5. Calculate ROI – ROI Basics, 2nd Edition

5

Calculate ROI

What’s Inside This Chapter

To continue building credibility for your talent development programs, you need to demonstrate the economic value they add to the organization. Specifically, in this chapter you will learn the basic steps to move from Level 4 to Level 5 by:

• converting data to monetary value

• tabulating fully loaded costs

• calculating the ROI.

 

 

Converting Data to Monetary Value

The fundamental difference between Level 4 and Level 5 begins with converting the benefits of the program (Level 4) to monetary value. For some, this is a frightening task; others recognize that if standard values for the measures are unavailable, there are other techniques to convert measures to money.

Level 4 measures are defined as the consequence of applying knowledge and skills (Level 3) learned in a program. These consequences result in measures categorized as hard data and soft data. But what do these categories really mean?

Hard Data Versus Soft Data

Hard data include measures that are easy to collect and measure, quantifiable, easy to convert to monetary value, objectively based, common measures of organizations performance, and immediately credible with management. They are the primary measurements of improvement, presented in rational, undisputed facts. Hard data include measures of output, quality, cost, and time.

Every organization, private, public, social, or academic, has some form of these measures. Table 5-1 provides examples of measures representing hard data. Although not all-inclusive, this list should cover some measures tracked by your organization.

On the other hand, soft data represent measures that are difficult to measure, difficult to quantify, subjectively based, less credible as performance measures, and behaviorally oriented. The measures, although important, are often perceived as less reliable when measuring performance, due to an inherent level of subjectivity. Soft data include measures such as work habits, new skills, climate, development, satisfaction, and initiative.

Every organization has some measure that can be categorized as soft data. Table 5-2 presents examples of each category.

Table 5-1. Hard Data

Output

Quality

Units produced

Tons manufactured

Items assembled

Reports processed

Students graduated

Research grants awarded

Tasks completed

Number of shipments

New accounts generated

Errors

Waste

Rejects

Rework

Shortages

Defects

Failures

Malicious intrusions

Accidents

Cost

Time

Budget variances

Unit costs

Variable costs

Overhead costs

Operating costs

Penalties/fines

Project cost savings

Accident costs

Sales expense

Cycle time

Response time

Equipment downtime

Overtime

Processing time

Supervisory time

Meeting time

Work stoppages

Order response time

Table 5-2. Soft Data

Work Habits

New Skills

Absenteeism

Tardiness

First aid treatments

Safety violations

Communication

Decisions made

Problems solved

Grievances resolved

Conflicts avoided

Interaction with staff

Climate

Development

Number of grievances

Employee complaints

Employee engagement

Organizational commitment

Employee turnover

Number of promotions

Number of pay increases

Requests for transfer

Performance appraisal ratings

Job effectiveness

Satisfaction

Initiative

Job satisfaction

Customer satisfaction

Employee loyalty

Increased confidence

Implementation of new ideas

Innovation

Goals achieved

Completion of projects

Think About This

Select whether you think the measure represents hard data or soft data. What is improvement in the measure worth?

Objective Hard Soft

Decrease error rates on reports by 20 percent.

Decrease the amount of time required to complete a project.

Increase the customer satisfaction index by 25 percent in three months.

Reduce litigation costs by 24 percent.

Improve teamwork.

Enhance creativity.

Increase the number of new patents.

Reduce absenteeism.

Tangible Versus Intangible Data

Many readers consider measures like customer satisfaction, teamwork, creativity, and absenteeism as soft data items. Do you? Now, think about this:

• If customer satisfaction is a soft measure, then how are quantitative values assigned to it to create a customer satisfaction index? Do you place numbers on (or quantify) customer satisfaction?

• If executives apply their newly acquired leadership skills and you find that there is increased teamwork, why do you care? You hope it yields greater productivity leading to increased sales and reduced costs.

• Why does it matter if your staff is more creative? Through the use of creative thinking, your product development meetings are more efficient.

• If an absence is a soft measure, then how do you track it? Is someone monitoring how many days employees fail to show up for work?

