On-farm Record Keeping

1. On-Farm Record Keeping
If it’s not measures
it’s not managed
ACORN 2016
Ironwood Organics

2. Historical Look Back
• Starts with sharing memories and methods
• History is based on it, it is our ‘knowledge
base’
• All living things carry a ‘memory’ of the
past
• Human records represent collective
learning:
– first in oral tradition, then mnemonics, then art, epic
poems, written texts, and wiki’s

3. Why Keep Records
• Compliance
• Financial
• Cost of production
• Traceability
• Too much to remember
• Long time frames
• Knowledge capital of the farm
• Form the basis for analysis and management

4. A management question
• Ultimately it is about management
• If it’s not measured, it’s not managed
• The success of management is tied to
success of measurement
• But if your not going to manage, why
measure – just another overhead
• Move towards organizational maturity
• If it didn’t happen twice,
it didn’t really happen
Assess
Change / Modify
Measure

5. Types of Records
• Assets / Inventory
• Activities
• Financial
• Spatial / Maps
• Certification /Accreditation / Memberships
• Observations
• Contacts
• Breeding (plant / animal)
…….

6. Record Keeping: All-in
• If you’re going to choose to record
something, make it complete and
accurate.
• Better to have less data that is relevant,
accurate and complete than more data
that is inaccurate and incomplete.
• Bad data results in bad decisions

7. What is appropriate data
• Mandatory recording keeps you in compliance
• Optional record keeping is based on your
questions
• Incomplete or inaccurate records can be very
costly
• Work backwards from your questions
– What are my questions?
– What do I need to answer that question over what
time period?
– Where can I get that data from?
– What do I need to record?

8. Possible questions
• Which crops take the most man hours, tractor hours?
• What equipment isn’t being used to its potential?
• What is costing me too much to maintain?
• Is preventative maintenance paying off?
• Which implement is being used the most – replace for a
‘better one’?
• What is the crop history for a certain field?
• What is the grow history for a certain crop?
• What is the max/min/mean rainfall for the last 5 years?
• Which crops were most profitable from a labour
perspective?
• Which crop varieties performed best in a drought year?

9. Moving from Lists to Insights
• Basic level is a series of lists or inventories
– List of equipment
– List of fields
– List of crops for the year
– List of field activities
• Linking lists provide a ‘view’ from a
different perspective
• Stand on the ‘entity’ and look at the
‘attributes’

10. Entities and Attributes
• Ones person’s entity is another person’s
attributes.
• The same ‘thing’ can mean something
different to different people.
• How do we model the vast array of ‘things’
on a farm operation, and the relationship
between and among those things, over
time?

11. Entity Relationship Diagram
• List the entities ( person, place, things)
• Lists of attributed that describe each entity
• List the relationships between those entities
• Each entity has a unique number or key
– Serial number
– Employee number
– Lot number
– Field number
– Variety Name

16. Data Model

17. Data Model with Attributes

18. How much fuel did it take to grow that crop?
11
22
33
44
55

19. Mapping
• Most events have a space and a time
• Spatial data (where) can be characterized
as points, lines or polygons
• Points have a location ( e.g. well head)
• Lines have bearing and distance ( e.g.
fence line)
• Polygons have perimeters and areas (e.g.
field or green house)

20. 1st record of the farm
• 1867 Survey
• 1 building
• Owner: Mrs Johnson
• A river headwater

21. W4 14.6
E2 7W2 11.5
E1 5
W5 7.5
W1 7.3
E5 6.5
E4 6.5
E3 6.3
W7 4
W6 4
WO 74.5
W3 3.6
E3H 1.8
GF 1
W0 1.1
SBC 4.1
SBE 3.6
SBW 3.7
E4H 0.2
W3O 0
BA 0
0 70 140 210 28035
Meters ³1 centimeter = 50 meters
W4 14.6
E2 7W2 11.5
E1 5
W5 7.5
W1 7.3
E5 6.5
E4 6.5
E3 6.3
W7 4
W6 4
WO 74.5
W3 3.6
E3H 1.8
GF 1
W0 1.1
SBC 4.1
SBE 3.6
SBW 3.7
E4H 0.2
W3O 0
BA 0
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W301
E208
W703
W704
E211
E210
E209
E207
E206E205
E204
E203
E201
E312
E311
E310
E309
E308
E307
E306
E305E304
E303
E302
E301
E411
E410E409
E408
E407E406
E405
E404
E403
E402E401
E512
E511
E510
E509
E508
E507E506
E505
E504E503
E501
W702
W701
W609
W608
W607
W606
W605
W604
W603
W602W601
W515
W514
W513
W512
W510W509
W508 W507
W506W505
W504
W503W502
W501
W405
W409
W408
W402
W401
W304
W303
W302
W201
W4 14.6
E2 7W2 11.5
E1 5
W5 7.5
W1 7.3
E5 6.5
E4 6.5
E3 6.3
W7 4
W6 4
WO 74.5
W3 3.6
E3H 1.8
GF 1
W0 1.1
SBC 4.1
SBE 3.6
SBW 3.7
E4H 0.2
W3O 0
Other Spatial
artifacts that
give context;
•Watersheds
•Soil maps
•Slope
•Zoning
•Elevation
•Hydrology
•Buildings
•Fences
•Well heads
Imagery Field Map Drain Tile Apple Trees

22. Work Flow
• Initial design and data population
– Do your compliance lists
– Ask your questions
– Build your reference data sets
– Set your primary keys
• On-going data population
– Field capture - real time
– Clean up and record in permanent log book - weekly
– Data entry to digital file – at least 1 pre quarter

23. Example of List Reporting

24. Field Activity

25. Litres of Fuel by Tractor by Year
Summary of Man Hours and Tractor Hours

26. Details of all ‘grow periods’ in 2015

27. Summary of Activities in W7 Since Inception

28. Detail and Summary Maintenance Logs

29. Back to the beginning
• Store only the data you have to or data that will
answer your questions.
• If you store it, make it complete and accurate.
• Do your analysis for prior year(s)
– What was profitable?
– More maintenance?
– Sell / acquire equipment?
– Crop / climate performance?
– Grow less and do more value add?
– Increase crop diversity?

30. If it’s not measured its not managed.