As use cases are defined bottom up, they identified very diverse Key Performance Indicators (see Table 3 below), highlighting the need for aligning them in a common impact framework. This will be established in the inception phase of the project, leading up to the first project milestone. It will include a methodology to estimate or measure baseline performance, against which performance on the project results can be plotted, and that can be used to establish the baseline in the first year of the project. As not all KPI’s will be suited for quantitative measurement, a mixed method approach, including a mix of quantitative and qualitative methods will be implemented. Moreover, the work will need to examine economic approaches, e.g. to determine cost structure of processes, differentiate its elements and identify ways to objectively calculate or survey economic effects of NIVA innovations. It is expected that this Impact Framework will need to be updated and improved during the running time of NIVA.


Table 2-1: Use case and their tentative KPIs to be elaborated during the project implementation. These KPI’s are preliminary indicators that will be extrapolated to MS running the trials.

Use case

Tentative KPIs to be elaborated

Earth Observation Monitoring and Traffic Lights

  • Minimum 3 land-related eligibility criteria monitored by imagery and traffic light processes deployed in MS; KPI2.a, KPI3.a
  • Minimum 5 % of farm holdings will be included in the participating MS in real conditions; (KPI1.a)

Agro-environmental monitoring

  • Minimum 3 environmental indicators deployed in participating MS: 1 at farm level, 1 at MS level and 1 at EU level; KPI3.a, KPI3.c
  • Minimum 5 % of farm holdings will be included in the pilot in real conditions; KPI1.a

 

Farmer Performance

 

  • API prototype available – Y/N; KPI3.a
  • Prototype tested and documented, including description of suitable standards – at least in 3 real cases; KPI3.a
  • Methodology of indicators created and evaluated with users. KPI4.c

 

Prefilled application, GSAA/Land link

 

  • Administration cost reduction = 10 % per year; KPI2.a, KPI2.b
  • The quantity of data automatically filled in application for farmers = 90 % per year;KPI2.a, KPI2.b and KPI3.a
  • Farmers time, spent on filling of application, reduced = 50 % per year. KPI2.b

 

Farm Registry

 

  • Reduction of more than 20 access to different databases. KPI2.a, KPI2.b, KPI1.a, KPI1.b
  • Minimum 5 % of farm holdings will be included in the participating PA-MS in real conditions; KPI1.a
  • At least 6 components with 3 main functionalities will be developed based on one shared and harmonized data model. KPI3.a

 

Geotagged photos

 

  • Minimum of 50 farmers participating in user-centred workshops; KP1.a
  • Minimum of 20 advisors attending user-centred training and skills workshops; KPI1.b
  • Minimum of 25 farmers trialling prototype smartphone app; KP1.a
  • Minimum of 2 think tanks to be held across consortium partners from 6 MS; KP1.b

 

Machine data in GSAA as added value data

 

  • Minimum of 50 farmers trialling prototype machine data service; KP1.a
  • 10% reduction of administrative burden of farmers; KP2.a, KP2.b
  • 15% reduction in error rate in IACS system; KP2.b

LPIS: Update & Change detection

 

  • Administration cost reduction = 2 % per year; KP2.a, KP2.b
  • Farmers reduction of consultant costs = 5 % per year; KP2.a, KP2.b

 

Scheme Eligibility and Payment Eligibility: click-and-pay

 

  • reduction by 45% of the average “per application” cost of handling (indicator to be confirmed based on the costing model expected from project AGRI-2017-EVAL-04); KP2.a, KP2.b
  • Achieve a Seamless service for area-related schemes for at least 45% of farmers in the test period