DeltaFramework

DELTA PROJECT

ISEAL Metrics WorkshopSept. 10th, 2020

DeltaFramework

❖ Delta Project Introduction

❖ Alignment challenges & solutions

❖ Technical challenges & considerations

Delta Project introductionKey info

Project’s aim: Bridging the gap in measuring and

reporting sustainability performance for the benefit

of both ends of the value chain

Funded by ISEAL Innovation Fund for 3 years

(Inception phase Q4-2018, and until Sept. 2021)

Partners: BCI, ICAC-SEEP, GCP, ICO.

+ Cotton 2040 Impact Metrics Alignment working

group (TE, FT, OCA, CC, CA, CMiA)

Delta Project introductionRationale (1/2)

Multiplication of labels / standards / certification

schemes that all promote sustainability in key

commodities

Large multinationals develop their own sustainability

frameworks

➢ Confusion of end-consumers and other stakeholders,

➢ Lack of transparency and credibility,

➢ Impossibility to aggregate sustainability performance

data at commodity or sector level.

Delta Project introductionRationale (2/2)

Besides, current approaches to measure sustainability:

Are not well-adapted to the agricultural sector

Do not effectively monitor change over time

Do not give insight into benefits (especially socio-

economic)

May lead to unintended, harmful burden-shifting

(e.g. from irrigated country to rainfed, or from

natural to synthetic fibers)

Delta Project introductionComponents & Value proposition (1/3)

1. Develop a Sustainability Framework: impact

indicators, guiding principles and data

standardization

➢ For the sustainability community: common

language on sustainability across agricultural

commodity sectors

Delta Project introductionComponents & Value proposition (2/3)

2. Link sustainability performance to business actors

and governments: method and guidance

➢ For companies & private sector: standardised

sustainability information to

customers/stakeholders, simplified data

consolidation, consistent data collection &

reporting on key indicators

➢ For government & public sector: SDG

commitments reporting, evidence-based decision

making for agricultural policies & services

Delta Project introductionComponents & Value proposition (2/2)

3. Add value for producers:

❖ Feedback performance data to farmers,

❖ Contextualise data by establishing links to

open data sources (e.g. weather, market

information),

❖ Enhance the development of farmer-centred

services (e.g. extension services, finance,

insurance, etc.)

➢ For farmers: better learning and decision

making, (improved) access to services

List of challenges

Alignment challenges:

❖ Different scopes and approaches❖ Different organisational structures❖ Basic definitions not harmonized❖ Debates on tools❖ Competing interests from different

stakeholders

Technical challenges:

❖ Data governance & privacy❖ Common definitions❖ Data schema❖ Ownership after the framework is released

Alignment challenges & solutions

Different scopes and approaches:

➢ Refer to the SDGs

➢ Agree on common sustainability goals

Different organisational structures:

➢ Assess potential indicators according to their relevance, usefulness and feasibility

➢ Integrate the indicators in regular M&E systems, with limited additional resources & costs

➢ Give precise guidance on data analysis, interpretation and reporting

➢ Leave data collection approach up to each organization but establish data quality requirements

Alignment challenges & solutions

Basic definitions not harmonized (e.g. calendar year vs harvest year for data collection & reporting)

➢ Agree on general definitions to ensure data comparability & potential aggregation

Ongoing debates on tools (e.g. GhG calculators):

➢ Not prescriptive on specific tools, only provide recommendations

➢ Guidance on requested scope & minimum requirements for the tools to be used

Interests of Retailers/Brands for communication purposes vs learning for farmers

➢ Develop data use cases for several categories of stakeholders

➢ Component 3 of the project – Ensure tangible added value for farmers from data

Technical Challenges & considerations

Data governance – Ensure proper data privacy while triggering exchange and cross learning:

❖ Aggregation levels, confidentiality and anonymization

❖ How to guarantee GDPR compliance?

Common definitions and data schema:

❖ Balance in addressing informational and technical requirements

❖ Ensuring adaptability

Framework established – and now?

❖ Global data warehouse for exchange and analysis

❖ Roles, responsibilities, ownership and cost ?

Technical Challenges & considerations

Join our discussions in the current phase on:

❖ Data governance

❖ Common definitions and data schema

Discuss in the community on how to operationalise and

technically showcase results:

❖ Global data warehouse – shared technical

resource

❖ Roles, responsibilities, ownership and cost

Thank you!Questions?

Do you have any input or ideas?

Would you like to participate?

www.deltaframework.org