On-Farm Record Keeping
If it’s not measures
it’s not managed
ACORN 2016
Ironwood Organics
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
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
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
Types of Records
• Assets / Inventory
• Activities
• Financial
• Spatial / Maps
• Certification /Accreditation / Memberships
• Observations
• Contacts
• Breeding (plant / animal)
…….
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
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?
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?
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’
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?
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
Data Model
Data Model with Attributes
How much fuel did it take to grow that crop?
11
22
33
44
55
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)
1st record of the farm
• 1867 Survey
• 1 building
• Owner: Mrs Johnson
• A river headwater
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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E207
E206E205
E204
E203
E201
E312
E311
E310
E309
E308
E307
E306
E305E304
E303
E302
E301
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E410E409
E408
E407E406
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E402E401
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W701
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W515
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W508 W507
W506W505
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W503W502
W501
W405
W409
W408
W402
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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
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
Example of List Reporting
Field Activity
Litres of Fuel by Tractor by Year
Summary of Man Hours and Tractor Hours
Details of all ‘grow periods’ in 2015
Summary of Activities in W7 Since Inception
Detail and Summary Maintenance Logs
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?
If it’s not measured its not managed.

B3 record keeping

  • 1.
    On-Farm Record Keeping Ifit’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 appropriatedata • 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 • Whichcrops 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 Liststo 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.
  • 17.
    Data Model withAttributes
  • 18.
    How much fueldid it take to grow that crop? 11 22 33 44 55
  • 19.
    Mapping • Most eventshave 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 ofthe farm • 1867 Survey • 1 building • Owner: Mrs Johnson • A river headwater
  • 21.
    W4 14.6 E2 7W211.5 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 õôó õôóõôóõôó õôó õôó õôóõôóõôóõôóõôóõôóõôó õôó õôó õôóõôóõôóõôóõôó õôó õôóõôóõôó õôóõôóõôóõôóõôó õôó õôó õôóõôó õôóõôóõôóõôó õôó õôó õôó õôó õôó õôóõôó õôóõôó õôó õôóõôóõôó õôó õôó õôóõôó õôó õôó õôó õôóõôó õôó õôóõôó õôó õôó õôó õôó õôóõôó õôó õôó õôó õôó õôó õôó õôó õôó õôóõôó õôó õôóõôó õôó õôó õôó õôó õôó õôó õôó õôó 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 • Initialdesign 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 ListReporting
  • 24.
  • 25.
    Litres of Fuelby Tractor by Year Summary of Man Hours and Tractor Hours
  • 26.
    Details of all‘grow periods’ in 2015
  • 27.
    Summary of Activitiesin W7 Since Inception
  • 28.
    Detail and SummaryMaintenance Logs
  • 29.
    Back to thebeginning • 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 notmeasured its not managed.