The other major component of revenue growth, unit sales, is driven by the growth in industry product demand and by gains in market share. Industry product demand often is correlated with one or two key variables. The determinants of unit sales will differ by industry. For example, beer, beverage and personal care products (e.g., shampoo) are heavily influenced by demographics such as population growth and changes in the age composition of the population. Sporting goods sales are directly related to advertising and marketing expenditures. Automotive sales are driven by a combination of changes in consumer real income (i.e., purchasing power), consumer confidence, and borrowing costs. Pharmaceutical product sales are impacted by research and development spending and the aging of the population. The demand for smart phone apps is correlated with the growth in handset sales.
Once the analyst feels that they understand what determines pricing power and unit sales growth historically, it is necessary to analyze the determinants of the cost of sales. Depending on the industry, the two largest components of the cost of sales are usually direct labor costs and purchased materials and services. Direct labor costs are those directly attributable to the production of goods and services. Indirect labor costs such as those affecting distribution, marketing and sales are excluded from the calculation of cost of sales. Factors affecting direct labor cost often include the availability of labor having the requisite skills, the degree of unionization, government regulation, and productivity (i.e., output per worker).
Purchased material and service costs correlate with the size of purchase (i.e., purchase discounts are larger for larger quantities purchased), the number of suppliers, product uniqueness, and substitutes. In addition to labor and capital costs, raw material costs are frequently impacted by external factors such geopolitical supply disruptions and the weather.
Since current sales can be satisfied from current production or from inventory, cost of sales is affected by how a firm values its inventory. The current cost of sales is reduced by units produced currently but not sold and placed in inventory and increased by current sales that are satisfied by reducing inventory. The two most common ways to value inventory are first in, first out (FIFO) and last in, last out (LIFO). FIFO uses inventory that is purchased earliest in the production process, resulting in lower priced inventory used to satisfy sales in the current period. Items placed in inventory that are purchased at earlier dates are generally considered to have been purchased at a lower price due to inflation. Thus, FIFO has the effect of reducing the cost of sales. In contrast, LIFO uses the most recently purchased inventory items resulting in higher cost inventory items, which adds to the cost of sales.
If the factors affecting sales, profit, and cash flow historically are expected to exert the same influence in the future, a firm’s financial statements may be projected by extrapolating historical growth rates in key variables such as revenue, with other line items on the financial statement projected as a percent of sales. If the factors affecting sales growth are expected to change due to the introduction of new products, total revenue growth may accelerate from its historical trend. In contrast, the emergence of additional competitors in the future may limit revenue growth by eroding the firm’s market share and selling prices.
Financial statements should be projected for at least three-to-five years and possibly more until the firm’s cash flows turn positive or the growth rate slows to what is believed to be a sustainable pace. Some firms may show profit growth in excess of the industry average. Since above average profit growth is not sustainable, cash flows for such firms should be projected until they are expected to slow to the industry average. This usually happens when new competitors are expected to enter the industry. Projections should reflect the best information about product demand growth, future pricing, technological changes, new competitors, new product and service offerings from current competitors, potential supply disruptions, raw material and labor cost increases, and possible new product or service substitutes.
Because accuracy diminishes rapidly the further the analyst projects detailed financial statements into the future, projections are typically made over two forecast periods: the planning period and the terminal period. The planning period represents the period of annual projections, while the terminal period approximates the present value of all cash flows beyond the last year of the planning period. The planning period forecast begins with an estimate of the firm’s revenue using either the top-down or bottom up approaches. The top down approach projects the size of the firm’s target market using macro (e.g., personal income, interest rates) or market level data (e.g., the number of customers) and then applies an estimated market share for the firm. That is, if the market is projected to grow to $800 million next year and the firm’s market share is expected to be 10% then the firm’s revenue next year is expected to be $80 million.13 The bottom up approach involves summing up forecasts made by the firm’s sales force by product line and by customer. Alternatively, the analyst could extend present trends using historical growth rates or multiple regression techniques, which implicitly assumes the factors affecting growth in the past will do so in the same way in the future.
Tables 9.3–9.7 illustrate the output of the Microsoft Excel spreadsheet model titled Target Valuation Model found on the website accompanying this text. The cells denoted in each worksheet in yellow represent input cells. Cells in black contain formulas. Entries into input cells change automatically the subsequent years to reflect the new data in the input cell. Changes to the model are made primarily by making changes in the worksheet labeled Target Assumptions (see Table 9.3), which contains the assumptions underlying the projected income statement, balance sheet, and cash flow statement. The analyst should input cell values one at a time using small changes to assess accurately the outcome of each change on valuation. It will become evident which variables represent key value drivers by noting their impact on firm valuation.
Table 9.3
Actual | Projections for the period ending December 31, | ||||||||
---|---|---|---|---|---|---|---|---|---|
