On-Farm Record Keeping
If it’s not measures
it’s not managed
Historical Look Back
• Starts with sharing memories and methods
• History is based on it, it is our ‘knowledge
• All living things carry a ‘memory’ of the
• Human records represent collective
– first in oral tradition, then mnemonics, then art, epic
poems, written texts, and wiki’s
Why Keep Records
• Cost of production
• 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
Change / Modify
Record Keeping: All-in
• If you’re going to choose to record
something, make it complete and
• 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
• Incomplete or inaccurate records can be very
• Work backwards from your questions
– What are my questions?
– What do I need to answer that question over what
– Where can I get that data from?
– What do I need to record?
• 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
• 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
• 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
• Stand on the ‘entity’ and look at the
Entities and Attributes
• Ones person’s entity is another person’s
• 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
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
How much fuel did it take to grow that crop?
• 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.
• 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
• 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
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?