Krishak
Client:
Nashik(City in Maharashtra, India) Government Agri department and Farmers of Nashik District
Duration:
6 months (June 2016 - November 2016)
Role:
Design Lead
Responsibilities:
User research, secondary research, synthesizing research into insights and ideas, concept ideation, designing solution architecture, incorporating user feedback into design iterations, aligning key stakeholders on product goals, validation
Conceptualised and Designed at Digital Impact Square, a TATA Consultancy Services(TCS) Foundation Incubator and MIT RedX lab.
CHALLENGE
Crop cutting exercise is carried to assess productivity levels of various crops, which in turn helps in estimation of total crop production and yield losses if any in case of insurance claims. Field surveys showed that the process of Crop Cutting Exercise is largely ineffective due to absence of scientific assessment of crop yield and loss. How can the situation be changed? How can we directly or indirectly assist the farmers to get their claims on time (One of the major causes of suicide).
BACKGROUND
India's crop production estimations are highly ineffective due to delay and lack of scientific assessments of crop productivity. This leads to unpredictable market situations where volatility of market supply and prices would be high for agricultural commodities. It also poses challenges for effective implementation of crop insurance programs in the country. India’s crop insurance program is the world’s largest with more than 25 million farmers insured. This insurance is expected to protect farmers in case of natural calamities such as drought, foods, pest and diseases. It is observed that insured farmers often receive their claim payments after 8 to 12 months, defeating the very purpose of insurance. Delays in settlements, in turn, make it challenging for farmers to repay the bank loans they have taken for buying seeds and fertilisers at the time of planting. This jeopardises their ability to borrow again for the next crop, reducing their planting, or pushing them into a vicious cycle of debt with money lenders.
PLANNED OUTCOME
Develop an ecosystem and a smart platform which will give real time and
accurate statistics of crop produced and the yield produced in the Country which will help prevent farmer suicides.
To comply with the government policies, I have omitted pictures and some of the government processes in this project.
SYSTEMS DESIGN | SOCIAL DESIGN | DESIGN RESEARCH
DESIGN PROCESS
Understanding the problem and the processes
Analysing insights
Ideation
Validating and Redesigning
Shadowing, user interviews, group interviews, attending trainings, meeting domain experts & desk research
Creating ecosystem maps, process maps, affinity maps, personas, current user journeys
Reimagine Journeys and process flows, preparing the solution architecture
Validating the solution architecture and process improvements with the stakeholders and redesigning
Prototyping the solution
Developing the software and the application
I was not part of this part of the project
According to National Crime Records Bureau 2,96,438 farmers have committed suicide in India since 1995.
60,750 in Maharashtra, India
Understanding the problem
and the processes
+
Analysing
Insights
Primary Research
Surveys | Interviews|Group Interviews | Shadowing | Connecting with Domain experts
40
Farmers
2
Insurance company officers
48
Taluka(Group of villages) officials
Talathi(Village inchare - Land and Revenue) + Joint District Assistant + DSO(District Supply Officer) + SDO(Sub - Divisional Officer) + Krishi Sahayak (Assistant - Agriculture)
1
District Collector
In charge of revenue collection and administration of a district in India.
2
Agri - Based companies
Sigma - Enviro
Farm connect
2
Tehsildaar
Executive Magistrate of the tehsil(Group of villages)
Two government processes
1
Crop Area Statistics (CAS)
Identify crop type and the area covered under the crop
Crop Area Statistics helps in understanding the area under agriculture land and the type of crop (Crop type) grown in a particular area (Crop Area). Reliable and timely information on crop area is of great importance to planners and policy makers for efficient and timely agricultural development and making important decisions with respect to procurement, storage, public distribution, export, import and other related issues. Most parts of the country have a detailed cadastral survey maps, frequently updated land records and institutions like permanent village reporting agency for providing reliable and continuous data on crop area. However with more emphasis on local area planning, there is further need for crop area with respect to different varieties grown in the area, irrigation Availability, the soil type etc. which can go a long way in rapid development of the region.
Ecosystem Mapping (CAS)
Stakeholder Mapping (CAS)
CROP CUTTING EXPERIMENT (CCE)
2
Crop Yield Estimation (CYS)
Identify yield of crop for productivity assessment
Crop production estimates are obtained by multiplying yield rates with area sown under the crop. The yield estimation in official series was normally done on the basis of normal yield and Condition factor. Normally, yield of crops in various states were estimated on the basis of crop cutting experiments, which used to be modified at the time of estimating yield on the basis of actual condition. Under this method production statistics was calculated by finding area under crop and average yield per acre of the particular crop.
The average yield was calculated by multiplying normal yield with condition factor. This method was known as condition factor or the Annawari estimate. The concept of normal yield and condition or seasonal factor was discarded in 1943 and the yield was estimated directly from crop cutting experiments.
Stakeholder Mapping (CYS)
Cooperative societies
+
Current Insurance Process during Crop cycle
Loss Reporting and Verification
Identified pain points of the personas
Farmers
Bank officer
Talathi (Govt. officer)
Lack of trust between farmers and Govt. officials
Farmers receive insurance claims 8-10 months later
+
Inaccurate Crop Area Statistics Results
Inaccurate data from farmers
Lack of awareness regarding the benefits among farmers
Unavailability of farmers for the CCE process
Tedious process of calculating and marking the plot.
148 jobs other than the CCE to tackle
Farmers misuse the money received from claims
+
Unreliable data due to Manual data filling
What is the reason behind such a long delay in the insurance claims to reach farmers?
The major delays in the claim processing takes place after the harvest, as the CCE data does not match the weather data which has to be then sent for rechecking. This can lead to delays of upto 8-10 months.
Ideation
Proposed Solution Architecture
STEP 1: Capturing aerial image
STEP 2: Processing the images
STEP 3: Classifying Data
STEP 4: Providing insights to the respective stakeholders
Parameters to consider
Soil type &
weather conditions
The reimagined process of Loss Identification
Validating and Redesigning
Final Concept
The final concept was developed after validating the prototype with the stakeholders involved and the domain experts(Agricultural and technological)
Execution Planning
Execution Timeline
Selected Season: Rabi (Winter crop) | Selected Crop: Onion
Specifications
Impact
Next Steps
I was a part of this project till the solution architecture designing, validating and redesigning. The next step was to develop the software using technical processes like Pattern Mining, Artificial Neural Network, K-means and Algorithms for weed detection. The software was developed by my teammates for the next 6 months. Demonstrated below are few of the screen shots of the processed output.
Challenges/Limitations
For each of the crop cycle, a customised solution had to be designed. We lacked the resources and the bandwidth as a team to be able to do so.