2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | ||
Income statement | |||||||||
Sales growth | NA | 5.2% | 4.8% | 7.5% | 7.5% | 7.5% | 7.5% | 7.5% | |
COGS as a % of sales | 41.3% | 44.1% | 42.0% | 41.0% | 41.0% | 41.0% | 41.0% | 41.0% | |
SG&A % annual increase (decrease) | NA | (1.4%) | 4.5% | 4.0% | 4.0% | 4.0% | 4.0% | 4.0% | |
Other operating expense as a % of sales | 13.1% | 12.0% | 10.5% | 11.0% | 11.0% | 11.0% | 11.0% | 11.0% | |
EBITDA growth | NA | 5.8% | 27.4% | 14.6% | 11.6% | 11.3% | 11.0% | 10.8% | |
EBITDA margin | 17.1% | 17.2% | 20.8% | 22.2% | 23.1% | 23.9% | 24.7% | 25.4% | |
Balance sheet | |||||||||
Receivable days | 59.8 | 61.6 | 64.3 | 49.0 | 49.0 | 49.0 | 49.0 | 49.0 | |
Inventory days | 79.6 | 82.8 | 88.5 | 74.0 | 74.0 | 74.0 | 74.0 | 74.0 | |
Other current assets % of sales | 7.8% | 5.2% | 6.3% | 5.5% | 5.5% | 5.5% | 5.5% | 5.5% | |
Accounts payable days | 43.0 | 39.1 | 40.9 | 40.0 | 40.0 | 40.0 | 40.0 | 40.0 | |
Other current liabilities % of COGS | 65.6% | 79.1% | 60.4% | 68.0% | 68.0% | 68.0% | 68.0% | 68.0% | |
Working capital/sales (excl cash and debt) | 1.3% | (7.5%) | 4.0% | (5.1%) | (5.1%) | (5.1%) | (5.1%) | (5.1%) | |
Cash flow | |||||||||
Capital expenditures | 26.7 | 13.8 | 10.3 | 17.0 | 18.3 | 19.7 | 21.1 | 22.7 | |
Capex as a % of sales | 0.7% | 0.4% | 0.3% | 0.4% | 0.4% | 0.4% | 0.4% | 0.4% | |
Depreciation | 123.0 | 123.6 | 126.0 | 136.2 | 146.4 | 157.4 | 169.2 | 181.9 | |
Depreciation as a % of sales | 3.4% | 3.3% | 3.2% | 3.2% | 3.2% | 3.2% | 3.2% | 3.2% |
Table 9.4
Actual | Projections for the period ending December 31 | |||||||
---|---|---|---|---|---|---|---|---|
2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | |
Sales | $3588.1 | $3775.7 | $3958.5 | $4255.4 | $4574.5 | $4917.6 | $5286.5 | $5682.9 |
Cost of goods sold | 1482.0 | 1665.7 | 1664.1 | 1744.7 | 1875.6 | 2016.2 | 2167.4 | 2330.0 |
Gross profit | 2106.1 | 2110.0 | 2294.4 | 2510.7 | 2699.0 | 2901.4 | 3119.0 | 3352.9 |
SG&A | 1023.2 | 1009.0 | 1054.6 | 1096.8 | 1140.7 | 1186.3 | 1233.7 | 1283.1 |
Other operating expense | 470.7 | 453.2 | 414.6 | 468.1 | 503.2 | 540.9 | 581.5 | 625.1 |
Depreciation | 123.0 | 123.6 | 126.0 | 136.2 | 146.4 | 157.4 | 169.2 | 181.9 |
Amortization | 299.6 | 313.9 | 302.9 | 300.0 | 300.0 | 300.0 | 300.0 | 300.0 |
EBIT | 189.6 | 210.3 | 396.3 | 509.6 | 608.7 | 716.8 | 834.6 | 962.9 |
Unusual (gain) loss | (37.2) | - | - | - | - | - | - | - |
(Income) from affiliates | - | - | - | - | - | - | - | |
Other expense (income) | 60.0 | 10.9 | 11.9 | - | - | - | - | - |
Interest (income) | (4.3) | (3.9) | (2.4) | - | - | - | - | - |
Interest expense | 152.3 | 162.1 | 123.9 | 95.5 | 80.5 | 65.5 | 50.5 | 35.5 |
Earnings before taxes | 18.8 | 41.2 | 262.9 | 414.1 | 528.2 | 651.3 | 784.1 | 927.3 |
Noncontrolling interest | - | - | - | - | - | - | - | - |
Taxes | 63.7 | 100.9 | 101.4 | 165.6 | 211.3 | 260.5 | 313.6 | 370.9 |
Net income before extra items | (44.9) | (59.7) | 161.5 | 248.5 | 316.9 | 390.8 | 470.4 | 556.4 |
Extraordinary items | 0.6 | 0.7 | 0.4 | - | - | - | - | - |
Net income after extra items | $(44.3) | $(59.0) | $161.9 | $248.5 | $316.9 | $390.8 | $470.4 | $556.4 |
Table 9.5
Actual | Projections for the period ending December 31 | |||||||
---|---|---|---|---|---|---|---|---|
2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | |
Cash | $854.9 | $882.1 | $276.3 | $1019.0 | $1480.4 | $2026.4 | $2663.8 | $3399.7 |
Accounts receivable | 587.5 | 637.0 | 697.3 | 571.3 | 614.1 | 660.2 | 709.7 | 762.9 |
Inventory | 323.1 | 377.9 | 403.5 | 353.7 | 380.3 | 408.8 | 439.4 | 472.4 |
Other | 281.0 | 196.6 | 248.1 | 234.0 | 251.6 | 270.5 | 290.8 | 312.6 |
Current assets | 2046.5 | 2093.6 | 1625.2 | 2178.0 | 2726.3 | 3365.9 | 4103.7 | 4947.6 |
Property, plant, and equipment | 870.4 | 858.7 | 871.4 | 888.4 | 906.7 | 926.4 | 947.5 | 970.3 |
Accumulated depreciation | - | - | - | (136.2) | (282.6) | (439.9) | (609.1) | (790.9) |
Net property, plant, and equipment | 870.4 | 858.7 | 871.4 | 752.2 | 624.2 | 486.5 | 338.4 | 179.3 |
Goodwill | 4372.1 | 4366.7 | 4503.4 | 4503.4 | 4503.4 | 4503.4 | 4503.4 | 4503.4 |
Intangible assets | 2040.2 | 1746.6 | 1525.8 | 1225.8 | 925.8 | 625.8 | 325.8 | 25.8 |
Deferred taxes | 26.8 | 28.8 | 23.0 | 23.0 | 23.0 | 23.0 | 23.0 | 23.0 |
Other | 130.2 | 93.6 | 89.2 | 89.2 | 89.2 | 89.2 | 89.2 | 89.2 |
Total assets | $9486.2 | $9188.0 | $8638.0 | $8771.7 | $8891.9 | $9093.7 | $9383.6 | $9768.3 |
Accounts payable | 174.4 | 178.4 | 186.6 | 191.2 | 205.5 | 221.0 | 237.5 | 255.3 |
Other | 972.0 | 1317.9 | 1005.8 | 1186.4 | 1275.4 | 1371.0 | 1473.9 | 1584.4 |
Current liabilities | 1146.4 | 1496.3 | 1192.4 | 1377.6 | 1480.9 | 1592.0 | 1711.4 | 1839.7 |
Revolving credit facility | - | - | - | - | - | - | - | - |
Senior debt | 2727.6 | 2297.7 | 2060.9 | 1760.9 | 1460.9 | 1160.9 | 860.9 | 560.9 |
Subordinated debt | - | - | - | - | - | - | - | - |
Total | 2727.6 | 2297.7 | 2060.9 | 1760.9 | 1460.9 | 1160.9 | 860.9 | 560.9 |
Deferred taxes | 558.0 | 410.6 | 287.4 | 287.4 | 287.4 | 287.4 | 287.4 | 287.4 |
Other | 616.1 | 384.1 | 443.9 | 443.9 | 443.9 | 443.9 | 443.9 | 443.9 |
Total liabilities | 5048.1 | 4588.7 | 3984.6 | 3869.8 | 3673.1 | 3484.2 | 3303.6 | 3131.9 |
Common stock | 5225.0 | 5443.2 | 5733.7 | 5733.7 | 5733.7 | 5733.7 | 5733.7 | 5733.7 |
Preferred equity | - | - | - | - | - | - | - | - |
Retained earnings | 532.5 | 911.0 | 1341.8 | 1590.3 | 1907.2 | 2297.9 | 2768.4 | 3324.8 |
Treasury stock | (1420.0) | (1820.0) | (2482.0) | (2482.0) | (2482.0) | (2482.0) | (2482.0) | (2482.0) |
Other adjustments | 96.6 | 65.1 | 59.1 | 59.1 | 59.1 | 59.1 | 59.1 | 59.1 |
Noncontrolling interest | 4.0 | - | 0.8 | 0.8 | 0.8 | 0.8 | 0.8 | 0.8 |
Total stockholders’ equity | 4438.1 | 4599.3 | 4653.4 | 4901.9 | 5218.8 | 5609.5 | 6080.0 | 6636.4 |
Total liabilities and equity | $9486.2 | $9188.0 | $8638.0 | $8771.7 | $8891.9 | $9093.7 | $9383.6 | $9768.3 |
Reconciliation | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
Table 9.6
Actual | Projections for the period ending December 31 | ||||||
---|---|---|---|---|---|---|---|
2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | |
Net Income | $ (59.0) | $161.9 | $248.5 | $316.9 | $390.8 | $470.4 | $556.4 |
Depreciation and amortization | 437.5 | 428.9 | 436.2 | 446.4 | 457.4 | 469.2 | 481.9 |
Change in | |||||||
Accounts receivable | (49.5) | (60.3) | 126.0 | (42.8) | (46.1) | (49.5) | (53.2) |
Inventory | (54.8) | (25.6) | 49.8 | (26.5) | (28.5) | (30.7) | (33.0) |
Accounts payable | 4.0 | 8.2 | 4.6 | 14.3 | 15.4 | 16.6 | 17.8 |
Deferred taxes | (149.4) | (117.4) | - | - | - | - | - |
Other liabilities | (232.0) | 59.8 | - | - | - | - | - |
