ECOSYSTEM FOR DELIVERING VOICE-BASED

AGRICULTURAL INFORMATION SERVICES TO RURAL INDIA

Himadri Das1, Mikko Ruohonen

2, Markku Turunen

3, Gururaj

Mahajan4 and Juhani Linna

5

Submitted as

Workshop/Interactive Paper

to

The 29th Euro-Asia Management Studies Association Annual Conference

31 October to 3 November 2012

National University of Singapore

Please do not cite without authors’ permission!

1 Corresponding author: International Management Institute, B-10 Qutab Institutional Area, Tara

Crescent New Delhi 110016 India, email: himadri.das@imi.edu 2 University of Tampere, email: mikko.j.ruohonen@uta.fi

3 University of Tampere, email: markku.turunen@cs.uta.fi

4 University of Tampere, email: gururaj.mahajan@uta.fi

5 University of Tampere, email: juhani.linna@uta.fi

Ecosystem for Delivering Voice-based Agricultural Information Services to

Rural India

Abstract

The market potential at rural India’s Bottom of the Pyramid (BoP) is huge. The BoP consumer is

illiterate and poor but they have access to mobile phones. This suggests that the mobile phone can

be used as a channel to deliver services to the BoP. Given that a large proportion of rural India’s

BoP are farmers, agricultural information services are an important bouquet of services that would

be useful. These services, however, have to be purely voice-based and cannot involve text of any

kind as the consumer at the BoP can neither read nor write. Spoken web technology developed by

IBM Research Labs can be used for developing voice sites on the line of web sites on the World

Wide Web. Voice sites can be interactive with content being in audio form and the consumer of the

content accessing it using voice commands. Language technology companies will be an important

component of this service delivery ecosystem in their role of langauge translation and voice

synthesis. The other important component of the service delivery ecosystem will be firms that will

deliver the agricultural information services to the consumer without directly charging anything for

it as the rural BoP consumer cannot afford to pay for these services. These firms will have to

develop innovative business models where they can make sustainable profits through commerce for

associated products that anyway have a market with these rural BoP consumers.

1. Introduction

A large market opportunity exists for businesses to create significant economic value by innovating

the design of products and services to more effectively serve the needs of the lowest income

segments of the population in emerging economies. This is especially true in the high population

emerging markets of China, India and increasingly in Africa. Innovations for the emerging markets

can become more attractive through the process of reverse innovation (Govindrajan & Ramamurti

2011), where new products developed for emerging markets are later introduced in the developed

markets. This phenomenon helps to build strong business collaboration between developed and

emerging markets.

The term bottom of the pyramid (BoP) was coined to describe the very poor and economically

deprived who have an unmet need for products and services that can be profitably exploited by

businesses (Prahalad and Hart, 2002). In this paper we focus on the opportunity that exists for

businesses to deliver agricultural information services to the BoP market in India. This market

segment is mostly in rural India, which is difficult to reach compared to urban India. The total

population of India is 1.21 billion with a break up of 833 million from rural India and 377 million

from urban India

(http://censusindia.gov.in/2011census/censusinfodashboard/stock/profiles/en/IND_India.pdf). This

indicates a huge 69% to 31% rural to urban skew. Poverty continues to be an issue in India in spite

of the high growth of the economy in the last several years. The Government of India defines Below

the Poverty Line (BPL) as an economic benchmark and poverty threshold to indicate economic

disadvantage and to identify individuals and households in need of government assistance and aid.

The total BPL population of India is 302 million with a break up of 221 million from rural India and

81 million from urban India (http://pib.nic.in/newsite/erelease.aspx?relid=44102). Expressed as a

percentage of the total population, the BPL population is 25% on an all India basis, 27% in rural

India, and 21% in urban India. The BPL rural to urban skew is larger at 73% to 27% as compared to

that for the overall population. The true bottom of the pyramid market size is, therefore, 302 million

with 221 million of this in the difficult to access rural India.

