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Linking Productivity and Energy Savings
When productivity-enhancing practices are implemented, the resulting gains and financial savings are often
difficult to quantify, especially when the savings result from practices not focused specifically on productivity.
The focus of this research is primarily on the productivity enhancements resulting from energy
management systems. For example, when recommending energy saving practices, the University of
Florida Industrial Assessment Center (UF IAC) recognizes that increased worker throughput due to more
temperate working temperatures or decreased absenteeism due to day-lighting enhancements can drastically
affect the payback associated with energy savings. However, actually quantifying the productivity increases
has proven difficult.
The university-based Industrial Assessment Centers (IACs) are funded by the Department of Energy to assist small
to medium-sized manufacturing companies find ways to save energy as well as improve productivity. Their work
is reported to their clients in terms of Assessment Recommendations (ARs) which focus on a cost-benefit analysis of
a recommended piece of equipment or technique. Though productivity savings can often surpass energy
savings, productivity savings are not always calculated along with the more obvious energy savings. The
primary reason for this is that data quantifying productivity enhancements is frequently derived from studies
outside of the field in which the IACs work, such as offices and schools, not manufacturing, or involves
longitudinal-type studies for which research time is not allotted. Also, undisputed results are difficult to find.
Though a wide range of energy-related components have an impact on productivity, this research has targeted two
of the most common: lighting and temperature. As shown in Table 1.1, these also have the highest
potential productivity savings.
Table 1.1 Potential Productivity Gains 
Potential U.S. Annual Savings of
Source of Productivity Gain Productivity Gain
Reduced allergies and asthma $1-4 billion
Reduced respiratory illness $6-14 billion
Reduced sick building syndrome symptoms $10-30 billion
Improved worker performance form changes in
thermal environment and lighting
The focus of this paper is to report on studies with hard data to assist in calculating ARs for the IAC; however,
the results of this work are not limited to industrial companies, but can be applied in the commercial sector as well.
The information discussed in this paper was obtained through three avenues. The first source was a review
of existing literature. The second was a survey of industrial engineering departments in a variety of
industries administered by an online questionnaire to approximately 135 industrial engineers. The last source
was interviews with various manufacturing personnel. These sources will be discussed further within the
Effects of Temperature on Energy and Productivity Savings
Environmental temperatures outside the human comfort zone have been shown to negatively affect
productivity. Mental performance such as creative thinking and problem solving, safety, and physical
performance are all areas affected by temperature.
According to Alan Hedge, professor of design and environmental analysis and director of Cornell's Human Factors
and Ergonomics Laboratory, "a cool temperature may affect performance indirectly via distraction and discomfort,
or directly via cooling hands and fingers, which slows movement" . While conducting a month-long study at
the Insurance Office of America's headquarters in Orlando, FL, he found that when the office temperature
was increased from 680F to 770F, typing errors fell by 44%and typing output increased 150%, decreasing
hourly labor costs by approximately $10. This translates to a savings of about $2 per worker per hour.
Temperatures that are too high, decrease performance as well. We know that in a worse-case scenario,
high temperatures may cause life-threatening heat strokes, but according to Work Design: Occupational
Ergonomics, "performance deteriorates well before physiological limits have been reached" . A study conducted
at a call center where registered nurses give medical advice found an average 2% decrement in work
performance per oC temperature rise above 250C. A second study of call center workers found a 15% reduction
in work speed as temperatures increased from 24.50C to 260C. A study of apparel factory workers reported an
8% productivity decrease when temperatures rose from 23.90C to 32.20C. A study of students found that
the performance on tests involving mathematics dropped 10-14% at temperatures of 27-290C from 240C .
A study of task performance in the heat by Ramsey claims that performance of perceptual motor tasks declines
when temperatures reach 30 to 330C . Though these studies differ in the level of productivity decrement, it
is evident that productivity decreases when temperatures are above 240C despite the industry.
