The literature review focused on levels of evaluation, calculating the return on investment, and electronic performance support systems. The team hoped to learn about any existing standards against which to measure return on investment and how such standards may be translated for use with EPSSs.
One thread consistently ran through all of the literature; in order for companies to be successful, they must provide employees with contextualized training and support such as that found in an EPSS. The emerging pattern today is one in which training and support are evaluated in terms of performance outcomes and strategic alignment with business goals. In many businesses, excellence is "a moving target" versus a stable, consistent, easily identified end-point. This makes it especially difficult to establish metrics by which to evaluate interventions. There is no one-size-fits-all cookie cutter approach that can be used to calculate overall return on investment (ROI).
Another emerging trend is the link between knowledge, known commonly as "human capital," and outcomes. Human capital can lead to increased productivity (both individual and organizational). These intellectual assets may be worth three to five times the value of an organization's physical assets (Stolovitch and Maurice, 1998) and point to the importance and tangible value of effective training and support. Once again, concerted efforts to identify and track human capital—let alone relate it to ROI—are the exception rather than the rule and there are no set standards that one can follow. Knowledge has always meant power yet executives and financial experts have been reluctant or unwilling to acknowledge the importance of the return on investment from training. Why is this? Perhaps there are several reasons why calculating the return on investment of training and support has been overlooked (Stolovitch and Maurice, 1998):
A new era of self-examination is beginning to emerge which places increased emphasis on issues such as human capital and the strategic alignment of business goals. Several studies have recently been conducted to determine what, if any, measures are being conducted by businesses and how the data are being used. Stivers, Covin, Hall, and Smalt (1998), for example, published the results of a survey involving 253 U.S. Fortune 500 and Canadian Post 300 companies. The survey was part of a study designed to identify which non-financial factors firms perceive as important, whether firms are measuring these factors, and whether or not the data influence their planning processes. Results of the study indicate that customer service factors are rated most important. Ninety-two percent of the survey respondents rated customer satisfaction and delivery performance/customer service as highly important. Product/process quality was rated as highly important by 206 (81.4%) of the companies and service quality was rated highly important by 205 or 81%. Market share was rated highly important by 79.1% of the respondents, and "productivity" was rated highly important by 83.4%. Innovation was rated highly important by 44.3% and employee turnover was rated highly important by 48.2%.
According to Stivers, et al., a number of critical non-financial factors must also be included in comprehensive performance measurement including: market standing, innovation, productivity, customer service, and employee involvement. This study highlighted the fact that respondents rated "innovation" and "employee involvement"—key aspects of human capital—as less important than other factors. The authors suggest that as intellectual assets increasingly impact the bottom line, methods of managing and controlling knowledge will become more important. This list of reasons why calculating the return on investment of training and support has been overlooked provided by Stolovitch and Maurice (1998) may be exemplified in this study.
Stivers, et al. (1998) indicates the importance of measuring performance gaps. One gap is called the "importance-measurement." While many companies view non-financial performance factors as highly important, they are not actively capturing the data. For example, from the employee involvement category of the survey, "moral and corporate culture" was rated as highly important by 75.9% of the respondents; however only 37.5% of the companies that responded are collecting data on this factor. Innovation is the factor least likely to be measured (21.8%). Another measurement gap revealed in this study was called the "measurement-use." Although the factors mentioned above might be rated by respondents as highly important and as being measured by companies, the data are often not fully used in strategic planning. For example delivery performance/customer service was rated highly important by 92% of survey respondents and close to 85% reported actually measuring this factor. However, only 71.1% reported using the data for planning. The largest gap is in the "employee involvement" category, which includes items such as employee satisfaction, employee turnover, internal recognition, and morale and corporate culture. About 40% of the survey respondents reported not using such factors in corporate planning although the data are collected and available.
