Chapter 5

System Selection

Installing supply chain management (SCM) systems, whether a stand-alone system or as a component of an enterprise resource planning (ERP) system, would seem to be a simple matter. After all, the software, while expensive, has been thoroughly tested by many customers. However, ERP implementations are consistently reported to have failure rates in excess of 60%.¹ A business case should be a key part of the process of selecting the form of supply chain software for an organization. This chapter will demonstrate fundamental means of financial analysis and show how other methods can be used to consider other factors describing expected project performance.

Cost-benefit analysis seeks to identify accurate measures of benefits and costs in monetary terms and uses the ratio of benefits to costs. Costs and benefits for software systems are inherently difficult to estimate accurately because the many uncertainties, many hidden (unexpected) costs, and potential benefits are difficult to measure precisely.

Total Cost of Ownership

Different types of cost are unique to supply chain software applications:

Total Cost of Ownership (TCO) has long been recognized as a significant factor in supply chain software strategies and decisions. Yet while both end users and vendors tend to talk about lower TCO, and many vendors claim it as a point of differentiation, seldom do they speak in terms of specific metrics.²

Because supply chain systems involve long time frames (for benefits, if not for costs as well), considering the net present value of benefits and costs is important. We will start with basic cost-benefit analysis and then consider value analysis (one way to deal with subjective benefits) and a simple version of multiattribute utility theory (a means to consider trade-offs across multiple measures of value).

Cost-Benefit Example

Consider a proposed supply chain software implementation involving an implementation study in Year 1 conducted by a small team of company personnel, aided by a hired consultant at $500,000 in the first year. This is a fairly small implementation, and at this stage of the analysis, typically expected costs are underestimated. This analysis in Year 1 includes some business process reengineering and the formation of a training team. This cost analysis assumes the purchase of a $500,000 supply chain software system from a reputable vendor, with maintenance costs for patches and upgrades of $100,000 each year thereafter. Extra hardware to support the proposed system will be needed in Year 1 at $750,000. Training expense will be low in Year 1, high in Year 2, and drop thereafter. The firm wants to treat software acquisition, hardware acquisition, and consulting in the first year as an investment.

Operating the system will also incur costs. This budget is expected to be $1 million in Year 1, growing at a rate of 10% per year thereafter. The firm’s cost of capital is 10%.

The board disagreed somewhat about the expected rate of growth of benefits. The dominant group on the board expects benefits from the supply chain system to be $2 million per year in Year 2, $3 million in Year 3, and to grow at 30% per year thereafter. The time horizon selected is 5 years, as new software is expected to outdate any currently available system after that time.

The board often disagreed about assumptions in cost-benefit models. A vocal minority thinks that this expectation is far too high and that benefits will only grow at the rate of 10% annual increase after Year 3. This data is summarized in Table 5.1.

Table 5.1. Cost-Benefit Analysis Input Data—Example Proposal
Year	Internal team	Consultants	Software	Hardware	Training	Benefits
1	1,000,000	500,000	500,000	750,000	500,000
2	1,100,000		100,000		750,000	2,000,000
3	1,210,000		100,000		1,000,000	3,000,000
4	1,331,000		100,000		800,000	3,900,000
5	1,464,100		100,000		400,000	5,070,000
Totals	6,105,100	500,000	900,000	750,000	3,450,000	13,970,000

Cost-benefit analysis is somewhat arbitrary because it usually is applied considering up-front expenditure as investment, used in the denominator, with net cash flow thereafter used in the numerator. Continuing with our earlier example, investment here is the $2,150,000 spent on consultants, software acquisition, and hardware. One version of the cost-benefit ratio would thus be the following:

($13,970,000 - $6,105,100 - $3,450,000)/$2,150,000 = 2.053

This looks like a very profitable investment, with the investment covered 2.053 times. Furthermore, the arbitrary nature of what to include as investment can be demonstrated by assigning all costs to investment (not recommended, but for purposes of demonstration):

$13,970,000/($6,105,100 + $500,000 + $900,000 + $750,000 + $3,450,000) = 1.193

Here benefits still cover investment, but the ratio is much lower. Another problem is that the benefits are all in the future, while the bulk of the costs are early. Money has a time value.