As mentioned previously, it is widely accepted that productivity is negatively affected by temperatures outside
the human comfort zone, but uniform limits for the comfort zone are not as generally acknowledged. The reason
for this is that there are varying factors that affect a person's comfort zone. The most obvious is the type of
work being performed. According to Work Design: Occupational Ergonomics , for each 30-watt increase in
a person's metabolism above 115 watts, the comfortable temperature associated with sedentary sitting must
be lowered by 1.70C. Gender and age also affect the comfort temperature. Women tend to have a
comfort temperature 0.20C higher than that of men; and older people generally prefer warmer temperatures.
Other factors include clothing, weight, and humidity. Surprisingly though, the season does not affect
comfort temperature. Lastly, aside from these factors, everyone has a personal temperature preference.
These issues make deriving a standard comfort zone difficult, if not impossible.
Many areas provide the potential to realize savings from increased productivity and reduced energy costs. One of
the easiest is to simply reduce air-conditioning if the temperature is too low. Insulating boilers or machines that
give off extra heat is another simple solution. Applying a coat of reflective paint to a rooftop will reduce
the absorption of heat in a facility. Lastly, according to a study done in the United States, "workers are more likely
to tolerate a wider range of temperatures if they have access to a window or other source for moving air within
eight to 12 feet of their workplace" .
Using the findings of the studies mentioned previously, the productivity and energy savings will be calculated
for insulating a machine located in the middle of a manufacturing facility. The following information is drawn from
an assessment recommendation given to this facility by the UF IAC. Using an infrared camera, the
surface temperature of the machine is determined to be 1400F, while room temperature was 790F. By insulating
this machine, energy usage is reduced because the machine will waste less heat when operating and the
air-conditioning load is decreased since the heat from the machine will no longer add to the room temperature.
By calculating the heat loss before and after insulation, the energy saved can be found as follows.
The heat loss (Qs) is determined for the uninsulated machine using the following calculations. The area to cover
has the following surface area: 4.5 ft x 5 ft:
Qs = U x A X (Ts - Ta)
Q = Overall conductance*, Btu/ft2-OF-hr
Ts= Temperature of surface**, ï¿½F
A = Surface Area, ft2
Ta = Temperature of ambient air around machine, ï¿½F
Qs = U x A x (Ts - Ta) = 628.93 Btu/ft2-OF-hr ' 22.5 ft2 ' (140OF - 790F) = 863,206 Btu/hr
*Conductance measures a material's ability to conduct heat. **Ts was determined using an infrared camera.
The heat loss from a covered machine (Qi) is calculated in the same fashion.
Qi = U x A x (Th - Ta) = 0.204 Btu/ft2-OF-hr ' 22.5 ft2 ' (140OF - 790F) = 280 Btu/hr
The energy savings by insulating the machine is calculated as follows:
ES = (Qs - QI) ' H ' uf' cf
H = Machine operating hours per year, hrs/yr
uf = Utility factor
cf = Conversion factor, 1 kWh/3412 Btu
ES = [(863,206 - 280)Btu/hr ' 8,736 hrs/yr ' 0.75 ' 1 kWh/3412 Btu] ' .15 * = 248,559 kWh/yr
*To be conservative, it is assumed that only 15% of the lost energy is saved.
The additional energy saved on air conditioning (ACS) is found to be 34,467 kWh/yr.
The total energy savings for one machine is the sum of the Air Conditioning Savings and the Energy Savings,
which can be calculated as follows:
TES = ACS + ES = (34,467 kWh/yr) + (248,559 kWh /yr) = 283,026 kWh /yr
Productivity savings on the other hand result from an allowance reduction. See Section 5.0 for more
information concerning these savings. The temperature immediately surrounding the machine is 1400F.
