The seven use cases prioritized in Kenya’s Digital Agriculture Strategy

A small scale farmer’s field with Maize and darkening clouds in Lower Eastern Kenya / credits: John Kieti

A report titled Digitization and Coordination of Kenya’s Agricultural Sector Data was completed in July 2019. It is a guide for implementing the data and innovation flagship number 8 of the country’s Agricultural Sector Transformation and Growth Strategy (ASTGS). I got my hands on a copy which was recently publicly available on the Kilimo Open Data portal (download full report (7.9mb pdf)). In this article, I refer to the report as a digital agriculture strategy for Kenya’s Ministry of Agriculture, Livestock, Fisheries and Irrigation (MoALFI).  It is the closest I see to Kenya’s national strategy for harnessing the transformative power of digitalizing agriculture. The report, authored by global consulting giant McKinsey and funded by AGRA on behalf of MoALFI prioritizes seven (7) use cases to be implemented. It is a four year plan covering the fiscal year 2019/20 to 2022/23. I find no in-depth coverage of the seven prioritized use cases, so I feel it’s “better late than never” to write about them, especially considering typical delays in Government strategy implementation. In this post I provide my nuanced summary of what I see as the rationale, and design of the use cases. This is more so as the use cases (at least the second one) typify instances of what my earlier published research conceptualised as an aggregator platform for digital services in agriculture.

Use case 1: Improving farmer inputs subsidization

This use case is designed to improve input subsidization programs supported by the Government and other funders. The problems to be solved under this use case are that government subsidised inputs are not necessarily aligned to soil health management principles, and the unintended creation of a dual-pricing system aggravated through diversion of subsidized inputs by cartels. Other problems to be solved across the stages of the existing subsidy system include rent-seeking behavior hurting farmers, and fertilizer delivery being delayed. The key problem solving elements of this use case are, (a) A digital farmer registry managed by MoALF, (b) eVouchers sent by the national treasury directly to farmers, and (c) Payments to registered agro-dealers being made in a timely fashion while securing traceability of inputs to fight counterfeiting. The spending decision on the eVoucher is to be made by the farmer and is to be guided by the farmer’s uptake of registered agronomic advisors. Funding for the e-incentives is expected to come from a “basket fund”, pooling GoK and development partner finances, and with checks and balances for any release of funds. This use case aims to impact 1.4 million farming households and 2,300 agro-dealers by 2023. Its implementation is estimated to cost KES 1.2 Billion (Approximately USD 11 Million) by 2023. The digital platform implementing this use case is to be hosted by the Kenya Agricultural & Livestock Research Organization (KALRO). The prospects of this use case can be enhanced by harmonizing efforts with concurrent input subsidization programs such as those at the 47 counties and by national programs such as KCEP-CRAL

Use case 2: Improving farming practices through customised e-extension

This use case is designed to improve practices among farmers to enhance their productivity through enhanced agronomic advisory services. This is more so considering a grower-to-extension-officer ratio as poor as 1:5,000 whereas the FAO recommended ratio is 1:600. Data analytics on weather, pest and disease trends, production yields and pricing are envisaged to help amplify improvements in farming practices. The use case envisages farmers accessing expanded resources on farming practices through extension service providers vetted by KALRO. These extension service providers are in turn expected to tap into a searchable portal of digital agriculture solutions to support their consultations with farmers. The extension service providers may include the traditional extension officers, village-based advisors, private sector field officers, model farmers and members of the 4-H foundation. Under this use case, the consent of growers is required for a digital agriculture service to incorporate a grower to its userbase through the government-run digital platform. Growers and other users of the digital platform can be expected to rate and review the constituent digital services. This can boost platform-wide efficiency according to the research on sources of value creation in such digital platforms. Under this use case, the platform reserves the right to remove digital agriculture services whose ratings remain low in what could contribute to loyalty-centredness as a source of value creation. The extension service providers are also to be paid an incentive to log details of their consultations with farmers in the digital platform. This is so as to help generate rich new insights for KALRO and MoALFI. Such details logged may include geolocation, type of digital service used and type of problem solved. This use case targets the registration of 2,300 extension service providers by 2023. It also targets 500,000 farmers per year accessing services to improve their farming practices. The estimated annual cost of this use case is KES 50 million (USD 460 million).

