Voices of the Silicon Savannah: Key challenges facing Kenya's social-tech ecosystem - views from within

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DOI: 10.13140/RG.2.2.28977.63842/1
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Abstract
The social-tech ecosystem in Kenya (often referred to as the ‘Silicon Savannah’) appears to be one of the world’s most thriving tech sectors. Views from inside, however, suggest it is not making the impact it could; is not as financially successful or sustainable as people had hoped; and may be stagnating and in need of nurture. Voices of the Silicon Savannah examines why this is so and what can be done to improve matters.
Key challenges facing Kenya’s social-tech
ecosystem - views from within
MATT HAIKIN
www.matthaikin.com
October 2018
VOICES
SILICON
SAVANNAH
OF THE
©Alextom2k
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Preface
I lived in Nairobi, Kenya briey in 2016 and immersed myself, as far as I was able, in the community of those using ICT
and digital technologies to try to improve the situation of poor and marginalised communities and individuals.
I enjoyed my time there, so when I found myself between consultancy roles and debating whether to set up something
on the ground, it was the obvious place to which to return.
Themes in my earlier research had included: identifying a trend towards funding going directly to organisations based
in the global South; widespread views that NGOs could work better and more supportively with their Southern partners;
NGOs and local tech rms typically not working well together; and many actors (from all sectors) not having embraced
what is already known about success/failure factors in social-tech work. This is where I started – exploring whether there
was a useful role I could play or an organisation I could establish within this ecosystem.
As I organised my trip, my plans evolved. The initial focus was on how NGOs and donors can be encouraged to spend
more of their budgets supporting local technology organisations. Realising that this was a very aid-focused perspective,
I decided to broaden my lens. While NGOs and donors are important players in the social-tech space in Kenya, they are
just one set of actors amid many.
Over time, and with a transition into a new job,1 my plans had to evolve away from direct involvement and moved from
a customer-discovery to a research focus, and the title Voices of the Silicon Savannah began to emerge.
I am suciently aware of the controversy over the references I am drawing on for this title – the World Bank’s ‘Voices
of the Poor’ and the widely abused term ‘Silicon Savannah’ – to be faintly embarrassed by the choice of title (a good
example of why can be found in this entertaining article on the iHub website). But I hope that by making the voices of
the Kenyans that I interviewed the central focus of the work, I have avoided falling into the trap of being yet another
Mzungu who thinks they understand Africa.
So, I have kept the Silicon Savannah title because, despite these issues, I like it!
1 As Manager, Insights and Impact at the Digital Impact Alliance (DIAL), digitalimpactalliance.org
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Executive summary
This report delves into the social-tech ecosystem2 in Kenya, often referred to as the ‘Silicon Savannah’. Peering in from
outside, Nairobi’s social-tech sector seems like one of the world’s most thriving tech sectors. Views from inside, however,
suggest it is not making the impact it could; is not as nancially successful or sustainable as people had hoped; and may
be stagnating and in need of nurture.
Voices of the Silicon Savannah examines why this is so and what can be done to improve matters. It draws on 40+ insider
perspectives from interviews conducted in early 2018 with people active in Kenya’s social-tech ecosystem — techies, hubs,
NGOs, donors etc. I have chosen to foreground their voices, basing my personal reections and recommendations primarily
on their observations, supplemented by additional research where appropriate.
The report begins with reections on each of the key groups in Kenya’s social-tech ecosystem — digital entrepreneurs,
NGOs and aid implementers, funders, donors and investors — as well as the ‘conspicuous absentees’: universities, the
government and big mobile network operators like Safaricom. It also casts its eye beyond Nairobi to the wider social-tech
community in Kenya.
A key nding is that the narrative of ‘success often focuses on the ‘successful Mzungu founder’3, who receives more
investment, has better networks and resources and can aord to take greater risks. This ignores the many local Kenyan
successes, and the fact that many perceived ‘failures contain valuable lessons, data and signals about market demands
and customer needs.
Similarly, the funding landscape, dominated by overseas funders, donors and private investors, skews how aid implementers
and entrepreneurs frame their projects, and distorts their incentives. Too much emphasis on numbers-based reporting to
donors, and high-risk, easily scalable products for investment creates a gap in funding for local entrepreneurs, experimenta-
tion, building local capacity and exploring local markets and needs — i.e. nding out what really works. It also reduces the
potential for creative and equal collaborations between NGOs and local entrepreneurs, a relationship that is more commonly
that of client and supplier.
There is a clear opening in this landscape for local investors and intermediaries such as tech hubs, who understand the
local context. While change is slowly taking place and social-tech projects with alternative models are evolving around
the country, the ecosystem requires new forms of leadership and collaboration between dierent groups.
The report also reects on major cross-cutting themes emerging from the interviews that resonated with my own and
others’ research, such as the skills gap spanning the social tech ecosystem — including modern project management
techniques, iterative product development and engagement with end users.
Tech hubs could perform a vital intermediation, incubation and acceleration role but, driven by the need for nancial
security and the needs of overseas investors rather than their local users. However, some do not attract serious entrepre-
neurs, some intimidate those from less auent backgrounds (excluding the very people that most social-tech programs
aim to serve) and many are responding to the challenge of sustainability by evolving in to co-working spaces with a
signicantly smaller community or convening role.
Finally, the majority of money being spent on tech or social tech in Kenya, is — directly or indirectly — going to overseas,
not Kenyan, companies. Given the pervasiveness of digital technology, this spend could have a huge impact on the local
social-tech sector and economy. However, purchasers tend to favour the convenience and eciency savings oered by
large, multinational contractors over buying from local organisations, who are often excluded by the scale of bids and
procurement requirements.
2 For the purposes of this document, ‘social tech’ is used to mean any use of technology for social good (incorporating terms such as
ICT4D, Tech4Dev and digital development). The term ‘ecosystem is used to encompass the major actors in this space as well as the
norms and dynamics they operate by and inuence.
3 Mzungu is typically used to refer to foreigners, usually but not exclusively well-o white foreigners.
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Executive summary: Recommendations
Section 4 of the report makes six broad recommendations to address the issues raised:
1. There is a need to develop a new narrative of Kenyan success stories
Whether or not overseas/Mzungu entrepreneurs are more successful at attracting investment, there is a need to
showcase and champion Kenyan success stories through successful role models; to promote modest-growth, low-risk
enterprises, and to embrace dierent kinds of ‘failure’ to destigmatise ideas for experimenting and adapting.
2. NGOs need to get better at partnering for ‘development in a digital age’
To better incorporate digital technology in their work, NGOs need to shift their focus from procurement to partnering.
This means working with local tech/social-tech rms on an equal basis to co-create solutions rather than seeing them
as suppliers of goods. This partnership and mutual exchange of skills and knowledge could in turn help them develop
the internal, hybrid expertise they need to bring together technology and the contexts in which they operate.
3. Tech hubs need to intervene and help the social-tech system full its potential
This can be done if tech hubs are able to nd a commercially sustainable business model that makes them less
dependent on external funding and investment; or if the intermediation and training roles that hubs provide are seen
by funders as a public service that requires ongoing funding, which may in turn inuence government to take on the
role of nancing this sector; or if new entrants enter the space and experiment with new business models matching
training with the needs of the market.
4. New ideas are needed to bridge the skills gap and change behaviour
For example: ‘halfway-house’ projects and training that nd ways for people or organisations with good technology
skills to engage with local or international projects; real-world learning provided by mentors from various sectors,
bringing together international experts in ‘what works when implementing digital technology in a development con-
text’ and newer entrants into the space in the Global South. Finally, social-tech skills could be grown beyond Nairobi
through a hub-and-spokes model, like that used by ICT4D Kenya, to train promising ‘social-tech champions in local
projects, community groups and NGOs in other towns and counties, who then continue to disseminate good practic-
es within their wider communities.
5. We need to encourage and enable purchasers to do more
The Kenyan government, aid funders and NGOs combined are a signicant source of demand in the social-tech space. To
persuade them to do more to support Kenyan organisations will require advocacy for new approaches to procurement,
such as breaking it down into smaller chunks to enable smaller and more local rms to bid and compete more fairly;
funding the development of local capacity rather than just going elsewhere; developing better local relationships, e.g.
through a revived tech-hub community, and supporting and funding the local ecosystem.
6. New approaches are required to the gaps in funding and investment
Understandings dier of the funding that is needed vs. what is available, but there is some consensus that more
funding should be specically designed for very early-stage ‘customer discovery’ and for testing the market/ business
models; there should be more investment in slow/modest-growth businesses, and more funding that supports
adaptive, user-centric and locally-driven approaches.
