Presentation on Dutch experiences in farm data management for the national Irish workshop in the MEF4CAP European project

1. National Irish Workshop , March 2023
Krijn Poppe
Benefits of data dashboards and
electronic data transfer in the NL
Dutch experiences in robotic accounting FOR
INTEGRATION OF FINANCIAL-, MGT-, ENVIRONMENTAL
ACCOUNTING DATA AND SENSOR DATA

2. Demonstration Case 1 - SITRA
System for information Transfer to Reduce Administrative burden
MEF4CAP Project
2-3-2023 2

3. Content
1. The need for sustainability data (by external stakeholders)
2. Current practices in data management
3. Invoices as most important data source: robotic accounting
4. Can we reduce the administrative burden of farmers and innovate the farm office?
5. Sensor data as a future pathway
6. Next step: MEF4CAP integration of farm financial accounting, farm management
information systems and sensor data in a farm dashboard
2-3-2023

4. Food becomes more (sustainability) data intensive:
Industry programs, national programs, CSRD-scope 3, CAP-ecoschemes, FSDN
4

5. Incentivise farmers on sustainability (PPP)`and manage
trade-offs between Key Performance Indicators
0
20
40
60
80
100
Cost price
per 100
kg milk
Income per
Family
Labour unit
solvability
(%)
Energy use
per euro output
Water use per euro output
Pesticide use
per hectare
Grazing days
Education
Surplus of
Phosphate per
hectare
Surplus of
Nitrogen per
hectare
PEOPLE
PROFIT
<< PLANET >>

6. 2. Current practices in data management
• Family farms do not have a lot of internal data needs (and do not run an ERP- Enterprise Resource
Package). The demand for sustainability data is external.
• Food processors (and government schemes) use often an option to collect sustainability data that
creates administrative burdens:
• Own set of forms or website for farmer to fill in basic data (or KPI)
• Use (a link to) a Farm Management Information System or a specific tool (e.g. Cool Farm Tool)
that requires manual input, and is currently not in use by many farmers.
• Industry organisations can create large external databases with (quarterly) data from food
processors and supply companies (based on authorisations by farmers). Full coverage but not well
integrated in farm management decisions.
• These options are also hard to audit in case they are used for payments or penalties.
• It is more attractive to work with the farm financial accounting system (obliged for all commercial
farms for VAT or income tax) >> In the NL designed under the Mineral Accounting System (1990s)
2-3-2023

7. 3. Reduce administrative burden: Invoices are key
• Typical data needed in compliance auditing: indicators on pesticide use, mass balances (especially
in organic farming, see organic regulation), material balances of N and P, energy use (and
production) , antibiotics, etc.
• Although some data is non-financial (grazing days, wateruse for irrigation etc): sensor data?
• Invoices provide a lot of financial and volume data needed for those indicators.
• Invoices on inputs and outputs (!) are typically created by trade partners of the farmer.
• In the NL invoices have been used for sustainability KPI in the FADN since the early 1990s, mainly
by manual data entry (accountants had digital banking data since the early 1980s)
• They can be digitalised, using digital standards like UBL, XML, UNCEFACT etc.
• The obliged MINeral Accounting System in the 1990s installed digital invoices and delivery notes
in the livestock industry and created a link with financial accounting (later abolished as EU ruled
against the Dutch Nitrogen approach, but no problems with the MINAS system as such)
2-3-2023 7

8. 2-3-2023 8
Invoice Feed Data entry (SITRA)
Amounts
in €
Invoice lines:
5 product items
+ 4 types of
discounts
Kg
Software allocates
discounts to product
items. Entry incl. VAT
generates excl. VAT and
vice versa
Allocation
to cows
based on
type feed
and N, P,K content are
known
Product
names of
supplier linked
to FADN
product code