In January 1998, a survey of 150 information systems executives was conducted by InformationWeek magazine. The results were published in the April 27 issue (Violino, 1998). Eighty percent of the respondents claimed that their organizations require demonstrated potential revenue, payback or budget impact from information technology (IT) projects--an increase of 45% from the previous year. The number of businesses requiring ROI measures are growing, especially in businesses involved in enterprise resource planning. Businesses recognize the need to show returns, yet in this survey, only one-fifth of the respondents reported planning to adopt any formal ROI measures within the next 12 months.
A common industry phrase is "what gets measured, gets done." Some of the literature suggests that the financial climate within corporations and industry is changing. The unlimited flow of dollars into new projects of any sort is coming under more careful scrutiny. More than ever before, in order to get things get done, there needs to be justification. According to several of the articles, massive amounts of money are being poured into solving Year 2000 computer problems, and shortages of technology-savvy labor have driven salary costs to exorbitant heights. These factors are part of the reason that more IT budgets are coming under more careful scrutiny. At the same time, businesses are finding a competitive edge in decentralizing their decision-making functions and allowing decisions to be made quickly and at the point where the activity occurs. This change in business tactics supports Drucker's (1992) assertion that "knowledge is only productive when integrated into a task" (p. 96). A visible result of changing business tactics is the development of IT tools that integrate specialized knowledge and are readily accessible to those employees who most need them. One such tool is an electronic performance support system (EPSS).
Levels of Evaluation
Let's return to the reasons why ROI calculations have not been integrated into
business practice. Two that stand out are: 1) training managers don't know how
to do it and 2) training managers don't know what to measure. Selecting an appropriate
ROI method requires some front-end analysis to determine which of the several
available methods are most appropriate. Appropriateness is determined by strategic
focus and, more importantly, the level at which the strategic focus takes place
(Foshay, 1998). Some of the various approaches are discussed below.
The Kirkpatrick Four-Level Approach
Kirkpatrick (1996) first defined four levels of evaluation when writing his dissertation
some 40 years ago on evaluating a supervisory training program. For years the
framework has been the most popular and primary evaluation approach used by training
professionals. Why? It's both simple and practical (Kirkpatrick, 1996). Table
1 below illustrates the concepts.
Table 1. The Kirkpatrick Four-Level Approach (Kirkpatrick, 1996).
| Level | Questions |
|---|---|
| 1. Reaction | Were the participants pleased with the program? |
| 2. Learning | What did the participants learn in the program? |
| 3. Behavior | Did the participants change their behavior based on what was learned? |
| 4. Results | What was the effect on the organization in terms of growth and change? |
Kaufman's Five Levels of Evaluation
Kaufman, Keller & Watkins (1996) promote an assessment strategy called the Organizational
Elements Model (OEM) which involves four levels of analysis:
Since the introduction of Kaufman's four-level OEM model,
many researchers have used it as a viable framework for evaluation. Others, though,
have found it restrictive and have attempted to modify and/or add to it. Kaufman,
et al. (1996), for example, later added levels of impact that go beyond the traditional
four-level, training-focused approach which they felt did not adequately address
substantive issues an organization faces. Such modification to the model resulted
in the addition of a fifth level, which assesses how the performance improvement
program contributes to the good of society in general as well as satisfying the
client.
Table 2. Kaufman's Five Levels of Evaluation (Kaufman et al.,
1996)
| Level | Evaluation | Focus | Suggested Levels* |
| 5 | Societal outcomes | Societal and client responsiveness, consequences and payoffs. | Mega |
| 4 | Organizational output | Organizational contributions and payoffs. | Macro |
| 3 | Application | Individual and small group (products)utilization within the organization. | Micro |
| 2 | Acquisition | Individual and small group mastery and competency. | Micro |
| 1b | Reaction | Methods', means', and processes' acceptability and efficiency. | Process |
| 1a | Enabling | Availability and quality of human, financial, and physical resources input. | Input |
| *Based on Kaufman's Organizational Elements Model (1992, 1995) | |||
The Phillips Five-Level ROI Framework
The evaluation framework favored by Phillips (1997) adds a fifth level to the
evaluation model. Instead of examining whether the program enhanced society, as
Kaufman et al. propose, he adds return on investment. Return on investment measurement
allows an organization to compare the monetary benefits from the program with
its costs. Using a cost/benefit ratio, evaluators can determine if the program
is cost-effective.