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Executive summary: Next steps
While Kenya’s social-tech ecosystem has a lot of activity and huge potential, only some this is being realised and there
are structural and systemic factors restricting its growth. I have suggested below a number of areas where I believe the
social-tech community could work together to enable this growth to develop:
1. Better collaboration
The lack of understanding amongst dierent players, limited communication and poor collaboration could be
improved immediately with limited resources — meetups, community events and workshops bringing together
dierent actors would be a good start and would pave the way for stronger community leadership in the long term.
2. Adopting known good practices where feasible
Funding and external pressures limit the degree to which things like adaptive management and human-centred
design can be implemented right now. However, there is no reason why they cannot be adopted as far as is
possible, and with wider discussion and training — adoption will inevitably improve. A good start would be to
ensure everyone in the ecosystem is aware of the support that already exists — e.g. Lean Impact for Social Good,
the Principles for Digital Development and the extensive array of useful social-tech blogs such as ITC Works.
3. Creating a shared voice — for advocacy, lobbying and telling the Kenyan story
Many of the above recommendations involve changes on the part of the bigger actors — government, funders,
investors and international organisations. Coming together to lobby for these changes more coherently increases
the likelihood of people listening and acting.
4. Experimenting to create models that others can adopt and adapt
This involves embracing the spirit of iterative and adaptive approaches, to trial ideas, see what work, and focus eorts
there. More such experiments would generate useful data on where technology can usefully help with some of
Kenya’s social challenges.
5. Further research
Lastly, there are key areas where further, more robust, research would help; for example, on dierent models for tech
hubs and gathering hard data on funding and investment successes/failures.
If any of these suggestions stir you into action, please contact me to discuss how I can support your work. I would enjoy
working with anyone experimenting with new ideas or approaches - helping you to draw out learnings, to adapt and
evolve as you continue to iterate. Please get in touch.
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About the author
Matt Haikin is an Information and Communications Technologies for Development (ICT4D) practitioner, researcher and
evaluator currently working at the Digital Impact Alliance (DIAL) as Manager, Insights and Impact.
He has published research for Oxfam GB — Digital Development: What is the Role for International NGOs? (2017) — and
the World Bank — Evaluating Digital Citizen Engagement: A Practical Guide (2016) and Impact of Online Voting on
Participatory Budgeting in Brazil in T. Peixoto and M.L. Sifry (eds), Civic Tech in the Global South: Assessing Technology
for the Public Good (2017).
He has also conducted research and consultancy work for FHI 360, Chemonics and Practical Action on what it means for
NGOs to do development in a digital age and, at Aptivate, managed the delivery of ICT4D solutions for the Department
for International Development (DFID) and the Government of Nigeria (managing the YouWiN! platform).
He has a Masters degree in ICT for Development from the University of Manchester.
Acknowledgements
I would like to thank all the people who kindly made time to be interviewed during my time in Kenya, and to support me
as the work continued to develop (see Appendix A: Interviewees for full list).
I would also like to thank those who helped review this document and oered insightful suggestions to improve its clarity
and purpose: Melissa Johns, Paul Quirk and Priscilla Lekalkuli from the Digital Impact Alliance (DIAL), Ricci Coughlan from
DFID, Anne Radl from Social Tech Trust and Ellen Pieterse from the Making All Voices Count evaluation team.
Thanks also to Munizha Ahmad-Cooke for reviewing and editing the nal draft and to Samantha DeTulleo for turning my
Word draft into a nicely designed publication. Finally, thanks to Kevin Barasa for motivating me to arrange the trip and
complete the work in the rst place, given the absence of external funding or wider organisational support, and for
helping me to connect with people working in this space in Kenya.
Copyright
This document aims to contribute to public debate and invite feedback on development and technology issues. The
information it contains is correct at the time of publication and the author does not guarantee the accuracy of any data
included in this work. The analysis and recommendations presented here are those of the author.
This publication is subject to copyright but the text may be cited free of charge provided that the source is acknowledged
in full. The copyright holder requests notication of any such use. Permission must be secured for copying in any other
circumstances, re-use in other publications, translation or adaptation.
Email: matt@matthaikin.com.
© Matt Haikin, 2018
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Table of contents
Executive Summary 3
Table of Contents 7
1. Introduction 8
2. Voices from within Kenyas social-tech ecosystem 9
2.1 On digital entrepreneurs 9
2.2 On NGOs and aid implementers 11
2.3 On funders and donors 12
2.4 On private investors 13
2.5 On the tech community 16
2.6 On conspicuous absentees 18
3. Reecting on the challenges 19
3.1 The sector-wide skills gap 19
3.2 The need for better intermediation — a role for hubs 22
3.3 Supply and demand — what role for social-tech purchasers? 24
4. What next? Experiment, learn, adapt and improve 26
4.1 A new narrative of Kenyan success stories 26
4.2 NGOs need to get better at partnering for ‘development in a digital age’ 26
4.3 Is it time for a tech-hub intervention? 27
4.4 We need new ideas to bridge the skills gap and change behaviours 28
4.5 How can we encourage and enable purchasers to do more? 29
4.6 Gaps in funding and investment and the need for new approaches 30
5. Conclusion and next steps 32
Appendix: Interviewees 33
Bibliography 34
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1. Introduction
Context
From 2016–18, I undertook various research projects looking at the impact of and opportunities for ICT4D/digital devel-
opment within the NGO sector — in East Africa for Oxfam, then globally for FHI 360, Chemonics and Practical Action.
I had wanted to dig deeper into this for some time and, in early 2018, found myself with the time and opportunity to do
some self-directed research and speak to people from what many consider the most vibrant and successful’ social-tech
(ICT4D/digital development) scene in the global South — Nairobi, the ‘Silicon Savannah’.
My starting assumption – from earlier research and interviews – was that the current model is not working as well as it
might; is not making the impact it could; and is not as nancially successful or sustainable as people hoped. I sought to
explore people’s thoughts on why? What are the real reasons behind this? What wider structural factors are at play? What can
be done to help?
Methodology
I have long been a champion of user-driven, participatory and agile/lean approaches to development, so I decided it was
important to embrace these in my own work. As a result, this came to be seen less as a piece of ‘research’ and more as a
‘customer-discovery’ phase of a potentially longer project to seek ways to enhance the impact of social tech in the South.
It also led to me seeking out as wide a range of dierent individuals as possible, and trying to clearly articulate their
thoughts and opinions separately from my own interpretation of what I heard.
In early 2018, I interviewed 40 people who are all active in Kenya’s social-tech ecosystem in some way — social entre-
preneurs, tech hubs, NGOs and donors. Apart from a few expats, the majority are native Kenyans and most have been
working in this space for a number of years. Interviewees were selected on the basis of prior relationships or personal
recommendations (‘snowballing’); discussions were open, loosely guided but primarily driven by the interests of the
interviewees, and all the views gathered are personal opinions on the state of the sector, rather than organisational
positions or hard data and facts.
About this document
Section 2 presents reections from or about each of the key groups in the ecosystem. I then go on, in Section 3, to outline
my own interpretation of the key themes emerging from these reections, and conclude, in Section 4, with what I hope are
helpful suggestions for the social-tech community and some of the key players who have inuence over it.
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2. Voices from within Kenya’s social-tech ecosystem
The tech scene in Kenya, and in particular Nairobi (sometimes referred to as the Silicon Savannah), is considered one of the
most vibrant, advanced and successful in Africa, and the innovation and startups within this scene are key drivers of economic
growth and job creation in Kenya (World Bank 2018). However, it is by no means the only such scene and while some of the
opinions in this document are specic to Nairobi, many apply to other places in Africa and the global South in general.
For clarity, I have chosen to use the term ‘social tech’ as shorthand for the myriad of terms that are used to refer to this
overlapping space of technology and those seeking to do good in the world: ICT4D, Tech4Dev, Digital Development, etc.
In parts of this work, the local technology ecosystem is used synonymously with ‘social tech’. This is deliberate — I found,
as have others, that ‘the two were seen as interchangeable by many interviewees’ (Rodrigues et al. 2018: 6).
2.1 On digital entrepreneurs
It is dicult to draw clear boundaries around the technology sector in Kenya. Though it is mostly located in Nairobi,
it is beginning to thrive in other parts of the country and includes a highly diverse range of people: social enterprises
and commercial start-ups; local Kenyans and expats (mostly white North Americans/Europeans, but also other Africans,
Indians and people from other countries and ethnic backgrounds); people working from tech hubs and those working
independently; experienced business people and students fresh out of college.
Despite this diversity, one concern emerged time and again: the story of the ‘successful Mzungu founder’. There is a widely
accepted idea that most of the successful digital/social-tech start-ups in Kenya have been established by overseas —
typically but not exclusively white — founders. A range of reasons are given to explain why this might be so, including a
lack of Kenyan role models, the idea that some younger Kenyan start-ups see entrepreneurialism as a hustle not a serious
decision, cultural factors around attitudes to risk, the lack of contacts and networks, and limited opportunities to gain
relevant education, training or hands-on experience.