However, the temperature at the location of the machine operator is 1000F. This is temperature will be used
in determining the appropriate allowances. Using Table 5.1, the fatigue allowance given at 1000F is 10%, while
at 790F it is 2%. Therefore, the allowance reduction is 8%. This results in the following productivity savings
per employee per year:
PS = Allowance reduction x Hours/shift x Wage/hour x shifts/week x weeks/year
= 0.08 x 8 hrs/shift x $15/hr x 5 shifts/week x 50 weeks/year = $2,400/employee per year
There are 30 machines with one operator per machine. Therefore, the total annual cost savings (CS) that will
be realized after the implementation of a covering around the machines can be determined as follows:
CS = (TES/machine x cost of electricity without demand x 30 machines) + (PS x 30
employees) (283,026 kWh/yr ' $0.063/kWh x 30) + ($2,400 x 30) = $606,919 /yr
Effects of Lighting on Energy and Productivity Savings
Light is described in terms of quantity and quality. According to the Energy Management Handbook, light
quantity can be described in terms of watts (electrical input), lumens (output of the lighting system), or foot-
candles (how much light reaches the workplace) . By utilizing daylighting, foot-candle output can be
maintained or increased, while potentially eliminating all watt input, thus making a direct contribution to
dollar savings from energy conservation. The quality of light is more subjective to measure, but its influence
on productivity can come from diverse sources of both physiological and psychological origins. A few of the
measures of lighting quality are color rendering index (ability to distinguish color differences), coordinated
color temperature (the color of the light source), uniformity, and glare. Humans react most favorably to
full-spectrum-color light sources most similar to sunlight, and as a result, it is a goal of commercially-used
lighting systems to replicate this characteristic. By utilizing daylighting methods such as strategic placement
of windows or the introduction of skylights, the color benefits affecting attitude and performance can be
provided, and through the use of window films or screening, the negative effects of glare can be eliminated. This
can result in considerable savings as lighting accounts for more than 30% of electric energy use in offices .
Numerous studies and surveys have shown this link between lighting and productivity. A 1998 Harris poll
found lighting to be the number one contributor to worker productivity . Diverse influences such as alertness
and mood, attitude and absenteeism, maintainability and safety can be realized. Certain jobs that involve
inspection or close detail work can be affected directly by light quality, namely visual acuity, and can be
accounted for directly through measurement and calculations. For example, workers' ability to detect flaws in
jet panels at a manufacturing facility of a US defense contractor improved by 20% once daylighting was added to
the facility . However, other aspects are more subjective and difficult to quantify, such as color
temperature's influence on absenteeism. A study conducted at Lockheed Martin found that absenteeism
dropped 15% when daylighting was added to the facility. A second study at Nederlandsche Middenstandsbank's
new headquarters in Amsterdam also found that absenteeism dropped 15% . On the other hand, a
California manufacturing facility found a 40% drop in absenteeism after natural lighting was incorporated .
In the interest of saving energy, certain European countries have passed building codes requiring a
certain percentage of lighting come from outdoors ; for example, in the Netherlands, this value is 37%.
The trend is spreading in the US. The California Energy Code Title 24 specifies certain buildings must have at
least 50% of their floor space illuminated by daylight. However, installing new skylights or windows is not the
only way to experience the benefits of improved lighting practices. Simply cleaning existing windows, skylights,
and lamps or painting walls and ceilings lighter colors also result in enhanced productivity and reduced energy
costs. For warehousing and manufacturing, lowering lamps decreases energy costs while providing improved lighting.
To illustrate the calculations that determine the energy and productivity savings for installing skylights,
an assessment recommendation given to a manufacturing facility in Florida by the UF IAC will be used. The
energy savings result from having sufficient daylight to turn off a fraction of indoor lighting. Energy savings
are divided into two categories: demand savings and energy usage savings. Demand is the rate at which
electrical energy is consumed, measured in kilowatts, while energy usage is the actual electrical energy
consumed, measured in kilowatt-hours.
