Lecture 8 (Chapter 11): Project Analysis and Evaluation

(1)

Lecture 8: Project Analysis and Evaluation 1

Lecture 8 (Chapter 11):

Project Analysis and Evaluation

• Discounted cash flow analysis is a very powerful tool, but it is not easy to use.

• We have already seen one difficulty:

– How do we identify the cash flows?

• Today we begin to focus on a second difficulty:

– What if our cash flows are not certain?

• Risk plays a crucial part in DCF analysis. To understand cash fl ow risk, we will use several tools:

– Scenario analysis – Sensitivity analysis

• Break-even analysis

• Operating leverage – Simulation analysis

Capital Rationing

Definition: A situation where a firm has positive NPV projects, but cannot obtain funding to undertake them.

• Soft Rationing: Firm sets internal limits on capital available to its divisions.

Ø Used by firms as an alternative means of controlling investments where DCF is too hard or not understood.

• Hard rationing: Capital markets refuse to finance the firm.

Ø If the firm was willing to pay a high enough rate, could it find someone to invest? If so, perhaps the opportunity cost of capital was calculated incorrectly. If not, perhaps the cash flows are not correct.

Ø Market inefficiency (asymmetric information)

(2)

Evaluating NPV Estimates

• The cash flows that we use in DCF analysis are projections of the future.

• What will be the effect if these projections turn out to be inaccurate?

Ø Forecasting risk: bad projections can lead to bad decisions

• One way to look for problems in DCF is to ask: Why should we expect this project to have a positive NPV?

• The project must be better than all the alternatives available to the investor (opportunity cost of capital)

• Where is the source of value?

• Innovation, Low cost, Market niche, Economies of scale/scope

• How competitive is the market?

“What-if” Analysis

• What happens if our projections turn out to be wrong?

• Start with a Base Case that gives our best estimate of the future cash flows.

• Then vary the cash flows using

– Scenario analysis: imagine different possible states of the world, and project cash flows and NPVs for each state.

– Sensitive analysis: change one input variable and see how this affects the resulting NPV.

• Break-even Analysis: find the value of an input variable (typically sales) that sets the projects NPV to zero

• Operating Leverage: the degree to which a change in sales impacts the NPV

– Simulation analysis: use random variables as inputs and calculate NPV many times to determine the distribution of possible NPVs .

(3)

Example Base Case

• Fairways Driving Range expects rentals to be 20,000 buckets at

$3 per bucket. Equipment costs $20,000 and will be depreciated straight-line over 5 years and have a $0 salvage value. Variable costs are 10% of rentals and fixed costs are $45,000 per year.

Assume no increase in working capital nor any additional capital outlays. The required return is 15% and the tax rate is 15%.

Scenario Analysis

• Imagine three states of the world:

– Base case (our best estimate)

• Rent 20,000 buckets

• Variable costs are 10% of revenues – Best case (everything works out perfectly)

• Variable costs are 8% of revenues – Worst case (nothing goes like it should)

• Variable costs are 12% of revenues

• How will this change our decision?

(4)

Sensitivity Analysis

• Change only one input variable at a time and see how the NPV is affected.

• Find which assumptions are the most important – We can then spend more time checking these

assumptions

• Gives us an idea of the riskiness (variability) of our NPV estimate

• Focus on variables that cannot be directly controlled by the firm to see the effects of “nature” on our project.

• For example, try “optimistic” and “pessimistic” values.

Break-Even Analysis

• Find the level of sales that the project must achieve to have a positive NPV

• Remember “finding the bid price” from Lecture 7?

• Set NPV = 0 and solve for sales.

• Often it won’t be so easy to solve by hand.

• Question: What is the break-even level of the discount rate

called?

(5)

Accounting Break-Even Analysis

• Level of sales that results in zero EBIT and Net Income

• EBIT = Sales3(1-0.1) – 45,000 – 4,000 = 0 Ø Sales = 18,148

• General formula: Sales = (FC + Dep)/(Price – var cost)

• Note that when EBIT = 0, Net Income = EBIT*(1-tax) = 0

• Accounting break-even < Financial break-even (typically) – Ignores time-value of money

• So NPV < 0 at accounting break-even level of sales – What is the IRR?

Cash Break-Even Analysis

• Level of sales that results in zero yearly cash flow

• OCF = { [Sales*3(1 – 0.1) – 45,000 – 4,000]*(1-0.15) + 4,000} = 0 Ø Sales = 16,405

• Textbook General formula: Sales = FC/(Price – var cost)

• But this ignores effect of taxes

• Cash break-even < Accounting break-even < Financial break-even – Initial investment completely ignored

– NPV = -Investment – IRR = -100%

• Cash Break-Even is useful for the treasurer/cash manager to determine working capital needs

(6)

Operating Leverage

• Degree of Operating Leverage (DOL): The degree to which a change in sales affects Operating Cash Flow

– Can also be expressed as: the ratio of fixed costs to OCF

• DOL = 1 + FC/OCF

• Projects with high operating leverage have high fixed costs and low variable costs

Intuition: In a project with high fixed costs and low variable costs, a change in the level of sales will have a large impact on OCF because revenues will increase while costs will stay steady.

High operating leverage ? riskier OCF

Lever

Leverage

• The Degree of Operating Leverage is often a choice of the firm.

– High DOL examples:

– Low DOL examples:

• A related concept is “Financial Leverage”: the degree to which changes in EBIT affect earnings.

• Financial leverage is higher for firms with higher debt loads – Changes in revenues have greater effect on shareholders – Resulting rate of return is riskier

• Operating leverage and financial leverage are chosen to

compliment each other.

(7)

Simulation Analysis

• Scenario analysis and sensitivity analysis are both very limited in their ability to reflect all the possible outcomes.

• Simulation analysis lets us describe possible values of the inputs in a much more complete way (often as random variables), and lets us vary many inputs at the same time.

– Too difficult to solve analytically

Ø Monte Carlo Simulations

• Sample the input variables many times, and each time calculate the NPV, then analyze the distribution of possible NPVs.

• Time consuming, so let the computer do it.

Managerial Flexibility (Options)

• We have imagined the sole job of the manager as a “yes/no”

then wait for the outcome.

• In reality, managers get the “big bucks” because they need to be constantly making decisions as the project progresses:

– Should we wait before deciding

– Should we expand/contract the project – Should we switch inputs

– Should we abandon the project

• This flexibility increases the value (and hence the true NPV)

of the project

(8)

Lecture 8 (Chapter 11): Project Analysis and Evaluation