As we dig into this perception, a subtler picture begins to appear. While it is certainly true that most investment goes to
expats4, it is less clear that this translates into the accepted story of Mzungu successes, although people certainly see a
range of other factors that could have an inuence here:
n Kenya is a country of young people with a high unemployment rate. This inevitably means that options such as
starting your own business will attract a wider range of people — serious start-ups, hustlers, people who would
rather be in a full-time job, etc. — many of whom lack direct relevant experience or educational resources.
In contrast, the type of North American/European who can aord to move all the way to Kenya to set up their own
business is far more likely to have savings and experience.
n Fewer Kenyans have the resources and support networks to take the risk of not earning money for 12 months while
exploring an idea; even less have a safety net that allows them to experiment, try a few ideas and succeed on their
third or fourth attempt (which is the norm for start-ups in most parts of the world).
n Many Mzungu founders have extensive real-world experience in the sector and bring networks of overseas contacts
with them. This is less often the case with Kenyan founders (perhaps because in Kenya’s economic climate, leaving a
well-paid job to become an entrepreneur is a much higher risk, and thus less likely to happen).
Most interestingly, however, many of those I spoke to disagreed fundamentally with the accepted story, and saw the
dierence as more related to the narrative itself: overseas founders, especially those from Silicon Valley, seem to be better
at self-promotion and the TechCrunch-style media are more interested in their investment-fuelled, high-growth, high-risk
stories than they are in reporting on other kinds of successes.
In reality, there are lots of successful start-ups founded and run by Kenyans5, so perhaps the more incisive question is
why these are rarely touted as the success stories, while the same few well-known, mostly US-led organisations — BRCK,
Andela, m-Kopa — continue to receive the bulk of media attention.
Perhaps the real dierence is that entrepreneurs with experience, connections and a safety net are more likely to succeed
than those without, and Mzungu’s in Kenya are more likely to match this description than Kenyans and more likely to pro-
mote their own success – perpetuating the myths. If this is the case, what can be done to level the playing eld?
4 A Village Capital study found that more than 90% of funding for East African start-ups went to expat founders (Matranga 2017). Although there is
some doubt over how reliable this gure is (it focused primarily on US venture-capital, ignoring other forms of investment nance), the ndings
resonate with feelings of many in Kenya and are likely to be similar when broadened to include other forms of nance, if perhaps not quite so stark.
5 Those that were highlighted include Pesapal, Innova, Senga, Sendy, Twiga, JamboPay, Sky. Garden, Little Cab, Eneza Education, Ongair, Node Africa,
Africa’s Talking and FarmDrive – I am sure there are many more!
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My reflections on failure
In the US, the failure rate for new businesses is around 50%, higher for Silicon Valley-style tech rms, yet we seem
to measure projects in Africa against a higher standard — despite the enabling conditions being signicantly less
favourable (for example, the poor infrastructure).
So, what do we actually mean by failure? It is hard to judge the success/failure of digital entrepreneurs or NGO-
led ICT4D interventions when, as a sector, we have confused and contradictory understandings of failure. This
compounds confusion over whether certain types of enterprise, or dierent kinds of founder, are genuinely more
‘successful’ than others.
While some cling to the idea that success or failure is entirely related to nancial success and long-term sustain-
ability, many involved in social tech have moved beyond this to recognise that ‘failure’ is not always bad and have
embraced the fact that some failures are actually the result of healthy experimentation and early-stage discovery
work and are thus better understood as learning opportunities.
However, discussions and research often unhelpfully conate these very dierent concepts. For instance, consider
these dierent types of project ‘failure’:
nFailing due to bad management, poor implementation and well-known problems
nMaking good progress but running out of money to continue
nDoing good work but another organisation has started to do the same thing
nUndertaking customer discovery work and prototyping but not securing the funding to take things to the
next level
nDelivering a service that people want and need, but nobody will pay for
nGrowing, but too slowly to keep investors happy
nSuccessfully delivering ‘movement towards’ social outcomes, but having to close before reaching the tipping
point where things actually change
The rst is clearly a failure and perhaps one with little potential for learning. The remainder contain valuable
lessons, useful data, clear signals about what the market wants and what customers need, and in some cases
simply reect a misalignment of funding and timescales, or our fetishised belief that all ‘social services’ should be
delivered by (poor) customers paying for them.
Voices of the Silicon Savannah . . .
. . . on digital entrepreneurs
It is so easy to start a business here — how many people are serious? For how many is it just the latest hustle?
We have so few good Kenyan role models in this space, it’s mainly Mzungus that people have heard of.
There is so much family pressure to get a real job’.
Who will take a chance on a 20-year-old?
We all know the myth of the successful Mzungu founder — actually there are plenty of Kenyan-founded
success stories.
Not enough of us Kenyans are willing and able to take risks — though this is slowly changing.
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2.2 On NGOs and aid implementers
Others seeking to use technology to solve social problems are NGOs and civil society organisations. This is a broad category,
including well-known international organisations, national NGOs and sector-specic organisations — mostly donor- or
government-funded — covering service delivery, governance and advocacy, or arms-length organisations delivering
through partnerships with local groups. Some are entirely new to digital technologies, some have many years’ experience.
A lot has been written on the challenges the NGO sector faces and how it needs to adapt to doing development in a
digital age’. Many of these same issues were raised by technology rms partnering with NGOs in Kenya, but I have tried to
highlight some new angles on this area:
n Many NGOs don’t have internal technology skills or know where to nd them
It is a known concern that many NGOs lack good digital technology skills — especially vital ‘hybrid’ analyst roles that
bring together digital expertise and sector/program knowledge. What was interesting to hear in Kenya, however, was
that while the same issue exists in the private sector, these organisations do not seem to have a problem pulling in
appropriate tech/analyst sta when they are needed. So, the problem is unlikely to be a lack of local expertise, but
simply a lack of knowledge of when and how to use it and the right incentives to attract it.
n Some NGOs approach partnership in an unhelpful way
Although in many cases the partnerships between NGOs and digital tech rms have signicant social and commercial
potential, this is often not being explored. Instead, internal NGO/donor processes and reporting distracts people and
draws their time and energy away from thinking about how to improve the partnership. It seems that NGOs rarely
seek equitable partnerships with technologists, often approaching the relationship as a one-o procurement exercise
rather than a partnership. This is ne if they are procuring o-the-shelf solutions, but inevitably does not work when
the technologists are developing or customising products for the NGO’s specic situation and needs.
n NGOs are embracing digital technology but sometimes reluctantly and because of donors
Some working in NGOs feel that the incentive to include digital technology can at times be simply to keep donors
happy or open up new funding streams, even when the requisite experience and skills to do it justice are lacking.
This runs the risk of including badly designed technology in proposals, without sucient budget. This in turn leads to
appointing a local partner (typically the cheapest because they are hungry for work), then reluctantly agreeing to try
and deliver — a recipe for failure.
Voices of the Silicon Savannah . . .
. . . on NGOs and aid implementers
NGOs rarely seem to seek equitable partnerships with technologists. They approach us with the mindset of procuring
oce equipment — ‘we need a dashboard’ — instead of telling us what they want to do and why, and looking to
co-create ideas.
Some of those working in NGOs feel that the incentive to include digital technology is, at times, simply that the
donor asked for it.
The ecosystem doesn’t sell or promote itself to NGOs like us very well.
Sometimes, the incentive for us to include technology is just to access new and dierent funding streams.
There is often commercial revenue-generating potential in the partnerships between NGOs and tech rms, but
NGOs rarely explore this angle.
Most NGOs don’t have strong tech personnel, and if they do they are usually more traditional IT people.
When we work and co-create stu, both the NGO sta and the tech org sta start to develop their expertise in what
really works.
NGOs usually select the cheapest vendor, not the best partner to co-create their work with.
Development programme leaders are usually not aware of the complications that come with implementing a tech
project at dierent stages.
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2.3 On funders and donors
Much of the work in this space is funded — directly or indirectly — by the major international funders: USAID, DFID, the
World Bank, etc. The inuence they have goes far beyond how their specic grants are managed and aects norms across
the ecosystem.
I have tried not to re-hash well-known sector-wide concerns over the way funding operates, but instead to focus on a few
pertinent points highlighted by discussions in Kenya:
n Many funders prioritise reporting over discovery and experimentation
Good practice in the development of digital solutions is to adopt a lean, iterative approach, design with the end-user
and carry out customer-discovery work to test ideas and prototype solutions, all to minimise the risk of building the
wrong thing. The donor community has embraced this in its rhetoric (e.g. the Principles for Digital Development,
USAID’s new Adaptive Management program cycle), but it seems that on the ground this has yet to materialise.