Table 3. The Phillips Five-Level ROI Framework (Phillips, 1997)
| Level | Questions |
|---|---|
| 1. Reaction and planned action | What are participants' reactions to the program? What do they plan to do with what they learned? |
| 2. Learning | What skills, knowledge, or attitudes have changed? By how much? |
| 3. Applied learning on the job | Did participants apply what they learned on the job? |
| 4. Business results | Did the on-the-job application produce measurable results? |
| 5. Return on investment | Did the monetary value of the results exceed the cost of the program? |
Most evaluation processes check for participant satisfaction (Level 1) and whether or not the knowledge and skills learned are useful (Level 2). But moving up the management ladder puts more importance on the outcomes of Levels 3-5. Immediate managers want their investment in training and development to yield measurable impacts on business performance (Levels 3 and 4). Top executives care only that the training is monetarily justified (Level 5). If measurements are not taken at each level, it is difficult to show that any improvement can be attributed to a program, process, or other intervention. Level 5 evaluation (ROI) is rapidly gaining acceptance by training professionals. It provides a solid framework for reporting the monetary benefits of a program.
Return on Investment
Several different methods for calculating return on investment were uncovered
during the literature search. Five areas were recommended by Davidson (1998) in
her recent article entitled, "Measure what you bring to the Bottom Line." She
suggests measuring:
Phillips (1997) believes that ROI measurement isn't complete until results are converted to monetary worth, as shown in Figure 1.
Figure 1: Return on Investment Model [Combined from Stolovitch (1998) and Phillips (1997)].
Phillips also recommends looking at combinations of 'hard'
and 'soft' data. Hard data include such traditional measures as output, time,
quality, and costs. In general, hard data are readily available and relatively
easy to calculate. Soft data include absenteeism, turnover rate, and other somewhat
subjective behaviors. Soft data are harder to gather and more difficult to convert
to dollars. In addition, soft data are often perceived as less valid than hard
data. The table below provides examples of the kinds of data that might be collected.
Table 4: Hard and soft data (Phillips,
1997)
| Hard | Soft |
Output
|
Work Habits
|
Quality
|
Work Climate
|
Time
|
Attitudes
|
Cost
|
New Skills
|
Development and Advancement
|
|
Initiative
|
After the hard and/or soft data have been determined, they may be converted to monetary values.
Step 1: Focus on a single unit.
Step 2: Determine a value for each unit.
Step 3: Calculate the change in performance. Determine the performance change after factoring out other potential influences on the training results.
Step 4: Obtain an annual amount. The industry standard for an annual-performance change is equal to the total change in performance data during one year.
Step 5: Determine the annual value. The annual value of improvement equals the annual performance change, multiplied by the unit value. Compare the product of this equation to the cost of the program, using this formula: ROI = net annual value of improvement – program cost.
(Phillips, 1996a)
Converting output to contribution. This reflects the "profit contribution" of an additional unit of product or service, or the contribution or the savings from producing an additional unit of output from the same input. Marginal-cost statements and sensitivity analyses can be used to pinpoint the values associated with changes if the output data are not available.Three more alternatives for calculating ROI were presented in a recent article by Maglitta (1997) in Computerworld magazine. [In fact, many of the models described immediately above incorporate these methods to varying degrees.] These alternatives are:
Calculating the cost of quality. Poor quality is waste generated by human error and bears a cost: defective products, spoiled raw materials, and discarded paperwork. The most costly waste occurs when a product is delivered to a customer and returned for repair. Staff performs the rework and cost is added to the overhead. The highest cost of poor quality is customer dissatisfaction.
