farming(together(program( …jersey.com.au/wp-content/uploads/2018/04/case-02304-jersey-milk... ·...

FARMING TOGETHER -‐ COMPLEX EXPERT SERVICES REPORT – Case 02304

FARMING TOGETHER PROGRAM JERSEY MILK COMPONENT PROJECT CASE NUMBER : 02304 OCTOBER 2017

2 Jersey Milk Component Project

ACKNOWLEDGEMENTS Several people have assisted with the compilation of this report. Thanks to Jane Sykes and Mike Weise from Jersey Australia, for their assistance with sourcing data and Paul Kerr for support with data analysis. Also to Paul Kerr and John Mulvany for their contribution over a long period of time towards public debate on improving the milk pricing systems in Australia. Thanks also to the Farming Together Program for funding this project.

Patten Bridge, Bridge Logic Consulting.

TABLE OF CONTENTS

1 PROJECT BRIEF ................................................................................................................... 3 2 BACKGROUND ..................................................................................................................... 3 Notes on Australian Milk Pricing Systems ............................................................................. 3 How do the current systems handle milk components? ................................................... 4

3 METHODOLOGY .................................................................................................................. 5

4 FARM DATA .......................................................................................................................... 5 Jersey vs Holstein Farm Gate Price Comparison ................................................................. 5 Processor component pricing .................................................................................................... 7

5 HANDLING AND CARTAGE COMPARISON .................................................................. 7

6 PROCESSING COMPARISON ............................................................................................. 8 Product Mix Options ..................................................................................................................... 8 Yield Comparison ........................................................................................................................... 9

7 MARKET VARIATION OVER TIME .............................................................................. 10 8 SUMMARY AND CONCLUSIONS ................................................................................... 11

9 RECOMMENDATION ....................................................................................................... 12

10 APPENDIX ....................................................................................................................... 12

FARMING TOGETHER -‐ COMPLEX EXPERT SERVICES REPORT – STAGE 1 DRAFT

1 PROJECT BRIEF To compare the milk component payment systems with 3 major processors. Undertake cost comparisons and relate to market returns for this Jersey Milk group using data from at least 2 farms for each of the 3 processors (total 6 farms). Please analyse impact of component variations and include carting, handling, processing for a variety of product types. Prepare report for Farming Together as a valuable report for industry.

2 BACKGROUND

Notes on Australian Milk Pricing Systems The Australian Milk Pricing System has changed significantly over the past 30 years. These changes are summarised concisely in a Milk Pricing Discussion Paper submitted by the United Dairyfarmers of Victoria to the 2016 ACCC inquiry into the competitiveness, trading practices, and transparency of the Australian dairy industry. https://www.accc.gov.au/system/files/Australian%2520Dairy%2520Farmers%2520-‐%2520Attachment%25201.pdf The fat + protein – volume system evolved in the late 1980’s as a way of managing milk component differences, and as a mechanism to account for milk density variation. Previous to this the milk payment system was based predominantly on the butterfat component of milk. Following industry deregulation in 1999/2000, pricing structures have become significantly more diverse and complicated. Companies have introduced an array of differential pricing arrangements and incentives in attempt to maximise their own operating efficiencies and hold and attract supply. Some examples of the mechanisms listed in the UDV report which are creating variability in pricing arrangements between companies include;

• Fat + Protein – Volume + Seasonal Incentive = Base Price + Step-‐ups. • Quality Incentives/Penalties. • Productivity Incentive. • Quality Assurance Incentive. • Stop Charges. • Seasonal Incentives, regionally priced for some processors. • Increasing Productivity Incentive. • Volume Charge discounts for improved milk tanker access. • Combined farm Productivity Incentives. • Alternative payment systems available (Changes to base price systems,

Seasonal, 7/5 December & March). • Growth Incentive. • Conversion and start up incentives.