People are still being asked to produce gures from day one, reporting on outcomes such as number of users rather
than softer results like co-designing and collaboration with local communities.
n Who is being funded?
There seems to be a perception that a lot of money is going to ‘techies with a bright idea. Given the amount of
innovation funding, this could well be true. Yet this funding could easily be altered to ensure such techies collaborate
eectively with the people who actually know the users, markets and business models of the services they are trying
to deliver.
n The funding landscape is confused
Listening to people’s perceptions of the funding available is fascinating. Some think there is too much funding fo-
cused on innovation, others that there is not enough; some see a gap in funding for scaling projects, whereas others
see the focus as being too focused on scale not experimentation.
Two gaps are highlighted fairly consistently: very early-stage funding for research, customer discovery and understand-
ing markets/business models (i.e. to help ensure that whatever product or solution is being considered is what is want-
ed/needed), and funding to continue, grow or replicate appropriately something that has been proven to work.
As the holders of the purse strings, donors have a hugely important and potentially pivotal role in changing the norms
and dynamics of the ecosystem for the better. Unfortunately, their understanding of what they can do to improve things
seems largely concentrated in head-oces or pockets of excellence and is slow in actually impacting the social-tech
community (i.e. changing their own procurement and reporting processes and funding mechanisms).
Undoubtedly, this is in part due to the same skills gaps outlined above and explored in more depth below. Without more
people in their teams who understand ‘how to do development in a digital age’, how can we expect donors to appreciate
the resources needed, understand the perverse incentives certain funding mechanisms perpetuate, and know which
proposals to select and partnerships to nurture?
Voices of the Silicon Savannah . . .
. . . on funders and donors
There are competing priorities between what is good for the users and what the donors ask for.
The focus for most donors is on the numbers. They want to see numbers from day one — that changes the way we
have to work.
Some of the Nordic donors have funding models that encourage sustainability for small enterprises. I don’t know
why the others don’t do this.
Aid funders are looking for quick xes and easy metrics. Complex problems take time and money and the road to
impact is slow. They aren’t interested in this.
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2.4 On private investors
Like donors, private investors (venture capitalists, etc.) play a major role in dening norms and practices across the eco-
system. This is potentially even more problematic with private investment, which, at least currently, mostly comes from
outside Kenya, from institutions with little or no understanding of the local context, needs or markets (this is beginning to
change, with some local African tech investment becoming visible, albeit slowly).
While, unfortunately, I did not manage to interview any investors directly, many interesting opinions were voiced by
entrepreneurs, hubs and funders who work with investors or operate in the space over which they exert inuence:
n The challenges of investors are not so dierent to those of donors, surprisingly.
In many areas of digital good practice, the private sector is years ahead of the aid community in its agile, lean
approaches, customer discovery and prototyping, etc. However, this does not necessarily extend to the way money
is invested in Kenya. Lots of the anecdotal reports cited similar problems to those in donor-driven work: lack of
support for early-stage user research and groundwork on markets and business models; lack of funding to test
ideas and prototype products, and a limited understanding of the need for customer discovery work and pivoting
before identifying a ‘product’ (or service) with potential to succeed.
n Who is receiving investment and where is it coming from?
As outlined earlier, the majority of overseas investment is going to companies with a US or European founder. And
the bulk of the money is coming from the US and Europe with comparatively little local African investment.
Given that these kinds of investments typically rely heavily on trusted relationships and word of mouth, this is
unsurprising but problematic and inevitably contributes to the ‘successful white founder’ story discussed earlier.
Money is going to people with shared connections and similar backgrounds to the investors, rather than to
local Kenyan entrepreneurs, irrespective of their ideas and potential.
This has a clearly observable compounding eect: once one investor gives some money to a team, others see this as
a signal and investment from other sources becomes easier for that team to nd. This is regardless of whether the
team being invested in has had, or is likely to have, any success.
n Investment overly favours high-risk, high-growth scalable products
Venture capital typically works on a high-risk, high-reward basis. One funder I saw present at the iHub explained that
they invest in 1 out of 100 proposals they receive and expect maybe 1 in 100 of those to succeed. This puts a lot of
pressure on ideas to demonstrate their potential to scale and become major global businesses.
This is not necessarily a problem (some may well meet this expectation), but various contextual factors in Kenya —
logistics problems, power outages and lack of institutional support, etc. — reduce the chances of this kind of global
success. More importantly, there do not appear to be any other types of investment available. This means that all ideas
need to be skewed and presented as having the potential for this enormous growth, whether or not this is realistic.
There are many kinds of business growth that are entirely valid and successful (see gure on the next page), but
it seems that the ‘revolutionary’, ‘j-curve’ or ‘hockey-stick’ growth are the only types that receive any signicant kind
of nance.
6 A Village Capital study found that in 2015–16, 90% of disclosed investments went to start-ups with one or more European or North American founder,
and 80% of disclosed investors in East Africa came from outside the continent (Matranga, Bhattacharyya, & Baird 2017: 48).
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Revenue
Revolutionary
Entrepreneur
o
Investment
Growth
Entrepreneur
Liestyle
Entrepreneur
Survivalist
Breadline
TIME
Types of entrepreneurial growth (Fisher 2011)
My reflections on the market distortions of investors and donors
The combined impact of the factors outlined in the sections above is highly problematic.
Many kinds of successful technology companies have the potential to boost the local economy, create jobs and have
a positive social impact, but for various reasons unrelated to the Kenyan economy, only certain types of organisation
generally receive investment or funding: companies developing ‘products’ in certain sectors, with the potential for
‘revolutionary’ growth, or organisations in a primarily aid-dependent position of supplier to the NGO sector.
This means that people end up either serving overseas NGO agendas, or pitching product-based business ideas,
which are often expensive to fund and take a long time to bring in any revenue, when what may really be needed
are service-based models based on local perceptions of local need. Ironically, such businesses are often cheaper to
start, with less intensive up-front capital requirements and can sometimes be revenue-generating from a far earlier
stage than product companies if given the support and modest initial investment they need.
In this way, private investors and donors may be, perhaps unintentionally, distorting the market by dening exter-
nally what it needs. This creates perverse incentives amongst local technology enterprises — people are following
the money and coming up with ideas to please either a small group of US/European investors or a similarly small
group of US/European donors. They are the only two games in town, and both have relatively narrow visions of who
and what they are prepared to support.
The impact of this is wider than it seems. In theory, it is still possible to set up a business with a modest investment
and adopt a slower model of growth, but the start-ups with investments and donor relationships have all the
advantages: they can aord to hire the best talent, undercut prices and saturate audiences with their marketing.
So, the investment going to the high-risk and donor-dependent companies may well end up crowding out
businesses with potential for modest, but important, success.7
Until local funders and local investors take on a bigger role, better local intermediaries could have a signicant
impact on these more modestly ambitious businesses. These are people who understand the local markets, local
contexts and also the needs of the international donors and investors. They can help guide donors’ and investors
decisions, help them identify good local teams, inuence them to invest in dierent ways and support less
high-risk companies, and to lobby others such as the Kenyan government to support them too.
Unfortunately, despite an active community of hubs, incubators and accelerators (who are the obvious candidates
for this activity), there do not seem to be many taking on this important intermediary role.
7 Another possible side eect of this is that start-ups feel they need to develop things from scratch in order to own the IP (Intellectual Property) they
believe is required for this high-growth approach. This causes a tension with sector norms of trying to re-use (often cheaper) existing open-source
frameworks where possible.
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Voices of the Silicon Savannah . . .
. . . on investors
What the investors want is what happens.
TechCrunch sells a narrative of “build it and they will come” — that doesn’t work in Africa, but people buy the myth.
A few well-known organisations are getting most of the interest from donors/investors.
Everyone wants to nd the “next big thing”, so this ends up with a lot of avour of the months.
As soon as one investor gives money to someone, they all pile on.
A lot of US and European funding goes to people with links to the home country.
Things are slowly improving — it used to be all white VCs [venture capitalists], now we are starting to see more local
African investors.
VCs tend to fund “people like me” — they pattern match based on what worked in Silicon Valley, but we are in a
totally dierent context.
A lot of investment relies on trust and relationships — overseas investors struggle to understand the local culture so
these trusted relationships are hard to build.
The man with the money decides what this year’s big thing is, not the market or the community.
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2.5 On the tech community
Many of us, when looking at Nairobi from the outside, get an impression of one of the most thriving and successful
social-tech communities in the world. This may or may not have ever been true, but the feeling from many who have
been part of this community since the beginning is that things have changed. Some feel the community is ‘stagnating or
that as an ecosystem it is not yet mature. There is a denite feeling that there is less money around than there used to be
and that things have become too commercialised. There is also a perception that nobody is trying to hold things together
or improve them.