Many people suggest that hard data represent tangible measures; others suggest that soft data represent intangibles. However, whether hard or soft, improvement in the measures lead to a quantified output that can then lead to economic value add, just like accountants may categorize products sold as tangible and services sold as intangible. In the end, both products and services are directly connected to revenue (and hopefully profit) for the organization. A better delineation of tangible and intangible measures is not whether they are objectively based (hard data) or subjectively based (soft data), but whether they are converted to money.

Noted

There are five levels of data. Intangible benefits are impact data not converted to money. They represent a sixth type of data when reporting an ROI due to their importance to the organization.

All data can be converted to monetary value. As shown in Figure 5-1, this is done by tying measures to either cost savings and avoidance or revenue converted to profit.

Though all measures can be converted to money, several factors should be considered. One factor is the cost to convert the measure. You should not spend more on data conversion than the evaluation itself. Importance of the measure is another consideration. Some measures, such as customer satisfaction and employee satisfaction, stand alone quite well. When that is the case, you might think twice before attempting to convert the measure to money. A third consideration is credibility. While most business decisions are made on somewhat subjective data, the source of the data, the perceived bias behind the data, and the motive in presenting the results are all concerns when data are somewhat questionable. Don’t risk credibility just to calculate an ROI. Intangible measures of success may be where you stop.

Figure 5-1. Data Conversion

Think About This

Rank the following research results in order of credibility based on your definition of credibility. Have a colleague do the same. Compare your rankings and discuss why you ranked the items as you did. These are likely the same considerations others will give to your evaluation projects. Rank: 1 = most credible and 4 = least credible.

Research Rank

Fatigued workers cost employers $136 billion per year.

Source: Fareed Zakaria, CNN Global Public Square, June 9, 2019.

 

Vulcan Materials Company produced 195 million tons of crushed stone during 2018.

Source: Annual Report.

 

IAMGOLD showed an ROI of 345 percent on a leadership program involving first-level managers.

Source: Parker, L., and C. Hubble. 2015. “Measuring ROI in a Supervisory Leadership Development Program.” In Measuring the Success of Leadership Development, by P.P. Phillips, J.J. Phillips, and R.L. Ray. Alexandria, VA: ATD Press.

 

St. Mary-Corwin’s Farm Stand Prescription Pantry saved money for the organization and avoided medical costs for recipients of service so much so that it resulted in a 650 percent ROI.

Source: Phillips, P.P., J.J. Phillips, G. Paone, and C.H. Gaudet. 2019. Value for Money: How to Show the Value for Money for All Types of Projects and Programs. Hoboken, NJ: John Wiley & Sons.

 

Data Conversion Methods

There are variety of techniques available to convert a measure to monetary value (listed in Table 5-3 in order of credibility). The success in converting data to monetary value is knowing what values are currently available. If values are not available, how best can you develop them? The first three techniques represent standard values. These are by far the most credible, because they are data that have been accepted by the organization. Following those are alternative techniques, which can also lead to credible values for the measures that matter.

Table 5-3. Techniques for Data Conversion

• Standard values

»Output to contribution

»Cost of quality

»Employee’s time

• Historical costs

• Internal and external experts

• External databases

• Linking with other measures

• Estimations

»Participants’ estimates

»Supervisors’ and managers’ estimates

»Talent development staff estimates

Standard Values

Many organizations have standard values for measures of turnover, productivity, and quality. Organizations that use Six Sigma have a plethora of measures and, along with them, the monetary values of those measures. Look around your organization. Talk to people and see what is being measured in other parts of the organization. Borrow from those other departments and functions. If a measure has had a monetary value developed and accepted by the organization, there is no reason for you to reinvent it. Take advantage of the work of others.

Basic Rule 10

When collecting and analyzing data, use only the most credible sources.