Cash flow from operating activities | 359.7 | 97.1 | 1059.7 | 779.7 | 865.7 | 958.5 | 1058.6 |
Capital expenditures | (13.8) | (10.3) | (17.0) | (18.3) | (19.7) | (21.1) | (22.7) |
Acquisitions | (0.1) | (149.0) | - | - | - | - | - |
Sale of assets | 3.4 | 25.5 | - | - | - | - | - |
Cash flow from investing activities | (10.5) | (133.8) | (17.0) | (18.3) | (19.7) | (21.1) | (22.7) |
Net change in equity | (213.3) | (377.5) | - | - | - | - | - |
Net change in debt | (429.9) | (236.8) | (300.0) | (300.0) | (300.0) | (300.0) | (300.0) |
Dividends paid | - | - | - | - | - | - | - |
Cash flow from financing activities | (643.2) | (614.3) | (300.0) | (300.0) | (300.0) | (300.0) | (300.0) |
Net change in cash | (294.0) | (651.0) | 742.7 | 461.4 | 546.1 | 637.4 | 735.9 |
Beginning cash balance | 854.9 | 882.1 | 276.3 | 1019.0 | 1480.4 | 2026.4 | 2663.8 |
Cash available for revolving credit | $560.9 | $231.1 | $1019.0 | $1480.4 | $2026.4 | $2663.8 | $3399.7 |
Beginning revolver | - | - | - | - | - | ||
Total repayment | - | - | - | - | - | ||
Ending revolving credit facility | - | - | - | - | - | ||
Ending cash | 1019.0 | 1480.4 | 2026.4 | 2663.8 | 3399.7 |
Note: In the Target Valuation Model accompanying this text, the components of working capital are calculated according to whether they represent a source or use of cash. Consequently, increasing annual accounts receivable would be shown as negative representing a use of funds as the firm’s revenues grow.
Table 9.7
2014 | 2015 | 2016 | 2017 | 2018 | |
---|---|---|---|---|---|
Free cash flow | |||||
EBIT | 509.6 | 608.7 | 716.8 | 834.6 | 962.9 |
Taxes | (203.9) | (243.5) | (286.7) | (333.8) | (385.1) |
Deprec. & Amort. | 436.2 | 446.4 | 457.4 | 469.2 | 481.9 |
Gross Capex | (17.0) | (18.3) | (19.7) | (21.1) | (22.7) |
∆ NWC | 180.4 | (55.0) | (59.2) | (63.6) | (68.4) |
Free cash flow | 905.3 | 738.3 | 808.6 | 885.2 | 968.5a |
Periodb | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
Mid-year conventionc | 0.50 | 1.50 | 2.50 | 3.50 | 4.50 |
Discount factord | 0.96 | 0.88 | 0.80 | 0.73 | 0.67 |
PV FCFF | $866.0 | $646.3 | $647.7 | $648.8 | $649.5 |
PV (years 1–5) | 3458.3 | ||||
PV (terminal value) | 10,453.5 | ||||
Enterprise value | 13,911.8 | ||||
Plus cash | 276.3 | ||||
Less debt & min. int. | 2061.7 | ||||
Equity value | 12,126.4 | ||||
Equity value per share | $69.49 | ||||
Assumptions: | |||||
WACC | 9.3% | ||||
Target D/E | 75.0% | ||||
Target D/TC | 42.9% | ||||
Marginal tax rate | 40.0% | ||||
ke | 14.0% | ||||
Rf | 2.5% | ||||
Rf − Rm | 5.5% | ||||
Beta | 2.09 | ||||
Terminal value | |||||
FCF 2020 | 968.5 | ||||
Terminal growth rate | 3.0% | ||||
Terminal period WACC | 9.4% |
a Free cash flow in the last year of the planning period is recalculated at the marginal tax rate of 40% rather than the lower effective tax rate used during the planning period, and then used to estimate the terminal value using the constant growth model.
b Period reflects months of actual data available for first forecast year, i.e., if have 9 months of actual data, period one equals 0.25, if have one half year of data, period one is 0.5; if 3 months of data available, period one equals 0.75. If the data available is less than a full year, it must be annualized.
c DCF valuation assumes that cash flows occur in a lump sum at the end of the year. What is more likely is that that they occur throughout the year. With the mid-year convention, cash flows are assumed to occur in the middle of the year. Consequently, those cash flows are discounted half a year instead of a whole year.
d A factor which when multiplied by the period cash flow converts it into a present value.
Note that the Target Valuation Model already contains input and output data and an estimated valuation for the firm. For our purposes, consider this projection the “base case” valuation. To simulate the impact of an assumption change, change the value in the appropriate input cell. For example, to assess the impact on valuation of an increase of one percentage point in the Target’s revenue growth rate, change the Target’s revenue growth rate assumption on the Target’s Assumptions Worksheet by one percentage point during the planning period (2014–2018) from 5.5% to 6.5% in the yellow input cell on the Sales Growth line for the year 2014. The model will increase automatically the growth rate annually from 2014 to 2018 by one percentage point. The model also accommodates a variable growth rate forecast. For example, if the growth rate in 2015 is expected to increase by an additional one percentage point and to continue at that higher rate in subsequent years, the analyst simply increases the growth rate by from 5.5% to 6.5% in 2014 and to 7.5% in 2015.
Worksheets labeled Target Income Statement (Table 9.4) and Target Balance Sheet (Table 9.5) provide the input for the worksheet labeled Target Cash Flow (Table 9.6) reflect assumptions provided in the Target Assumptions Worksheet. If the balance sheet is in balancing properly, the values in the red cells at the bottom on the Target Balance Sheet should be zero, as they represent the difference between total assets and total liabilities plus shareholders’ equity.
This step requires the analyst to estimate the sum of the PV of the cash flows during the planning period (in this instance, 2014–2018) and the PV of those beyond the planning period. The PV of the cash flows beyond the planning period is commonly referred to as the terminal value which is estimated using the constant growth valuation method (see Chapter 7).
Table 9.7 illustrates the calculation of the enterprise and equity values of the firm. The former represents the value of the firm to all those supplying funds to the firm, while the equity value represents the value of firm to common shareholders only. Target’s enterprise value is estimated on the model’s Valuations Worksheet using inputs from the Target Assumptions Worksheet. Enterprise value often is defined as the sum of the market value of a firm’s equity, preferred shares, debt, and non-controlling interest less total cash and cash equivalents. Cash is commonly deducted since the amount in excess of what is needed to satisfy working capital requirements is a non-operating asset whose value is implicitly included in the market value of equity since it is owned by the shareholders. Unimportant to the ongoing operation of the business, it can be used by an acquirer to finance the deal.14 Once the enterprise value has been estimated, the market value of equity is then calculated by adding cash to and deducting long-term debt and non-controlling interests from the enterprise value.