Converting employees' time.Converting the value of time saved is relatively easy and is an important measure of a program's success. The most obvious measure is the reduced cost of performing work. Monetary savings equal the hours saved multiplied by the per-hour labor cost. Time saving is realized when the amount of time saved translates to a cost reduction or profit contribution and the additional time saved is used productively. Most ROI calculations simply use the average wage (with a percent added for employee benefits). Some experts recommend adding in "employee maintenance" costs including such items as office space, furniture, telephone, utilities, computers, calculators, and administrative support.
Using historic costs.Company records can often show the cost and value of one unit of improvement.
Using internal and external experts. Experts can provide the cost (or value) of one unit of improvement.
Using data from external studies. For some soft data, it may be appropriate to use information from studies or research projects that focus on the cost of those data items to estimate value or determine benchmarks and industry standards.
Using participants', supervisors', and/or senior mangers' estimates.Sometimes the people closest to an improvement can provide the most reliable estimates on its value.
Using Human Resources estimates.These may be perceived as biased. After all, the HR department will determine the basis for its claim for improvements due to training.
According to the 1998 InformationWeek survey mentioned previously, the most popular method of calculating ROI is traditional cost/benefit analysis (about 97% of all respondents selected this option.) Cost benefit analysis is easy to understand and easy to calculate. Other measures also used are Net Present Value reported by 44% of the respondents, weighted scoring (22%), and applied information economics (12%). Also gaining popularity is the Economic Value Added (EVA) method developed by Stern Stewart and C. (Violino, 1998). EVA measures the difference between after-tax operating profit and the cost of capital employed to generate the profit (in other words, the equity involved in producing profit). In Fall, 1997, the Society of Information Management (SIM) introduced an ROI model called the Value Measurement Model. This model brings Chief Executive Officers (CEOs), Chief Financial Officers (CFOs), business division heads and Company Information Officers (CIOs) into the project-assessment process. Each has their own particular area of interest: for the CIO, it might be the investment in hardware, software and services required in a new project; for the business-line partners productivity gains, cost-savings, and effectiveness might be at issue; for the senior management, overall return on investment.
Finally, Stolovitch et al. (1998) present a detailed plan for calculating ROI for training interventions that might be adaptable for the present evaluation. It consists of seven distinct steps, each of which is addressed here:
Step 1: Calculate Potential for Improved Performance
The potential for improved performance may involve tangible and intangible elements. Tangible elements include productivity, increased sales, and decreased errors. Determining whether these elements have been affected involved pre- and post-testing and comparing the results to industry standards and averages. Intangibles include listening skills, counseling techniques, and systematic thinking. These elements are generally measured over time using the following steps:
- determine purpose of training (mandated, new system, performance gap)
- identify desired and actual performance
- identify feelings related to desired performance
- identify causes for not achieving desired performance
- identify solutions
- describe the major job competencies (people skills)
- based on survey and estimation, assign a value to each competency as a percentage of the time spent on each competency
- break down further within competencies into performance requirements
- assign numeric values for actuals and optimals within competencies, calculate the gap (subtraction)
- total across all competencies, then put into percentage between actuals and optimals
- convert the potential for improvement into a dollar amount based on salaries (use percentages of time spent on tasks from number 2)
Step 2: Calculate Estimated Training Costs
Includes:
- Training Development Costs: human resources, travel, media production, fees, licenses.
- Training Implementation Costs: training facilities and equipment, instructors, trainees, replacement of trainees, lost opportunities, travel, materials, communications, administration.
- Training Course Maintenance: updating, revisions (can vary from 5 percent of original development costs to 50 %).
Step 3: Calculate Worth Analysis
This step verifies the worth of training versus potential outcomes.
- estimate the highest number of annual deficiencies or improvements
- estimate the lowest number of annual deficiencies or improvements
- assign a dollar value to each based on annual cost per deficiency
- calculate the annual cost of each high and low
- estimate the range of expected deficiencies corrected or improvements obtained from training in percentages
- estimate low and high annual value of training
- multiply the low and high annual value by the expected lifetime of the training and divide by the estimated training costs to obtain potential worth
Step 4: Train
This step is the design, develop, implement, support, monitor, and evaluate stage.
