Research Insights
Framework to assess the sustainability impact of digital technological solutions in agriculture
This research develops a managerial tool to monitor and evaluate the sustainability performance of Digital Agricultural Technological Solutions (DATS). This tool is an assessment framework designed to evaluate both the benefits (monetary and non-monetary) and costs of DATS's implementation. The assessment framework is developed with the study of 30 cases in Europe, working with different crops and breeds, with and without DATS. The framework is developed in three phases. First, it combines top-down and bottom-up approaches to identify the most relevant assessment categories, sub-categories, and key performance indicators from a sustainability perspective, according to the type of technology adopted and the process in which the DATS are implemented. Next, the assessment framework design involves determining the calculation methods, considering both monetary and non-monetary evaluations. Finally, the framework is applied to each case to evaluate the costs and benefits, as well as the appropriateness and feasibility of the performance calculations. The contributions of the study to literature and practice are threefold, i) developing an assessment framework with a feasible and affordable subset of indicators linking theory and reality, ii) combining a dual lens assessment in monetary and non-monetary terms, and, iii) develop a dynamic living assessment tool that facilitates processing information about DATS adoption in a multi-season perspective. In the future, researchers could further refine, replicate and expand the use of the assessment framework in other geographies or for specific DATS or agricultural sectors.
Key Executive Takeaways
Our analysis distills critical findings into actionable metrics, showcasing the tangible impact of DATS in agriculture.
0
Sustainability Challenges Addressed
0
Cases Studied
0
Framework Phases
0
Average Net Benefit (EUR/ha)
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
The research methodology is structured in three main phases to design and implement a concrete managerial tool. These phases involve identification of performance measures, assessment framework design, and assessment framework application, following Bourne et al. (2000).
- Phase 1: Identification of performance measures combines top-down (literature review) and bottom-up (farmer input) approaches to identify relevant assessment categories, sub-categories, and KPIs.
- Phase 2: Assessment framework design focuses on monetary (cost-benefit analysis) and non-monetary (sustainability impact) evaluations.
- Phase 3: Assessment framework application involves iterative calculation, revision, and updates with 30 case studies across Europe.
The framework application revealed several key insights from the 30 case studies:
- Complexity of Data Management: Farmers found the quantity of data required often excessive and sensitive, highlighting a trade-off between granularity for analysis and ease of use.
- Non-Immediate Benefits: Positive benefits from DATS adoption were not always immediate, suggesting the need for longer payback periods.
- Customization Needed: A high level of customization is crucial for the framework to be relevant to specific farm types, crops, and DATS.
- Positive Impacts: Economic benefits often came from increased yields and reduced fuel/energy. Social benefits included reduced workload and improved decision-making. Environmental impacts showed mixed results, with some reductions in water/energy use but varying effects on pesticide/fertilizer application.
For farmers, managers, and technology providers, this framework:
- Offers a Practical Tool: Piloted with 30 diverse cases, it emphasizes indicator choice based on relevance, data availability, and feasibility.
- Provides Dual-Lens Evaluation: Integrates monetary and non-monetary impacts for a clear understanding of DATS' financial viability and sustainability.
- Is a Living Instrument: Designed to be dynamic and customizable, allowing for updates and revisions across seasons, supporting long-term decision-making.
- Bridges the Gap: Connects technology design with day-to-day implementation, helping farmers operate systems and evaluate performance from a sustainability perspective.
30+
Diverse Case Studies Across Europe
Assessment Framework Development Workflow
Identification of Performance Measures
→
Framework Design
→
Framework Application
| Aspect | Before DATS | After DATS |
|---|---|---|
| Resource Usage | General, often inefficient application of inputs. | Precise, optimized use of water, fertilizers, pesticides. |
| Decision Making | Based on traditional methods and experience. | Data-supported, real-time decisions, improved forecasting. |
| Labor Workload | High manual effort, repetitive tasks. | Automated monitoring, reduced physical workload, enhanced flexibility. |
| Productivity & Yield | Variability due to generalized practices. | Increased yields, improved quality due to precision agriculture. |
Case Study: Romanian Farm (Case 10)
A large Romanian farm utilizes a Decision Support System (DSS) to optimize water and agrochemical use across 552.67 ha. The DSS integrates yield maps, meteorological data, satellite images, and scheduling tools. The initial analysis showed a net benefit of €426.66 per hectare, with a payback period of approximately 3.6 months. Key benefits included increased yields, reduced fuel/energy costs, and improved labor productivity, despite a slight rise in labor costs for certain treatments.
Key Metric: €426.66 Net Benefit per Hectare
Quantify Your Potential ROI
Use our interactive calculator to estimate the potential cost savings and reclaimed productivity hours for your organization with AI.
Estimated Annual Savings
$0
Reclaimed Hours Annually
0
Your AI Implementation Roadmap
Embark on a structured journey to integrate AI and digital solutions, ensuring sustainable impact and measurable success.
Phase 1: Discovery & Strategy Alignment
Conduct a comprehensive assessment of current agricultural operations, identify key pain points, and align DATS adoption with sustainability goals. Define specific KPIs for economic, environmental, and social impact.
Phase 2: Pilot & Framework Customization
Implement DATS in a controlled pilot environment. Apply the assessment framework with real-world data, customizing indicators and calculation methods to fit your specific crops, breeds, and geographical context. Iterate and refine based on initial results.
Phase 3: Scaled Deployment & Continuous Monitoring
Expand DATS implementation across your operations. Establish a dynamic monitoring system to track sustainability performance over multiple seasons, ensuring ongoing optimization and adaptation to evolving needs and technologies.
Phase 4: Impact Evaluation & Future Refinement
Regularly evaluate the long-term monetary and non-monetary impacts. Use insights to refine DATS usage, explore new digital solutions, and ensure sustained improvements in productivity, efficiency, and overall sustainability.
Ready to Transform Your Operations?
Schedule a personalized consultation to explore how our framework can optimize your DATS implementation for sustainable growth.
Ready to Get Started?
Book Your Free Consultation.
Let's Discuss Your AI Strategy!
Lets Discuss Your Needs
Select a Date
Sun
Mon
Tue
Wed
Thu
Fri
Sat