• Herd test rebates. • Changes to contracts for domestic markets processor suppliers. • Stop charge rebates for farms on skip a day all year. • Price increases, rather than retrospective step ups. • Subsidised factory finance available. • New milk sign on bonuses. • Merchandise store account terms and discounts. • Loyalty payments become more common than step ups. • Linkage between months of supply for milk volume for additional payments

(SRP, DMI, SRP Plus, FMI). • Productivity incentives calculated and paid monthly. • Field Staff touted as being able to offer better services to farmer suppliers,

adding significant value. • Changes to fat and protein value ratios. • Adjustment to seasonal incentives lessening the value of winter milk. • Quality incentives that cumulate and pay bonuses to those with particularly

good milk quality. Not surprisingly this has created an almost impenetrable matrix of complexity by which farmers are trying to assess whether they are being paid a fair and reasonable price for their milk. And because of this complexity a price/value comparison between companies will not be able to account fully for all individual farm variation. It is also important to note that the pricing systems which have evolved are a mechanism for buying milk and do not necessarily represent the market value of the milk components. This will be discussed in Section 6 of the report.

How do the current systems handle milk components? Milk composition is affected by a range of factors including breed, diet and environment. The indicative extent of compositional variation as related to breed differences can be gauged in Table 1. (Note Research From Virginia Tech, 1998)

Holstein Jersey Total solids, % 12.4 14.6 Fat, % 3.7 5.1 Solids-not-fat, % 8.7 9.5 Protein, % 3.1 3.7 Lactose, % 4.9 5.0 Ash, % 0.7 0.8

Table 1


The Australian milk payment systems use the fat and protein components of milk as one of their key payment criteria. This payment is usually combined with a volume charge to account for variations in milk density. It is important to note the other major components of milk, are not taken into account in payment systems. In the above example the fat and protein fractions make up 55% of the Holstein Milk and 60% of the Jersey Milk respectively. This means that over 40% of the Milk Solids component of milk is not captured within the pricing structures. (Note : The two main components of milk which are not accounted for in the payment system are the Lactose (Carbohydrate) and Ash (Minerals) component . Both these components represent value to processors in the market, but are not part of the price signal which is given to farmers.)

3 METHODOLOGY The approach taken in this analysis has been to focus on how the milk pricing system from three of the major processors treats milk solids component variation. The steps taken have been as follows –

1. Current income estimation data has been obtained from six (6) Jersey Farms. There is variation across the six farms to incorporate

a. Three supply companies (MG, Fonterra, Warnambool Cheese and Butter)

b. Seasonal and Split Calving c. Herd Size d. Location (Tasmania, Western Victoria, North East Victoria)

2. Comparison with two Holstein farms representing a seasonal and a split calving herd. The Holstein component configuration was compared against the pricing structures for MG, Fonterra and WCB.

3. Comparative analysis of the treatment of component variation across the three companies.

4. High level cost comparison for handling and processing of high density milk solids milk vs lower density milk solids milk.

4 FARM DATA

Jersey vs Holstein Farm Gate Price Comparison As indicated there is variation in the way individual companies have built their payment systems. Broad features include;

• MG – base fat and protein varies month to month, quality payment, volume charge with two options, loyalty incentive, productivity system that pays much lower for small farmer and is based on each months production, FMI a complicated calculation and value not known until end of the season, restrictions on receiving incentives if a farmer changes processors mid-‐season


• Fonterra – monthly base price the same each month, different seasonal incentive for some months, volume charge, quality payments, productivity payment fixed on annual production volumes and growth incentives

• WCB – monthly base price the same each month, different seasonal payment for some months, volume charge, quality payment, split productivity payments with a monthly and end of year payment, farms with the same ownership able to group together for productivity, growth incentive and forecast step-‐ups included in the income forecasts.

Table 2 summarises the price outcome data for the 6 Jersey and 2 Holstein farms which have been put through a pricing model based on the current payment systems for MG, Fonterra and WCB, and which have taken into account the different payment profiles for each company. Note: Details which would allow identification of individual farms have been omitted to preserve confidentiality.