While this definition may reasonably approximate the takeover value of a company, it does not encompass all of the significant nonequity claims on cash flow such as operating leases, unfunded pension and healthcare obligations, and loan guarantees. Thus, the common definition of enterprise value may omit significant obligations that must be paid by Acquirer and whose present value should be included in estimating Target’s purchase price. When calculating the ratio of enterprise to EBITDA as a valuation multiple, the analyst needs to add back leasing and pension expenses to EBITDA in order to compare the ratio for a firm with substantial amounts of such long-term obligations with other companies.
Chapter 7 discusses ways of estimating the market value of a firm’s long-term debt. Commonly used methods for modeling purposes involve either valuing the book value of a firm’s long-term debt at its current market value if it is publicly traded or book value if it is not. Alternatively, the market value of similar debt at a firm exhibiting a comparable credit rating can be used to value a target firm’s debt. For example, assume the book value of Target’s debt with 10 years remaining to maturity is $478 million and its current market value or the market value of comparable publicly traded debt is 1.024 per $1000 of face value. The market value of the firm’s debt can be estimated as $489.5 million (i.e., 1.024 × $478).
The market value of non-controlling interests can be estimated by multiplying the book value of such interests by the price-to-earnings ratio for comparable firms. That is, if the book value of the non-controlling interests in the firm is $25 million and the price-to-earnings ratio for comparable firms is 15, the market value of non-controlling interests would be $375 million (i.e., 15 × $25 million).
Converting projected pro forma cash flows to a PV requires estimation of the weighted average cost of capital (WACC) during the planning period and the terminal period. The data, with the exception of borrowing costs, used in estimating Eqs. (9.2) and (9.3) comes from Table 9.7. From Chapter 7, the WACC assumed during the planning period can be expressed as follows:
where
The weighted average cost of capital is estimated as follows:
The terminal value represents the present value of all cash flows beyond the planning period (i.e., 2014–2018). Recall from Chapter 7, the weighted average cost of capital, WACCTV, used during the terminal period is assumed to equal the current industry average WACC. The terminal value, PTV, is calculated using the constant growth valuation method (see Chapter 7).
where16
Table 9.8
2014 | 2015 | 2016 | 2017 | 2018 | |
---|---|---|---|---|---|
Discount factor | 1/(1 + 0.093)1 − 0.5 = 1/(1 + 0.093)0.5 = 0.96 | 1/(1 + 0.093)2 − 0.5 = 1/(1 + 0.093)1.5 = 0.88 | 1/(1 + 0.093)3 − 0.5 = 1/(1 + 0.093)2.5 = 0.80 | 1/(1 + 0.093)4 − 0.5 = 1/(1 + 0.093)3.5 = 0.73 | 1/(1 + 0.093)5 − 0.5 = 1/(1 + 0.093)4.5 = 0.67 |
a Using the mid-year convention will result in a larger discounted cash flow valuation than using full year discounting. Why? Full year discounting results in a larger discount rate and a smaller discount factor. For example, assume cash flow in 2014 is $100 million, using the mid-year convention, its present value would be $95 million (i.e., [1/(1 + 0.098)0.5 = 0.95] × $100 million), but using full year discounting, it would be $91 million (i.e., [1/(1 + 0.098)1 = 0.911] × $100 million).
The present value of the terminal value is calculated as follows:
Financial models are said to balance when total assets equal total liabilities plus shareholders’ equity. This may be done manually by inserting a value equal to the difference between the two sides of the balance sheet or automatically forcing this equality. The latter has the enormous advantage of allowing the model to simulate multiple scenarios over many years without having to stop the forecast each year to manually force the balance sheet to balance.
The mechanism in the model illustrated in this chapter for forcing automatic balance is the use of a revolving loan facility or line of credit. Such arrangements allow a firm to borrow up to a specific amount. To maintain the ability to borrow to meet unanticipated needs, firms have an incentive to pay off the loan as quickly as possible. Once the maximum has been reached, the firm can no longer borrow. If total assets exceed total liabilities plus equity, the model borrows (the “revolver” shows a positive balance). If total liabilities plus shareholders’ equity exceed total assets, the model first pays off any outstanding “revolver” balances and uses the remaining excess cash flow to add to cash and short-term investments on the balance sheet.
How does the model determine the firm’s ending cash balances? Ending cash balances will always equal minimum cash if available cash is less than the loan balance. Why? Because only that portion of the loan balance greater than the minimum balance will be used to repay the loan. Conversely, if available cash exceeds the loan balance, the ending cash balance equals the difference between available cash and the loan payment, since the total loan balance will not be repaid unless there is cash available to cover the minimum balance. See Chapter 14 for an illustration of how the model automatically balances when input values are changed.
Financial models often require large amounts of historical data inputs to operate. For publicly traded firms, most of the financial statement data is available in the firm’s annual 10k submitted to the US Securities and Exchange Commission. The 10k contains detailed income, balance sheet, and cash flow statements as well as numerous footnotes explaining these financial statements. The annual 10k provides the current year and two historical years. Firms often make 10ks available for many years. Consequently, by downloading past 10ks, the analyst can create an historical time series for analysis. However, in doing so, the analyst should check for revisions to the data to ensure that the historical information is recorded properly. Morningstar is also a good source of selected historical data on public firms.
While the SEC mandates that all publicly traded firms submit certain types of information, it does not require that each firm’s 10k be formatted in precisely the same way due to the differing circumstances for each firm. For example, one firm may have extraordinary or nonrecurring events which need to be displayed, while others do not. Consequently, financial information may be displayed differently from one firm to the next depending on their circumstances. Explanations of specific line item detail are available in the Notes to the Consolidated Financial Statements. Additional data required by financial models such as industry credit ratios and firm betas often are available for free through various sources of publicly available information accessible via the internet. What follows is a discussion of the sources of data for each financial statement and for other data inputs required by the model.
Typically, sales, cost of sales, gross profit, SG&A, other operating expenses, extraordinary (nonrecurring) expenses, and the provision for taxes are shown in a firm’s annual 10k. However, depreciation and amortization expense often are not shown as separate line items as they are frequently included in the cost of sales or in some instances such as for retailing businesses in sales, general and administrative expenses. These data usually are broken out separately on the firm’s cash flow statement. Note that it is not necessary to separate amortization expense from depreciation if they are included as one line item. It is only important that we add non-cash expenses back to net income in the calculation of cash flow. Earnings per share and fully diluted EPS also are commonly displayed. When we include depreciation and amortization expense as a separate line item on the model’s income statement, it is important to deduct such expenses from the cost of sales or S,G&A, if these line items taken from the firm’s 10k include depreciation and amortization expense.