This perception, however, is very Nairobi-centric and the dominant overseas media perception would suggest that the
social-tech ecosystem is focused entirely around the likes of iHub, mLab and Nairobi Garage. In reality, while Nairobi is
without doubt the epicentre of the tech and social-tech scene in Kenya, there is a lot of noteworthy activity happening
elsewhere that is often overlooked.
Although on this trip I only got to meet a few, there are many interesting social-tech ‘projects’ in other parts of Kenya,
such as ICT4D Kenya in Kili. This has a ‘hub-and-spokes’ training model that identies and trains technology champions
from local colleges, who then go to neighbouring villages to train promising tech-minded people there, who in turn train
more people in their village — an innovative model to scale impact, which would not easily meet the ‘high-risk product’
orientation of most investors.
There are also many tech hubs outside of the capital – those I have had some contact with are listed below, but there are
now 38 across Kenya (World Bank 2018).
n LakeHub (Kisumu)
n Swahilipot Hub (Mombasa)
n EldoHub (Eldoret)
n Mt Kenya Hub (Nyeri)
n Sote Hub (Voi and Kwale)
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My reflections on the evolution of a (social) tech ecosystem
Understanding the dynamics behind ecosystem growth and changes is extremely complex, but one interviewee
suggested that the Kenyan community may be at a natural ‘storming’ stage in its evolution.
If this is true, there are interesting lessons for the aid-sector funders who have injected so much money into the
Kenyan tech sector and have perhaps left it to its own devices too soon.
It also raises interesting questions about ‘leadership’ within an ecosystem that has no formal structures.
At rst, there was a clear group of leaders — some Kenyan, many from overseas — promoting and guiding the
sector, and facilitating collaborative models (such as the original iHub). Most have now moved on to new projects
but remain involved to diering degrees.
Does this confused situation mean that there is a leadership gap, but no real opportunity for it to be lled by new
blood? Or do the new entrants have dierent goals, not seeing the value of collaboration and nurturing a vibrant
community?
There is some suggestion that most of the new enterprises are purely commercial without a social aspect, which
could be a factor. Either way, it raises interesting questions about how to execute succession planning in an
ecosystem as diverse as this.
So, what could a vibrant social-tech community look like? How can the disparate communities (social enterprises,
tech start-ups, NGOs, funders and investors, etc.) come together to engage both socially and meaningfully8? How
can the dense Nairobi community work usefully with the more dispersed social-tech communities in the rest of
Kenya? Who is in a position to facilitate this and make it happen?
These challenges will be key to the success, or otherwise, of the ecosystem in coming years.
Voices of the Silicon Savannah . . .
. . . on the tech community
Community spaces are what put Nairobi on the map.
We used to work regularly with the tech hubs but this zzled out.
There used to be a social enterprise meetup but it stopped.
The innovations no longer seem to be about solving local Kenyan problems, but focus primarily on solving
problems for the global North.
In the past, we were riding a wave — the silicon savannah — it accelerated for a while but now we are atlining.
Things used to be vibrant, in the last year or so they have been stagnating.
We used to have a community, but we killed it — we commercialised everything, even relationships.
The ecosystem is not mature — it is entering its adolescent phase — as a child it was all fun, easy to sell the story,
easy to get money, lots of goodwill, we didn’t need results … Now people want to see results and impact … It has
to go/get through this phase.
We all remain friends but the pie is too small to share and nobody is working to improve things.
8 I started a Nairobi ICT4D Meetup group in 2016, which others are planning to revive soon. This might be a step in the right direction!
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2.6 On conspicuous absentees
The actors outlined so far make up most of the social-tech community. This leaves some very obvious actors who should
be an integral part of this ecosystem but, for some reason, are not very engaged.
n Universities
Although some universities have their own tech hubs (e.g. C4DLab at the University of Nairobi and @iLabAfrica at
Strathmore University), there is room for far broader engagement between the social-tech ecosystem and
universities, both for research (overseas universities engage regularly, after all) and in terms of course content.
Lessons from the sector (see Section 3.1 on the skills gap) could be more actively inuencing the curriculum to
ensure graduates have the skills that the ecosystem needs to be more successful and impactful. Universities’ inuence
on government and business would also be a valuable addition to any kind of ‘shared voice across the sector.
n The elephants in the room: the Kenyan government and Safaricom
It is interesting and surprising that neither the Kenyan government, Safaricom nor any of the other mobile operators
came up much in discussion; when they did, this was mostly in response to explicit prompts. Although in many
countries, the equivalents are seen as major players, in Kenya they are either seen as irrelevant or actively hostile
towards the local tech community.
The Kenyan government
‘IT-Enabled Services’ is a a core economic pillar in the government’s Vision 2030 development blueprint, with
a Ministry of ICT containing the ICT Authority, whose vision is to ‘be the leader in transforming Kenya into a
regional ICT hub and a globally competitive digital economy’, yet many feel that government bodies remain
at arm’s length from the social-tech community, do not understand what they could do to help and have no
interest in engaging (apparently, the ICT Authority used to be more engaged but went quiet).
This may all be set to change with the recent $50m investment in the Kenya Industry & Entrepreneurship Project.
Safaricom
In any conversation around social tech, mobile network operators are key actors and partners. This is especially
true in Kenya where Safaricom has a dominant market position. Yet many perceive them as unfriendly towards
the tech community - dicult to engage with or, in some cases, stealing their ideas. Greater, more supportive
involvement would be welcomed, and would be invaluable (as would their often-overlooked network of
real-world agents).
Voices of the Silicon Savannah . . .
. . . on Government
Our government seems to have no interest in engaging or even understanding what it could do to help
What incentive is there for government sta to learn or to change?
A lot of success relies on the role of government or other institutions, but few in the social- tech space think to
engage with them before they start developing things.
ICT is a core issue for the Kenyan Government with their Vision 2030 initiative so why are they at arm’s length from
all this - don’t they understand what they could be doing?
A lot of people in this space see Safaricom as unfriendly to the social-tech community, and as stealing their ideas.
The government is a negative inuence — they don’t understand the ecosystem so they try to control it and end
up stiing it.
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3. Reecting on the challenges
Section 2 primarily reported the views of the people I spoke to in Kenya who are part of its social-tech ecosystem. In this
section, I dig a little deeper into some of these themes, drawing on more of my own analysis, reections and related
prior research.
3.1 The sector-wide skills gap
That there is a skills gap in social tech, especially at the local/country level, is not exactly news. However, exploring
dierent conceptualisations of the skills that are needed or missing with people from dierent sectors and backgrounds
highlighted some dierent ideas and new perspectives.
In Nairobi, there is no shortage of good technology people with excellent design and coding skills; there is even a reason-
able amount of more in-demand skills such as User Experience design. But despite this, there is a shortage across the board
of key business skills and the hybrid ‘socio-technical’ skills essential for Tech4Dev work to succeed. More surprisingly, this
need spans the entire ecosystem — entrepreneurs, NGOs, the public sector, the local sta of funders and investors.
Table 3 provides an overview of the breadth of skills needed in the social tech sector (this does not include specic
technology skills, which are changing too fast to track). This skills gap is often discussed in regards to technology, aid/
development and social-tech in countries in both the global North and South, it is not unique to Kenya but nevertheless
is an important constraint to the growth of Kenya’s social-tech sector.
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Examples
Time and workload management, eective teamwork, managing sta,
how to hold good meetings, how to talk to techies/non-techies
Agile, lean start-up, adaptive management, user/human-centred
design, design thinking, innovation models, product management
Designing for intermittent connections and low bandwidth,
oine modes
Avoiding waterfall design, understanding end users, building in
time for experimenting and prototyping, budgeting for deployment,
maintenance and training, MERL tech
Partnering with digital producers/NGOs, working with government,
developing relationships, building collaborative partnerships
Knowing your customer, negotiation, advertising, promotion, pricing
Knowledge from known successes/failures, existing reusable
open-source frameworks
Managing clients, managing vendors, agile procurement/
contracting
User research, participatory design, user-design/testing workshops,
facilitation skills
How to pitch, the hidden rules of the game, writing good bids/
proposals, negotiating, sustainable business models, value propositions,
reporting on progress, monitoring and evaluation, what happens once
the money is received
Big data, open data, responsible data collection and management,
data analysis and visualisation, combining multiple data sources for
decision making, cheap randomisation methods
How ‘things are done’ in dierent contexts: government, the aid sector,
humanitarian response and international business
Skills
Self-management, teamwork and
communications
Newer approaches to iterative
product development
Technology issues specic to social
tech in the global South
How to design development
programs that incorporate digital
technology
Partnerships
Sales and Marketing
Solid grounding in what works and
common problems
Modern project and business
management
Techniques for engaging with end users
Funding and investment
Data-driven development
Sector norms
Table 3. The skills gaps in social tech
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This is not, of course, a list of competencies for any one individual, but it demonstrates the range of skills that teams/
organisations in this sector need to be eective. While some are more relevant to delivery sta and others relate to
technology sta, NGOs, commissioning and funding, etc., the broader categories apply across the board.