Demand reduction (DR) can be calculated using the following formula:
DR = N X BFXWeX K
N = Number of lamps
BF = Ballast Loss Factor
We = Wattage of existing lamps
K = Conversion constant, 0.001 kW/W
The demand reduction (i.e., turning off lights) for the 400 W metal halide (MH) lamps in one warehouse is:
DR = 96 lamps x 1.20 x 400 W x 0.001 kW/W = 46.08 kW
The annual energy savings can be calculated as follows:
ES = DR X H
Therefore, if one skylight is added for every 400 W MH fixture, the number of hours (H) that will have
sufficient daylight to turn off the 400 W MH lights is approximately 2,470 hours per year. Consequently, the
energy savings for these lamps is:
ES = 46.08 kW x 2,470 hours/year = 113,818 kWh/year
The energy cost savings (ECS) for turning off lights can be calculated as follows:
ECS = (ES x CEWD) + (DR x ADC x 12 months/year)
CEWD = Cost of Electricity without Demand, $0.031/kWh
ADC = Average Demand Cost, $5.88 /kW/mo
ECS = (113,818 kWh/yr x $0.031/kWh) + (46.08 kW x $5.88/kW/month x 12 months/yr) = $6,780/yr
On the other hand, productivity savings result from an allowance reduction and are calculated similarly to
the insulation example in Section 3.0. See Section 5.0 for more information concerning these savings. Using
Table 5.2, an allowance reduction of 1% would apply after installing skylights. Productivity savings would be:
PS = Allowance reduction x Hours/shift x Wage/hour x shifts/week x weeks/year
= 0.01 x 8hrs/shift x $15/hr x 5 shifts/week x 50 weeks/year = $300/year
With 50 employees in this area:
PS = $300/employee per year x 50 employees = $15,000
Absenteeism reduction is another area of productivity that would result in savings. The studies listed above found
a 15% drop in absenteeism when installing skylights. According to the US Department of Labor Bureau of
Labor Statistics, the absenteeism rate for manufacturing is 3.8% . Therefore, there would be approximately
71 fewer absences a year. For each absence, there is the additional overtime cost of a replacement plus the cost
of finding the replacement. These results in an absenteeism saving (AS) of:
AS = 71 x (overtime cost + finding replacement cost*)
= 71 x ($15/hour xl1.5 x 8 hours/shift + $15/hour x 0.5 hours) = $13,313/year
*Assuming it takes 30 minutes to find a replacement.
Total cost savings (TCS) can be calculated as follows:
TCS = ECS + PS + AS = $6,780 + $15,000 + $13,313 = $35,093/year
Allowance Impact on Productivity Savings
In addition to the productivity enhancements mentioned in previous sections, another way to quantify
improvements is through the percentage of allowance time that must be included when calculating the standard
time of a task. The standard time is the measured time (found through conducting time studies) with additional
time given to compensate for time not spent working. This additional time is an allowance. There are three types
of allowances: personal, delay, and fatigue. Personal allowances are given for everything from using the restroom
to getting a drink of water. Delay allowances are given for machine breakdowns or supervisor interruptions.
Fatigue allowances are used to compensate for time lost due to fatigue. To calculate the effect lighting
or temperature has on productivity, we are interested in the allowances for vision fatigue and for physical fatigue
due to the influence of temperature. Through surveys of industrial engineering departments throughout
various industries, it was found that very few industrial departments consider the effects of temperature or
lighting when conducting time studies and allotting allowances though they can have a substantial impact.
From Work Design: Occupational Ergonomics, the following tables are used to calculate the allowances. They
were developed by the International Labor Organization in 1992 .