A discontinued operation occurs when a business unit or product line within a company’s business has been sold, disposed of or abandoned and is subsequently reported on the company’s income statement as income separate from continuing operations. Discontinued operations are reported under GAAP as long as two conditions are satisfied: (1) the discontinued operation is completely removed from the financial statements and (2) the former parent has no ongoing relationship with the unit. Both current period and prior period operations are disclosed in the discontinued operations section and not under extraordinary items.18
The following observations are helpful in projecting discontinued operations. Firms are less liable to report divestitures on which they incur losses in the year of an acquisition and more likely to discontinue operations, especially those with recorded losses, two or three years after an acquisition. The magnitude of the acquisition has little influence on the timing of divestitures by smaller firms, but large firms are more likely to discontinue businesses showing gains in the year of or the year following a major acquisition. This is consistent with the observation that unwanted assets are often shed soon after large, complicated acquisitions. Highly diverse firms are more prone to divest assets, particularly following a period of significant diversification. The first announcement of a discontinued operation is usually a precursor to a series of similar announcements as part of a downsizing process.19
Table 9.9 identifies the income statement information usually available (Column 1) in a firm’s 10k and shows how this information corresponds to the input data requirements (Column 2) of the financial model discussed in this chapter. Column 3 indicates where data not available on the income statement may be found in the “Notes to the Consolidated Financial Statements.” Brackets in Column 1 indicate that multiple line items on the firm’s 10k are included in a single line item in the M&A Model. Similarly, brackets in Column 2 indicate that multiple line items in the model are included in a single line item on the firm’s 10k financial statements and that the detail is found in the Notes to the Financial Statements.
Table 9.9
Col. 1: Typical 10k income statement | Col. 2: Financial model income statement input requirements | Col. 3: Notes to financial statements |
---|---|---|
Revenue/sales (consolidated and by major business segment) | Sales | See note on business segment data |
Cost of product/service sales (consolidated and by major business segment). May include depreciation and amortization expense | Cost of goods sold | See note on business segment data |
S, G & A (consolidated and by major business segment) | S, G & A | See note on business segment data |
Research & development expenses restructuring & other costs, net | Other operating expenses | |
Depreciation | See 10k’s cash flow statement | |
Amortization | See 10k’s cash flow statement | |
Operating income | EBIT | |
Total other expense, net Unusual (gain) loss Income from affiliates Interest (income) Interest expense | Unusual (gain) loss (Income) from affiliates Other expense (income) Interest (income) Interest expense | See note on other expense, net for detail on interest income and interest expense |
Income from continuing operations before income taxes | Earnings before taxes | |
Taxes | Taxes | |
Net income (loss) before extraordinary items | Net income before extraordinary items | |
Loss (income) from discontinued operations after tax | Extraordinary items | |
Loss (gain) from disposal of discontinued operations after tax | ||
Net income after extraordinary items | Net income after extraordinary items |
Current asset items such as cash and cash equivalents, short-term investments, accounts receivable, inventories, the current portion of deferred tax assets, and other current assets are readily available on 10ks. Long-term asset categories provided on 10ks often include net property, plant and equipment (i.e., gross property, plant and equipment less accumulated depreciation), other assets, and goodwill. See Table 9.10. Current liabilities usually displayed on 10ks include short-term obligations and current maturities of long-term obligations (i.e., the current portion of long-term debt), accounts payable, accrued payroll and employee benefits, deferred revenue, and other accrued expenses. Long-term liabilities contain deferred income taxes (i.e., taxes owed but not paid because of timing differences), other long-term liabilities, and long-term obligations (e.g., long-term debt).
Table 9.10
Col. 1: Typical 10k balance sheet | Col. 2: Financial model balance sheet input requirements | Col. 3: Notes to financial statements |
---|---|---|
Assets | ||
Current assets | ||
Cash and cash equivalents Short-term investments | Cash (includes short-term investments) | |
Accounts receivable (net of reserves) | Accounts receivable (net of reserves) | |
Inventory | Inventory | |
Deferred tax assets (current portion) Other current assets | Other | See note on income taxes for details |
Long-term assets | ||
Net property, plant and equipment | Property, plant and equipment Less accumulated depreciation = Net property, plant & equip. | See note on property, plant and equipment for accumulated depreciation |
Other assets | Intangible assets Deferred taxes Other | |
Goodwill | Goodwill | |
Liabilities and shareholders’ equity | ||
Current liabilities | ||
Accounts payable | Accounts payable | |
Short-term obligations Accrued payroll and employee Benefits Deferred revenue Other accrued expenses | Other | |
Long-term liabilities | ||
Deferred income taxes | Deferred taxes (long-term portion) | See note on income taxes for details |
Other long-term liabilities | See note on pensions | |
Long-term obligations | Revolving credit facility Senior debt Subordinated debt | |
Shareholders’ equity | See consolidated statement of shareholders’ equity | |
Preferred stock, par value, shares authorized and issued | Preferred stock | |
Common stock, par value, shares authorized and issued | Common stock | |
Retained earnings | Retained earnings | |
Treasury stock (at cost) | Treasury stock | |
Capital in excess of par Accumulated other comprehensive items | Other adjustments | |
Noncontrolling interest (if any) | Noncontrolling interests | |
Total shareholders’ equity | Total stockholders’ equity | |
Liabilities and shareholders’ equity | Liabilities and shareholders’ equity |
The components of shareholders’ equity shown on the 10k balance sheet include preferred stock (par value and the number of shares authorized and the number issued) and common stock (par value and the number of such shares authorized and the number issued). Authorized shares have been approved by shareholders and the SEC but have not yet been issued by the firm. Capital in excess of par value (also called “additional paid in capital”) shows the value of the issued shares when issued in excess of their par value when authorized. The remaining shareholders’ equity items include retained earnings (i.e., accumulated historical net income after preferred dividends), treasury stock, and accumulated “other comprehensive items” (e.g., corrections made due to prior accounting errors and restatements).
The Note on Debt and Long-term Obligations describes the types of debt outstanding, maturity dates, associated interest rates, and usually gives a five year projection of the annual debt repayment schedule. Principal repayments beyond the fifth year are shown as a total figure. Interest expense and principal usually can be estimated by using a weighted average of each type of debt (i.e., senior, subordinate, etc.) and applying the applicable amortization rate (i.e., annual principal repayment) for the largest amount of debt outstanding in each category.
The firm’s cash flow statement (see Table 9.11) typically shows the key cash inflows and outflows from operating, investing and financing activities. This financial statement determines ending cash balances for the firm which is also reported on the firm’s balance sheet.
