Financial and resource performance of small to medium sized businesses (SMEs) in the ecoBiz program

Financial and resource performance of small to medium sized businesses (SMEs) in the ecoBiz program 2017-2020 Griffith Centre for Sustainable Enterprise May 2020

Dr Rob Hales, Ian Edwards, Tilak Liyanaarachchi, Dr Savindi Caldera and Vanessa Taveras Dalmau

Contents Executive summary 4 1 | Introduction 6 1.1 ecoBiz 7 1.2 Terminology 7 2 | Data included in study 8 2.1 Types of Businesses 8 2.2 Consumable lines 11 2.3 Data limitations 11 3 | Methodology 12 3.1 Data selection 13 3.2 Calculations 13 3.2.1 Change in productivity and avoided cost savings calculations

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3.2.2 Greenhouse gas emissions calculations 13 4 | Findings 14 4.1 Productivity 15 4.2 Avoided costs 16 4.3 Avoided emissions 18 5 | Economic impacts 20 5.1 Energy efficiency economic impact 21 5.2 Further study 21 Appendix A | Data analysed 22 Study data selection 22 Business characteristics 22 Consumable line characteristics 23 Appendix B | Calculations 25 Avoided savings 25 Avoided emissions 25 Appendix C | Study results 26 References 28 3

Executive summary

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Between late 2017 and early 2020, ecoBiz has had over 700 businesses participate in its program and there have been many reports outlining positive benefits of the program. The current research provided in this report supplements previous research by providing an in-depth analysis of businesses that have had a long period of reporting within the program. As such, estimates of the impact of the program can be made with more confidence relating to the relationship between ecoefficiencies and productivity of SMEs. The following key findings illustrate the impact of the program: • Over $7.4 million in costs were avoided due to productivity increases apparent between base and subsequent years.

• The average cost/efficiency savings in energy, waste and water consumption was $80,434 per business.

• Productivity increases averaged 24%, 23% and 22% per annum for energy, waste and water consumption, respectively.

• CO²e emissions were reduced in businesses amounting to almost 30,000 metric tonnes of CO²e.

• Energy was the dominant source of both absolute and average avoided costs recording savings of almost $6.7 million.

• Increases in energy efficiencies from manufacturing in the Darling Downs Maranoa region contributed the greatest absolute and average avoided costs.

• Over 90% of businesses recorded an increase in productivity for at least one consumable line.

• Based on avoided costs and the large increase in productivity it is estimated that there would be a significant impact on the Queensland Gross Domestic Product (GDP) resulting from a scaled up ecoBiz program. Further analysis including costs of implementing ecoBiz measures and multiplier effects on the economy is needed to determine the extent of the positive impact.

The ecoBiz program has high levels of cost savings and economic impact resulting from eco-efficiency initiatives. If the program were to be scaled up with corresponding investment, large scale impacts on SMEs and the economy can be expected. The challenge will be to determine ways to increase the scale of the program in ways that can maximise the benefits of increased financial program cost. Now that robust data systems are in operation at ecoBiz, more detailed economic analyses of future scaled up operations is possible.

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1 | Introduction

6

This report presents the findings of an analysis of financial and resource performance of small to medium sized businesses (SMEs) subsequent to their participation in the ecoBiz program.

1.1 ecoBiz ecoBiz is a fully subsidised program implemented by the Chamber of Commerce and Industry of Queensland (CCIQ) and the Queensland Government’s Department of Environment and Science (DES).

The objective of the program is to help Queensland SMEs reduce their environmental impact while saving money. ecoBiz’s vision statement is: Delivering scalable and responsive program that supports growing demand from Queensland businesses to reduce their environmental impacts and increase their productivity and competitiveness. ecoBiz is an essential component of the Queensland Government’s sustainability agenda through targeting climate change, waste and energy initiatives for SMEs. The program provides a one-on-one coaching session and a report tailored to each business’s needs and ambitions. Participating businesses receive an action plan that identifies no, low, and higher cost options for efficient practices. Between late 2017 and early 2020, the program had delivered personalised one-on-one coaching sessions to over 700 businesses with over 220 of these achieving ecoBiz Star Partnership1 status.

1.2 Terminology The following terms are used as defined in this study.

Consumable line: The type of energy, water or waste resource consumed or inadvertently produced in the delivery of a product or service. Consumable lines analysed in this report are: • Energy: diesel petrol; unleaded petrol; liquid petroleum gas (LPG); natural gas and electricity.