Standard values are grouped into three categories: output to contribution, cost of quality, and employees’ time. When considering output to contribution, look at the value of an additional output. For example, organizations that work on a profit basis consider the marginal profit contribution in monetizing an additional sale. Think about Starbucks. The primary driver for customers coming to Starbucks is coffee. However, as you have noticed, there are cups, mugs, travel mugs, coffee grinders, and elaborate coffee pots, not to mention biscotti, chocolate, bottled water, juices, and milk. What if, you, as store manager, find that these other items are not moving off the shelf as quickly as expected? You, along with other store managers, attend a one-week program to learn about these products and develop skills that will help you sell more products along with the coffee. Six months after the program, a comprehensive evaluation is conducted, and you find that there has been an increase in sales in these peripheral products. The output is the increased sale. The contribution to the company, however, is the profit from the sale. Most organizations have a gross profit margin on sales readily available.

Another example of converting output data to contribution is with productivity measures. Organizations that are performance driven rather than profit driven have a variety of data that represent productivity. The idea here is increasing the production or processing of one more item at no additional cost, thus saving the company money equivalent to the unit cost of processing or producing that item.

Let’s say you work at a passport office, and your entire role is to process passports. If you can process one more passport, given the resources and time you have available, the value of that one passport is equivalent to the cost of processing one passport. This one additional output—the passport—times the cost of processing the passport is the monetary contribution of increasing the output to the organization.

Now, consider the cost of quality, another standard value in organizations, especially in manufacturing and service firms. Placing the monetary value on some measures of quality is quite easy. For example, waste, reject rates, and defects are often monitored in organizations and already have a monetary value placed on them. Other measures, such as rework, can be converted to monetary value by looking at the cost of the work. For example, when employees make mistakes and errors in reporting, the cost (or value) of those mistakes is the cost incurred in reworking the report.

Think About This

Using salary plus benefits as the basis for placing value on time for all positions enables you to standardize your approach. One caveat in this approach is when working with commissioned salespeople. The value of their work is ultimately the profit gain for the sales they make. However, if they are selling services or products that add no profit (for example, loss leaders), there is no direct value added by selling that specific product or service. When treating their time as money, use their average commission. This will ensure you capture value for their time and in such a way that it can be standardized across all commission sales positions. If they are paid base plus commission, use their salary plus benefits plus commission as the basis for time value.

The third category of standard value is employee time, probably the simplest and most basic approach to data conversion. If time is saved due to a program, the first question to ask is, “Whose time is it?” Then, convert time to monetary value by multiplying hourly salary plus the percentage of additional value for employee benefits (the human resources department can provide the benefits factor). A word of caution: When considering employee time as a benefit, the time savings is only realized when the amount of time saved is actually used for productive work. So, if a manager saves time by reducing the number of ineffective meetings the manager attends, the time saved should be applied to more work that is productive.

Historical Costs

When no standard values exist, look for historical costs. These are costs for which there is a receipt, so to speak. Using this technique often requires more time and effort than desired. In the end, however, you can develop a credible value for a given measure.

An example of using historical costs is the case of a sexual harassment prevention program that was implemented in a large health care organization. The measure of the investigation was formal, internal complaints. The value of the complaint was determined by looking at the historical cost of a complaint. These historical costs included litigation costs, legal fees and expenses, settlement losses, and costs of the investigation and defense of the organization. The cost of each of these was developed based on previous costs incurred by the organization for each complaint. Following the prevention program and at the end of the evaluation period, it was discovered that the organization had prevented 14.8 complaints due to the program. (This is after isolating other variables.) The monetary value for one complaint based on historical costs was then multiplied by the number of complaints reduced for the year due to the program.

Internal and External Experts

When standard values are unavailable and developing the monetary values through historical costs is not feasible, the next option is to go to internal or external experts. Using this approach, ask the expert to provide the cost for the value of one unit of improvement for the measure under investigation. Internal experts have knowledge of the situation and the respect of management; external experts are well published and have the respect of the larger community. In either case, keep in mind that these experts have their own methods to develop the values. Therefore, it’s important for the experts to understand your intent and the measure for which you want to develop the monetary value.

An example of using an internal expert to provide monetary value for a measure is in looking at the electric utility industry. All electric utility companies have on staff an expert in the development of rates. When a utility adjusts rates—either raising or lowering rates—the monetary effect of that adjustment needs to be considered. This often falls to the economist. If rates were being manipulated, the executive staff calls the expert and asks for the estimate for the economic impact of the rate adjustment.