To my mind, one of the most interesting sets of conversations were not around the skills themselves, but the behaviour
changes implied by certain skills (iterative and user-centred methods in particular) and the reasons why these are not
taking place.
It is widely accepted that iterative and user-centred approaches need to be embraced far more often and there is
recognition of a skills gap in this area. Yet, despite this, the skills gap is being lled extremely slowly, and these
approaches remain exceptions to practice rather than the norm.
It is likely that there are structural or systemic factors at play — something that denitely requires more in-depth
exploration.
Voices of the Silicon Savannah . . .
. . . on why good practices still aren’t being adopted
Smaller NGOs don’t have the budget for this — every shilling spent on learning is a shilling that could be spent on
measurable outcomes that bring in funding.
The middle managers get in the way — the executive and the frontline might buy in, but the middle don’t get it,
they need to maintain their centrality and power.
The way our funding is constructed forces us into a cycle of build deliver report and we aren’t able to adopt
the more useful cycle of experiment learn adapt that we’d like.
Both sides of the client–supplier relationship need to share the same understanding of these techniques, otherwise
it just won’t work.
User research is expensive.
Good user-focused design isn’t possible in the timescales prescribed by most funders.
This isn’t just a tack-on to a project — doing this stu well needs an organisational mindset structured around
being user-led or design-led — most organisations don’t have this.
Good UX/UCD is expensive and slow so most people see it as optional.
Adopting new approaches requires organisational chance and conscious eort to build core capabilities — most
organisations have more immediate challenges so this gets postponed while they deal with project
implementation.
We have a culture of just getting on with it — people don’t think they need to do research rst.
Fear of someone stealing or copying our ideas means less sharing and less experimentation.
People are trying to survive — they need to just build something fast.
How do I explain research and prototypes to my family — I need a tangible product to show them that I am
working on something real.
A lot of techies are arrogant — think they know what people need already. They don’t want to listen, especially to
women or people in villages.
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3.2 The need for better intermediation — a role for hubs
Some of the factors inhibiting growth of the innovation sector include limited contact between tech startups and
traditional industry, limited connections to international networks, funders and investors (World Bank 2018).
From the conversations about challenges relating to investment and collaboration, it is clear that there is a need within
the ecosystem for actively facilitated intermediation between startups/hubs and other technology providers, suppliers
and purchasers (e.g. NGOs/government), potential customers, and funders/investors.
This role requires people with both experience of global business or the development sector and an understanding of the
local context, markets and users, enabling them to help people pick good bets’ and good local teams. Overseas investors
and large international organisations have neither the local knowledge nor the resources to carry out this kind of analysis
themselves. Perhaps one of the reasons why so much overseas money goes to ‘people like me’ is that in the absence of
trusted intermediaries, people tend to pattern-match based on their understanding of what works in their own countries.
The numerous technology hubs9 would be the obvious candidates to play this facilitative, mediating role and to an extent
they already do, but the current model is not working eectively for a range of reasons:
n What kind of tech hubs really exist?
GSMA’s Tech Hubs Landscape 2018 report (Giuliani 2018) suggests there are at least 30 active tech hubs in Kenya
(and 442 across the whole of Africa). While there are lots of interesting companies emerging from these hubs,
my own experience and that of other recent research into hubs globally (Rodrigues et al. 2018) suggests many
tech-hubs are co-working spaces with some added services”, and more transformative “incubators and accelerators
are harder to nd” – this leaves an important need being signicantly under-addressed.
n Who are the hubs reaching?
Some suggested that hub populations are over-represented by younger entrepreneurs fresh from university, people
operating casually, hustling or just hanging out, and that many of the more serious entrepreneurs are working
outside the hubs and their networks. Also, the majority of hub residents are apparently well-educated, middle-class
techies — the spaces appear to be less appealing or even intimidating to those from less auent backgrounds or
at an earlier stage in their tech-skills development. If true, this includes exactly those people most social-tech
programs are serving, and who have invaluable perspectives on the design and delivery of such programs.
n How are the hubs managing their pipeline?
There were suggestions that the hubs are doing very little to engage with other organisations who could act as
‘feeders’ — technology training programs, universities, etc. — and are thus missing an opportunity to intermediate
between the skills that social-tech projects/investors/employers need and the skills in which people are being trained.
n How successful are the outcomes?
There is little easily-accessible data on the success of hubs or their residents, not only in terms of how many businesses
are receiving funding, but also how many are still going concerns, how many are protable and how many are having
any kind of social impact. This is dicult to measure in any context, but the diculty is exacerbated by funders/
investors not asking for relevant information, and the way in which people who are in competition shift between hubs
and tend not to share such information with each other.
n Are hubs actually delivering the services that are needed?
The perception is that many hubs are overly focused on how to get money from VCs in a short (6-month) time period.
This raises questions about what they are doing in terms of actual tangible business support, with many feeling that
this is either absent or weak.
n Do the hubs work together?
There is a feeling that the Kenyan hubs rarely collaborate or work together — nor do they have much incentive to
so do. Their models are driven primarily by an understandable need for nancial security, and by the needs of
overseas investors. This leaves little room to accommodate the needs of their actual users. It is also dicult to
understand the dierences between the varying models that hubs operate on; even when external funders have
tried to facilitate some rationality here, they have struggled.
9 For the purposes of simplicity, I am including co-working spaces, accelerators and incubators under this general heading.
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While this is not a glowing recommendation for the hub models that are of such interest to the wider world, there is a
clear answer to why these problems persist: money. Tech hubs are struggling to survive and trying to nd nancially
sustainable business models. This impacts on their eectiveness, their ability to provide the services their residents need,
and whether they can oer more intensive incubation/accelerator services or are only able to operate sustainably as
co-working spaces (a model many are moving to).
This is entirely understandable — without a sustainable revenue stream, they will be out of business. However, it also
means that they are currently not playing the essential intermediation role that the community so clearly needs and
nobody else is stepping in to ll this gap.
Voices of the Silicon Savannah . . .
. . . on challenges with tech hubs
Current hubs are intimidating to people without the right background — people from the slums, non-techies still
working on their skills.
The hubs aren’t really producing that many successful start-ups.
Some start-ups jump from hub to hub.
What are they doing? Lots of their start-ups have never even seen the Business Model Canvas.
Their advisors are rarely people who have set up or run businesses in Africa.
The hubs are doing a terrible job of supporting people to adopt lean and agile methodologies.
There are so many hubs, I don’t know what they do or what the dierences are.
In the past, the World Bank tried to develop local technology ecosystems but ended up just talking to the same
people over and over.
Most of the hubs have lost core funding, so they have been forced to worry about their own sustainability ahead
of whether they are oering the services that are most needed.
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3.3 Supply and demand — what role for social-tech purchasers?
A common theme in the conversations I had was that the vast majority of money being spent on tech or social tech in
Kenya, is — directly or indirectly — going to overseas, not Kenyan, companies. For example:
‘The UN Environment Program is based in Gigiri (Nairobi), yet less than 5% of its software is procured locally. (Interviewee)
Given that virtually every aspect of government, public service delivery, aid and development involves some element of
digital technology, the total spend on this kind of work in Kenya alone is likely to be billions of shillings every year.
While this is also an issue in many other sectors and is a longstanding concern in the development sector, it has particular
relevance to ICT and digital technologies:
n Digital is now pervasive, controls many aspects of our day-to-day lives, economies and public services, and has enor-
mous transformative potential. There is a strong ethical push to ensure that this technology can be controlled and
created locally rather than this power resting with overseas or multinational institutions.
n The ICT sector is a major potential driver of economic growth and job creation — exporting this work overseas means
these economic benets are being realised elsewhere.
n Local companies tend to understand local context, market and users, and speak local languages. This tends to lead to
better-designed and more appropriate tech products and digital services.
n Local development/customisation is often cheaper (though less so than people initially anticipate).
n For certain sectors such as civic tech, control of the technology platforms is integral to ensuring they are managed
democratically. In these sectors, the drivers to have local control and ownership of the technology are even greater.
As one interviewee described it: ‘Technology is part of the issue as well as part of the solution.