• Waste: cardboard; co-mingled recycling and general.

• Water: potable.

Resource type: Grouping of consumable lines by over-riding nature, i.e. energy, waste and water.

Productivity unit: Reflects an input to the SME as either a unit of product or service produced or provided, e.g. billable hours, tonnes of product produced, guest nights, patronage, etc. Productivity units closely correlated to resource consumption can provide a view of resource efficiency and productivity.

Productivity: Refers to how much output can be produced with a given set of inputs. Productivity increases when more output is produced with the same amount of inputs or when the same amount of output is produced with less inputs.

See Methodology section for how productivity is calculated in this report.

1 ecoBiz Star Partnership is awarded to businesses that have completed initial program requirements and achieved a minimum 10% reduction in their energy, water and/or waste use.

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2 | Data included in study This section provides an overview of ecoBiz data analysed in this study. Further details are provided in Appendix A. 2.1

2.1 Types of Businesses 92 businesses form the data set analysed in this study. Of these, 85 provided energy data whilst 32 and 19 provided water and waste data, respectively.

Table 1. Number and type of businesses analysed.

Energy Number of businesses

Waste

85

Water

19

Total

32

92

Over half of the businesses (63%) are from the arts and cultural services, manufacturing, and professional, scientific and technical services sectors (Figure 1). Businesses from South East Queensland comprise 65% of those analysed (Figure 2). 75 businesses provided only one year of data subsequent to base year, i.e. two data points (Table 2).

Table 2. Sample businesses dissected by number of years of data.

Number of data points

Energy

Waste

Water

Total

2

67

14

26

75

3

11

3

1

12

4

4

1

3

4

5

1

1

2

2

6

2

Total

85

2 19

32

* Note that three businesses submitted consumable data sets with differing data points (e.g. Company x provided 2 years of energy data but only one year of waste data).

Industrial Spread of Businesses Studied

Prof, Scientific and Tech Services 19%

Accomm, Cafes, Rest's & Food Services 9% Educ & Training 5%

Personal & Other Services 4%

Retail Trade 5% Ag, Forestry and Fishing 2% Other Industries 24%

Construction 2% Healthcare & Social Assist 2%

Manufacturing 20%

Transport, Post & W'housing 2%

Wholesale Trade 2% Arts/Cultural & Recreation Services 23%

Other 5%

Figure 1. Sample data categorised by business industry (n=100).

8

95*

9

10

Regional Spread of Businesses Studied

Other SEQ 16% Cairns 6% Sunshine Coast 10%

Central Queensland 3% Downs - Maranoa 8%

Gold Coast 9%

Other 35%

Mackay - Isaac - W'sunday 3%

Townsville 6% Brisbane Inner City 21% Other Regional 9%

Brisbane - South 9%

Figure 2. Sample data categorised by region where business is located (n=100).

2.2 Consumable lines The majority of data analysed related to electricity and water consumption (approximately 50% and 20% of all data, respectively) (Table 3). Concerning waste, little information was submitted about cardboard and co-mingling recycling. This is because the waste metric is defined as reduction in waste to landfill, and therefore general waste billing information is most important for calculating partnership.

Table 3. Business submissions of data by consumable line.

Consumable line Diesel

Energy

Waste

Water

Total

6

6

85

85

LPG

3

3

Natural Gas

9

9

Electricity

Potable Unleaded

32

32

4

General

4 19

19

Cardboard

1

1

Co-mingled recycling

1

1

Total Consumable Lines Total Individual Businesses (see Section 2.1)

107

21

32

160

85

19

32

92

2.3 Data limitations These results should be interpreted within the context of the data available. As noted above, only a small sample of data was ultimately available for analysis. This data was significantly skewed towards electricity consumption and in the vast majority of cases only one annual data point was available to compare with base data.

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3 | Methodology

12

3.1 Data selection The full dataset that underpins this study was derived from that originally received through the following process: Step 1. Cleanse data

Step 2. Exclude any excessive movement

Records were excluded from the final dataset where characteristics (e.g. costs, productivity or consumable units) were absent or where only one year of data had been received (typically the base year only).

Any consumable lines that displayed an excessive increase or decrease in efficiency (set at greater than 70%) were excluded from the final data.

Result: 100 businesses with 160 consumable lines.