Step 5: Calculate the True Cost of Training
This step mirrors step 2; but uses actual costs versus estimated. Stolovitch recommends
using salary plus benefits of 35 percent for calculating costs in the U.S. Other
costs: equipment maintenance, shipping, handling and storage of materials, correction
of errors caught after implementation, trainer training, course publicity, enrollment,
and tracking might also be included.
Step 6: Calculate Organizational ROI for
Tangibles
It is difficult to isolate the value of training from other solutions that may
have resulted from a performance intervention. It is best to wait about six months
and then:
- Calculate an expected range of impact due to training
- Calculate the value of results against training costs only on projects where training has been the major performance intervention
Step 7: Calculate Individual Increased Value of
Human Capital
It is assumed that each employee has a value at least equal to their salary. As
employee competency rises, so does their value. Although Stolovitch does not say
so, it is assumed that calculating the value of increased competency would involve
going back and measuring against the standards set in Step 1 and comparing against
cost criteria established in Steps 2, 3 and 5.
Process simplification looks at the steps needed to perform a task, breaks them down into manageable chunks and then provides resources and support that helps employees complete the tasks in less time, using less steps or using the most effective steps with the least amount of effort. An EPSS supports this function by putting job aids, templates, macros, best practices, and benchmarking data within reach of employees and by integrating the EPSS into the very interface used to perform the task.
Performance information reduces the time and cognitive effort (memory) needed to perform procedures by providing just-in-time knowledge. Decision support enables an employee to make the required action without fully understanding or recalling the rules that govern the decision-making process. A key factor is recognizing the set of conditions that lead to the correct decision-making support tools. These tools might be flow charts, diagrams, or decision algorithms. Within each of these functions is a set of variables that might be used to measure and evaluate the effectiveness of the performance support system. At the most basic level, performance improvement measurement can be calculated by determining whether:
EPSS often base their ROI justification on the more straightforward assessment of intellectual capital (a measurement of organizational capabilities) instead of performing a human capital calculation such as the one that Stolovitch et al. (1998) recommends. Because intellectual capital is considered an intermediate product, EPSS ROI calculations tend to use a "cost-effectiveness" strategy. Phillips' ROI calculations, which are based on valuations of the improved work product, exemplify this strategy. In general, cost-effectiveness focuses on improvement of existing processes or installation of new processes or technologies that facilitate improved organizational output. These goals are consistent with the goals of an EPSS.
In their recent article, Hawkins, Gustafson, & Nelson (1998) documented the construction, implementation and evaluation of an EPSS within the U.S. Department of Veterans Affairs that was designed to replace traditional training. As the system was built, evaluation methodology and resources for implementing evaluation and ROI were carefully considered, and a web-based system was created that would calculate ROI. The system uses five down-loadable spreadsheets that are used to calculate ROI at various stages (planning, development, and implementation) and assist the user in decision-making by estimating possible cost savings and benefits. For instance, when an employee embarks upon the process of being supported by the EPSS, an Initial Benefits Worksheet (Table 5) tracks one-time or initial cost items such as hours per employee, average cost per employee hour, number of employees affected, and total dollar amount saved. This lead to calculations such as reduced learning time, reduced supervision hours, reduced help from coworkers, and other factors, as listed in Table 5 below.