The poor are vulnerable by virtue of lack of education, lack of information, and economic, cultural,

and social deprivations (Karnani 2007). Accessibility to this large rural bottom of the pyramid

market is a huge challenge specially for services. The distribution channels for products have been

established with large investments by some of the large consumer product companies but services

have been a hitherto more or less unexplored category for this market. A notable exception to this

service drought in rural India has been telecommunication services. Mobile phone penetration in

India, in general, and rural India, in particular, has been growing at a breakneck pace. The total

number of mobile phone connections in India is 919.17 million with 595.90 million connections in

urban India and 323.27 million connections in rural India. (http://www.trai.gov.in/ ). This higher

share of urban subscribers at 65% as compared to the lower share of rural subscribers at 35% is

because mobile connectivity was originally rolled out exclusively in urban centers as that was

where the purchasing power existed for the then expensive service. As the service prices have

dropped drastically the market in rural India has now opened up and that is where the growth is

much higher than that in urban India. Every month 8 million new mobile connections are added

across India at a monthly growth rate of 0.88%. This is made up of 1.79 million new connections in

urban India at a monthly growth rate of 0.30% and 6.21 million new connections in rural India at a

monthly growth rate of 1.96% (http://www.trai.gov.in/ ). It is expected that by 2013, the number of

mobile phone subscribers will be 1 billion. The national mobile connection teledensity is 70.23 with

an urban teledenisty of 154.18 and a rural teledenisty of 34.13. What appears to be a comparatively

low rural teledenity for mobile connections is very misleading in terms of a measure of the power of

the mobile phone for accessing the rural market. This is because in rural India the mobile phone is

not a personal device like in urban India but a shared device across the entire family. This makes

the addressable market size using mobile phones larger than that suggested by the teledenisty

figures.

Typically value added services through mobile phones have been delivered through text and web

platforms. Both of these require the service consumer to be literate. Whereas literacy is a given in

developed markers for mobile value added services, it is not the necessarily the case in the rural

India bottom of the pyramid market segment. The illiteracy rate in India is 26%, with 31% illiteracy

in rural India and 15% illiteracy in urban India.

(http://censusindia.gov.in/2011census/censusinfodashboard/stock/downloads/Profiles_6/PDF/IND_

6.pdf). It is no coincidence that the illiteracy rate in rural India (31%) and the BPL population in

rural India (25%) are similar in numbers. In this rural India BPL segment poverty and illiteracy go

hand in hand. It is, therefore, safe to assume that essentially the entire 221 million rural India

bottom of the pyramid population is illiterate. Illiteracy makes text base and web based service

delivery platforms unusable. This creates a need for services that can be delivered on a voice

platform instead of text or web.

The abject poverty at rural India’s bottom of the pyramid make the conventional business model

untenable where the mobile phone subscriber pays for value added services consumed. The

dichotomy is that the need to consume services exists at the bottom of the pyramid but the ability to

pay for these services does not. This requires an innovative business model where the service

provider pays for the services instead of the consumer and in a manner such that the service

provider generates profits in doing so on a sustainable basis.

2. Background

2.1. Agriculture in India

Agriculture is the main source of occupation in rural India and plays an important role in the Indian

economy. Agriculture has contributed 14.7 per cent of GDP for the year 2010-11 (Economic Survey

2011, Govt. of India). According to the 2011 Indian census, agriculture accounted for 58 percent of

total Indian employment. In order to achieve inclusive growth and attain sustainability in agriculture

and allied sectors, the Government of India is giving huge support to the agriculture sector.

In recent years, a huge demand has been observed from farmers for need based agricultural

information. They are in need of information and support in different stages of farming like

production, processing and marketing (see Figure 1). In spite of this demand, agriculture

information access for farmers is lacking. In rural India, for example, if a farmer is in need for

information on a particular pest, then he must visit the nearest Department of Agriculture office and

then consult the employee concerned to get the required information about the pest. Given the

penetration of mobile phones, the farmer would now like to use this technology to access the

agriculture information at different phases like production, processing and marketing. Such an

agricultural information system that could be accessible through mobile phones is, however, highly

complex in nature and given the large number of crops and their many varieties. Providing the user

the needed information is, therefore, a challenging task.