Many in the development sector support these ideas in the abstract, but few NGOs or funders have actually adopted
policies and practices to make this a reality. And, according to one interviewee, the Kenyan government has done so in
ways that are easily circumvented, resulting in contracts often being awarded to a local ‘front’ organisation which serves to
channel the majority of the work to overseas/multinational partners). So why is it that these policies remain the exception?
n Local ownership is not the only factor in these decisions, it is also important to consider the scalability and sustain-
ability of solutions, and eciency-savings gained by using the same systems and tools across multiple projects and
countries. In some situations, these factors outweigh the benets of local ownership.
n Engaging with the local ecosystem can be time-consuming and confusing, though this would be less of a factor if
good intermediaries existed, as highlighted in Section 3.2.
n Procurement from large institutions (including governments) often actively excludes smaller, local/national bidders.
Many bids are so large that only global prime contractors with specialist teams are in a position to apply.10
n Smaller organisations are further excluded by procurement requirements such as needing to demonstrate things like
ve years of audited accounts by a certied and recognised auditor’, and being able to demonstrate a track record in
administering large contracts.
Purchasers of various sorts could be instrumental in increasing the demand side of the social-tech sector if they found
practical ways of spending more of their technology budgets within the local Kenyan tech sector.
10 For example, Kenya’s recent Regional Communication Infrastructure Programme spent over $200m on e-government and creating a fast network
for Kenyan universities. The majority of this was spent outside of Kenya.
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Voices of Silicon Savannah . . .
. . . on the power of purchasers
Sometimes it is easier to just buy something than to think about what impact dierent ways of buying it could have.
We tend not to promote RFPs [requests for proposals] to the local ecosystem.
What incentive is there for procurement sta to change — after all, the old adage “nobody was ever red for
awarding a contract to IBM” still holds true.
Procurement from government, big multinationals, MNOs [mobile network operators] and large international
bodies/NGOs tends to actively exclude in-country bidders — I don’t think they do this on purpose, but it happens.
The local social-tech ecosystem doesn’t sell or promote itself to NGOs like us very well.
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4. What next? Experiment, learn, adapt and improve
Based on the observations and themes that emerged during my conversations, I have drawn out some broad recom-
mendations that I believe could help. Some are practical suggestions that could be implemented immediately, some are
hypotheses or areas that would benet from robust research and some are avenues for exploration or experimentation.
When I embarked on this work, I hoped to take some of what emerged and initiate some lean, adaptive and user-focused
experiments to help move forward our understanding of the problem, and to start to shape a viable business/project/
solution to address some of the barriers. I have since taken on a full-time job, so no longer have the bandwidth to do this,
but am very interested in supporting or engaging with others who feel able to take forward any of the ideas that follow.
4.1 A new narrative of Kenyan success stories
Whether or not there is truth in the idea that white/Mzungu entrepreneurs are more successful at attracting investment,
there is denitely a need for a new narrative based on the fact that local Kenyan entrepreneurs can be successful, are
successful and should be taken more seriously both locally and internationally. This entails:
n Showcasing Kenyan success stories
n More honest and public reections on what lies behind these stories (did they rely on rich family, NGO grants or
overseas ties, or did they build from modest savings using earned revenue)
n Finding a way to highlight modest-growth, low-risk enterprises as successful not ‘boring’
n Explaining why certain things work and setting good examples for others, including embracing dierent kinds of
‘failure’ to help destigmatise ideas for experimenting and adapting
n Above all, nding successful role models who can champion this narrative, to help those following in their footsteps
The immediate question though, given the fragmented nature of the ecosystem at present, is who could champion this
work and build some momentum behind it?
4.2 NGOs need to get better at partnering for development in a digital age
Most NGOs have identied that they need to get better at incorporating digital technology into their work, but very few
have yet made the structural and organisational changes needed to succeed in this new digital age. Closer working with
the local social-tech ecosystems could be a fantastic way to move this work forward, while also supporting the social-tech
ecosystems in Kenya (and other countries they operate in). However, the way they work and partner would need to
change:
n Partnering over procuring — working with local tech/social-tech rms on an equal basis to co-create solutions
rather than seeing them as suppliers of goods. This requires a change in mindset and excellent management and
facilitation, but produces demonstrably better results.
n Developing hybrid expertise internally — NGOs need ‘ICT4D analysts’ with hybrid skills to succeed in the modern
world, bringing together expertise in both the tech world and the sectors in which they operate. While some NGOs
may be able to simply hire in these people, most will need to grow these skills internally — what better way than by
the partnership approach above?
n Learn from each other’s strengths — technologists do not have all the answers; far from it (some commented on
certain kinds of digital start-up demonstrating an arrogant ‘we know what users need’ attitude, sexism and a failure to
listen to poor and marginalised users). But these community and programming skills are exactly what development
actors should be promoting. Both sets of partners have a lot to learn.
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4.3 Is it time for a tech-hub intervention?
As one funder commented when reviewing this work, it feels like time for a hub intervention. I could not agree more. Tech
hubs are a potentially vital element of growing Kenyas social-tech ecosystem, which is not living up to its potential.
Why is this? I suspect it is in large part due to the search for the elusive nancially sustainable business model for a tech
hub, enabling it to cease its reliance on aid funding.
While we can remain optimistic, much of the available evidence suggests such a commercially sustainable model
may not exist — most tech hubs that are thriving and oering valuable services to the community are doing so with
external funding.
“Most active and productive hubs have core costs covered.(Rodrigues et al. 2018)
Many of those that seem to have found a sustainable model have evolved into very nice co-working spaces, but with
signicantly less of the important community building, intermediation and skills development of their past.
So, what can be done?
n More robust research is needed into the dierent business models — if nancially sustainable models do exist, they
need to be better understood, widely publicised and then adapted to dierent contexts.
n If the elusive nancially sustainable model for a hub that genuinely supports the growth of the local ecosystem
doesn’t exist (as seems likely), we simply need to recognise this and see the community-building, intermediary and
training roles as public services that need ongoing funding. We do this for other public services, so this is not a
problem; it just means that funders need to adopt a dierent approach. Perhaps they could support this work for
10 years while working closely with government to help it understand the economic benets of supporting the
sector and subsequently take on the nancial burden.11
n We could experiment with new and dierent models that bring together the community and intermediary activities
with new forms of revenue. For example, many funders and investors know their sta need a signicantly better
understanding of local markets and communities. Perhaps using tech hubs as bases for local sta (and launching
themselves beyond just the capital cities), and being active contributors helps to create an intermediary space while
at the same time –through paying commercial rental rates — supporting the nancial models of the hubs at which
they are based.
n Or perhaps we need entirely new entrants to the hub/intermediary market — new experiments with entirely new
models — for example, by bringing together the training organisations as feeders, working more closely with
employers/investors and ensuring that training-program design matches need. This is a much-needed niche for
tech-skills recruitment.
As of June 2018, it seems hope may be on the horizon - in the form of the $50m Kenya Industry and Entrepreneurship
Project (supported by the Kenyan government and the World Bank) which has an explicit focus on startups, SMEs,
incubators and accelerators including setting out to:
n improve survival and growth rates of technology-enabled startupss
n build intermediaries’ capacity including developing their sustainable business models
n connect the Kenyan ecosystem to international networks
n establish an industry-academia collaboration platform
It is early days but worth watching carefully.
11 Some hubs do continue to oer incubation, acceleration and/or a wider community role. These tend to have alternate sources of funding (from
universities or from the World Bank’s infoDev, for example).
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4.4 We need new ideas to bridge the skills gap and change behaviours
The skills gaps outlined earlier are wide-ranging and, although this has been common knowledge for many years, the
problems persist. Either training is not being made available to the right people, or it is not eective, or translating into
tangible changed real-world behaviours. New ways of looking at this might help. Some ideas to explore further include:
n Building bridges to bigger projects
In Kenya, I came across some extremely interesting demand-driven models of in-work training (in the UK charity sec-
tor we used to refer to these as ‘halfway-house employability projects12) that found ways for people or organisations
with good technology skills to engage with large-scale or international projects that they typically would not be able
to access - giving them the experience and credibility they need to take on more such large/international projects in
the future.
These kind of training ‘bridges’ work, are successful and have enormous potential for growth.
n Learning in the real world
It is by now well-established that learning is best when it happens in real-world environments rather than a training
room. It is probably unrealistic to establish training ‘projects’ like the above for everyone in the sector, but support-
ing people during their work rather than in separate o-the-job training might be achievable. However, this would
necessitate a large-scale network of ‘mentors’ who could oer advice and guidance and set learning tasks. These
people probably exist — in successful and established Tech4Dev organisations, NGO ICT4D projects, government,
civil society and the private sector (depending on the specic skills gap identied), but they need to be attracted and
trained and the process needs to be managed and evaluated for it to be of any help. Can we work with employers to
convince them to make sta time available? Is this helpful if the relationship is remote? Could someone take it up as a
core project and nd funding for the operations and overheads?
n Finding ways to leverage the expertise of global ICT4D experts
There exists a pool of broad and deep expertise in ‘what works when implementing digital technology in a
development context’ amongst those who have been working in the space for many years. Unfortunately, due to
the nature of funding historically, much of this expertise sits within consultancies, organisations or NGOs based in
the US and Europe.