External Databases

Sometimes there are no standard values, no receipts, and no expertise. When this is the case, go to databases. Today, more than any time in the past, talent development professionals have good research at their fingertips. External databases provide a variety of information, including the monetary value of an array of measures. Take the use of external databases to convert a measure to monetary value in the case of turnover. A company implemented a stress management program, which was driven by the excessive turnover due to the stress that came from changing a bureaucratic, sluggish organization into a competitive force in the marketplace. After implementing the stress management program, turnover was reduced along with improvements in other measures, such as productivity and job satisfaction. In calculating the ROI, the evaluators went to a variety of databases to determine the value of turnover for a particular employee leaving the organization. The turnover studies used in the research revealed that a value of 85 percent of the annual base pay is what it was costing the organization for the people in this job classification to leave. While senior managers thought the cost of turnover was slightly overstated using the databases, it did give them a basis from which to begin determining the value of this measure.

Linking With Other Measures

When standard values, historical costs, and internal or external experts are not available and external databases do not provide the information that you need, another technique to convert a measure to monetary value is linking the value of that measure with other measures that have already been converted to monetary values. This approach involves identifying existing relationships showing a correlation between the measure under investigation and another measure to which a standard value has been applied. In some situations, the relationship between more than two measures is connected. Ultimately, this chain of measures is traced to a monetary value often based on profits. Keep in mind that the further you get from the actual monetary value, the greater the assumptions built in and the lower the credibility of the information. Using a methodology to link measures to other measures that have been converted to monetary value is often sufficient for converting measures when calculating the ROI of talent development programs.

Think About This

Effective database research takes time. Consider the following steps to help reduce time and increase effectiveness of your search:

1.  Select a database that aligns with the measures you are trying to convert to money.

2.  Formulate a specific research question or objective.

3.  Define the key words in the research question.

4.  Identify synonyms for the key words, just to ensure you get complete coverage on the topic.

5.  Search your databases.

Keep track of your findings. It may even be helpful to document them in a software application database so you can easily reference them in the future. If you don’t have time to search, call a librarian!

Estimations

When the previous methods are inappropriate and you still want to convert a measure to monetary value, use an estimation process that has been proven conservative and credible with executives in your organization. The estimates of monetary value can come from participants, supervisors, managers, and even the talent development staff. The process of using estimation to convert a measure to monetary value is quite simple. The data can be gathered through focus groups, interviews, or questionnaires (discussed in chapter 3). The key is clearly defining the measure so that those who are asked to provide the estimate have a clear understanding of that measure.

The first step in the estimation approach is to determine who is the most credible source of the data. Typically, the participants realize the contribution they are making to the organization after participating in a talent development program. But, depending on what job group those participants work in, you might develop data that are more credible if you go to the supervisors or managers. Only fall back on the talent development staff when you have no other option and are under pressure to come up with a monetary value. The concern with using talent development staff is their ownership of the program in question increases bias and often results in loss of credibility, especially when reporting a very high ROI.

Let’s consider an example of using estimation to convert the measure of absenteeism to monetary value. Say you have an absenteeism problem, you implement a solution, and, as a result, the absenteeism problem is resolved. You now want to place a monetary value on an absence. You have no standard value. You don’t want to invest the resources to develop a value using historical costs. There are no internal or external experts who can tell you. You’ve been unsuccessful in looking for an external database. You have no other measures that have been converted to monetary value to which you can link absenteeism. With pressure to come up with an ROI for this particular program, you decide to go to estimation.

The first step is determining who knows best what happened when an unexpected absence occurred. So, to convert the measure to monetary value, you call in five supervisors from similar work units to discuss the issue and help develop a value for an absence. Using a structured focus group approach, the scenario plays out as follows.

At the beginning of the focus group session, discuss the issue with the five supervisors, explaining why they have been brought together and that you are attempting to place a monetary value on an unexpected absence. Spend a few minutes in conversation about the issue before continuing the process. Then ask Supervisor 1, “What happens when someone does not show up for work?” Supervisor 1 ponders the question for a moment and says, “When someone doesn’t show up for work, I have to call in a replacement. I hand the most pressing issues off to another employee who then has to interrupt her work to tend to the urgent tasks of the absent employee.” Then go to Supervisors 2, 3, 4, and 5. Each supervisor takes about two minutes to tell what happens when someone doesn’t show up for work.