Use case 3: A food balance sheet monitoring national emergency reserves

This use case aims to maintain a reliably robust Food Balance Sheet (FBS) to help MoALFI and the Strategic Food Reserve Trust Fund (SFRTF). This is so as to reduce food shortages during emergencies. The use case is about digital inventory monitoring of national food reserves with accurate and real time data. It includes the use of satellite imagery to gather production data and to predict future stock needs. It also includes gathering intelligence from customs declarations and other trade records as proxy signals for fraudulent or anomalous market trends. Other features of this use case include gathering intelligence from consumption data and projecting future consumption patterns. With a robus FBS, the government agencies will be expected to make informed decisions that will also reduce the cost of procuring stocks under duress. This use case targets reducing volatility in stocks purchased for the SFRTF by 50%. It also targets boosted food resistance among close to 4 million high risk households during emergencies. The annual cost of this use case is estimated at KES 200 million (USD 1.84 million) by year three of the plan.

Use case 4: Early Warning System (EWS) for food price inflation 

This use case seeks to facilitate dynamic trade and price stability decisions using an Early Warning System (EWS) for food price inflation. The problems solved through this use case include the unreliably varying levels of accuracy and frequency of data collection on production which is manually done by enumerators and with limited validation. This use case integrates data with early warning elements to indicate likely changes in the prices of food commodities. Data on production, soil quality, pest and disease trends is expected to have early warning components. So is data on commodity trade from sources such as the Regional Agriculture Trade Intelligence Network (RATIN). The resulting early warning system is expected to be a single-source of information to forecast food price inflation. With such reliable information, MoALFI, the SFRTF and Cabinet can be expected to make timely, cost effective and targeted interventions with minimal distortion to market mechanisms. This use case targets to reduce volatility in food prices by 50% to match regional averages by 2023. The estimated annual cost of maintaining the system for this use case is KES 8 million by year 3 of the plan. I’d argue for additional consideration in this use case to incorporate market data from proven private sector driven price stabilization platforms such as Twiga Foods in the fruits and fresh vegetables space. This is especially with the demonstrated potential to use big data to power inclusive food markets. 

Use case 5: Optimal agricultural value chain selection 

This use case envisages selection and prioritization of focus value chains (crops, livestock, fishing etc) based on land use optimization models. The existing processes for selecting focus value chains by national and county level organs are faulted for having contradictory objectives and not being adequately evidence driven. Data to be fed into the optimization models may include aspects such as soil health and economic data including export markets. The land optimization models  may be tuned with parameters such as environment protection and yield optimization. Integrating the large datasets onto a single platform facilitating modeling under this use case anticipates support from enabling policies for data sharing, security and privacy potentially addressed under use case 7. This use case on value chain selection targets doubling the yields among small-scale farmers by 2023. It also targets boosting household food resilience for 1.3 million farming, pastoralist, and fishing households during drought in arid and semi-arid regions of Kenya. The use case estimates an annual cost of KES 120 million (USD 1.1 million) by year three of the plan’s implementation. It is notable that the implementation of this use case is envisaged to be county-based, allowing more local-level prioritizations that are more likely to resonate with growers on the ground. Grower-level solutions for value chain selection such as Waterwatch, CropIn are also acknowledged in  the plan and are considered complementary to the national and county level prioritizations. This begs the question of whether value chain selection should not be considered a grower-level decision made with the support of agronomic advisory under use case #2.

Growers often prioritise for themselves multiple value chains / photo credits: John Kieti

Use Case 6: M&E dashboard for data collection, verification and visualization

This use case is expected to streamline the data collection, verification and visualization of the outcomes targeted in use cases 1-5 (above). It builds on the observation that there are more than 10 visualization efforts capturing Kenya’s agricultural sector data from 200+ data sets. Some of these efforts are observed to be inactive or outdated, ostensibly due to their scope-related cost constraints. Examples of such visualization efforts include the upcoming KCSAP big data platform funded by the World Bank, the National Crop bulleting, the AfDB’s Africa Information highway, and the defunct Kenya National Bureau of Statistics visualization portal. For simplicity, the focus of the dashboard in this use case is limited to approximately 10 KPIs considered most relevant to the senior leadership at MoALFI. Upon success with the simplified, focused dashboard, the cascading of the same is envisaged within MoALFI and among the 47 counties. More granular project tracking tools are then expected to emerge, automating the build-up of insights for the macro-level dashboard. The estimated annual cost of this module is KES 20 million (USD 184,000)

