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Our blog often reviews innovative farming architecture and tools in the context of their business practicality. Today we’ll tell you how we created the farm scouting app helping to increase crop yield by gauging extra farming land.
The project app description: a mobile farm scouting app used for field and crop examination
App users: field scouts working as employees of the agricultural company
The app’s goal: visualize field examination results and assist field scouts with their daily tasks
What field scouting does
Field scouting is the detailed examination of crop performance and pest pressure aimed at preventing pest risks and the resulting increase in crop yield. Field examination takes a long time, from the crop emergence to the harvesting time. Scouts control the entire plant development process, observing the presence of weeds and pests. The information collected from fields and Meteo stations is analyzed to plan for herbicide spraying, plant treatment, and application of pesticides and fertilizers. Field scouting is a part of complex works determining the quality and volume of crop yield. A farm scouting app is a great way to perform all examination tasks.
How modern technologies help with field scouting
Present-day agricultural technologies are booming, and scouting techniques are not an exception. To facilitate rapid and efficient field scouting, farmers can use different types of apps. Based on the approach to the collection of data, we can conditionally divide them into two types of apps:
1) Centralized. Complex digital farm scouting app with a centralized database and additional role-specific applications. Usually, a chief agronomist tracks central data collected with the help of various soil sensors, drones, Meteo stations, farm scouts and workers, agronomists, etc.
2) Autonomous. Modern digital tools can distribute functions and delegate duties according to the pre-defined roles and zones of users’ responsibility. There are also so-called point applications used without a centralized data flow. Every employee will use their part of the app to control a specific work area, collect data and generate reports.
Both digital methods have pros and cons; the farmer’s goals and requirements determine their use. We want to tell you more about the app we created, as it can be used as both an autonomous and centralized app.
Main stages of the farm scouting app development
- Research and discovery
- Analysis of the information: mapping out the user journey
- Prototyping the farm scouting app
- Evaluation of the first results and progress of the app
Research and discovery
First, improving a farm scouting app took us to analyze the activity of the ordering company carefully. To perform the requirements analysis, we scrutinized public sources, observed the work of farm scouts in action, and interviewed them to validate our initial hypothesis.
Analysis of public sources
It was necessary to have a clear and complete understanding of the field scout’s scope of work. The Internet articles and research aside, we checked the job sites. We scanned more than 50 crop scout job descriptions to collect the information about the duties and responsibilities of field scouts that are represented in the below summary:
- Going to fields to monitor the cultivation of agricultural plants
- Requesting for and obtaining expendable materials from the warehouse
- Communicating with a farm machinery operator about the volume of plant protection agents and fertilizers
- Making sure that tractor and machinery operators are duly protected from the impact of pesticides and providing them with the means of individual protection and field scout clothing
- Accompanying the transfer of agricultural machinery within field zones
The next stage of our research was on-site monitoring of the scout work in the fields.
Three representatives of our team went to the fields and accompanied a group of field scouts working in the partnering company. We monitored their actions, found meaningful details to reflect them in the app development, and learned about their challenges and needs.
As a result, we came up with a summary of the agro-scouting routine and the check-list of their actions:
- Examine the field route to understand the tasks required to be done along the route
- Getting the necessary tools ready
- Get to the destination
- Taking necessary action
- Recording the data
- Processing the results
- Making plans according to the results
- Reporting the data
- Making the next day’s schedule
Next to it, our team prepared the survey to validate our hypothesis and understand which app functions must be developed first.
We chose employees with different backgrounds, work experiences, and scopes of duties to be interviewed and talked to the eight field scouts.
It was found that the record of data is the priority in the work of scouts. It was also critical for them to rapidly process the data and obtain tips for various scenarios generated by the app.
Once we’ve compiled the information, we set it to the data analysis. For this purpose, our team has shaped User Map, Job Story, and Customer Journey Map. Let’s go through the findings of every diagram.
User Map of the Farm Scouting App
All user requirements were united into the following groups and logically connected as the User Map.
The Job Story helps to navigate users following their needs in certain situations and understand these needs from the viewpoint of motivations.
Building Customer Journey Maps helps to see how the user will move along the way and which difficulties are possible throughout the journey. Using this approach allowed for highlighting the essential functionality for the first iteration. These functions were supposed to be intuitive and smooth.
The resulting CJM described the working day of a field scout, prioritized their tasks, and enabled the planning of the following iterations. The arguable positions in the plan were redefined based on the results of the Kano survey, which helps to prioritize the product features.
This way, we could break the app development plan into iterations.
Prototyping was done to draft the representation of the final product and take the possibility of receiving feedback from users during the first iteration. The deliverables of this stage were Wireframe/Wireflow layouts and Low/High Fidelity design, which we’ll focus on below.
Interviews and surveys guided our vision of the layouts, later reflected in the Wireframe and Wireflow maps.
Users’ actions and pathways were detailed with the help of Wireframe/Wireflow layouts. These maps visualized the interaction between the app and future users. It also shows how the offered exchange will solve their challenges or simplify the fulfillment of their tasks.
Our designers also prepared low- and high-fidelity layouts step-by-step according to the UI Kit guidelines.
Layouts were evaluated by the customer company and reviewed by developers. The first design version was created within two weeks and tested with the help of the focus group. The main idea of the first design version was to create a convenient app that assists field Scouters with their daily routine.
To enable more rapid and smooth application development, we limited the first product version to the minimum set of features listed below:
- The everyday check-list;
- Creation of fast voice and text notes
- The map with the field route
- E-mail export of the scout results
Then we proceeded with the implementation of the functions planned by the road map, which was needed according to the feedback of the app users.
The last app version has expanded functions, including tips on improving crop yield, automatic generation of reports, the option to submit them to the chief agronomist’s virtual reception, and many other features.
Evaluation of the app’s efficiency
A target focus group used the app’s beta version within three months. According to the results of this test, we found that the gauge of the scouted area was increased by 18%, and the time required to process results was 1,5 hours less than before. These results encouraged us to release this functionality as a full version for all field scouts of the customer company.
The test results for a larger representation group were similar. Every iteration of the app brings positive changes in the goal indicators.
Below you’ll find significant results of the app use reflected within a year:
- Surveyed land area increased by 21%;
- The average time for the report generation is only 13 minutes now;
- The crop yield in problem areas spotlighted by the program increased by 1.2;
These changes led to positive improvements in crop quality and volume.
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