Figure 1: Agricultural phases and information needed in each stage

2.2. Existing voice-based services

Currently, voice-based services are used successfully in many areas in many countries. They use

wide but varying set of language technology depending on the extent, complexity and environment

of the tasks they are developed for. Typical examples of voice-based services include transport

information services, such as automated train and bus timetable services. The first (automated)

voice-based services were telephone-based interactive voice response (IVR) systems, which used

speech outputs and telephone keys for interaction. These applications are still popular and possibly

the most important examples of widely used commercial voice. Typically, these applications are

designed to replace human operators. Problems with these systems include that the telephone key

pad interface may be awkward and user satisfaction poor, if the service does not match the quality

offered by human operators. On the other hand, these applications can be very useful for users if

they introduce new services which are not possible or affordable with human operators (or in any

Production

Cultivation materials and

practices Yield

Crop protection

Pest Management

Disease Management

Weed Management

Processing

Harvesting

Post Harvesting

Storage

Marketing

Market price information

Local agri-market information

other way). This is exactly the case in rural India, where human-operated services are not viable in

many cases.

The current trend is that the telephone key pad inputs are replaced by speech inputs. This may

promote both greater user satisfaction and cost savings in some application areas. In addition to IVR

applications, many other forms of telephony applications have dominated the field. These include

information services, such as timetable, weather forecasting and banking services, e-mail

applications and voice portals. Most of the well-known commercial applications and research

prototypes fall into this category. When these applications are collected together, they create voice

portals which integrate several applications into a unified speech interface. Conventional voice

portals, however, have several problems in the rural India context, such as that they do not support

user created content, which makes many services impossible. The Spoken Web is a system to

address these challenges, and is the central medium in the ecosystem presented in this paper.

2.3. Spoken Web

Spoken Web, a technology developed by IBM Research Labs India, is designed to deliver data and

information to illiterate people (Agarwal et. al. 2010a). Spoken Web content is stored in the form

of voice-sites instead of text based web-sites. The content is in local dialects, making it much easier

for illiterate people to access this information. Voice-links allow for navigation between voice-sites

using voice commands from a limited permissible vocabulary set. The interconnection of voice-

sites leads to a WWTF or World Wide Telecom Web on the lines of the traditional World Wide

Web (Kumar et. al. 2007). The lack of internet access limits access to the World Wide Web. Voice-

sites can be accessed by dialing a phone number. The much higher access to mobile phone

connections, therefore, makes access to voice sites much easier.

The underprivileged in India, who otherwise have limited access to information, are receptive to

using ICT enabled methods to access information (Kumar et. al. 2008). Using ICT to reach this

segment, though challenging, is possible with appropriate social settings for technology adoption

(Agarwal et. al. 2010b). The falling price of mobile phones has resulted in widespread adoption of

these devices in the Indian rural hinterland across all strata of society and income levels. Artisans

like plumbers, electricians, and carpenters have mobile phones for business reasons to be accessible

to their clients. In a pilot study these artisans have set up voice-sites to give clients information

about their availability, rates, and references (Agarwal et. al. 2008). Another pilot was conducted

for small farmers in rural India using interactive voice-sites for creating a lively social space to ask

questions and provide answers (Patel et. al. 2010). For all users in this pilot this was the first

experience in participating in an online community. The most popular usage of this forum was

asking questions and browsing answers to questions asked by others.

In addition to the target segment of illiterate people, the spoken web is also useful wherever Internet

access is not available. This is still the situation with a majority of the world’s population. For these

people the spoken web with mobile phone access provides the only source of information. The

spoken web supports user generated content creation and dissemination in areas that do not have

internet access. A study conducted on usability in 600 Indian villages over nine months suggests the

importance of locally created content in their own language (Agarwal et. al. 2010c).

Traditionally Human Computer Interface (HCI) research has focused on high end devices owned by

affluent users. For the Spoken Web to work for the rural impoverished masses, high end devices are

out of the question as the only device available is the low end mobile phone. A study using these

simple devices show that richer mobile interfaces can be created that allow for interaction with

audio content through simple audio gestures (Robinson et. al. 2011).