Next have each supervisor estimate the monetary value or what it is costing the organization when unexpected absences and associated events occur. Ask Supervisor 1, “Based on what you have told us about what occurs when someone does not show up for work, how much do you think one absence costs the organization per day?” Supervisor 1 considers her issues and all that occurs around an unexpected absence and says, “Based on what happens in my office when someone doesn’t show up for work, I believe it costs us about $1,000 per day per absence.” Write it on a flipchart. Ask Supervisor 2 the same question. Supervisor 2 considers what Supervisor 1 said, but then she thinks about her own situation. She responds: “I understand where Supervisor 1 is coming from with her estimate, but given what happens in my department, I believe it costs more. I estimate it costs about $1,500 a day for an unexpected absence.” Write it on a flipchart. Ask the same question of Supervisors 3, 4, and 5. Now it’s time to adjust for error.

Estimates are subjective; therefore, to reduce the error in the estimate, adjust for the supervisors’ confidence. Start with Supervisor 1 saying, “You’ve explained what happens when someone doesn’t show up for work. You estimate that it costs you $1,000 per day per unexpected absence. You’ve heard what happens in other supervisors’ functions and how much they believe it’s costing them when someone doesn’t show up for work. Now, given what happens in your organization and your estimated costs and what you have heard from others, how confident are you that your estimate is accurate?” After thinking this over, Supervisor 1 says, “Well, it is an estimate, but I know what happens when people don’t show up for work and I can be pretty sure what it’s costing us from a time perspective. Given that it is an estimate and I’m not totally sure, I’ll say that I am 70 percent confident in my estimate.”

Write it next to his or her estimate. Repeat the process with Supervisors 2, 3, 4, and 5. Table 5-4 shows the estimates of the five supervisors and their error adjustments. Multiply each estimate by the error adjustment, then total and average the adjusted values. The results are an average adjusted per-day cost for one absence of $1,061.

Figure 5-2 shows what happens when you adjust original estimates by factoring for confidence level. The top line represents the original estimate for each supervisor. The bottom line shows the adjusted value. The additional step to adjust and estimate for error reduces variability in the estimates and provides a more conservative value, hence improving the reliability of the estimated value of one absence.

Table 5-4. Absenteeism Is Converted Using Supervisor Estimates

Figure 5-2. Estimated Value of Absenteeism

Data Conversion Four-Part Test

For those times when you cannot decide whether you can credibly convert a measure to monetary value, complete this four-part test:

1.  If the measure you want to convert has a standard value, convert it to monetary value.

2.  If there is not a standard value, is there a method other than standard values to get there? If there is not a method, then report the measure as intangible.

3.  If there is a method to convert the measure, can you do so with minimum resources? If no, then report it as intangible. (You don’t want to spend more on data conversion than the evaluation itself.)

4.  If you can convert the measure to monetary value using minimum resources, can you convince your executive in two minutes or less that the value is credible? If no, report the measure as intangible. If yes, convert it!

Figure 5-3 presents the four-part test as a flowchart.

Figure 5-3. To Convert or Not to Convert

Five Steps to Calculating Monetary Benefits

When you have decided to convert a measure to monetary value and chosen the technique that you’re going to use to calculate the monetary value, then you are going to follow five steps to calculate part of the numerator in the ROI formula, or the program benefits:

1.  Focus on the unit of measure.

2.  Determine the value of each unit.

3.  Calculate the change in the performance of the measure.

4.  Determine the annual improvement in the measure.

5.  Calculate the total monetary value of the improvement.

Basic Rule 11

In converting data to monetary value, when it doubt, leave it out!

Focus on the Unit of Measure

The first step is simply reducing the objective to specific units of measure. If you are evaluating a measure of productivity and the output is credit card accounts, the unit of measure is one credit card account.

Determine the Value of Each Unit

In determining the value of each unit, use standard values or one of the other operational techniques. In the credit card account example, you may find that one new account is worth $1,000. This figure is based on standard values using profit contribution. So, the value is $1,000 in profit.