Table 9.11
Col. 1: Typical 10k cash flow statement | Col. 2: Financial model cash flow statement input requirements | Col. 3: Notes to financial statements |
---|---|---|
Operating activities | ||
Net income Loss (income) from discontinued operations Loss (gain) on disposal of discontinued operations Income from continuing operations | Net income | |
Depreciation and amortization | Depreciation and amortization | |
Change in deferred income taxes | Deferred taxes (current portion) | See note on income taxes |
Changes in assets and liabilities | ||
Accounts receivable | Accounts receivable | |
Inventories | Inventory | |
Other assets | ||
Accounts payable | Accounts payable | |
Other liabilities | Other liabilities | |
Net cash from operating activities | Cash flow from operating activities | |
Investing activities | ||
Acquisitions, net of cash acquired | Acquisition | See note on acquisitions |
Purchases of property, plant and equipment | Capital expenditures | |
Proceeds from sale of property, plant and equipment Proceeds from sale of investments Proceeds from sale of businesses Other investing activities, net | Sale of assets | |
Net cash from investing activities | Cash flow from investing activities | |
Financing activities | ||
Net proceeds from issuance of long-term debt Redemptions and repayments of long-term debt | Net change in debt | |
Purchases of company common stock Net proceeds from issuance of common stock | Net change in equity | |
Dividends paid | Dividends paid | |
Other financing activities, net | ||
Net cash from financing activities | Cash flow from financing activities | |
(Decrease) increase in cash and cash equivalents | Net change in cash | |
Cash and cash equivalents at beginning of period | Beginning cash balance | |
Cash and cash equivalents at end of period | Ending cash balance |
Historical betas for public firms and industry credit ratios are available from a number of sources: Yahoo Finance, Google Finance, Morningstar, Value Line Research Center, Standard & Poor’s Net Advantage, One Source, and Thomson One Banker. Go to the Yahoo.com/finance website and search in the “look up” block for a specific firm. The firm’s beta is located below the day’s closing price in the table of daily trading activity. Or, go to google.com/finance and search for your firm; the firm’s beta will be at the top of the page among the daily trading data.
Following certain protocols will help simplify the process of applying the model to analyze different situations. Save the model once historical data and forecast assumptions have been entered into the model. Make additional changes to copies of the saved model. If errors arise and cannot be resolved, it is helpful to return to an earlier version of the model. This obviates the need to reload historical and forecast information. Make sure the model’s balance sheet “balances” as denoted by the red cells at the bottom of the balance sheet worksheet equal to zero (i.e., total assets equal total liabilities plus shareholders’ equity). Do not be concerned about “fine-tuning” the model’s forecast until the model “balances.” Adjusting the model’s forecast should start with a focus on making small changes to model value drivers one at a time. To test the reasonableness of the model’s output, check key output variables such as net present value and the trend in earnings per share, outstanding debt, and cash balance. Avoid making too many changes to the model before saving its output.
Chapter 7 discussed the challenges of valuation in a sustained artificially low interest rate environment. While adjustments can be made in an attempt to offset potential underestimation in the calculation of the cost of capital and the resulting overvaluation of a target firm, they tend to be highly subjective and therefore problematic. Financial models can be used to address this problem by providing a range of valuation estimates enabling senior management to have a reasonable understanding of potential outcomes.
A model can be used to define alternative scenarios which can be as basic as three outcomes: optimistic, pessimistic, and most likely. This approach has the advantage of simplicity and ease of understanding. Alternatively, more sophisticated statistical methods can be used to estimate the most probable outcome. One method is Monte Carlo simulation. The primary advantage of a Monte Carlo simulation (which involves the random sampling of model inputs to simulate a range of outcomes and their likelihood of occurring) is its ability to allow the user to vary assumptions such as the cost of capital. This is also its foremost disadvantage since the outcomes are only as good as the quality of the inputs. Another major disadvantage is that Monte Carlo simulations tend to underestimate the likelihood of extreme events (so-called “black swan events”) such as the 2008–2009 financial market crisis.
Financial modeling helps the analyst understand determinants of value creation, provides a means of assessing options and risks, and identifies how firm value is affected by different economic events. The estimation of firm value involves a three step procedure: (1) analyze the target’s historical statements to determine the primary determinants of cash flow; (2) project 3–5 years of annual pro forma financial statements (i.e., the planning period); and (3) estimate the present value of the projected pro forma cash flows, including the terminal value.
Answers to these Chapter Discussion Questions are available in the Online Instructor's Manual for instructors using this book (https://textbooks.elsevier.com/web/Manuals.aspx?isbn=9780128150757).
Solutions to these Practice Problems are available in the Online Instructor's Manual for instructors using this book (https://textbooks.elsevier.com/web/Manuals.aspx?isbn=9780128150757).
Life Technologies (Life Tech), a leading global life sciences firm, had rewarded its shareholders by almost doubling the firm’s share price from its 2009 low of $26 per share to $51 by mid-2012. Despite this stellar performance, Gregory T. Lucier, Life Tech’s Chairman of the Board and Chief Executive Officer since 2008, felt uneasy about the firm’s future financial performance.
The life sciences industry is facing major challenges. Foremost is the increasing pressure on profit margins stemming from the escalating cost of healthcare due to the growth in chronic diseases, an aging population, and new medical therapies. Efforts to control healthcare costs are resulting in a reduction in the reimbursement rate for healthcare providers such as hospitals, testing laboratories, and physicians. Furthermore, pressure to reduce runaway government deficits is reducing the funding of scientific research.
These developments are driving consolidation among Life Tech’s customers. Such consolidation reduces the number of potential new accounts and enables customers to increase their negotiating leverage with vendors such as Life Tech. There is also a growing trend for customers to reduce the total number of vendors they use. Customer consolidation is driving consolidation among life science companies in an effort to realize economies of scale, scope, and purchasing. Underway for several years, consolidation among Life Tech’s competitors is expected to continue as companies attempt to strengthen or hold their market positions. Increased concentration within the life sciences industry is expected to result in stronger competitors that are better able to compete as sole-source vendors for customers.
The combination of customer and competitor consolidation could put significant downward pressure on Life Tech’s profit margins. Mr. Lucier and the Life Tech board faced a dilemma: whether to continue to pursue the firm’s strategy of growing market share through customer focused innovation or to consider alternative ways to maximize shareholder value such as selling the firm or aggressively growing the firm.
Founded in 1987, Life Tech had established itself as a leading innovator of life science products and services that improve the effectiveness and efficiency of professionals in the pharmaceutical, biotechnology, agricultural, clinical, government and academic scientific communities. The company’s products also are used in forensics, food and water safety, animal health testing and other industrial applications. Life Tech produces lab analytical and testing instruments; robotic systems to automate labor intensive research, research consumables including glassware, plastic ware, vials, tubes, and syringes; equipment from centrifuges to microscopes; lab furniture; and lab information management and testing systems.
On January 18, 2013, Life Tech announced that it had hired investment banks Deutsche Bank and Moelis & Co. to explore strategic options for the firm as part of the board’s annual strategic review. Mr. Lucier offered additional details in a subsequent earnings-related telephone conference call to investors and Wall Street analysts saying that the review has begun in the summer of 2012 and that “all ideas were on the table.” Sensing the possibility of a sale, investors drove the share price up by 10% to $58 by the end of February.
Mr. Lucier and the board’s decision would be based on a continued analysis of industry trends and the firm’s overall competitive position. Mr. Lucier directed his accounting and finance department to assess the impact of the results of this analysis on the value of the firm under different sets of assumptions. What follows is a discussion of these considerations.
The life sciences comprise fields of science involving the study of living organisms such as plants, animals and humans. While biology remains the centerpiece of the life sciences, technological advances in molecular biology and biotechnology have led to a burgeoning of specializations and new interdisciplinary fields. Because of the extremely high research and development costs coupled with little revenue in the initial years of development, many life sciences firms partner with larger firms to complete product development. However, the industry tends to be dominated by handful of big companies. Table 9.12 lists the major market segments of the industry.