Milk Price $'s Per Kg MS

FMI Litres Butterfat % Protein % MG Fonterra WCB Jersey 1 -‐ WCB 42.4%

951,382

45,063 4.74%

34,588 3.64%

5.00

5.79

5.15

Jersey 2 -‐ WCB 49.6% 1,029,578

51,790 5.03%

39,991 3.88%

5.15

5.94

5.47

Jersey 3 -‐ Fonterra 42.2% 2,619,802

130,309 4.97%

100,027 3.82%

5.11

5.99

5.21

Jersey 4 -‐ Fonterra 46.5% 1,304,115

59,862 4.59%

46,980 3.60%

5.10

5.88

5.51

Jersey 5 – MG 42.3% 3,629,586

179,431 4.94%

141,823 3.91%

5.18

6.04 5.21

Jersey 6 -‐ MG 45.7% 1,279,878

63,247 4.94%

49,616 3.88%

5.07

5.91

5.58

Holstein1 44.8% 2,889,941

115,411 3.99%

96,932 3.35%

5.25

6.03

5.23

Holstein 2 43.1% 2,890,474

111,606 3.86%

96,167 3.33%

5.19

6.02

5.22

Table 2 ***Note Fonterra and MG figures reflect payment parameters as described in their respective Handbooks – this study did not have access to the WCB handbook – so assumptions have been made based on the Income Estimation sheets.

The table shows there is little difference in the value Fonterra and WCB pay for the milk solids they purchase between Jersey and Holstein milk profiles. The MG figures suggest lower milk solid density (Holstein) herds are receiving a slight advantage in the payment system.


Processor component pricing It is interesting to note the variation which exist between the price companies pay by proportion for fat and protein ( see Table 3). Table 3 Milk Model

Kgs/Lts

MG

Fonterra

WCB

Litres Vic Av 10,000 $'s $'s $'s

Fat 4.12% 412

1,409 37.8%

1,191 32.6%

1,220 35.5%

Protein 3.40% 340

2,322 62.2%

2,458 67.4%

2,213 64.5%

Total 752

3,731 100.0%

3,649 100.0%

3,433 100.0%

These figures show MG is paying more for fat and less for protein by proportion of milk price than WCB and Fonterra. This would suggest that Jersey milk should be advantaged under the MG pricing system, but we have seen that this is not the case, when all features of the pricing system are taken into account.

5 HANDLING AND CARTAGE COMPARISON The cost of handling and carting higher density milk is lower per Total Milk Solids received than for lower density milk – on the basis of the cartage of less water – which is costly to handle and transport. An estimate of the variation of this cost is listed in Table 4. Through this example it is calculated that it is 8.5c/kg Milk Solids or 0.6c/litre of milk less expensive for the processor to be carting and handling Jersey profile milk compared to Holstein profile milk. Table 4 Cartage & Receival Costs Jersey Milk Litres 10,000

Butterfat 4.95% 495

Protein 3.85% 385

Total Milk Solids 880

Cartage & Receival Costs CPL 3.5 350 Costs Cents per Kg MS 39.77


Holstein Milk Litres 10,000

Butterfat 3.90% 390

Protein 3.35% 335

Total Milk Solids 725

Cartage & Receival Costs CPL 3.5 350 Costs Cents per Kg MS 48.28 Holstein Milk Additional Cartage and Receival Cost cf Jersey Milk 8.5cents/kg MS Holstein Milk Additional Cartage and Receival Cost cf Jersey Milk 0.60cents/litre

6 PROCESSING COMPARISON

Product Mix Options Dairy products vary widely in composition as can be seen in Table 5. The value of the milk solids will therefore vary for each processor depending on their processing capability and position in the market. Table 5

The following schematic (Table 6) demonstrates how the components that make up 10,000 litres of milk can be processed in four fundamentally different ways to generate four different product outcomes. See Appendix 3 for a high level description of what is involved in these processes .


Table 6

This demonstrates that each processor will be generating different value from the milk they purchase, based on a range of factors including their product mix, the current market conditions and their own operating efficiencies. The milk price paid to farmers does not attempt to take all of these factors into account, and there is no direct line of transparency between milk components provided by farmers and the profitability of the products sold by the processor.

Yield Comparison There is a fundamental reality however that higher density milk is less expensive to handle and provides higher yields per litre of milk processed than lower density milk. Jersey milk will yield more powder per liter processed than Holstein milk, due to its higher milk solids density, and the conversion costs to powder will be lower (due to the reduced expenditure required to remove less water). The figures in Table 7 demonstrate a 13% increase in powder yield for Jersey profile vs Holstein profile milk. Table 7 Powder Processing Yields Jersey Milk