Calculate the Change in the Performance of the Measure

Step 3 is the result of the Level 4 analysis, after isolating the program effects on improvement in the measure. How many new credit card accounts did you open due to the program? Let’s assume that on average the bank saw an increase in five new credit card accounts per month.

Determine the Annual Improvement in the Measure.

Annualize the improvement in the measure. Remember that Guiding Principle 9 (from chapter 2) says that for short-term programs you are going to report only first-year benefits. You are not going to wait one year to determine the annual impact. Rather, based on the program objectives, you will pick a point in time to get the average improvement to that date, and then annualize that figure, but only for one year versus multiple years. The first-year-only rule maintains a conservative approach. In the credit card account example, the unit of measure is one account and the value of the measure is $1,000. The change in performance of the measure due to the program (after isolating the program) is five new accounts per month. To determine the annual improvement in the measure, multiply the change in performance by 12 months. So, five per month times 12 months equals 60 new accounts due to the program.

Calculate the Total Monetary Value of the Improvement

Take the number from step 4, annual improvement in the measure (60 in the example) and multiply it by the value of the measure ($1,000 in the example). The total monetary value of improvement is $60,000. This is the value that goes in the numerator of the equation. Table 5-5 shows this calculation step-by-step.

Table 5-5. Five Steps to Program Benefits

1. Focus on the unit of measure.

1 credit card account

2. Determine the value of each unit.

$1,000 profit per 1 credit card account per year

3. Calculate the change in the performance of the measure.

5 new credit card accounts per month (after isolating other variables)

4. Determine the annual improvement in the measure.

5 accounts per month × 12 months = 60 new credit card accounts per year

5. Calculate the total monetary value of the improvement

60 per year × $1,000 per account = $60,000 annual value of the improvement

Now, you do it! Exercise 5-1 provides the information for each of the steps. All you have to do is complete steps 4 and 5. The answer to this exercise is found at the end of this chapter.

Exercise 5-1. Converting Data to Monetary Values

Scenario: Placing monetary value on grievance reduction

Step 1

Focus on the unit of measure

Our unit of measure is 1 grievance.

Step 2

Determine the value of each unit

The value of each unit is $6,500, as determined by internal experts.

Step 3

Calculate the change in the performance of the measure

The number of grievances declined by 10 per month; and after isolating the effects of the program, 7 of the 10 fewer grievances were due to the program.

Step 4

Determine the annual improvement in the measure

The annual change in performance equals _____.

Step 5

Calculate the total monetary value of the improvement

The annual change in performance times the value equals _____.

The value that you put in step 5 is the value that goes in the numerator of the formula.

Tabulating Fully Loaded Costs

This next step in the move from Level 4 to Level 5 is tabulating the program costs. The final cost figure will be inserted in the ROI formula twice: first to be subtracted from the final benefits figure to calculate net program benefits; second to be divided into the net program benefits figure. When taking an evaluation to Level 4 only, this step is not necessary; although, regardless of how you evaluate your programs, it should be common practice to know the full costs of the talent development function and its various programs.

What is meant by fully loaded costs? It means everything. Table 5-6 shows the four categories of costs. Which do you think make up the full cost of the program?

Table 5-6. Cost Categories

Which Cost Category Is Appropriate for ROI?

A B

• Operating costs

• Support costs

• Administrative costs

• Participant compensation

• Facility costs

• Classroom costs

C D

• Program development costs

• Administrative costs

• Classroom costs

• Participant costs

• Analysis costs

• Development costs

• Implementation costs

• Delivery costs

• Evaluation costs

• Overhead and administrative costs

If you selected category D, you are correct. The analysis and the development costs are prorated over the life of the program, so one ROI study will not be weighed down by the full costs of analysis and development. But a fair portion of those costs will be included. The lifetime of the program is considered the time until a major program change occurs. Say you are evaluating a program that will not change for one year and you offer the program 10 times during the year. When you conduct an ROI study on one offering of that program, your analysis costs and your development costs will be included only at the rate of one-tenth of the total of the analysis and development costs. The other offerings are going to benefit from the investment in analysis and development as well. Program materials, instructor and facilitator costs, facilities costs, travel, lodging, meals, participant salary and benefits, and evaluation costs are expensed—they are the direct costs.