In addition to providing information access to illiterate people, the Spoken Web also provides

information access to the visually impaired. A study with partially blind and completely blind

people showed that the time required to complete a specific task on a voice-site was quite

acceptable and did not necessarily require prior computer skills (Rajput et. al. 2008). Since the rural

India bottom of the pyramid (BoP) also does not have prior computer skills this finding is

encouraging for the effective use of voice sites for content creation and dissemination.

A number of pilots and studies conducted have given encouraging results regarding the viability of

spoken web enabled voice-sites as an alternative to the World Wide Web for those who do not have

Internet access and/or cannot read or write. No commercial application using the spoken web is

known so far but the success of the pilots suggests that commercial applications are possible. This

paper explores the possibility of commercial applications using the spoken web targeted at the rural

India BoP segment.

3. Ecosystem for Service Delivery

The ecosystem is composed of the users (agricultural service consumers), domain knowledge

expert, the Spoken Web platform, voice-based applications built on the Spoken Web platform,

companies delivering the services using these applications, and the research teams designing the

structural relationships between the different players. This involves Indian and Finnish players,

making it an international ecosystem.

The users are Indian farmers in the BoP. The domain knowledge expert is University of

Agricultural Sciences Dharwad (UASD), a top notch agricultural research university in India. The

Spoken Web platform is developed by IBM Research Labs in India. The voice-based applications

on the Spoken Web platform will be developed by Finnish MSMEs, given their expertise in voice-

based systems in their work in the Nokia centric ecosystem in Finland. The companies delivering

the services will be Indian companies that serve the agricultural market. The research teams are

based at the University of Tampere (UTA) in Finland and the International Management Institute

(IMI) in India. Figure 2 shows the entire ecosystem with all its players.

Figure 2: Indian and Finnish players in the Voice-based Agricultural Information Ecosystem

The critical success factors for this ecosystem to be vibrant will be the acceptability of this service

delivery mode with the agricultural service consumers, the ability of the Finnish MSMEs to develop

voice applications in the Spoken Web platform, and a business model that will be sustainable in the

long run to continue delivering these services. The following is an assessment of these three critical

success factors.

3.1. Acceptability with Agricultural Service Consumer

A preliminary field study was conducted to understand acceptability of this service delivery mode

with the farmers. This field study was carried out in the northern villages of the state of Karnataka

in India. A prototype voice site with agricultural information content was designed and

implemented in order to obtain usability and acceptability feedback from farmers. A total of 51

farmers were interviewed out of which 35 were men and 16 were women. This sample included the

following categories of farmers:

Marginal farmer (holds below 1 hectare of land)

Small farmer (holds 1-2 hectares of land)

Medium farmer (holds 2-4 hectares of land)

Large farmer (holds 4 and above hectares of land)

The key findings of the field study conducted on the sample of 51 farmers were as follows.

All farmers liked the prototype and its approach to delivering agricultural information

services.

A particularly attractive feature of the service was that it was in the local dialect that made

understanding easy.

The other existing sources of agricultural information are elders in the family, radio and

television. Radio and television do not have the advantage of information on demand that

the voice site provides.

Most of them are aware of IVR (Interactive Voice Response) services. They use them

mostly for downloading ringtones for their mobile phones and to check the talk-time

currency available on their mobile phone. They are also use IVR to access agricultural

information from the agricultural help lines. Getting used to a voice site was, therefore, not a

significant transition.

46 out of the 51 farmers said they cannot afford to pay for these services and would like

these services could to be given free of cost. These were marginal, small and medium

farmers. 5 out of the 51 farmers said they were willing to pay a small monthly subscription

charge for the service. These were large farmers. It, therefore, appears that for this service to

be consumed it must be given free of cost.

3.2. Language Technology MSMEs in Finland

In a Finnish context, a qualitative study was conducted among eight MSME’s that operate in the

field of human language technology and develop their own products. Language technology is a field

of that aims in getting computers to perform useful tasks that involve human language, for example,

in human-machine communication or meaningful processing of text or speech (Jurafsky and Martin,

2008).

Mobile and language technology companies in Finland are in general highly developed in the

technological sense. This is mainly due the advanced education system and the immense direct and

indirect impact that Nokia Corporation had on the business sector especially during the decades

before and after the millennium. In spite of this, the key group of MSME’s that operate in the field

of language technology and develop and govern their own products consists of only a handful of

companies. This is mainly due to confined markets in Finnish language and difficulties in market

entry for other market areas.

