The quantification of benefits is where most valufiers become gun shy. They are afraid of putting themselves or their organizations on the line by projecting benefits based on their calculations. If there is an industry-standard way of calculating benefits, there is generally no hesitation.

So how does one quantify benefits? Let’s walk through two examples. Consider the benefits scenario of improving operations efficiency at a manufacturing plant. There are many ways to develop key value measurements for this benefit scenario. One example of key-value measurement would be to “reduce rework in product development” as a way to improve plant efficiencies. Another way to quantify plant operations efficiency could be to “measure factory worker productivity.” These are hard benefits that can be easily measured.

For example, to measure the benefit of reducing rework in product development, the calculation is as follows:

((Expected percent reduction in material waste/100) * Average cost of materials per unit * Number of units produced) + (Rework cost per unit * Number of units produced * Percent of produced units that are worked * (Expected percent reduction in rework/100)) + (Number of service calls that are in warranty * Average cost per service call * (Expected percent reduction in service calls/100))

If you examine each of the metric attributes (equation variables) in the above benefit metric calculation (key value measurement), except for “Expected percent reduction in material waste” and “Expected percent reduction in service calls”, the data for the rest of the attributes is easily obtained. So how do you get data for these two attributes in question? If you have paid subscriptions to some of the industry reports, that is an easy place to look for them. However, many of us do not have the luxury of subscribing or buying these expensive reports. So our best bet is to scour the internet through well phrased search terms.

To measure factory worker productivity, here’s an equation to use:

Number of factory workers * ( Percent of working time spent in collaboration / 100 ) * Number of working hours per year * ( Expected percent improvement in employee collaboration / 100 ) * Annual Salary of Factory Worker * ( 1 – ( Rate on which company is taxed / 100 ) ) / Number of working hours per year

Again, the only metric attribute that needs some benchmark data is the “Expected percent improvement in employee collaboration”. Everything else is easily obtained through operational data from the company.

Employee productivity was once considered a soft benefit by CFOs. But these days with advanced workplace analytics being provided by at least the top productivity tools, it is easy to quantify productivity at the workplace.