Use case 7: Standards and protocols for a national data sharing platform

This use case seeks to establish standards and protocols for a national shared-access platform for agriculture data. The idea is to start with data handled by GoK and to progressively incorporate data handled by private sector players. Under this use case, platform users are expected to build on the high volume, highly interoperable data to create new insights for their interventions in agriculture. The problem to be solved by this use case is typified by the existence of multiple siloed farmer registries profiling more than two million farmers. These registries include those maintained by MOA-Info, Digifarm and OneAcre Fund. Under this use case, The Zambia Agriculture Management Information System – ZIAMIS, a FAO supported platform, is indicated as a candidate for adapting and scaling out in Kenya. The estimated annual cost of this use case is KES 20 million which is indicated as already funded by the World Bank under the Kenya Climate Smart Agriculture Project (KCSAP).

Caveat: Government prioritized value chains and intervention areas

It is worth noting the intentional prioritization of digital interventions that the government is well placed to champion and implement among the seven use cases. As such, digital agriculture services deemed best implemented by the private sector and players other than Government agencies were not prioritized in the strategy. For instance, my favourite topics of overall market efficiency and demand driven production did not feature among the digital agriculture use cases. This is ostensibly because such issues are arguably best addressed by the private sector and are arguably related to market linkage concerns being addressed in the warehouse receipt system law enacted in 2019. Furthermore, the use cases have inherent prioritization of selected value chains, especially the grains sub sector including beans, maize, rice, wheat. In any case, I encourage readers keen on the full context and finer details about the planned implementation of these use cases to read the full report. Moreover, the full report has additional insights about implications for data ecosystem requirements in the use cases that should be of interest to the digital agriculture ecosystem actors, especially the providers of digital services.

Appreciation: For this post, I am grateful to Nixon Gecheo, AGRA’s Senior Program Officer for Digital Systems and Solutions for Agriculture. He brought this report to my attention, I have been otherwise clueless.

Loyalty-centredness in digital platforms – What really is that?

My co-authors and I have proposed a two-factor structure to explain the underlying structure of the sources of value creation in an aggregator platform for digital services in agriculture (AP4DSA). This is in a recently published research paper in the Digital Business Journal. We termed the two concepts represented in the two-factor structure as platform-wide efficiency and loyalty centredness. I wrote a brief summary of the issues in the research here. It’s has been some weeks since the publication was out. As I further explore the prospects of AP4DSAs, I ask myself – what really does loyalty centredness mean? In the paper’s discussion section, we attempted to explain the concept in line with where our evidence pointed us. I am obliged to look further into the term and to perhaps solicit more insights from all you fellow thinkers and readers.

Loyalty centredness according to the research is an attribute arising in the viewpoint of likely digital platform users, meshing together the ideas of loyalty and innovativeness. It evokes the notion of altruism and engagement with a digital platform according to the paper. This is as the users or stakeholders feel an increased sense of ownership and affiliation to the platform. The research paper further relates loyalty-centredness with an accountability arrangement among participating actors to generate win-win scenarios for both providers and consumers of services on a platform. According to the paper, the concept suggests the need for a platform to safeguard its ecosystem-wide integrity whereby, “genuineness and legitimacy of actors as well as the information, goods and services accessed through the platform can be guaranteed”. You may read further on these and other explanations of the concept in the research paper which is freely downloadable under a creative commons licence on the link below.

sciencedirect.com/science/article/pii/S2666954421000065

To further illuminate the concept beyond the inherent space limitations of a published scientific article, I have hived off the loyalty-centreness half from the two-factor structure in the figure below :-

Loyalty centredness as a source of value creation in an AP4DSA (adapted from Kieti et al. 2021)

In the diagram, the rectangular boxes illustrate the indicators measured to have strong influences on the loyalty centredness concept. For instance, creating and moderating a virtual community – L4 for users to interact on such a digital platform is influential in value creation as an indicator of loyalty centredness. Likewise, introducing new to the world products, services or information – N1 on the digital platform can strongly influence loyalty centredness as a source of value creation. As such, an increase in any of the 10 indicators results in an increase in loyalty centredness as a collective notion and a source of value creation in the platform.

Essentially, we used the term Loyalty centredness to represent a collective of the 10 indicators in the rectangular boxes. The notion captured in these 10 indicators is certainly not about user-human centred design as might be tempting to broaden out to. It is also more distinct than the wider concept of user centricity. The indicators in yellow(ish) boxes were initially from the concept of loyalty while the items in pink(ish) boxes were from the concept of innovativeness. In the research, the two indicators with the highest influence on loyalty centredness were from the loyalty concept. These most influential indicators were, (a) guarantees for reliability and quality – L6 and (b) upholding trust – L2 which includes ensuring data protection, safety and security guidelines are adhered to. For more on these influences and their strengths, see their factor loadings in Figure 4 of the published paper. These stronger influences and the higher number of indicators from loyalty than innovativeness informed our conceptualization of the collective notion as loyalty centredness.