More details of this cleansing process are provided in Appendix A.

Result: 92 businesses with 122 consumable lines.

3.2 Calculations 3.2.1 Change in productivity and avoided cost savings calculations For a given business, cost savings presented in this study reflect the impact of productivity increases on the total number of products or services produced subsequent to ecoBiz participation. That is, what is the difference between the cost as incurred versus the one that would have been incurred without any change in productivity. This approach is illustrated in the below example.

Table 4 indicates the changes in productivity in the following in their base year and a change directly after the ecoBiz program.

Table 4. Change in business activity post ecoBiz program.

Total recorded

Key

Base Year

Year after EcoBiz

Change

Widgets Produced

A

100

120

20

Electricity Consumed (GJ)

B

25

24

(1)

Electricity Cost ($)

C

2,500

2,880

380

Cost per GJ ($)

D

100

120

20

The above table displays that since the ecoBiz program, 1 GJs of electricity produces 5 widgets compared to 4 widgets prior.

This represents an increase in productivity of 25% ((5-4)/4). Thus, if productivity had not increased, Business X would have consumed 25% more electricity than it actually did, i.e. 30 GJs instead of the 24 GJs. At most recent prices ($120), this equates to avoided costs of $720.

In ring-fencing the impact of productivity on cost, the objective of this approach is to highlight the influence of the ecoBiz program on business profitability. This approach explicitly excludes any impact on total cost due to changes in consumable unitary prices typically driven by broad market factors over which individual firms hold no control. Note that where there is more than one year of post-program data available, the most recent data (termed "final year") is applied to calculate any productivity change. In this circumstance, avoided costs are a yearly figure that represent those costs avoided in the final year of data available for each business based on productivity increase between that year and the base year. An average productivity figure is calculated on the assumption that productivity increases linearly between base and final years.

3.2.2 Greenhouse gas emissions calculations Avoided carbon dioxide emissions are based on productivity increases as detailed above. They are presented in equivalent tonnes of carbon dioxide (CO²e) that has been aggregated from estimated CO², methane (CH4) and nitrous oxide (N²O) emissions. These are calculated in accordance with the Australian Greenhouse accounts factors detailed in Appendix B. Avoided emissions are calculated for energy consumption only due to the immateriality of waste savings and lack of requisite information to determine water related savings. The findings are likely to be an underestimation of real CO² emissions based on 13 calculation of productivity above.

4 | Findings

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This section presents highlight results of this study.

4.1 Productivity Of the 92 businesses analysed in this study 88 (> 90%) recorded an increase in productivity for at least one of their consumable lines (Table 5). This represented an increase in productivity in over 75% (122) of the 160 consumable lines analysed of which energy displayed increases for over 80% of consumable lines (Figure 3). Productivity increases averaged 24%, 23% and 22% per annum for energy, waste and water consumption, respectively (Figure 4).

Table 5. Direction of productivity changes dissected by individual businesses (n=92) and consumable lines (n=160), where both equals both consumable line increases and decreases in productivity for a given business.

Number of individual businesses Productivity change:

Number of consumable lines Increase

Increase

64

Decrease

8

Decrease

95

Total 95

12

12

Both

20

27

26

53

Total

92

122

38

160

Direction of Change in Overall Productivity (Dec = decreased productivity; Inc = increased productivity) 100%

Proportion of Consumable Lines Movement

90% 80% 70% 60%

21

15

86

50% 40% 30% 20% 10%

11

6

21

0% Energy

Waste Dec

Water

Inc

Productivity Direction (Labels represent Consumable Data Sets)

Figure 3. Proportion of consumable lines that showed an increase or decrease in productivity (n=160).

15

25%

Average Annual Increase in Productivity

by Resource Type

24%

24%

Productivity Increase

24%

23%

23%

23%

22%

22%

22%

21%

Energy

Waste

Water

Figure 4. Average increase in resource productivity by resource.

4.2 Avoided costs Total avoided costs across the three resource types equated to over $7.4 million (Table 6). Energy was the dominant source of both absolute and average avoided costs, recording savings of almost $6.7 million. The manufacturing industry recorded highest avoided costs, attributable predominantly to reduced consumption of electricity and natural gas per productive unit (Figure 5). Avoided savings were highest in the Darling Downs-Maranoa region due predominantly to the extent of manufacturing located there (Figure 6). Avoided costs are calculated on an annual basis (Table 6). They are a function of productivity increase between final and base year performance applied to final year total production and per unit resource cost. Table 6 shows the total and average avoided costs as the final year total and average avoided costs by consumable line calculated in accordance with Section 3.2.1�

Table 6. Total and average avoided savings.

