MEF4CAP workshop Dublin March 2023.pdf

MEF4CAP workshop Dublin March 2023.pdf

• 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
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  Demonstration Case 1- SITRA System for information Transfer to Reduce Administrative burden MEF4CAP Project 2-3-2023 2
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  Content 1. The needfor 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
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  Food becomes more(sustainability) data intensive: Industry programs, national programs, CSRD-scope 3, CAP-ecoschemes, FSDN 4
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  Incentivise farmers onsustainability (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 >>
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  2. Current practicesin 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
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  3. Reduce administrativeburden: 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
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  2-3-2023 8 Invoice FeedData 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
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  The data flowin 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
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  The data flowin 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
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  4. Can weinnovate 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
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  Pay button • Basis forrobotic 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
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  13 Order Delivery (dispatch note) Invoice Payment Useof 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
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  5, Sensor datacan be added: Map Farm XYZ NO2 Pollution rose R O A D
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  Data flows to/fromfarms 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
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  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.
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  Thank you foryour attention Presentation by: Krijn Poppe [email protected] 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