Net Present Value Calculation

Net present value (NPV) is calculated by discounting the net cash flow in each period by the discount rate to the power of the time period and then adding these discounted cash flows over the horizon of the analysis. Table 5.1 organizes cash flows for each category by the time period used in the analysis (in this case, by year). Note that a more accurate NPV can be obtained using a shorter time period. Ultimately you could calculate NPV per second, but that is far too precise. Your savings account is probably calculated on a daily basis. For purposes of analysis, a monthly period is probably good. But the shorter the time period, the more spreadsheet rows would be required, and the harder it would be to display. We will use a year as our time horizon.

NPV is obtained by aggregating each time period’s cash flow and dividing by the discount rate to the power of the time period, as shown in Table 5.2 using a discount rate of 1.1 per year.

Table 5.2. Net Present Value Calculation—Example Proposal
Year	Net cash flow	Discounted
1	-3,250,000	-2,954,545
2	+50,000	+41,322
3	+690,000	+518,407
4	+1,669,000	+1,139,949
5	+3,105,900	+1,928,520
Total	+2,264,900	+673,653

For Year 1, the total cash flow (benefits minus all five expense categories) is -$3,250,000. That is equivalent in today’s value to -$3,250,000/(1.1^1), or $2,954,545. For Year 2, the total cash flow is +$50,000, equivalent in today’s value to $50,000/(1.1^2), or $41,322. In this case, over the 5-year planning horizon, nominal net cash flow is estimated to be a net gain of over $2 million. This stream of cash flow at the cost of capital (discount rate) of 1.1 is a net gain of $673,653, indicating that at the cost of capital used, over the planning horizon considered, this is a worthwhile investment. (The indicator is whether or not the sum of discounted cash flows is positive or not.)

Note that if we increased the discount rate to 1.2, the NPV would be a negative $221,234, meaning that the proposal would not financially justify a cost of capital of 20% per year. This implies that the proposal would break even if the project achieved somewhere between a 10% and a 20% rate of return. We can try various discount rates on a spreadsheet until we identify a discount rate just above 16.9% where the NPV will be zero. The implication is that this investment would return 16.9% per year on the investment.

Cash flow analyses of this type are very useful, especially with spreadsheet support. It clearly displays the many assumptions made. It is common for business decision makers to be uncertain about most of the entries in the spreadsheet. In fact, it is common for different individuals to have different beliefs about specific assumed values. The good thing about spreadsheet analysis of expected cash flow is that each different set of assumptions could be entered, and expected NPV identified.

Payback

One of the most common reasons for company failure in the United States is lack of cash flow. In our example, if the firm has cash flow difficulties, the investment would be less attractive than if they had adequate cash reserves. Making the assumption that over time cash flow will turn positive at some point and remain positive thereafter, we can use another metric, payback, to identify the time until the investment will be recovered. This could be done in net present value terms (using discounted cash flows), or in nominal terms (with undiscounted cash flow). Either way, payback is interested in how long it will take to recover investment. The calculation is simply cumulative cash flow. Given the assumption of an initial investment leading to future positive cash flows, the time until cumulative cash flow turns positive is payback time. This is often used by decision makers to gauge the attractiveness of an investment. Table 5.3 shows calculations for our example SCM system, for both nominal and discounted cash flow.

Here the payback period is under 5 years in both cases. Using nominal (undiscounted) values, it would take 4 years and just over 3 months to recover the initial investment (assuming a linear rate of cash flow in year 5). With the discounted numbers, it would take 4 years and almost 8 months to recover the investment. In either case, the payback is between 4 and 5 years. We can also see that the firm will need cash reserves of at least $3,250,000 to survive the project (nearly $3 million in net present value terms).

Table 5.3. Payback Calculation
Year	Net (undiscounted)	Cumulative	Net (discounted 10%)	Cumulative
1	-3,250,000	-3,250,000	-2,954,545	-2,954,525
2	+50,000	-3,200,000	+41,322	-2,913,223
3	+690,000	-2,510,000	+518,407	-2,394,816
4	1,669,000	-841,000	+1,139,949	-1,254,866
5	+3,105,900	+2,264,900	+1,928,520	+673,653

Sensitivity Analysis

A very good thing about spreadsheet cash flow models is that you can include any assumption. (On the other hand, the bad thing is that so many assumptions are required!) To demonstrate, we might assume a vocal minority on the board thinks that the expected rate of benefit increase is too high, and instead of 30% growth in benefits after Year 2, they expect that these benefits will only grow at the rate of 10% annually. We can demonstrate the impact of this assumption change in Table 5.4. (That’s what sensitivity analysis is—checking for the impact of changed entries into the model.)