Overhead and administrative costs, however, are allocated based on the number of days or hours required of participants to engage in the program. Table 5-7 provides an example. As you see in the table, the unallocated budget in the example is $548,061. To calculate the total number of participant-days, consider the number of days for a program and multiply it by the number of times the program is offered (a five-day program offered 10 times a year equals 50 participant-days). In the example, there are 7,400 participant-days. The next step is to determine the per-day cost of the unallocated budget. The unallocated budget divided by the number of participant-days gives a per-day cost of $74 ($548,061 ÷ $7,400 = $74). The per-day costs are allocated to the number of days involved in the program being evaluated. If the program is a three-day training program, you would allocate $222 to overhead and administrative costs.

Basic Rule 12

When developing the denominator, when in doubt, leave it in.

Table 5-7. Allocation of Overhead and Administrative Costs

Unallocated budget

$548,061

Total number of participant-days

(5-day program offered 10 times a year equals 50 participant days)

7,400

Per-day unallocated budget

($548,061 ÷ 7,400)

$74

Overhead and administrative costs allocated to a three-day program

(3 × $74)

$222

Table 5-8 provides a worksheet to help you develop the fully loaded costs for your talent development programs.

Calculating the ROI

As explained in chapter 1, while there are any number of metrics indicating economic success of an organization and its individual investments, two metrics work with all types of programs: the benefit-cost ratio (BCR) or the ROI percentage. In simple terms, the BCR compares the economic benefits of the program with the cost of the program. A BCR of 2:1 says that for every $1 you invest, you get $2 back in gross benefits.

The ROI formula is reported as a percentage. The ROI is developed by calculating the net program benefits divided by program costs times 100. A BCR of 2:1 translates into an ROI of 100 percent. This tells you that for every $1 you spend you get $1 back, after costs. Remember that you’re working with net benefits and the ROI is reported as a percentage. The formula used here is essentially the same as ROI in other types of investments where the standard equation is annual earnings divided by investment.

Noted

It is incorrect to multiply the BCR by 100 and report it as an ROI.

Table 5-8. Cost Estimating Worksheet

Remember that intangible benefits are those that you choose not to convert to monetary value. But they are sometimes more important than the actual ROI calculation. Typical intangible benefits that you do not convert to monetary value are job satisfaction, organizational commitment, teamwork, and customer satisfaction. You can convert these measures to monetary value; typically, however, when job satisfaction, organizational commitment, teamwork, and customer satisfaction are improved, you’re satisfied enough with the improvement in these measures that the dollar value with that improvement is not relevant.

Getting It Done

You have completed almost all the steps in the ROI Methodology. Now, it’s time to complete the next three columns in the ROI analysis plan. In chapter 4, you transferred your Level 4 measures to the ROI analysis plan; you selected techniques to isolate the effects of the program on the measure. Now, determine how you will convert these measures to monetary value. If your measure does not pass the four-part test explained earlier, move the measure to the intangible benefits column. Identify the program costs that you plan to consider and those benefits that you plan to categorize as intangibles.

In the next chapter, you will read about the final phase in the ROI Methodology: Optimize Results. This phase requires that you communicate results to key stakeholders and use black box thinking to drive an increase in your talent development funding.

Answers to Exercise 5-1. Converting Data to Monetary Values

Scenario: Placing monetary value on grievance reduction

Step 1

Focus on the unit of measure

Our unit of measure is 1 grievance.

Step 2

Determine the value of each unit

The value of each unit is $6,500, as determined by internal experts.

Step 3

Calculate the change in the performance of the measure

The number of grievances declined by 10 per month; and after isolating the effects of the program, 7 of the 10 fewer grievances were due to the program.

Step 4

Determine the annual improvement in the measure

The annual change in performance equals 84.

Step 5

Calculate the total monetary value of the improvement

The annual change in performance times the value equals $546,000.

The value that you put in step 5 is the value that goes in the numerator of the formula.