Finding the Right Fit
The growing competition and the advancement of technology has led farm machinery companies globally to innovate on technology and business models. One such business model idea is farm equipment-as-a-service model, where any machinery can be rented by the farmers. While, we first attempted this use case with a client in 2018, the current client had a more willingness to adapt to the new technology. Their approach was fairly simple, ‘Fail Fast, Learn Fast’. However, the one thing which was to be a ‘constant’ in each of their ideas was the adoption of geospatial data.
Unlike the main business, which focused on the sale of the machinery, equipment-as-a-service is fairly complicated, since just like cab services, the system, decision making and deployment of the services has to be very agile. This requires continuous and near real-time monitoring of crop progress and its condition which has to be linked with the on field service deployment strategy and decision making to increase the chances of conversion for the company.
Additionally, along with access to current data, access to historical data becomes important to capture patterns and trends and create forecasts for sales and market targeting before the start of the season. However, before getting into the solution, let us understand challenges this model faces.
Challenges: What the Current System Lacks
Lack Of Insights and Alternate Data
Most of the organisations engaged in agriculture rely heavily on field staff for any information pertaining to crop monitoring and associated decision making. However, in many cases, the staff on the ground is limited which makes it difficult to reach the exact location at the right time. What makes matters worse is alternate resources are either costly, unavailable or inaccessible for gathering information.
Lack Of Granular Crop Information
In this case, granular information can be termed as the unit at which the crop information can be made available. Most companies rely on Government records, which are usually available at district level or on the field staff for information pertaining to any event that affects the crop growth. However, sales and market planning can require estimations at village and taluka level as well, to enhance the effectiveness of the forecasts and market planning.
Inefficient sales and market planning
Due to lack of alternative data sources and granular data, companies rely on information provided by the field staff. However, the information capturing and distribution mechanisms itself are in question here. Information asymmetry can arise due to factors like:
This information asymmetry leads to incorrect revenue predictions for inventory, sales and market planning, which leads loss of efficiency thus impacting revenues.
Using SatSure Sparta for Farm Machinery-as-a-Service Model
SatSure worked with the client focusing on the following areas of engagement:
In short, equipping the field staff with tools and information to help them be more productive and improve overall efficiency of the services.
The primary interest was to deploy the machinery at the ‘right location, and at the right time’.
Thus, Crop Monitoring became an important element of the delivery. We provided the client with details of crop growth stages at village level. Using this information, the client was not able to plan marketing activities and manage inventory requirements as per the cropping intensity and expected demand in a particular region.