Here the assumption in benefit growth in Years 4 and 5 doesn’t change the decision if payback is desired within 5 years. But the project would be expected to be much less profitable (to the tune of $2 million in nominal cash flow). The NPV at 10% discount would drop to -$630,282, indicating that with the lower benefit growth assumption, the project would not return 10% per year. The return on investment (ROI) turns out to be 1.021, or an average of 2.1% return on the firm’s money. They could probably find better things to do with their investment capital should benefit growth be the more conservative.

The problem with cash flow spreadsheet analysis is that practically every entry is an assumption, which could be debated. As we said, the nice thing is that it is easy to change and see the impact of any one assumption (or set of assumptions). But there can be many details to check.

Table 5.4. Impact of Benefit Growth Rate
Year	Expenses	High benefits	High cumulative	Low benefits	Low cumulative
1	3,250,000		-3,250,000		-3,250,000
2	1,950,000	2,000,000	-3,200,000	2,000,000	-3,200,000
3	2,310,000	3,000,000	-2,510,000	3,000,000	-2,510,000
4	2,231,000	3,900,000	-841,000	3,300,000	-1,441,000
5	1,964,100	5,070,000	+2,264,900	3,630,000	+224,900
Totals	11,705,100	13,970,000		11,930,000

Value Analysis

Peter Keen proposed value analysis as an alternative to cost-benefit analysis in the evaluation of proposed information system projects. These projects, clearly attractive to business firms, suffer in that their benefits are often heavily intangible. For instance, decision support systems are meant to provide decision makers with more complete information for decision making. But what is the exact dollar value of improved decision making? We all expect the success of firms to be closely tied to effective decision making, but better decision making cannot be rationally and accurately measured.³

Value analysis was presented as a way to separate the benefits measured in intangible terms from costs, which are expected to be more accurately measurable. Those tangible benefits as well as costs can be dealt with in net present terms, which would provide a price tag for proposed projects. The value of the benefits would be descriptive, with the intent of showing the decision makers accurate descriptions of what they were getting, along with the net present price. The decision would then be converted to a shopping decision. Many of us buy automobiles, despite the fact that the net present cost of owning an automobile is negative. Automobiles provide many intangible benefits, such as making the driver look very sporty, letting the driver speed over the countryside, and letting the driver transport those they would like to impress. The dollar value of these intangible benefits is a matter of willingness to pay, which can be identified in monetary terms by observing the purchasing behavior of individuals. This measurement requires some effort and is different for each individual.

Assume a firm is considering five different ways to implement some or all of an SCM (plus the alternative of doing nothing). The options, with estimated investments and benefits, are given in Table 5.5.

Table 5.5. Alternative System Implementation Options for Example ERP
Alternative	Investment	NPV
A–Full vendor ERP implementation, all modules	$15 million	$5 million
B–Vendor ERP, only FA, MM and SCM modules	$11 million	$7 million
C–Vendor, only SCM module	$8 million	$8 million
D–In-house development	$25 million	-$2 million
E–Open-sourced system	$3 million	$4 million
F–Do nothing (current system)	0	0

Table 5.6. Qualitative Features of ERP Options in Example
Alternative	BPR	Standardize	Internet	Advantage	Keep up	Disruption
A–Full	Complete	Complete	Best	Equal	Best	5 years
B–FA, MM, SCM	Partial	Partial	Best	Less than A	Less than A	4 years
C–SCM	Minimal	Partial	Best	Less than B	Less than B	1 year
D–In house	Complete	Complete	Problematic	Best	Mediocre	7 years
E–Open source	Minimal	Partial	Good	Moderate	Low	2 years
F–Nothing	Nothing	Nothing	Worst	Worst	Worst	0

Value analysis would consist of presenting the decision maker with the intangible comparisons in performance and placing the decision in the context of whether or not the decision maker thought the improvements provided by the new machine were worth their price tag. This requires an analysis of expected benefits from each system. The following are reasons this particular management team is interested in an SCM:

The expected performance of each alternative on the six qualitative factors is given in Table 5.6.

In this approach, the expected benefits are understood to be highly variable and are treated as a rough estimate. Costs are assumed to be a bit more reliable. Thus the options, in descending order of price, are as follows:

A—Full implementation of vendor product expected to cost $15 million:

Expected benefit: NPV $20 million, for net gain of $5 million.

B—Partial implementation of vendor product expected to cost $11 million:

Expected benefit: NPV $18 million, for net gain of $7 million.

C—Minimal implementation of vendor product expected to cost $8 million:

Expected benefit: NPV $16 million, for net gain of $8 million.