Table 9.12
Healthcare: Drugs, vaccines, gene therapy, and tissue replacements | Research: Understanding the human genome and better disease detection |
Agriculture: Improved foods and food production, pest control, and plant and animal disease control | Industry: Oil and mineral recovery, environmental protection, waste reduction; improved detergents, chemicals, stronger textiles |
In general, the ratio of R&D spending to revenue drives new products in this industry. The key to successful companies is achieving a proper balance between R&D spending and expense control. Because of the long R&D phase, during which there is very little revenue being generated, projecting earnings requires looking at both a firm’s products under development and in production. For firms already selling products, looking at sales trends makes projecting revenue growth rates easier. Firm value in this industry is largely driven by their intellectual property and the ability to derive commercial products from their proprietary knowledge to generate future profits and cash flows. Because life sciences firms require substantial amounts of capital, they are prone to maintaining substantial amounts of cash on hand. Table 9.13 provides an overview of the factors contributing to the intensity of industry competition.
Table 9.13
For firms to succeed in this industry they must be able to innovate cost effectively. Furthermore, to minimize product distribution costs and to gain access to needed R&D capabilities, firms need to be able to work collaboratively with product distributers, universities, and government agencies. Finally, because of the long lead time in developing new products and services, firms must have continuing access to financing. These three success factors ultimately drive future cash flow and firm value in this industry.
Life Tech’s business is described in terms of its targeted markets; products, services, and after sale support; research and development activities; license agreements; and suppliers. These factors (in italics) are discussed next.
Life Tech’s targeted markets include life sciences, applied sciences, and medical sciences. Customers within the life sciences segment consist of laboratories generally associated with universities, medical research centers, government institutions, and other research institutions as well as biotechnology, pharmaceutical and chemical companies. Researchers at these institutions use Life Tech products to conduct research, clinical trials, and to improve the efficacy of drugs. The applied sciences segment serves a diverse range of industries, with a focus in the areas of forensic analysis; quality and safety testing; animal health testing, and the commercial production of genetically-engineered products. The medical services segment includes customers in clinical labs and medical institutions that use commercial technology for clinical and diagnostic purposes, and medical researchers that use Life Tech’s research-related technologies to search for new discoveries. Approximately 20% of the Life Tech’s revenues are derived from federal, university and/or research institutions funded by the US government.
Life Tech’s services and support activities provides limited warranties on equipment it sells for periods of up to two years from the date of the sale. The firm also offers service contracts to customers that are generally 1–5 years in duration after the original warranty period. Life Tech provides both repair services and routine maintenance services under these arrangements, and it also offers repair and maintenance services on a time and material basis to customers without service contracts.
Life Tech’s continued growth in market share is heavily dependent on research and development. Its core R&D skills include expertise ranging from biology to chemistry to engineering. The Company invested $341.9 million, $377.9 million and $375.5 million in research and development for the years ended December 31, 2012, 2011 and 2010, respectively. These expenditures comprise about 10.5% of annual revenue, slightly above the industry average. As of December 31, 2012, the Company had approximately 1200 employees engaged in research and development activities in the United States, Singapore, India, Germany, Norway, France, and the Netherlands.
Life Tech’s sales and marketing activities include a direct sales force of 3700 employees and a presence in more than 180 countries. The company also has over 1000 supply centers worldwide based in close proximity to customers’ laboratories to provide convenient access and an e-commerce website to provide easy online ordering of Life Tech products.
The firm manufactures and sells some of its existing products under the terms of license agreements that require it to pay royalties to the licensor based on the sales of products containing the licensed materials or technology. Although the company emphasizes its own research and development, its ability to license new technology from third-parties is, and will continue to be, critical to Life Tech’s ability to offer competitive new products.
The firm buys materials from many suppliers and has contracts with many third-parties for the manufacturing of products sold under the firm’s brand. The firm is not dependent on any one supplier as raw materials are generally available from a number of suppliers.
Competitor profiling consists of subjectively ranking a firm against its primary competitors in terms of critical success factors (i.e., those factors most responsible for determining success in an industry). A common technique is to create detailed profiles on each of major competitors. These profiles give an in-depth description of the competitor’s background, finances, products, markets, facilities, personnel, and strategies.
Table 9.14 provides a ranking of Life Tech compared to its primary competitors by those factors critical for success in the life sciences industry. These include the ability to innovate, collaborate with research and distribution partners, and to finance ongoing R&D spending. The critical success factors are weighted by their presumed importance and sum to one. Each competitor is ranked on a scale of one to ten with respect to each success factor. These scores are then totaled to create a competitor ranking in terms of the success factors. The primary competitors were selected from among twenty competitors each of which had a market value at yearend 2012 of $2.4 billion or more (see Table 9.15). Of those twenty firms, only those having a market value of greater than $9 billion were included the comparison of Life Tech and its competitors. Unlike the other firms listed as competitors, Thermo Fisher Scientific, Agilent Technologies, Quest Diagnostics, and Laboratory Corporation of America share many products and services in common with Life Technologies. Based on this subjective ranking, Life Tech has a slight competitive edge over Thermo Fisher Scientific and Agilent Technologies, its largest competitors in terms of size.