In the published paper, we argued that, “a new innovation may be onboarded and showcased on a platform yet not be ready to exhibit the kind of reliability and quality guarantees expected by the loyal platform users“. Among the Kenyan participants, it would be that aspects of innovativeness foster the sense of loyalty and pride in affiliating with the platform. Arguably, the indicators from innovativeness might have proved to be more impactful on the resulting collective concept if the research was conducted in a country where the history of innovations in digital agriculture was not as long as Kenya’s. Likely users in those countries may as well have rated the innovativeness indicators more highly, being more easily impressed by such nascent efforts. As such, it may be that innovativeness aspects can be more impactful than the loyalty aspects in those countries.

I am thinking that loyalty-centredness might have acquired a slightly different name if the research was conducted in a country where the excitement and buzz about digital innovations for agriculture are still fresh. This thinking may be worth validation with further investigation among likely AP4DSA users in other sub-Saharan African countries. It may also be argued that in due course, such sub-Saharan African countries would still evolve their digital agriculture ecosystems to the slightly more advanced situation in Kenya. Therefore they would still have to face the concept of loyalty-centredness as a source of value creation in an AP4DSA as their ecosystems evolve.

I am curious to hear what others interested in the value creation mechanisms of digital platforms think about this notion of loyalty centredness.

How could value be created in a one-stop-shop platform aggregating digital solutions for agriculture?

Reports by GSMA, CTA, and Disrupt Africa consistently position Kenya as a global leader in the number of tech ventures and digital solutions for agriculture (DSAs). By GSMA’s 2020 report which tracked 713 active DSAs, 437 (61%) were in sub-Saharan Africa. In the report focusing on low and middle income countries, Kenya led with 95 instances and Nigeria was second with about half of Kenya’s number. The trends suggest fragmentation in digital agriculture ecosystems among other pitfalls. Studies have questioned the ability of these DSAs to scale out so as to significantly impact a sector that is the mainstay of most sub-Saharan African economies (including Kenya).

My co-authors and I sought to diversify the thinking about efforts to unlock the promise of digitalization and digital transformation of agriculture in sub-Saharan Africa as a contribution to literature. We conceptualized an aggregator platform for digital services in agriculture (AP4DSA). This is a special type of digital platform for agriculture whose characteristics can partially be observed in nascent platforms such as Safaricom’s DigiFarm, EcoFarmer in Zimbabwe, Bayer’s Climate FieldView, and an “imaginary instance of Google play store for agriculture”. Such a platform can be expected to address DSA discoverability challenges including fragmentation of the digital agriculture ecosystem, absence of a one-stop-shop, and an unmet desire for comprehensiveness. My co-authors were Prof. Timothy Waema, Prof. Bitange Ndemo, Dr. Tonny Omwansa and Dr. Heike Baumüller

We proceeded to examine the underlying structure of value creation sources in such a digital platform as perceived by likely users in Kenya. Our findings suggest that sources of value creations can be explained in three themes, namely (a) platform-wide efficiency (b) loyalty-centredness (c) platform inclusivity. We have recently published the findings in the peer-reviewed Digital Business Journal via Elsevier. Click on the link or graphical abstract below to access the full article. 

sciencedirect.com/science/article/pii/S2666954421000065 

Sources of value creation in an aggregator platform for digital services in agriculture – source: Kieti et al. (2021)

The article is readable online and can also be downloaded freely as a pdf on the basis of the creative commons (CCBY4.0) license. Our findings should be of interest to practitioners such as tech entrepreneurs, accelerator program managers, and large tech corporations endeavouring to actualize the digital transformation of agriculture. Policymakers seeking to unlock the transformative power of digital platforms for agriculture through may also find our findings useful. I look forward to feedback on our findings that could further inform my ongoing research on the prospects of AP4DSAs in sub-Saharan Africa.