9. The data flow in farm accounting classic paper flow
2-3-2023 9
Invoices
Digital
bank
data
Data entry
and coding
Data store
invoices
Data store
bank data
Classification
maintance
Classification
rules
coding
Data store
coded and
auditable
transactions
(+ payments)
Reports

10. The data flow in farm accounting robotic accounting
2-3-2023 10
Invoices
Digital
Invoices
Digital
bank
data
Data entry
and coding
Data store
invoices
Data store
bank data
Classification
maintance
Classification
rules
coding
coding
Data store
coded and
auditable
transactions
(+ payments)
Reports
Dutch FADN

11. 4. Can we innovate the Farm Office to reduce the farmer’s
administrative burdens
..based on robotic accounting
* integrate payment process, farm financial accounting
* with farm management information systems
* and environmental accounting
* and sensor data on emissions (IoT: internet of things).
2-3-2023 11

12. Pay
button
• Basis for robotic accounting: generates VAT forms, KPI data on sustainability for
certification including material balances, mass balances (organics) etc.
• And data for management / extension by advisors.
• Coherent integration with FMIS possible (next slide)
Financial software: farmer pays EDI-invoices, checks bank account
Bank data

13. 13
Order
Delivery (dispatch note)
Invoice
Payment
Use of input
Output produced
Sales Order
Delivery
Inventory
Inventory
Offer (after tender call)
Invoice
Payment
Business processes
Integration Farm Financial
Accounting and FMIS
Inventory Check
Bought and
delivered inputs
Sold and
delivered outputs
Farm Profit
/ income
and
material
balance
Complete allocation
to production units
(gross margins, cost
prices, material
balance) that can be
audited, has correct
prices and adds up
to farm total
Inventory Check
Record use of inputs per production unit
Record output per production unit
prices

14. 5, Sensor data can be added: Map Farm XYZ NO2 Pollution rose
R
O
A
D

15. Data flows to/from farms via dashboard: potential future situation
Incoming
data for
farmers
Offers
Orders
Invoices
Bank data
Governments’ IACS (Integrated
Administration and Control
System)
Maps Subsidy data
IoT (Internet
of Things)
Sensor data
Satellite data
Etc.
Calculations
EDI
Shared Service: Coding of data and Allocation of data to activities (crops, fields etc.)
Data carrier
• Financial accounts
• Management accounts (gross margins)
• Environmental accounts (GHG, CO2, P)
• Certification schemes (Skal, SGS: GlobalGap,
KPI)
• Food industry / Retail
• Government reporting (SBR)
Management Software
(Agrovision, Crop-R, etc.)
Informed consent data platforms (Agriplace, JoinData)
Information
EDI
Software
Accounting Office
2-3-2023 15
Problem frame: Realise a “future-proof”, international and scalable plaform where structured and non-
structured data for farmers can be combined. The created data can be used as a base for reporting,
compliance and –monitoring, AI, Machine Learning, etc Based on Data Space concept for data governance.
DASHBOARD

16. Conclusions
1. Digitalisation (XML) of invoices is needed for farm level
sustainability data
2. Centralisation of such data in an industry data base is a short term
solution, but not well integrated in day to day farm management
and audit-trail is difficult.
3. Providing farmers with a digital copy of their invoices reduces
current administrative burdens with farmers, their advisors and
accountants and the FADN-sample.
4. Digital banking, Farm Accounting (VAT etc.) and FMIS (and
sustainbility apps) can be integrated in an easy to use digital
dashboard in which data are coherent.
5. Sensor and satellite data can be added to further improve the
data quality and reduce manual data input.

17. Thank you for your attention
Presentation by:
Krijn Poppe
kjpoppe@hccnet.nl
This project has received funding from the European Union’s Horizon 2020
research and innovation programmeunder grant agreement No. 101000662.
The content of this publication exclusively reflects the author's view and the
Research Executive Agency and the Commission are not responsible for any
use that may be madeof the information it contains.
@MEF4CAP
www.mef4cap.eu