Energy Total avoided costs Number of consumable lines Average avoided cost per consumable lines

16

Waste

Water

Total

$6,668,769

$41,494

$713,539

$7,423,802

86

15

21

122

$77,544

$2,766

$33,978

$60,850

135

85

Total Savings ($'000)

35

Savings per Consumable Line ($,000)

Avoided Savings by Industry

4,000 3,000 2,000 1,000 0 Arts/Cultural & Manufacturing Recreation Services

Savings $ Avg Savings $

Retail Trade

Information Media & Telecommunica tions

Education & Training

Agriculture, Forestry and Fishing

Professional,Sci entific and Technical Services

Other

4,775

1,987

166

144

90

54

47

160

165

74

55

72

18

27

2

5

Figure 5. Avoided savings by industry.

17

350

250

150

50

Savings per Consumable Line ($,000)

Avoided Savings by Region

Total Savings ($'000)

3,000

2,000

1,000

0

Savings ($'000) Avg Savings ($'000)

Darling Downs Maranoa

Ipswich

Brisbane Inner City

Brisbane South

Gold Coast

Sunshine Coast

Moreton Bay - North

Brisbane East

3,335

1,289

1,230

474

345

290

208

137

30

87

303

161

41

39

43

24

30

27

7

9

Other South Other East Qld Regional Qld

Figure 6. Avoided Savings by region.

4.3 Avoided emissions Analysis of the most recent annual energy data of organisations analysed in this study displayed in Table 7 below indicates that almost 30,000 metric tonnes of CO2 equivalent were avoided subsequent to ecoBiz participation. This is equivalent to taking just over 6,500 cars off the road1. Note that the final year avoided emissions by energy consumable type calculated in accordance with Section 3.2.1.

Table 7. Avoided emissions by energy consumable type.

Diesel Electricity LPG Natural gas Unleaded Total

Avoided consumption (GJ)

Avoided cost ($)

Avoided CO2 emissions (metric tonnes)

60

2,062

164

98,039

4,478,422

22,059

46

2,044

74

125,039

2,166,096

6,443

537

20,144

1,241

223,719

6,668,769

29,980

1 Based on average annual CO² emissions of 4.6 metric tonnes per annum (https://www.epa.gov/greenvehicles/greenhouse-gasemissions-typical-passenger-vehicle).

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5| Economic impacts

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5.1 Energy efficiency economic impact The shift caused by demand-side ecoefficiency initiatives such as the ecoBiz program can result in economy-wide macroeconomic impacts, such as effects on income, employment, and overall economic output. An analysis of the magnitude and direction of the impacts can help policy makers design policies that provide the greatest overall benefit to a state or locality. Given the proportion of energy data analysed in this study compared to other resource types we consider the EcoBiz avoided costs will have significant positive impacts on the broader economy.

Direct economic effects of demand-side initiatives, energy efficiency and renewable energy initiatives typically change the energy consumption patterns of business by reducing the quantity of energy required for a given level of production or service. Energy plays a significant role in the economy as a major factor of production. Given higher real energy prices, the efficient use of energy can contribute positively to economic growth. The European Commission modelled four different scenarios of energy efficiency in 2017 (IEA, 2019). The GDP impact ranged from 0.1% increase in GDP in the least ambitious scenario, up to 2.0% increase in GDP resulting from energy efficiency. Other studies from Germany indicate larger increases of 3.38% resulting from 1% increase in energy efficiency (Hartwig et al., 2017). Table 8 shows the selected benefits of the ecoBiz program.

Table 8. Table 8. Selected benefits of the ecoBiz program.

Present Program Average cost of ecoBiz per year

$1.2 million

Avoided costs SMEs in ecoBiz/year

$7.4 million

Average number of ecoBiz participants per year

384.83

Number of QLD SMEs 2019

438,000

GDP of SMEs in QLD (2019)

$113,000,000

ecoBiz SMEs as proportion of QLD SMEs/year

0.09%

The above table indicates the size of ecoBiz program is relatively small compared to the number of SMEs in QLD. However, productivity increases and avoided costs indicate large benefit to business from participating in ecoBiz program. It must be noted that the ecoBiz program does not collect data from businesses on the cost of implementing the eco-efficiency measures resulting from advice from ecoBiz. Some estimation of costs could be undertaken from survey work. Future collection of actual costs of implementing the eco-efficiency measures is needed to accurately assess the return on investment.