The Top 10 agricuture Facebook groups in Kenya

There is serious agriculture going on in Facebook. At least among Kenyan farmers, there is those that have found Facebook as the place to research and gather knowledge for application in their agricultural related ventures. Others are finding prices of inputs and produce on Facebook groups. Can one be practicing agriculture on Facebook? I think research and access to relevant knowledge for application in one’s agricultural venture is part and parcel of the venture’s activities; hence there can be agricultural practice on Facebook. I think this is one aspect of information technology driven innovation that Agriculture is facing in emerging economies. As I once wrote earlier last year, these innovations may just matter.
Here is my list of the top 10 Facebook Groups covering agricultural interests that involve Kenyans by membership size.


Rank
Facebook Group Name
Size of membership
(March 13th,  2015)
1
34,360
2
20,719
3
14,466
4
8,308
5
7,676
6
5,373
7
3,951
8
3,730
19
2,239
10
2,018


In the list we see an apparent trend of groups forming around a particular agricultural sub-sector such as poultry, dairy, rabbit and pig production. Incidentally, majority of the groups in the list also seem to have a specific livestock focus. This could be resulting from my interest bias or there could be something about the livestock sector that renders itself better to this online phenomenon than crop cultivation.


Joseph Macharia – Founder of Mkulima Young
Omission of Mkulima Young in the list above is deliberate. Their Facebook page has seen phenomenal growth in the last two years. I note it separately as an organizational page rather than an interest group. Also very noteworthy is Mkulima Young’s advancement towards creating their own web platform for not only knowledge exchange on agricultural practice but also a agricultural commodities market place. They also have an active twitter and youtube channel. It appears to be run as an outright business rather than a special interest group. Apart from Mfarm\’s and Shamba Shape up\’s, I have not come across comparable pages built around existing Kenya focused farming and agriculture related enterprises with “page likes” above five thousand. Mkulima young has forty one thousand “page likes” as at mid March 2015.


The Farming Kenya group appears to follow Mkulima young’s path of creating their own independent website. Their website is http://farmingkenya.org where only signed up

FarmingKenya.Org Logo

members are allowed to contribute content. Guests are allowed to view content. The website has sections for questions and answers, forums, blogs and photo sharing. Membership in this website requires a special signup process independent of Facebook’s.


Agriculture focused Facebook groups, pages and related websites seem to have a promise for providing the youth with a platform for exchanging best practices in agriculture. They also appear to be an increasingly popular mechanism for market price discovery as regards agricultural inputs and produce. It will be interesting to see how the landscape unravels as agriculture becomes a more youthful economic activity while the youth have greater access to the internet and internet enabled phones.
Since the above list of top agriculture Facebook groups is my first version, I may have omitted an important one with significant membership. I welcome suggestions for additional entries in the list.

mAgric Innovations – Do they matter anyway?


Over the last decade, contribution of Kenya’s agriculture sector to the nation’s Gross Domestic Product (GDP) has been below 30% but above 25%. Across East African countries, contribution of Agriculture has been similar to that of Kenya or declining altogether. The chart below shows the trend since 2001 in Kenya, Tanzania, Rwanda and Uganda.

Contribution of Agriculture to national GDP remains significant but sub-optimal

Weight of the matters

Perhaps there’s no need to worry about this trend if it can be seen as a deliberate outcome of economic diversification strategies among individual countries. However agriculture continues to be the mainstay of most East African economies. Agriculture accounts for 61% of total employment in Kenya for instance. Contribution to national employment statistics by agriculture seems even higher among other East African countries as indicated in the chart below.


Agriculture contributes to the majority of employment opportunities


With such significance of Agriculture in employment creation, a question of proportions begs. That is the question of why the many jobs attributable to agriculture do not result in a commensurate contribution to national GDP growth by the sector in East Africa.

Necessary Mind Shift?

Everyone is capable of a radical mind shift at some point in their short lives. Health IT, eHealth and mHealth have been my favorite ICT4D areas for over half a decade. In 2013, I found myself shifting interests away from health towards agriculture. For avoidance of doubt, health is a great field to achieve results at a personal level, institutional level or otherwise. I wrote much about eHealth or related topic here in the “yester-years“.

In East Africa, the health sector has employed many brilliant minds especially in NGOs and government – from health care workers to health systems practitioners. Opportunities for innovation, entrepreneurship and even job careers in health continue to knock at doors of the region’s talented workforce. However this article in the East African based on a report titled  “Investments to End Poverty” by Development Initiative’s (DI) does much to present an alternative view which is validating my shifting focus.

