Acquisition Modeling Mistakes
Insufficient or inadequate analysis of an acquisition candidate is an invitation for calamity—the proverbial equivalent of running with scissors. In fact, studies have listed “insufficient analysis” as one of the leading causes of M&A failure. By not performing a diligent and complete analysis, a buyer significantly increases the risk of stepping into the overpayment trap.
Financial models are used to analyze historic financial statement data, to prepare forecasts and projections (forward-looking statements), to support valuation and pricing considerations and to evaluate return on investment.
Acquisition modeling errors fall into four general areas:
- Accuracy and completeness of the base data.
- The analytical procedures utilized.
- The variables and assumptions used by the analyst.
- The inadvertent or intentional misuse of the output generated by the acquisition modeling process.
Errors or mistakes in any of the above areas can reduce the efficacy of any quantitative analysis and its ability to support sound, economic decision making—a key defense in side-stepping the overpayment trap.
The base data used in acquisition modeling starts with the target company’s financial statements, but may also include budgets, financial projections and other reports prepared by the company. Data from external sources includes industry outlooks, financial benchmarking data, and valuation data (e.g., value multiples, premiums/discounts, and comparable transaction data). Errors with base data include:
- Historic financial data that is not complete, accurate or fairly presented.
- Not analyzing a sufficient number of years of historic data to be able to identify emerging trends, weaknesses and possible accounting irregularities.
- Inappropriate add-back or normalization adjustments to historic financial statements (recasting).
- Using industry benchmark data that is not consistent with the operations of the target company.
- Only preparing a projected income statement. Without a balance sheet and cash flow projection, cash flow metrics can not be properly calculated.
- Inappropriately applying pricing multiples. No two companies are a perfect comparison. Comparison data can be misapplied an number of ways such as:
- Using the wrong industry or market sector.
- Not making adjustments based upon company size, transaction size, transaction terms and differences in the calculation of the multiples used in the source data.
- Applying public company multiples to a private company without applying a discount for lack of marketability.
There are a number of analytical procedures (methodology) that are available for acquisition modeling. These procedures are used to analyze and benchmark historic data, create projections, value and establish a price for an acquisition and evaluate return on investment. These procedures can be performed using a variety of tools or can be integrated in a single system. These procedures should be based upon established valuation and finance theory. When the theory is misapplied, the model’s ability to support sound decisions is diminished. Errors involving modeling procedures arise from:
- Using various models within an organization that don’t work together and are each designed by a different person (who may no longer even be associated with the company).
- Only preparing annual projections when monthly statements are needed to determine the adequacy of short-term cash flow and liquidity given the company’s business cycle.
- Embedding assumptions directly into a spreadsheet so they become hidden and sometimes forgotten.
- Not including transaction costs and actual funding terms in the model.
- Not adjusting for the changes in the form and structure of the transaction (stock or asset purchase and any related debt or liability assumptions).
- Not considering the adequacy of working capital and capital expenditures. This is a common shortfall when using when EBITDA as the earnings base for valuation and pricing purposes. (We recommend that buyers use discounted free cash flow to evaluate ROI.)
- Fixating on a “favorite” valuation method as opposed to using a number of methods under each of the main approaches (Income, Asset and Market Comparables).
- Relying on valuation “rules of thumb” such as multiples of earnings that may not be relevant or appropriate given the specific risks and rewards of the contemplated transaction.
- Not reconciling GAAP with Tax Basis projections.
- Using the present value (PV) of future cash flows instead of net present value (NPV), which equals the PV of cash flows less the amount of the investment.
- Evaluating investments solely on the basis of a non-discounted “payback period,” which doesn’t account for the time value of money.
- Calculating the NPV of discounted free cash flow using the wrong investment base. There are two methods of calculating FCF: FCF available to Equity and FCF available to Total Invested Capital. FCF to Total Invested Capital is usually employed when evaluating returns on a debt-free basis.
- Confusing cost of capital, discount rate, hurdle rate and capitalization rates.
- Estimating a discount rate that’s appropriate for a specific earning base and then applying that rate to the wrong earnings base.
The base financial data is the input—raw numeric materials. The procedures utilized in an acquisition model along with an analyst’s assumptions (variables) create a “quantitative product” that can be used to facilitate decision making.
In the next portion of this article will examine errors arising from the inappropriate assumption and the misuse or abuse of an acquisition model’s “quantitative product.”
Once developed and populated with base data, an acquisition model can test a host of variables and assumptions. These assumptions can be applied to historic data and can yield many insights into the viability of an acquisition. However, a model, no matter how accurate its base data and methodologies, will yield specious results if unreasonable or inappropriate assumptions are applied. This list of inappropriate assumptions that can be applied includes:
- Not updating the analysis based upon changes in proposed transactions terms and updated data that surfaces through the due diligence, negotiation and funding process.
- Developing projections based upon rules of thumb or arbitrary percentages rather than actual plans along with their attendant expenditures and anticipated outcomes.
- Not factoring the actual purchase price package into the projection. The purchase price package includes all forms of consideration paid to the seller.
- Overly optimistic projections of future revenues, cost savings and profits.
- Not adjusting line-item expenditures and expenses to keep up with revenue growth.
- Not considering future funding and internal investment requirements.
- Using an inappropriately low cost of capital and investment hurdle rate when evaluating ROI.
- Applying the wrong earnings base when evaluating ROI. The preferred earnings measure is free cash flow.
- Using discount and capitalization rates that do not appropriately reflect the risk of the investment. (The cost of capital is only the starting point.)
- Failure to include the expense of exploiting assumed synergies and cost savings.
An analyst can take great care in gathering base data, use exquisite modeling techniques and apply reasonable and appropriate assumptions; however, the results of the analysis (output) can be misused or abused. The list of potential misuses includes:
- Analyzing an acquisition as a mere formality that, if it makes it out of the CFO’s office, is not taken seriously by management or integrated into the senior-level decision process.
- Using “post-acquisition” assumptions to project earnings in order to arrive at a “pre-acquisition” value or purchase price. Increasing the price to the seller for improvements to be made by the buyer is tantamount to rewarding the seller for the fruits of the buyer’s efforts—a surefire way to overpay.
- Cherry-picking the results of the analysis to confirm the biases of the analyst or the ultimate consumer of the information.
- Manipulating assumptions in order to confirm an already-decided outcome.
- Marginalizing the results of the analysis if they don’t confirm the thinking of the “team” or those championing the acquisition.
- Assuming that a high level of detail implies a high degree of accuracy.
- Relying upon a model as a literal representation of the future.
- Presenting projections and ROI analysis without disclosing assumptions.
- Using the results of the analysis as a promise, or implied promise of future performance.
Finally, financial models are ultimately driven by the people whose judgment and expectations frame the analysis. These subjective drivers shape the assumptions, which then determine the quantitative output of the model.
An honest financial model in the hands of an informed and diligent analyst can provide valuable feedback on the implications of a host of financial assumptions and variables to arrive at an economically sound transaction—one of the best ways to avoid the overpayment trap. In the final analysis, an honest financial model is a “best estimate” of the cost of the transaction and the anticipated returns. Just as a drawing of a glass might look good on paper, the real test for any financial model is whether it holds any water in real life.
With sophisticated valuation and financial models like MoneySoft DealSense Plus, a buyer can evaluate the significance of a host of variables and assumptions to support smart decision making. In order to make the most of a model, the analyst/planner wants to carefully weigh the appropriateness and reasonableness of all assumptions. A blueprint for a glass might look good on paper, but the real question is, “will it hold water in real life?”
By Robert B. Machiz
© 2007 MoneySoft, Inc. All rights reserved.