A total of 8 MSMEs were interviewed and based on this it was not possible come up with a typical

MSME in language technology in terms of a common company profile. The activities of the 8

MSMEs represent, for example, machine translation, speech synthesis, speech recognition, proof

reading and text analysis for various purposes. The number of staff ranged from 2 to a couple of

dozens, and revenue from under 100 000 Euros to a few million Euros. Both staff size and revenue

fluctuate quite a bit in most companies. While it is difficult to analyze all of the reasons behind this

fluctuation, it can be safely said that the development phase the company is in with its product or

products has a significant effect on the financial situation of the company as well as the staff

composition. The product catalogues were built around one concept in the smallest of the

companies, but the largest company had a full range of language services from translation and

consultancy services to a palette of software. The downturn of 2008 and the chronic uncertainty in

the European economy, the most important market area for these companies, have evidently had a

negative impact on product and service demand.

In order for the Spoken Web to become a truly successful and widespread system, it needs

commercial service providers, commercial application developers, and commercial language

technology companies to do reasonable business on the platform. While Spoken Web is a highly

promising platform both in terms of technology and application development potential, it needs

language technology companies to be able to deliver voice-based services in multiple languages.

Technical future development areas include the infrastructure itself (hosting the Spoken Web

applications), the language palette (more languages are needed), navigation (due to its sequential

nature, voice content can be arduous to navigate) and multimodality support (Agarwal et. al. 2010a;

Kumar et. al. 2010). While languages are different, the majority of the technical challenges that

relate to the use of natural language are universal. Companies that have expertise in some areas of

language technology are likely able to contribute on the development of Spoken Web with

reasonable efforts, regardless of their country of origin or existing selection of languages.

In the voice-based agricultural information services ecosystem the Finnish the language technology

companies in Finland will have an important role of building on the Spoken Web architecture. In

particular, machine translation services for new languages are needed. For example, a weather

information service that mines English or Hindi information (mother content or mother text) needs

to translate that information to local Indian languages in order to be viable. Further, an acoustic

modeling for every used language is needed for the speech synthesis to be serviceable. The Census

2001 suggests that Bengali (82 million speak as mother tongue), Telugu (74), Marathi (71), Tamil

(61), Urdu (51), Gujarati (46), Kannada (38), Malayalam (33), Oriya (33) and Punjabi (28) are the

most common mother tongues after Hindi spoken in rural India and, therefore, the most applicable

launch languages for the voice-based agricultural information services.

3.3. Business Models

A demand for certain types of agricultural services exists in the rural India BoP even though the

consumers of these services do not have the capacity to pay. It, therefore, is necessary to innovate

and create business models where these services can be profitably delivered on a sustainable basis

without charging the consumer for it. This requires Indian service provider companies to build

innovative business models around the delivery of these services to generate their profits. The

following are the specific agricultural services farmers need and our proposed business models that

can be used to deliver them. Figure 3 shows these business models in terms of sustainable cash

flows that can make them profitable for all concerned.

3.3.1. Agri-commodity prices and weather

The farmers need to know the prices of agri-commodities they produce so that they can ascertain a

fair price at which they should sell their crops after harvest. Currently they are completely at the

mercy of the price offered by the middleman who buys from them and are typically exploited.

Farmers also need weather information as this often affects their decisions on irrigation as well as

harvest. If scarcity of rainfall is forecast then they need to spend money to make arrangements for

irrigation. If heavy rains are forecast that could destroy their crops close to harvest time, they can

consider an early harvest to save the crops.

The companies from the food processing industry can run voice sites giving price information as

well information on how to sell the agri-commodities at that price. These companies can then dis-

intermediate the supply chain and buy directly from farmers. This will lower the procurement price

for the food processing companies and increase the farmers’ realization from the farm produce by

being able to sell at a price higher than at what they sold to the middlemen. The lower procurement

prices for the food processing companies will increase their profitability. The food processing

companies can also run voice sites to provide weather information to help farmers take decisions on

what they should sow and when they should harvest to optimize the price realization from their

efforts. Weather information coupled with price of agri-commodities will help farmers make more

informed and better decisions.