Table 5. Initial Benefits Worksheet (Hawkins et al. 1998)
| Employee | Hours/Person Avg | Cost/Hour | # of People | Total $ Saved |
| Reduced time to learn system/job (worker hours) | 40 | $15.00 | 500 | $300,000.00 |
| Reduced supervision (supervision hours) | 20 | 25.00 | 100 | 50,000.00 |
| Reduced help from coworkers (worker hours) | 15 | 20.00 | 500 | 150,000.00 |
| Reduced calls to help line/user assistance (technical assistance hours + phone call) | 5 | 25.00 | 500 | 62,500.00 |
| Reduced "down" time (waiting for help, consulting manuals, etc.) | 5 | 15.00 | 500 | 37,500.00 |
| Fewer or no calls from help line to supervisor about overuse of help service | 5 | 25.00 | 500 | 62,500.00 |
| TOTAL SAVINGS OVER LIFE OF SYSTEM | $662,500.00 |
| Continuing Worker Hours Saved | Hours/Person Avg. | Cost/Hour | # of People |
Total $ Saved
|
| Reduced time to perform operation (worker hours)** | 120 | $17.50 | 600 | $1,260,000.00 |
| Reduced overtime*** | 60 | 26.25 | 500 | 787,500.00 |
| Reduced supervision (supervisor hours) | 80 | 25.00 | 30 | 60,000.00 |
| Reduced help from co-workers (worker hours) | 50 | 17.50 | 100 | 87,500.00 |
| Reduced calls to help line/user assistance (technical assistance hours + phone call) | 3 | 17.50 | 500 | 26,250.00 |
| Reduced "down" time (waiting for help, consulting manuals, etc.) | 3 | 17.50 | 500 | 26,250.00 |
| Fewer or no calls from help line to supervisor about overuse of help service | $- | |||
| Fewer mistakes (e.g., rejected transactions)* | $- | |||
| Fewer employees needed | 2000 | 15.00 | 1 | 30,000.00 |
| Total Savings in one year | $2,277,500.00 | |||
| Expected life of system in years = 7 | ||||
| TOTAL SAVINGS OVER LIFE OF SYSTEM | $15,942,500.00 |
Other worksheets include the Quality Benefits Worksheet
(Table 7), which calculates number of mistakes or rejects due to EPSS use, and
the Other Benefits Worksheet (Table 8), which calculates less tangible benefits
such as employee turnover, grievances, absenteeism, and tardiness. A dollar value
can be assigned to all of these elements. The final spreadsheet is the ROI Calculation
Worksheet (Table 9), a calculation based on sum of all dollars saved less the
cost of the EPSS (includes development, maintenance and operation). The balance
is then divided once again by the cost of the EPSS to obtain the ROI. There is
an integrated help system that assists the user throughout the entire process
and within each individual worksheet.
Table 7. Quality Benefits Worksheet (Hawkins et al. 1998)
| Quality Improvements w/Fixed Costs (per year) | Unit Cost | # of Units | Total $ Saved |
| Fewer mistakes (e.g., rejected transactions)* | $32.00 | 1000 | $32,000.00 |
| Fewer rejects-ancillary costs* | 32.00 | 250 | 80,000.00 |
| Total savings in one year | 112,000.00 | ||
| Expected life of system in years = 7 | |||
| TOTAL SAVINGS OVER LIFE OF SYSTEM | $784,000.00 |
| Benefit | $ Saved per Year |
| Reduced employee turnover | $2,000.00 |
| Reduced grievances | 1,000.00 |
| Reduced absenteeism/tardiness (morale improvements) | 20,000.00 |
| Total savings in one year | 23,000.00 |
| Expected life of system in years = 1 | |
| TOTAL SAVINGS OVER LIFE OF SYSTEM | $23,000.00 |
| ROI Calculation | $ Saved |
| Initial time saved total over life of system | $662,500.00 |
| Continuing worker hours saved total over life of system | 15,942,500.00 |
| Quality improvements with fixed costs total over life of system | 784,000.00 |
| Other possible benefits total over life of system | 276,500.00 |
| Total benefits | 17,665,500.00 |
| Total system costs (development, maintenance, and operation | 500,000.00 |
| ROI = (BENEFITS - COSTS) / COSTS = | 34.3 |
This project is the work of former San Diego State
University edtec students,
Deb Linder
and Linda Woods Hyman.
Last revised April 23, 1999.