Temperature Allowances (%) 
Conditions Temperature ï¿½C
Ventilation and Circulation and Humidity Below -1 -1 to 13 13 to 24 24 to 38
Adequate ventilation and circulation; normal climatic 10 to 20 1 to 10 0 1to 10
Inadequate ventilation and circulation; nonstandard 20 to 25 5 to 10 0 to 5 5 to 15
climatic conditions, causing some discomfort
Very poor ventilation and circulation, fumes, dust, 20 to 30 10 to 20 5 to 10 10 to 20
steam, causing irritation to eyes, skin, nose, throat
Light Allowances (%) 
Allowance (%) Category
1 "Normal" lighting (200 to 500 lux in most industries; 500 to 1000 if offices and inspection); absence of
glare is apparent
2 Occasional glare is inherent part of job or where substandard or special lighting is required.
Continual glare is inherent part of job; also for work requiring constant change from lighted area to
darkness (less than 50 lux); also work requiring "Venetian blind" effect (shiny and dull surface in lathe
3 Work in absence of light or where sight is obstructed (noticeable by feel of fingers or feet); eyes not
used or are straining (photo darkroom, mechanic under machine)
Visual Allowances (%) 
Category Adequate Lighting Inadequate or Disturbed
No special eye attention required 0 0
Close eye attention intermittently; or continuous 0 1
eye attention with varying focus
Continuous eye attention with continuous focus 1 to 3 4 to 8
Using these tables, the effect of temperature and lighting was demonstrated in the previous sections. For example,
if the temperature in a work environment were 38ï¿½C with adequate ventilation, using Table 5.1, a task would
take 10% longer to complete in normal conditions.
In addition to the direct productivity enhancements discussed previously, temperature and lighting indirectly
affect productivity. For example, lower employee turnover is a side effect of improved working conditions.
Harris Rothenberg, LLC, a New York City-based performance consulting firm, estimates that "replacing an
employee costs 1.2 to 2 times their annual salary due to organization inefficiency while the position is vacant and
the processing costs related to the new hire" . According to this study, a new employee will reach
maximum efficiency and performance only after 13.5 months of employment. Reduced turnover results
in significantly high savings, however, these savings are difficult to quantify. Another productivity component
that may be affected by temperature and lighting is safety. An employee's job satisfaction and motivation
also increase, but again, quantifying this is not an easy task.
An additional challenge faced when calculating savings comes from the Hawthorne effect. An employee's
behavior may be altered because they know they are being studied . This may cause differentiating the
savings from lighting or temperature to be difficult if not impossible.
In conclusion, though difficult to compute at times, environmental temperature and lighting do have a
substantial effect on worker productivity regardless of the industry. This effect is evidenced through standard
time allowances. Despite the fact that studies measuring the effect of temperature or lighting on productivity
have found varying results, all agree there is a measurable link between productivity and environmental conditions.
1. Fisk, William J. "Health and Productivity Gains from Better Indoor Environments and Their Relationship with
Building Energy Efficiency." 2000. .
2. Hedge, Alan. "Linking Environmental Conditions to Productivity." Cornell University. Ithaca, NY. 2004.
3. Konz, S. and Johnson, S. Work Design: Occupational Ergonomics. 6th Ed. Holcomb Hathaway, Publishers, Inc.
4. Seppanen, 0., Fisk, W., and Faulkner, D. "Cost Benefit Analysis of the Night-Time Ventilative Cooling in
Office Buildings." .
5. Ramsey, J. "Task Performance in the Heat: a Review." Ergonomics, Vol. 38, p 154-65. 1995.
6. Zambito, V. "The Connection between Office Temperature and Productivity." May 23, 2000.
7. Energy Management Handbook, 2004.
8. Knisley, J. "Improve Employee Productivity with Custom Office Lighting." 2005.
9. Westfall, Robert. "Tubular Skylights Take Lighting to Natural Heights." Solatube - The Miracle Skylight -
Daylighting for Everyday Living. 2005. .
10. Pierson, John. "Design: If the Sun Shines In, Workers Work Better, Buyers Buy More." Wall Street Journal,
p B1. Nov. 20, 1995.
11. US Department of Labor Bureau of Labor Statistics. "US Employee Absences by Industry: 1997." The Public
Purpose, Labor Market Reporter. .
12. Konz, S. and Johnson, S. Work Design: Industrial Ergonomics. 5th Ed. Holcomb Hathaway, Publishers, Inc.
13. Clark, Donald. "Hawthorne Effect." 1999. .
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