Even though cost of implementation of eco-efficiency measures is not included it is expected there would be a high return on investment (in terms of funding from the Queensland Government to the ecoBiz program) especially given the findings from other studies which indicate positive contribution to GDP and other social, environmental and economic benefits. We recommend that further studies be conducted to determine the full range of benefits of the ecoBiz program which also include an accurate inclusion of cost of implementing ecoBiz recommendations.

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5.2 Future research Further research into the following aspect of the benefits of ecoefficency measures implemented in business as a result of participation in ecoBiz programs. The following list outlines further areas of research.

• EcoBiz collection of actual costs from business of implementing the eco-efficiency measures to accurately assess the return on investment of Queensland Government funding of the program • The economic effect of the implementation of ecoefficiency measure. Most modelling only includes one or two parameters whereas multiple parameters need to be included in cost benefit analysis.

Multiple parameters include: • GDP increases from energy efficiency (1% increase in energy efficiency has a range of 1.03.8% increase in GDP) • GHG savings from all ecoefficiency measures not just energy avoided costs • Avoided deaths and illness caused by fossil fuel pollutants • Innovation impacts resulting from avoided costs and productivity gains • Employment effects of increased productivity and avoided costs • Public budget effects (tax) of increased revenue on productivity and increased employment • Increased sales/inputs as a response to increase sustainability reputation • Financial return from increased competitiveness • Financial benefits of continuity and security of supply (energy, water) • Increase in asset value of commercial properties We recommend future research which includes cost to businesses of implementing ecoefficiency measures as per advice provided by ecoBiz and a full assessment of benefits of implementing these measures on business and the economy. Given present and predicted economic downturn, ecoefficiency funding is a guaranteed way of economic stimulus through small business assistance and has the added benefit of being one of the most cost-effective greenhouse gas abatement actions that governments can undertake. The findings of this research indicate that there is a high likelihood of large benefits to business and economy of an expanded program of ecoBiz given high productivity increases and high avoided costs of participating business, and the findings from other initiatives that have shown large economic benefits of strong ecoefficiency programs.

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Appendix A | Data analysed Study data selection The following table shows that of the 6,871 records representing 129 individual businesses. Data from many of these businesses were excluded due to invalid or missing data such as product units or costs.

Further reduction in the number of data records was undertaken to exclude outliers. Businesses that had an average annual efficiency movement were deemed to be outliers (i.e. greater than 70%). A total of 92 business with 4614 records were included in the survey.

Table 9. Comparison and data and received and included in study.

Included in study Records received

Average annual move > 70%

Data quality issue

Total

4,614

701

1,556

6,871

92

8

29

129

Individual businesses

Business characteristics The following tables display the industries and Queensland regions included in this study. As noted in the main body of this report, three sectors represent over 61% of businesses analysed (noted in red in Table 10) whilst the majority of businesses are located in South East Queensland (see Table 11).

Table 10. Sample businesses dissected by industry sector.

Industry sector

Energy

Waste

Accommodation, cafes, restaurants and food services

6

Agriculture, forestry and fishing

2

Arts/cultural and recreation services

Water 1

Total 2

8

1

2

22

5

6

23

Construction

2

1

1

2

Education and training

5

3

5

Electricity, gas, water and waste service

1

1

1

Healthcare and social assistance

2

Information media and telecommunications

1

1

1

1

17

7

7

17

1

1

Manufacturing

1

2

Mining Personal and other services Professional, scientific and technical services

2

2

2

4

15

1

5

16

Public administration, defence and safety

1

Rental, hiring and real estate services

1

1

1

Retail trade

4

1

4

Transport, postal and warehousing

2

2

Wholesale trade

2

2

Total

85

1

19

32

92

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Table 11. Sample businesses dissected by region.