D—In-house implementation expected to cost $25 million:

Expected benefit: NPV $23 million, for net gain of -$2 million.

E—Open-sourced system expected to cost $3 million:

Expected benefit: NPV $7, for net gain of $4 million.

F—Do nothing, expected to cost $0:

Expected benefit: NPV $0, for net gain of $0 million.

Management can now view each option as a market basket of benefits, each with its own price tag. In this case, the key difference is building the system in-house, adopting a variant of the vendor system, installing an open-source software system, or doing nothing. Building the system in-house clearly has many risks and involves the most out-of-pocket investment. Management might well discard that option unless they are very confident in their ability to develop complex software projects. The open-sourced option has attractive features but involves more uncertainties and doesn’t provide the best BPR options. Among the vendor options, Option A has the best features on reengineering, standardization, and Internet connectivity. But it would involve 5 years of disruption, and call for a $15 million investment. Option B would save $4 million in investment with the same Internet access at only 4 years of disruption but would sacrifice a bit on BPR factors, standardization, relative competitive advantage, and keeping up with competitors. Management might feel that the gains in disruption are worth the sacrifices in BPR, standardization, competitive advantage, and competitiveness. For only an $8 million investment, Option C would involve sacrifice of even more BPR, strategic advantage, and competitiveness but would save 3 additional years of disruption. However, it may be paramount to obtain higher degrees of methods improvement through business process reengineering and standardization of business functions across the organization. By focusing on the important features involved, management may be able to conclude that Option A, B, or C is preferable to the other options available.

Taking value analysis one more step, to quantify these intangible benefits in terms of value (not in terms of dollars) takes us to multiple criteria analysis.

Multiple Objective Analysis

Profit has long been viewed as the determining objective of a business. However, as society becomes more complex, and as the competitive environment develops, businesses are finding that they need to consider multiple objectives. While short-run profit remains important, long-run factors such as market maintenance, product quality, and development of productive capacity often conflict with measurable short-run profit.

Conflicts are inherent in most interesting decisions. In business, profit is a valuable concentration point for many decision makers because it has the apparent advantage of providing a measure of worth. Minimizing risk becomes a second dimension for decision making. Cash flow needs become important in some circumstances. Businesses need developed markets to survive. The impact of advertising expenditure is often very difficult to forecast. Yet decision makers must consider advertising impact. Capital replenishment is another decision factor, which requires consideration of trade-offs. The greatest short-run profit will normally be obtained by delaying reinvestment in capital equipment. Many U.S. companies have been known to cut back capital investment in order to appear reasonably profitable to investors. Labor policies can also have impact on long-range profit. In the short run, profit will generally be improved by holding the line on wage rates and risking a high labor turnover. Some costs are not obvious, however, in such a policy. First, in a high-turnover environment, training costs rise. The experience of the members of an organization can be one of its most valuable assets. Second, it is difficult for employees to maintain a positive attitude when their experience is that short-run profit is always placed ahead of employee welfare. And innovative ideas are probably best found from those people who are involved with the grassroots of an organization—the workforce.

This variety of objectives presents decision makers with the need to balance conflicting objectives in ERP option selection. We will present the simple multiattribute rating technique (SMART), an easy-to-use method to aid selection decisions with multiple objectives.

Multiple criteria analysis considers benefits on a variety of scales without directly converting them to some common scale such as dollars. Multiple criteria analysis (with its many variants) is not at all perfect. But it does provide a way to demonstrate to decision makers the relative positive and negative features of alternatives and gives a way to quantify the preferences of decision makers.⁴

Fit with business procedures was selected among the three most important criteria by about one-half of the respondents and was listed as the single most important criterion by over one-third. While ERP vendors have devoted a great deal of effort to making their packages match existing business processes, the importance of this criterion is based on the high cost and bother of configuring and implementing ERP systems. Selection of a vendor involved less variance among criteria. Product functionality and quality were the criteria most often reported to be important.

Perhaps the easiest application of multiple criteria analysis is the SMART analysis, which identifies the relative importance of criteria in terms of weights and measures the relative performance of each alternative on each criterion in terms of scores.⁵ We will first explain scores.

Scores: Scores in SMART can be used to convert performances (subjective or objective) to a zero-to-one scale, where zero represents the worst acceptable performance level in the mind of the decision maker and one represents the ideal, or possibly the best performance desired. Note that these ratings are subjective, a function of individual preference. Scores for the criteria given in the value analysis example could be as in Table 5.7.