According to DI’s report, “East Africa received nearly $9 billion of aid in 2011, with the biggest chunk channeled to the health sector“.  This according to the report is disproportionate to the real needs expressed by people in developing countries. The report suggests, “On the other hand, there are few political champions for those issues that top the list of citizens’ priorities in sub-Saharan Africa or Latin America, such as jobs/income, security or infrastructure.” Furthermore, a World Bank Development Report in 2008 indicated that among developing countries, 1 percent GDP growth originating in agriculture potentially reduces poverty by at least 2.5 times as much as the same GDP growth originating in the rest of the economy. 

An all season water mass in a Kenyan rural under-utilized for Agriculture

Job creation and income generation for poverty eradication are the reasons I am betting big on mobiles for agriculture (mAgric) in 2014. It could be either mAgri or mAgric am referring to, or both. To me they both refer to the application of mobile technologies to help increase efficiency and productivity in agricultural value chains.There is the mAgri program of the GSM Association (GSMA) that makes generic use of the term mAgri difficult. To avoid confusing the GSMA program and the emerging discipline around mobiles for agriculture, I shall stick to mAgric as my reference abbreviation. 

Needless to say, mobile phones have become ubiquitous computers and communication devices in most developing countries. Mobile technology therefore appears top on the list before any other technology for fostering development in East Africa. This is already demonstrated in the area of financial inclusion. I have had my own observations, rants and raves on this in previous articles here. Ostensibly then, not much effort should be spent explaining the narrowing act of embracing mobile technology in development and not all information and communication technology in general. 

Agriculture is complex; Why mAgric anyway?

It should not be easy to convince everyone that advancements in mAgric innovation will single handedly solve the matter of sub-optimal productivity in East Africa’s agricultural sector. I shall argue though, that innovations and entrepreneurship in mAgric can play a big role in revitalizing and optimizing activities in agricultural value chains.


In his book “The New Harvest – Agricultural Innovation in Africa”, Calestous Juma, a renown professor of innovation and sustainable development argues that “Agriculture needs to be viewed as a knowledge-based entrepreneurial activity”. It is access to information and transactional efficiencies for value chain actors possible through mobile applications that I would bet on in mAgric. Such applications are bound to enhance the knowledge-based entrepreneurial activities that Prof. Juma refers to. 

growing array of mAgric innovations by local entrepreneurs

 Arguably, for developing nations serious about uplifting agricultural productivity, the role of mAgric in revitalizing agricultural practice is big. This is validated by the notion that for national economies to grow sustainably, deliberate premium has to be placed on a learning culture and improved problem solving skills in the productive population. These can be fostered through promotion and use of appropriate mobile applications in the case of agriculture.

Is mAgric stalling?

Many mAgric applications including Mfarm, iCow, eSoko, and M-shamba have been introduced to East Africa\’s agriculture actors over the last three years. Although it would seem obvious that uptake of such innovations will be rapid in East Africa, that has not been the case. m:lab East Africa has since 2012 organized a series of focus group discussions dubbed \”Wireless Wednesday\” that have highlighted issues bedeviling mAgric and the opportunities in the region. A recap of one such meet-up held in October 2013 highlights many issues including awareness and ease of use. Observations made in April 2012, are similar to those made in the more recent meet-ups and this beg the question of whether progress is being made. 

A video clip taken of Qureish Noordin (pardon the quality) from AGRA elaborating concerns from enablers\’ perspective below may help to demonstrate the complexity of issues affecting uptake of mAgric innovations in East Africa.




More efforts continue to be made to attract more innovations in the ICT for agriculture (ICT4ag)space. This is exemplified in CTA\’s ICT4ag competition in 2013 among other similarly themed contests targeting innovators in developing nations. The emerging concern among actors and enablers in the mAgric space is therefore whether any of the new or existing innovations can amass significant uptake for meaningful impact in the agricultural sector to be realized while achieving sustainability. 

Adjusted blogging interest ..

2013 had its own highlights and disappointments. One major highlight for me was a win against procrastination, whereby I got to register for long overdue doctoral studies. It is the apparent slow uptake, and sustainability challenges of mAgric applications that I shall be investigating in my PhD thesis throughout 2013 and beyond. That may explain the increased analysis and \”opinionation\” about mAgric applications, and the promise for agricultural prosperity throughout East Africa in this blog as 2013 comes along.

For now I shall leave you with another video clip (pardon the quality) taken of Safaricom\’s Peter Gichangi sharing his thoughts with developers at a Wireless Wednesday meet-up addressing the challenges for uptake of mAgric applications.