Region

Energy

Waste

Water

Total

Brisbane—East

4

4

Brisbane—North

1

1

Brisbane—South

7

2

Brisbane—West

1

1

17

6

Brisbane Inner City

3

8 2

12

19

Cairns

5

5

Central Queensland

3

3

Darling Downs—Maranoa

8

2

2

8

Gold Coast

7

1

4

9

Ipswich

4

3

1

4

Logan—Beaudesert

2

1

Mackay—Isaac—Whitsunday

3

Moreton Bay—North

3

Moreton Bay—South

1

Queensland—Outback

2

Sunshine Coast

3 1

3

2

3

3

1

1

1 2

10

4

10

Toowoomba

1

1

1

Townsville

5

5

Wide Bay

1

1

Total

85

19

32

92

Consumable line characteristics The following tables present the extent of consumable lines ultimately applied to the study. Table 12 displays that electricity represented the majority of data applied to the study. Little data was received for other energy consumable lines and waste. Thirty-two datasets for potable water were applied.

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Table 12. Consumable data sets analysed by industry.

Agriculture, forestry and fishing

2

Arts/cultural and recreation services Construction

2

2

1

3 35

1

1

6

3

Electricity, cas, water and waste service

1

1

Healthcare and social assistance

2

Information media and telecommunications

1 17

10

5

5

3

1

6

Education and training

Manufacturing

Co-mingled recycle

Cardboard

Potable water

Unleaded

2 1

22 1

Natural Gas 1

Total

6

Water Waste General

Accommodation, cafes, restaurants and food services

LPG

Electricity

Consumable / industry

Diesel

Energy

8 1

2 1 2

5

1 1

Mining

7

1

1

4

7

43

1

Personal and other services

2

Professional, scientific and technical services

3

1

15

1

2

1

5

2

8

1

21

Public administration, defence and safety

1

Rental, hiring and real estate services

1

1

2

Retail trade

4

1

5

Transport, postal and warehousing

2

Wholesale trade Total

6

1

2

1

2

1

85

3

5 3

9

4

32

1

1

19 160

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Appendix B | Calculations Avoided savings The following table shows that of the 6,871 records representing 129 individual businesses. Data from Avoided savings are calculated as a function of final year costs in accordance with the following steps.

Step 1 Calculate avoided consumption (AvCons) AvCons = ((Cons UnitsBaseYear)/(Prod UnitBaseYear) x Prod UnitFinalYear) – Cons UnitsFinalYear Step 2 Calculate avoided costs (AvCost) AvCost = AvCons x Per unit consumable costFinal Year

Avoided emissions The avoided emissions presented below (Table 13) are calculated from avoided resource type consumption in accordance with Australian Greenhouse accounts factors (Table 14).

Table 13. Avoided emissions by energy consumable.

Avoided Type

Unit

Diesel

Consumption (GJ)

Avoided emissions (CO2-e tonnes)

Consumption (Unit)

Cost ($)

CO2

CH4

N2 O

Total

GJ

60

60

2,062

162

0

1

164

KWH

98,039

27,232,935

4,478,422

22,059

-

-

22,059

LPG

GJ

46

46

2,044

72

1

1

74

Natural gas

GJ

125,039

125,039

2,166,096

6,427

13

4

6,443

Unleaded

GJ

537

537

20,144

1,237

0

4

1,241

223,719

27,358,616

6,668,769

29,957

14

9

29,980

Electricity

Grand Total

Table 14. Emission factors sourced from Australian National Greenhouse Accounts August 2019 Emission Factor (kg CO2-e) Unit GJ

Energy content factor

CO2

CH4

N2O

38.6

69.9

1

0.81

GJ

26.2

60.2

0.6

0.7

Table 4

GJ

1

51.4

0.1

0.03

Table 2

GJ

34.2

67.4

0.02

0.2

Table 4

KWH

0.1

0.5

Table 4 Table 5

(Source column in this table references tables in the Accounts from which factors sourced).