Table 5.7. Scores by Criteria for Each Option in Example
Option	BPR	Standard	Internet	Advantage	Competition	Disruption	Financial
A	1.0	1.0	1.0	0.7	1.0	0.1	0.85
B	0.9	0.7	1.0	0.5	0.8	0.3	0.90
C	0.6	0.7	1.0	0.2	0.6	0.9	0.95
D	1.0	1.0	0.6	1.0	0.1	0.0	0.0
E	0.6	0.7	0.8	0.6	0.4	0.8	0.7
F	0.0	0.0	0.0	0.0	0.0	1.0	0.2

Table 5.8. Worst and Best Measures by Criteria
Criteria	Worst measure	Best measure
Update systems (BPR)	Nothing	Complete
Standardize business processes	Nothing	Complete
Internet connectivity to suppliers and customers	None	Modern
Gain strategic advantage	Do nothing	Develop unique system
Keep up with competition	Do nothing	State-of-the-art vendor
Minimize disruption	7-year installation	Current system
Financial implications	Risk $25 mil, lose $2 mil	Risk $3 mil, gain $4 mil

Weights: The next phase of the analysis ties these ratings together into an overall value function by obtaining the relative weight of each criterion. In order to give the decision maker a reference about what exactly is being compared, the relative range between best and worst on each scale for each criterion should be explained. Many methods are available to determine these weights. In SMART, the process begins with rank-ordering the four criteria. A possible ranking for a specific decision maker might be as given in Table 5.8.

To obtain relative criterion weights, the first step is to rank-order criteria by importance. Two estimates of weights can be obtained. The first assigns the least important criterion 10 points and assesses the relative importance of each of the other criteria on that basis. This process (including rank-ordering and assigning relative values based on moving from worst measure to best measure based on most important criterion) is demonstrated in Tables 5.9 and 5.10.

Table 5.9. Weight Estimation From Perspective of Most Important Criterion
Criteria	Worst measure	Best measure	Assigned value
1-Gain strategic advantage	Do nothing	Develop unique system	100
2-Keep up with competition	Do nothing	Use state-of-the-art	70
3-Internet connectivity	None	Modern	50
4-Update systems (BPR)	Nothing	Complete	30
5-Minimize disruption	7-year installation	Current system	20
6-Financial implications	Risk $25 mil, lose $2 mil	Risk $3 mil, gain $4 mil	10
7-Standardize business processes	Nothing	Complete	3

Table 5.10. Weight Estimation From Perspective of Least Important Criterion
Criteria	Worst measure	Best measure	Assigned value
7-Standardize business processes	Nothing	Complete	10
6-Financial implications	Risk $25 mil, lose $2 mil	Risk $3 mil, gain $4 mil	25
5-Minimize disruption	7-year installation	Current system	30
4-Update systems (BPR)	Nothing	Complete	50
3-Internet connectivity	None	Modern	60
2-Keep up with competition	Do nothing	Use state-of-the-art	70
1-Gain strategic advantage	Do nothing	Develop unique system	100

The total of the assigned values in Table 5.9 is 283. One estimate of relative weights is obtained by dividing each assigned value by 283. Before we do that, we obtain a second estimate from the perspective of the least important criterion, which is assigned a value of 10 as in Table 5.10.

These assigned values in Table 5.10 add up to 345. The two weight estimates are now as shown in Table 5.11.

Table 5.11. Criterion Weight Development
Criteria	Based on best	Based on worst	Compromise
1-Gain strategic advantage	100/283	0.35	100/345	0.29	0.33
2-Keep up with competition	70/283	0.25	70/345	0.20	0.23
3-Internet connectivity	50/283	0.18	60/345	0.17	0.17
4-Update systems (BPR)	30/283	0.11	50/345	0.14	0.12
5-Minimize disruption	20/283	0.07	30/345	0.09	0.08
6-Financial implications	10/283	0.04	25/345	0.07	0.05
7-Standardize business processes	3/283	0.01	10/345	0.03	0.02

The last criterion can be used to make sure that the sum of compromise weights adds up to 1.00.

Value Score: The next step of the SMART method is to obtain value scores for each alternative by multiplying each score on each criterion for an alternative by that criterion’s weight and adding these products by alternative. Table 5.12 shows this calculation.

These value scores (shown in the totals row) provide a relative score that can be used to select (take the alternative with the highest value score), or to rank-order (by value score). In this case, the SMART analysis indicates a preference for Option A, the full version of the vendor ERP system. This is followed relatively by Option B, which is to reduce functionality to finance and accounting and materials management modules. Other options have lower ratings, while doing nothing is practically off the chart in a negative way.

