The Power Of Unified Digital Agricultural Services

By Soko Directory Team / May 20, 2020 | 12:54 pm



Mt Elgon agricultural region Farmers

Digital agricultural services can be valuable in multiple ways to the cultivating smallholders and a range of other stakeholders in the agriculture sector.

However, these services are largely offered independently and somewhat in silos. Most service providers have a “walled-garden” approach and do not provide complementing services from other synergistic platforms.

Unification of individual digital agricultural services offers a significantly more powerful proposition for smallholders and other actors in agricultural ecosystems.

A broad range of digital agricultural services has either been evolving or is now available.

The most basic of services provided through digital platforms are weather forecasts and advisories. The accuracy of these forecasts is critical for the recipients. Even minor discrepancies can lead to disastrous consequences. For example, if the rainfall forecast is off-the-mark, farmers can end up flooding the fields or irrigating too little. These errors can destroy harvest-ready crops and risk their entire earnings in a season. Therefore, many innovators, such as Skymetweather and ileaf are increasingly relying on local weather stations or Internet of Things (IoT) sensors located on the field to predict critical weather parameters as precisely as technology allows them to do.

Several agri-tech firms offer precision agricultural advisory services to farmers based on Artificial Intelligence (AI) and Deep Learning (DL) technologies. They collect data through drones, IoT sensors, or satellite images. This advice can help farmers take precise actions to realize higher productivity levels or to prevent disease and pest infestation. For example, they can apply appropriate doses of nutrients, select an appropriate mix of fertilizers or chemicals, and maintain the required water levels and temperature of their crops.

The Third Eye project uses recreational drones equipped with near-infrared sensors and tailored software to capture and analyze data locally. Data gathered during project implementation indicates that crop production had increased by 41%, while the total use of water reduced by 9%, resulting in a 55% increase in water productivity.

However, most extant platforms focus on providing only a handful of use-cases, such as advisory services, the supply of inputs, digital credit, or selective captive buying. This is a major downside of their approach. Moreover, the platforms often offer each of these services piecemeal and not as a basket of multiple services to farmers.

This offers an important opportunity for providers to integrate multiple services on a unified platform to make them more powerful. These services can include financial services, input demand aggregation and delivery, output (production) estimation and market linkages with multiple buyers, and digital payments, among others. Such integrated and unified services would be immensely useful to farmers.

Access to credit remains the biggest barrier to the sustainability of small and marginal farmers. Digital agricultural platforms can have a critical role to enable access to credit. It can address several of the barriers that currently limit the availability of credit. Banks are risk-averse to work with farmers due to the limited availability of financial information around them. Digitized data can provide digital footprints in the form of sales records and purchases to determine the capacity to repay loans.

Kenya Commercial Bank (KCB) introduced a mobile-based platform for smallholder farmers called MobiGrow. The platform is accessible to over two million farmers in Kenya and Rwanda, who avail loans, savings, insurance, and agribusiness training opportunities. In its first year of operations, it registered over 400,000 farmers and saw transactions worth USD 22.4 million being conducted.

FarmDrive runs a credit-scoring system by using agronomic data, satellite data, and social data to link-local financial institutions to lend to eligible farmers. Impact Terra is a digital agricultural platform in Myanmar that bundles services as well. Its Golden Paddy platform reaches 2.8 million unique users and offers relevant information on best practices, weather, pricing information, and access to buyers, suppliers, and financial institutions.

A unified digital agricultural platform requires collaboration between multiple actors with complementary expertise. An open and shared data platform approach can be even more compelling, as this approach would offer significant upsides. These include: reduced and shared costs; ability to spread risks and bring innovations to market collaboratively and more quickly; mutually beneficial solutions, such as unified loyalty programs on the platform; ability to achieve scale and volumes rapidly; and to engage and provide support to governments. However, this also requires a much greater willingness on the part of providers to collaborate and share data and resources.

Innovative forward-looking providers, that realize the power and the value of unified services, can take a lead and the first steps to unify digital agricultural service. Philanthropic funding can provide a much needed initial support for proofs-of-concept and early demonstration of unified services, to catalyze crowding-in of additional investments for scale-up efforts.

By Elizabeth Berthe and Puneet Chopra (partners at MicroSave Consulting-MSC)





About Soko Directory Team

Soko Directory is a Financial and Markets digital portal that tracks brands, listed firms on the NSE, SMEs and trend setters in the markets eco-system.Find us on Facebook: facebook.com/SokoDirectory and on Twitter: twitter.com/SokoDirectory

View other posts by Soko Directory Team


More Articles From This Author







Trending Stories










Other Related Articles










SOKO DIRECTORY & FINANCIAL GUIDE



ARCHIVES

2020
  • January 2020 (272)
  • February 2020 (310)
  • March 2020 (390)
  • April 2020 (322)
  • May 2020 (336)
  • June 2020 (74)
  • 2019
  • January 2019 (253)
  • February 2019 (216)
  • March 2019 (285)
  • April 2019 (254)
  • May 2019 (272)
  • June 2019 (251)
  • July 2019 (338)
  • August 2019 (293)
  • September 2019 (306)
  • October 2019 (313)
  • November 2019 (362)
  • December 2019 (320)
  • 2018
  • January 2018 (291)
  • February 2018 (219)
  • March 2018 (278)
  • April 2018 (225)
  • May 2018 (238)
  • June 2018 (178)
  • July 2018 (256)
  • August 2018 (249)
  • September 2018 (256)
  • October 2018 (287)
  • November 2018 (284)
  • December 2018 (185)
  • 2017
  • January 2017 (183)
  • February 2017 (194)
  • March 2017 (207)
  • April 2017 (104)
  • May 2017 (169)
  • June 2017 (205)
  • July 2017 (190)
  • August 2017 (195)
  • September 2017 (186)
  • October 2017 (235)
  • November 2017 (253)
  • December 2017 (266)
  • 2016
  • January 2016 (165)
  • February 2016 (165)
  • March 2016 (190)
  • April 2016 (143)
  • May 2016 (245)
  • June 2016 (182)
  • July 2016 (271)
  • August 2016 (248)
  • September 2016 (234)
  • October 2016 (191)
  • November 2016 (243)
  • December 2016 (153)
  • 2015
  • January 2015 (1)
  • February 2015 (4)
  • March 2015 (166)
  • April 2015 (108)
  • May 2015 (116)
  • June 2015 (120)
  • July 2015 (148)
  • August 2015 (157)
  • September 2015 (188)
  • October 2015 (169)
  • November 2015 (173)
  • December 2015 (207)
  • 2014
  • March 2014 (2)
  • 2013
  • March 2013 (10)
  • June 2013 (1)
  • 2012
  • March 2012 (7)
  • April 2012 (15)
  • May 2012 (1)
  • July 2012 (1)
  • August 2012 (4)
  • October 2012 (2)
  • November 2012 (2)
  • December 2012 (1)
  • 2011
    2010
    2009
    2008
    2007
    2006
    2005
    2004
    2003
    2002
    2001
    2000
    1999
    1998
    1997
    1996
    1995
    1994
    1993
    1992
    1991
    1990
    1989
    1988
    1987
    1986
    1985
    1984
    1983
    1982
    1981
    1980
    1979
    1978
    1977
    1976
    1975
    1974
    1973
    1972
    1971
    1970
    1969
    1968
    1967
    1966
    1965
    1964
    1963
    1962
    1961
    1960
    1959
    1958
    1957
    1956
    1955
    1954
    1953
    1952
    1951
    1950