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Source

39%

42%

19%

28%

Electricity, gas, water and waste service

Healthcare and social assistance

Information media and telecommunications

Manufacturing

8%

26%

39%

16%

24%

24%

Rental, hiring and real estate services

Retail trade

Transport, postal and warehousing

Wholesale trade

Total

23%

Professional, scientific and technical services

Public administration, defence and safety

10%

Personal and other services

33%

Education and training

Mining

19%

Construction

Productivity increase (PA)

19%

Consumable data sets

Arts/cultural and recreation services

2,440

23,423

165,814

3,176

6,214

45,780

23,142

4,309,064

126,363

24,083

6,544

86,535

6,435

1,745,685

53,867

86 6,668,769

3

3

3

1

1

14

3

20

1

2

1

4

3

18

Avoided costs $

2

Productivity increase (PA)

12%

23%

13%

2%

26%

27%

31%

Consumable data sets

Agriculture, forestry and fishing

42

255

24,801

63

16,251

15 41,494

1

2

6

1

4

Avoided costs $

81

22%

6%

15%

10%

55%

20%

18%

19%

46%

24%

48%

Productivity increase (PA)

1

21

1

5

2

1

3

1

1

1

5

1

Consumable data sets

22%

713,539

18

1,289

831

1,521

441,283

17,743

244

3,608

225,467

21,534

Avoided costs $

40,204

24%

24%

16%

39%

16%

8%

20%

8%

55%

26%

19%

42%

28%

35%

19%

22%

12%

29%

Productivity increase (PA)

7

Water

Total

122

3

3

3

2

1

20

7

1

29

2

2

3

5

3

27

2

9

Consumable data sets

27%

Waste

7,423,801

2,440

23,423

165,814

3,194

6,214

47,111

24,229

1,521

4,775,148

144,106

24,083

6,852

90,143

6,435

1,987,403

53,867

61,820

Avoided costs $

Accommodation, cafes, restaurants and food services

Industry

Energy

Appendix C | Study results

This appendix presents calculated productivity increases and avoided costs aggregated by both industrial sector and region.

Table 15. Industrial sector increases in productivity (pre-sector aggregation).

27

28 24% 20% 23% 23% 29% 27% 43% 56% 16% 15% 6% 42% 26%

Brisbane—West

Brisbane Inner City

Cairns

Central Queensland

Darling Downs - Maranoa

Gold Coast

Ipswich

Logan—Beaudesert

Mackay—Isaac— Whitsunday

Moreton Bay—North

Moreton Bay—South

Queensland Outback

Sunshine Coast

20% 12% 24%

Townsville

Wide Bay

Total

86

1

5

9

1

3

4

3

2

5

5

9

3

3

18

6,668,769

429

33,573

225,595

4,756

2,856

148,112

16,158

14,298

1,281,258

307,096

2,944,156

28,053

8,938

1,042,814

1,031

23%

6%

27%

1%

40%

11%

64%

18%

13%

Consumable data sets

15

1

1

1

3

1

1

4

1

2

41,494

975

63

122

8,190

15,172

9,648

6,637

181

507

Avoided costs $

1

Productivity increase (PA)

15%

22%

46%

14%

4%

16%

6%

51%

42%

17%

28%

Productivity increase (PA)

472,267

544

21

1

3

1

2

1

2

1

8

2

Consumable data sets

8

1

713,539

3,608

64,090

656

59,446

18

23,055

381,425

180,361

879

Avoided costs $

Toowoomba

19%

Brisbane—South

Productivity increase (PA)

20%

Consumable data sets

Brisbane—North

Avoided costs $

136,835

24%

12%

20%

46%

23%

42%

5%

17%

14%

37%

42%

31%

33%

23%

23%

19%

18%

20%

20%

24%

Productivity increase (PA)

5

Water

122

1

5

1

12

1

5

7

4

3

8

8

11

3

3

30

2

12

1

5

429

33,573

3,608

289,685

4,756

4,487

207,621

16,176

14,420

1,289,448

345,323

3,335,229

28,053

8,938

1,229,812

1,212

473,653

544

136,835

7,423,801

Total Consumable data sets

24%

Waste

Avoided costs $

Brisbane—East

Region

Energy

Table 16. Regional increases in productivity (pre region aggregation).

References • Hartwig, J., Kockat, J., Schade, W. & Braungardt, S. 2017. The macroeconomic effects of ambitious energy efficiency policy in Germany – Combining bottom-up energy modelling with a non-equilibrium macroeconomic model. Energy, 124, 510-520.

• IEA. 2019. Multiple Benefits of Energy Efficiency: From “hidden fuel” to “first fuel”. [Online].

International Energy Agency. Available: https://www.iea.org/reports/multiple-benefits-ofenergy-efficiency/economic-benefits-2 [Accessed 24 April 2020].

CRICOS No. 00233E

Griffith Centre for Sustainable Enterprise gcse@griffith.edu.au griffith.edu.au/griffith-centre-for-sustainable-enterprise