Litres 10,000

Butterfat 4.95% 495

Protein 3.85% 385

Other SNF 5.80% 580

Total Milk Solids 14.60% 1,460

Powder Kgs 4% Moisture 1,521

Water Removed 8,479


Holstein Milk

Litres 10,000

Butterfat 3.90% 390

Protein 3.35% 335

Other SNF 5.60% 560

Total Milk Solids 12.85% 1,285

Powder Kgs 4% Moisture 1,339

Water Removed 8,661

Additional Powder from Jersey Milk Kg 182 Improved Powder Yield 13.6% A similar logic holds for manufacture of butter and cheese with increased milk solids density generating higher yields per litre of milk processed. Detailed analysis of this difference would be possible with a more in depth study but is not in the scope of this report. Different manufacturing processes and configurations would need to be taken into account, as well as the efficiency and cost of production for different operations.

7 MARKET VARIATION OVER TIME The market value for fat and protein goes up and down over time. An examination of the Indicative International Spot Prices for Butter, Cheddar, Skim Milk Powder and Whole Milk Powder shows the high level of price variation in the last five years. See Table 8. Butter prices for instance are currently at record high’s and more than double the market price from 5 years ago. In contrast Skim Milk Powder prices are at five (5) year lows, and less than half the price the product demanded 4 years ago. Milk companies must work with this variation without needing to change the pricing system as a constant reaction to the peaks and troughs of these price fluctuations. Given the high prices for cream and butter at present it is understandable that Jersey farmers are feeling their product is being undervalued. Whilst this may be correct in the current market this will not necessarily hold over time.


Table 8 Five Year Indicative International Major Commodity Spot Prices

8 SUMMARY AND CONCLUSIONS This report has highlighted that the current milk price systems in Australia are complex and do not demonstrate a direct line of transparency between the market value for milk products and the price paid to farmers for the components of the milk they produce. From the farm data analysis it is difficult to draw the conclusion that Jersey Milk is disadvantaged relative to Holstein Milk on the basis of milk solids provided at farm gate. The exception to this is with Murray Goulburn which demonstrated a slight advantage to Holstein profile milk. It is reasonable to conclude however that Jersey profile milk is relatively cheaper to collect and more efficient to process in relation to yields and handling costs than lower milk solids density milk. This value does not appear to be accounted for in the payment systems reviewed, which is a disadvantage to Jersey farmers. Industry concerns around the current payment systems are focused on firstly their increasing complexity, which makes them hard to understand and compare between processors, and secondly their lack of ability to translate market signals to farmers.

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Aug-‐12

Nov-‐12

Feb-‐13

May-‐13

Aug-‐13

Nov-‐13

Feb-‐14

May-‐14

Aug-‐14

Nov-‐14

Feb-‐15

May-‐15

Aug-‐15

Nov-‐15

Feb-‐16

May-‐16

Aug-‐16

Nov-‐16

Feb-‐17

May-‐17

Aug-‐17

USD/Tonne FOB

Butter SMP WMP Cheddar


The issues covered in this report relate more directly to the second category. There is value in high density milk which is not being recognized in the current payment systems, to the disadvantage of Jersey farmers. It is the overall value of the milk solids which is important to processors, and their capability to convert the raw material efficiently into a market outcome. It is difficult to see how the current allocation of fat and protein prices is linked to market outcomes, particularly when there is such significant variation in commodity markets over time. It would be fairer for Jersey producers if the payment systems were based on milk solids rather than individual ratios for fat and protein. That way the value of higher density milk can be more accurately and transparently recognized, and send a more accurate signal to the industry in relation to component value. Improving transparency around pricing, and market signals is critical to effective farm decision making. It would be useful if Jersey Australia could advocate for the simplification of the overall pricing system which would include a review of component pricing as part of a broader process of reform.

9 RECOMMENDATION That Jersey Australia adopt an advocacy position for reform of the milk pricing system in Australia, which would include the following areas

• a simplification of payment systems to provide clearer and more accurate market signals,

• a review of current systems to more accurately reflect the net component value of milk solids (fat and protein), and

• consideration within the payment system for the efficiencies and value generated through processing high density vs low density milk.

10 APPENDIX Appendix 1 -‐ Dairy Australia excerpt regarding components in manufacturing


Appendix 1 – Dairy Australia excerpt regarding components in manufacturing

farming(together(program( …jersey.com.au/wp-content/uploads/2018/04/case-02304-jersey-milk... ·...

Documents