Table 9.14
Key industry success factors | Weight | Life technologies | Thermo Fisher Scientific | Agilent Technologies | Quest Diagnostics | Laboratory Corp of America |
---|---|---|---|---|---|---|
1—Ability to innovate | 0.4 | 8 | 8 | 7 | 4 | 3 |
2—Effective collaboration | 0.3 | 8 | 7 | 6 | 6 | 5 |
3—Access to capital | 0.3 | 8 | 7 | 7 | 4 | 2 |
Totals | 1.0 | 24 | 22 | 20 | 14 | 10 |
Table 9.15
Market cap $mil | Net income $mil | P/S | P/B | P/E | Dividend yield% | 5-Yr rev CAGR% | Net oper. margin% | Interest coverage | D/E | |
---|---|---|---|---|---|---|---|---|---|---|
Thermo Fisher Scientific Inc. | 34,749 | 1307 | 2.7 | 2.1 | 26.5 | 0.6 | 5.1 | 11.4 | 6.3 | 0.4 |
Agilent Technologies Inc. | 16,556 | 938 | 2.6 | 3.5 | 18.7 | .9 | 4.8 | 13.3 | 11.3 | 0.6 |
Life Technologies Corp | 13.064 | 476 | 3.5 | 2.6 | 27.9 | – | 24.3 | 17.1 | 5.3 | 0.4 |
Quest Diagnostics Inc. | 9263 | 762 | 1.4 | 2.4 | 11.8 | 1.9 | 1.9 | 16.9 | 7.5 | 0.8 |
Laboratory Corporation of America Holdings | 9118 | 567 | 1.7 | 3.6 | 17.2 | – | 6.9 | 18.7 | 11.0 | 1.0 |
Waters Corporation | 8381 | 484 | 4.6 | 5.2 | 17.7 | – | 4.6 | 27.4 | 18.4 | 0.7 |
Mettler-Toledo International, Inc. | 7336 | 298 | 3.3 | 9.0 | 25.6 | – | 5.5 | 15.1 | 17.8 | 0.5 |
Quintiles Transnational Holdings Inc | 5679 | 188 | 1.1 | − 8.0 | 29.1 | – | – | 8.2 | 3.0 | – |
Idexx Laboratories | 5633 | 187 | 4.4 | 10.5 | 31.6 | – | 7.0 | 18.5 | 68.7 | 0.0 |
Qiagen NV | 5298 | 47 | 4.2 | 2.0 | 114.9 | – | 14.1 | 16.3 | 7.2 | 0.3 |
Covance, Inc. | 4809 | 167 | 1.9 | 3.2 | 28.8 | – | 7.7 | 8.1 | 20.0 | – |
Lonza Group AG | 4693 | 139 | 1.2 | 2.0 | 31.0 | 2.3 | 6.5 | 9.7 | 3.4 | 1.2 |
PerkinElmer Inc | 4092 | 84 | 1.9 | 2.1 | 49.8 | 0.8 | 3.4 | 7.9 | 2.1 | 0.5 |
Eurofins Scientific Group S.A. | 3556 | 69 | 2.5 | 7.3 | 40.5 | – | 16.0 | 7.2 | 5.6 | 1.2 |
Cepheid | 2767 | − 2 | 7.2 | 10.1 | – | – | 20.7 | − 6.4 | − 144.1 | 0.0 |
Alere Inc | 2721 | − 130 | 0.9 | 1.8 | – | – | 27.4 | 3.9 | 0.5 | 2.6 |
Swedish Orphan Biovitrum AB | 2670 | − 211 | 8.7 | 3.6 | – | – | 8.9 | − 2.8 | − 0.7 | 0.2 |
Icon PLC | 2484 | 80 | 1.5 | 3.1 | 31.2 | – | 19.0 | 7.3 | 35.5 | – |
Industry average | 7357 | 277 | 2.3 | 3.2 | 26.9 | 0.4 | 8.9 | 11.3 | 25.4 | 0.7 |
Notes: P/S, price to sales ratio; P/E, price to earnings ratio; PB, price to book ratio; CAGR, compound annual average growth rate.
Life Tech’s historical performance in terms of its gross profit margin has been remarkably stable over time at approximately 56% (see Table 9.16). This table displays simple averages over different time periods as well as that estimated using regression analysis. The historical resiliency of the firm’s gross margin caused Mr. Lucier to use the historical gross margin in valuing the firm, despite anticipated future pricing pressures. The firm’s revenue growth rate has averaged a 6.5% compound annual average growth rate since 2008 when the firm completed an acquisition that nearly doubled the size of the company. Mr. Lucier directed his financial staff to evaluate the impact of different revenue growth rate, cost reduction, and asset utilization assumptions, as well as increasing Life Tech’s leverage, to assess the impact of alternative strategies on the firm’s market value.
Table 9.16
Average 1998–2012 | 56.46% |
Average 2003–2012 | 56.38% |
Average 2008–2012 | 56.83% |
Regression 1998–2012 | 56.73% |
The firm’s historical performance has exceeded major financial benchmarks. Life Tech’s price to earnings, cash flow, and sales ratios exceeded both the life sciences industry average and the S&P 500 average as of the end of 2012 (see Table 9.17). Table 9.18 shows Life Tech’s historical data for selected financial metrics.
Table 9.17
Life technologies | Life sciences industry avg. | S&P 500 | Life technologies 5 yr. avg. | |
---|---|---|---|---|
Price/earnings | 27.9 | 26.9 | 17.1 | 42.7 |
Price/book | 2.6 | 3.2 | 2.5 | 1.7 |
Price/sales | 3.5 | 2.3 | 1.6 | 2.3 |
Price/cash flow | 16.1 | 10.4 | 10.7 | 11.5 |
Note: Price/cash flow = 3 yr. avg.
Table 9.18
2003–12 | 2004–12 | 2005–12 | 2006–12 | 2007–12 | 2008–12 | 2009–12 | 2010–12 | 2011–12 | 2012–12 | TTM | |
---|---|---|---|---|---|---|---|---|---|---|---|
Revenue ($millions) | 778 | 1024 | 1198 | 1263 | 1282 | 1620 | 3280 | 3588 | 3776 | 3799 | 3842 |
Gross margin (%) | 60.3 | 59.4 | 58.7 | 59.5 | 55.9 | 58.1 | 55.6 | 58.7 | 55.9 | 56.2 | 57.9 |
Operating income ($millions) | 89 | 136 | 127 | − 158 | 178 | 167 | 386 | 612 | 648 | 665 | 683 |
Operating margin (%) | 11.5 | 13.3 | 10.6 | − 12.5 | 13.9 | 10.3 | 11.8 | 17.1 | 17.2 | 17.5 | 17.8 |
Net income ($millions) | 60 | 89 | 132 | − 191 | 143 | 31 | 145 | 378 | 378 | 431 | 476 |
Earnings per share ($s) | 0.59 | 0.82 | 1.17 | − 1.86 | 1.48 | 0.30 | 0.80 | 1.99 | 2.05 | 2.40 | 2.71 |
Shares (millions) | 103 | 121 | 120 | 103 | 97 | 104 | 181 | 191 | 186 | 179 | 175 |
Book value per share ($s) | 16.64 | 18.67 | 19.32 | 16.95 | 18.96 | 37.43 | 22.36 | 24.33 | 25.76 | 27.17 | 28.79 |
Operating cash flow USD mil | 168 | 253 | 309 | 235 | 324 | 366 | 714 | 739 | 809 | 778 | 826 |
Cap spending ($millions) | − 32 | − 39 | − 726 | − 70 | − 78 | − 82 | − 181 | − 131 | − 108 | − 136 | − 142 |
Free cash flow ($millions) | 136 | 214 | − 417 | 165 | 245 | 284 | 534 | 608 | 701 | 642 | 684 |
The Life Tech CEO, Greg Lucier, and the Life Tech Board, were at a cross roads. The ongoing trend toward customer consolidation would require increased consolidation among life science companies. The strategic options available to the firm were clear: continue the firm’s current strategy, acquire a sizeable competitor to achieve economies of scale, scope, and purchasing, or to sell the firm to a competitor. The firm lacked the financial resources to acquire a major competitor. Therefore, that option was dismissed. Of the remaining two options, maintaining the current strategy or selling the firm, which would maximize shareholder value? In April 2013, the firm announced that it had agreed to merge with the industry leader, Thermo Fisher Scientific. The merger, discussed in detail in Chapter 14, was completed in 2014.
Use the Microsoft Excel model entitled Target Firm Valuation Model Case Study Final Version on the companion site to this book to answer the following questions. Please see “Chapter Overview” section of this chapter for the site’s internet address. The model already contains data and an estimate of Life Tech’s enterprise and equity valuations based on this data and a set of assumptions about the planning period spanning 2014 through 2018, as well as the years beyond. In answering the following questions, assume the valuation provided in this model represents the firm’s base case and reflects what the firm could do if it continued the business strategy in effect in 2012.
Solutions to these case study discussion questions are available in the Online Instructor’s Manual for instructors using this book (https://textbooks.elsevier.com/web/Manuals.aspx?isbn=9780128150757).