Table 5.12. Value Score Calculation
Criteria	Weight	Option A	Option B	Option C	Option D	Option E	Option F
Strategic advantage	0.33	× 0.7 = 0.231	× 0.5 = 0.165	× 0.2 = 0.066	× 1.0 = 0.330	× 0.6 = 0.198	× 0.0 = 0.000
Competition	0.23	× 1.0 = 0.230	× 0.8 = 0.184	× 0.6 = 0.138	× 0.1 = 0.023	× 0.4 = 0.092	× 0.0 = 0.000
Internet	0.17	× 1.0 = 0.170	× 1.0 = 0.170	× 1.0 = 0.170	× 0.6 = 0.102	× 0.8 = 0.136	× 0.0 = 0.000
Update (BPR)	0.12	× 1.0 = 0.120	× 0.9 = 0.108	× 0.6 = 0.072	× 1.0 = 0.120	× 0.6 = 0.072	× 0.0 = 0.000
Minimize disrupt	0.08	× 0.1 = 0.008	× 0.3 = 0.024	× 0.9 = 0.072	× 0.0 = 0.000	× 0.8 = 0.064	× 1.0 = 0.080
Financial	0.05	× 0.85 = 0.043	× 0.9 = 0.045	× 0.95 = 0.048	× 0.0 = 0.000	× 0.7 = 0.035	× 0.20 = 0.010
Standardize	0.02	× 1.0 = 0.020	× 0.7 = 0.014	× 0.7 = 0.014	× 1.0 = 0.020	× 0.7 = 0.014	× 0.0 = 0.000
Totals	1.00	0.822*	0.710	0.580	0.595	0.611	0.090

Supply Chain Software ERP Issues

Supply chain software can be very effective in managing large supply chains. Unfortunately, more than 90% of the companies that have implemented ERP systems have not had a truly successful implementation the first time around.⁶

These two points may seem obvious, but supply chain management is not usually initially approached in this manner. As a result, many problems come to pass during and after implementation. This often requires a reimplementation effort or at least a major tune-up. ROI comes from process improvements that supply chain software supports, not from new software itself. What’s the difference? Software alone, no matter how good it is, has little impact on improving business performance. If you continue to use presoftware business processes after implementation, you can anticipate identical or possibly worse performance. Software can, on the other hand, enable many new processes.

Table 5.13. Toroid International ERP Selection Data
Criteria	Weight	SAP score	IFS score	Syteline score
Business strategy	0.323	0.327	0.369	0.304
Change management	0.040	0.311	0.266	0.423
Risk	0.040	0.250	0.416	0.334
Functional fit	0.149	0.360	0.345	0.295
Cost and benefits	0.288	0.271	0.135	0.594
Technology	0.063	0.333	0.333	0.333
Vendor position	0.097	0.409	0.305	0.285
Overall score		0.320	0.287	0.392

The study confirmed the decision that Toroid had made, with the adopted Syteline system receiving the highest score. Table 5.13 demonstrates that Syteline’s greatest advantage was in cost and benefits, which had a relatively high weight.

Conclusion

Many costs arise when implementing supply chain software. Many of these are hidden and especially difficult to estimate because most organizations don’t repeat the exercise. We have reviewed some of the primary methods used to evaluate SCM proposals. Cost-benefit analysis (with net present value used if the time dimension is present) is the ideal approach from the theoretical perspective but has a number of limitations. It is very difficult to measure benefits and also difficult to measure some aspects of costs accurately. One view of dealing with this problem is to measure more accurately. Economists have developed ways to estimate the value of a life and the value of scenic beauty. However, these measures are difficult to sell to everybody.

Cost-benefit analysis provides an ideal way to proceed if there are no intangible factors (or at least no important intangible factors). However, usually such factors are present. Intermediate approaches, such as payback analysis and value analysis, exist to deal with some cases. More complex cases are better supported by multiple criteria analysis. One of the most obvious difficulties is that benefits, and even costs, can involve high levels of uncertainty. The element of chance can be included in cost-benefit calculations by using Monte Carlo simulation.⁸

Value analysis is one such alternative method. Value analysis isolates intangible benefits from those benefits and costs that are more accurately measurable in monetary terms and relies on decision-maker judgment to come to a more informed decision. The SMART method, one of a family of multiple criteria decision analysis techniques, provides a way to quantify these intangible factors to allow decision makers to trade off values.