3.3.2. Seeds

Farmers need information on the alternatives they have in the choice of seeds for the crops they

plan to grow. The usage of right seeds goes a long way in increasing farm yields and growing the

right quality that can fetch higher prices. Farmers are often not aware of the full range of seeds

available and the developments that have occurred in high yielding seeds.

The companies from the seed industry can run voice-sites giving information as to what seed is

relevant depending on the crop and the type of soil. In the process the seed company can promote

their sales.

3.3.3. Pesticide

Attack of crops by pests can completely ruin a farmer. At the first signs of a pest attack, farmers

need immediate information about the appropriate pesticide to use to nip things in the bud.

Preventive pesticide usage is, unfortunately, often not possible because of the poverty these farmers

at the BoP live in.

The companies from the pesticide industry can run voice-sites giving information as to what

pesticide is relevant to which crop disease. In the process the pesticide company can promote their

sales.

3.3.4. Fertilizer

Farmers need information on crop specific fertilizer usage to optimize yields. Overuse of fertilizers

is a waste of money as well at times toxic for the next crop that may be sown in the same field as

different crops require different types of fertilizers.

The companies from the fertilizer industry can run voice-sites giving information as to what

fertilizer is relevant depending on the crop and the type of soil. In the process the fertilizer company

can promote their sales.

3.3.5. Agricultural equipment

With the advantages of mechanization becoming obvious to farmers, they need information on what

agricultural equipment is relevant in different phases of a crop life cycle. Since they cannot afford

to buy and own these equipments, they have to resort to renting them. For this, in addition to

knowing which equipment to use, they also need to know fair rental rates.

The companies from the agricultural equipment rental industry can run voice-sites giving

information as to what agricultural equipment is relevant depending on the phase of the crop life

cycle and also provide current rental rates. In the process these companies can promote their rental

business.

.

Figure 3: Business Models for Agricultural Information Services

4. Discussion

The language technology companies in Finland are not Spoken Web application developers as such,

but exploratory research suggest that language technology companies that are also Spoken Web

application developers do not exist anywhere at the moment. For these language technology

companies it is necessary to work with local talent when developing solutions for a new language.

Further, the procedure of employing or outsourcing needed software engineers in the development

stage of a new product or feature is common in this business. This means that if a company has a

deep understanding about the use of natural language in software, building a component for the

Spoken Web ecosystem, whether it is a technical feature, a new language or a full-blown

application like a voice site, is a matter of coordination for the most part. This is of course assuming

that the resources are adequate and a clear business case exists.

A key challenge is going to be in the multiple language requirements to service the Indian rural BoP

segment. It may not be possible to have all local dialect but at least the official languages of each

major state will be necessary to cover a significant portion of the market. The mother content would

preferably be in text form in any one language with machine language translation at the text level

and then voice synthesis from text to voice in the different languages being critical success factors

for the successful delivery of agricultural information services.

5. Conclusions

A distinct opportunity exists for delivering agricultural information services to farmers in rural

India’s BoP. These services have to be voice-based as the consumers can neither read nor write. In

addition, they also have to be delivered for free as the rural BoP consumer cannot afford to pay for

it. Since the consumers have mobile phones, these voice-based services can be delivered through

mobile phones. The Spoken Web technology developed by IBM Research Labs in India supports

voice sites through which a user can navigate using voice commands. The success of Nokia has

resulted in the establishment of language technology companies in Finland that have developed

expertise in machine translation and voice synthesis that are important for scaling up voice content

across multiple languages spoken in India. A vibrant ecosystem to deliver agricultural information

services to rural India’s BoP will require IBM India’s Spoken Web platform, language technology

companies in Finland, and companies in India who will deliver the agricultural information services

to the rural BoP consumer. A critical success factor for the viability of this ecosystem will be the

ability of the Indian companies to deliver services without charging anything for it but instead

developing innovative business models that can generate sustainable profits through commerce of

associated products that have demand in the rural BoP market segment.

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