Can we nd new ways of bringing these people together with newer entrants into the space in the Global South in
ways that bring together global and local contexts, enable knowledge and skills sharing and encourage changed
behaviour on both sides?
For example, DFID now includes potential impact on the UK economy as a factor in some of its funding. Utilising
the signicant resource of UK-based organisations with ICT4D expertise could open doors to funding, new kinds of
partnerships on bids and advisors on boards, as well as providing the kinds of mentors outlined above.
n Skills development needs to go beyond capital cities like Nairobi
In Kenya, the majority of training is conned to Nairobi. Exploring a ‘train the trainer’ model like that operated by
ICT4D Kenya could be a fascinating way to experiment with broadening and improving social-tech skills across Kenya.
Starting with established experts (Kenyan or overseas), this would identify champions in or within easy reach of
Nairobi and initiate a hub-and-spokes model to train promising ‘social-tech champions in local projects, community
groups and NGOs in other towns and counties, who can continue to disseminate good practices within their wider
communities.
12 I spoke to Code Pamoja, the Fair Trade Software Foundation and Caspar Coding. There are many others.
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4.5 How can we encourage and enable purchasers to do more?
The Kenyan government, aid funders and NGOs combined are a signicant source of demand in the social-tech space.
This could be signicant in growing and improving the local ecosystem, for example:
n Advocating for new approaches to procurement
There is need for increased advocacy to those spending money (particularly government) that they can do more to
enable the money to be spent locally. This, however, requires changes to procurement/funding policies and processes:
A simple ‘Buy Kenyan’ policy is not sucient and may be overly simplistic and reminiscent of 1970s-style trade
barriers.
Breaking procurement into smaller chunks enables smaller/local rms to bid and compete more fairly. Agile
procurement and better partnerships can help further.
Oering masterclasses in relevant kinds of procurement and moving to more transparent e-procurement systems
Ensuring policies and process that are supportive of local suppliers are propagated down through supply chains
Changing individual incentives to encourage new approaches. Procurement takes time; procuring smaller
projects locally means more work and more partners, adding to the workload of those responsible for this
activity. Without their buy-in, it will not happen. This potentially entails training, additional stang, and changing
the culture and perceptions around failure. Local procurement of small projects seems higher risk to many, but
when done through an agile procurement approach it actually reduces risk, i.e. if there is a problem, it can be
discovered after $50,000 rather than $10m has been spent.
n Spending money in ways that increase local capabilities
Where local capabilities are not adequate or competitive, rather than simply going elsewhere, awards can incorporate
training and developing local capacity so that there is a better chance of securing this kind of work in the future.
n Developing better local relationships
For any of this to make sense, better intermediation and matchmaking is required between buyers and sellers. This
means that dierent sectors need to come together and understand each other better. This would be a potentially
exciting and useful role for a revived tech-hub community.
n Supporting and funding the local ecosystem
Beyond any policy or relationship, ‘support for the local’ is only possible if the right kinds of people, organisations,
skills and networks exist. Kenya has made a good start at this, but it is slowing down. In the past, the World Bank,
DFID and the Kenyan government, amongst others, have funded tech hubs or other aspects of the social-tech
ecosystem — they could continue to do so.
What can be done to trial this approach?
The actor with the biggest incentive for buying local is government. Introducing stricter data sovereignty laws (as they
have in India) and/or ‘buy local’ policies in key areas of procurement would create a market where this approach could be
trialled. However, support would denitely be needed from people with experience of this smaller, more agile method of
procurement.
On the NGO side, if a donor and/or a large international NGO could be convinced to pilot this kind of approach for an
upcoming ICT4D program, it would create a great learning opportunity, case study and vehicle through which to develop
some good practice guidance on when this ‘prefer local’ approach is appropriate and how to do it well. With this in hand,
the Kenyan ecosystem would be in a much stronger position to advocate for similar changes in other organisations.
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4.6 Gaps in funding and investment and the need for new approaches
Although there is general agreement that there are gaps in the funding and investment available to technology rms,
there are dierences of opinion over exactly where these gaps lie. Some argue that while funding of up to ~$100,000
exists, there is a gap between this and very large gures ($1m+); for some, there is too little innovation funding, for others
too much; some see no support for taking things to scale, while other perceive the gap to be at a much earlier stage;
some regard existing funding as not small enough, while others see it as far too small; and some see too strong a focus
on funding products, while others see this as the only way to take things to scale. This is interesting because it reects
diering understandings of both what the need is and what is available in the market. Despite these dierences, some
suggestions with a high degree of consensus did emerge:
n Funding specically designed for ‘customer discovery’ and testing models
At the moment, there is a lot of seed funding, early-stage investment and innovation funding, but little of this
supports user research, exploring the problem space, testing ideas, brainstorming solutions, engaging with
potential customers, building and testing prototypes and rening business models and value propositions.
Without these activities, the chances of success of any new venture, project or program are signicantly reduced.
In the global North, these very early stages are typically self-funded. Few Kenyans have the savings to make
this possible.
Self-nancing of early-stage entrepreneurs (Jabarov 2017)
To bridge this gap, more funding streams could be designed to explicitly support the needs of this early stage, with mech-
anisms tied to these goals (disbursements tied to learning and adaptation rather than hard outcomes, rapid iteration of
prototypes, etc.). These would play an invaluable role in the space and lead to better and more robust ideas being taken
forward for more traditional funding or early-stage investment.
n Investment in slow/modest-growth businesses
At the moment, most technology funding is either for ‘hockey-stick’, high-growth ‘products’, or for short-term social
‘projects’, which may or may not have a sustainable business model. This leaves a gap in support for what are perhaps
the most common kinds of business — technology rms with an idea that works and a market willing to pay, which
might grow to employ half a dozen people but will never become huge global businesses. These are more likely to be
local ‘service’ businesses, perhaps less exciting and innovative, but with lower barriers to entry and, when taken en-
masse, a huge potential to create jobs and boost the local economy.
Micro-nance already exists for very small investments in livelihoods and enterprise. Could it evolve to meet the
digital ecosystem’s need for slightly higher levels of investment with a modest but important potential for growth,
particularly in regions outside Nairobi that are often overlooked? Is there room in the market for a new micro-nance
initiative specialising in the social-tech space?
Revenue
Time
Maturity
Scaling
Accelerated
Growth
Development
Ideation
Prototype
Launch
Acquisition/IPO
Traditional
Funding
Venture Capital
Corporate Investors
Angel InvestorsSelf-Financed
50
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n Deliver funding that encourages adaptive, user-centric and locally-driven approaches
In addition to gaps where new forms of funding or investment would be useful, there are ways in which existing
sources of nance could adapt to be more helpful and successful:
Adopt adaptive learning approaches — for example, fund promising teams and co-create the results with them
rather than funding a proposal for a specic ‘idea which cannot then be adapted
Include key concepts in funding streams, such as iterative approaches, supporting and not damaging local tech
economies, engaging with end-users and prototyping, with disbursements attached, so the funding mechanism
reinforces rather than undermines the rhetoric
Provide explicit ring-fenced funding for vital hybrid roles (lled internally or by bringing in expert consultants)
and ensure that technology and community/business experts are being brought together and facilitated eec-
tively when exploring problems, assessing markets and building solutions and associated business models
Make more use of local intermediaries who understand the local people, actors and marketplace.
‘Devolve distribution of funding to local people where possible, without pressuring intermediaries to exercise draconian controls
on grantees … spend more time on the ground, working with and meeting local people’. (Rodrigues et al. 2018)
While these suggestions align with recommendations of other research to a degree13, they bring a slightly dierent
perspective and it would be valuable for funders to understand these dierent perspectives as they design new funding
or investment programs.
Some of these changes are underway, but they are slow and and are being brought about by only a few actors. How can
we bring people together with a shared voice to lobby for this?
13 For example, the recent Kenya Industry and Entrepreneurship Project identies funding gaps in the innovation sector as ‘limited funding for core
operations’, ‘limited funding for growth strategy’ and ‘limited funding for management development’.
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5. Conclusion and next steps
I hope you have found this work interesting and useful. I believe the observations paint a mixed picture of the Kenyan
social-tech ecosystem: while there is a lot of activity and huge potential, some of which is being realised, there are signicant
structural and systemic gaps holding things back. There are key areas where more work would be extremely valuable.
1. Better collaboration
Many of the concerns outlined arise from a lack of understanding amongst dierent players, limited communica-
tion and poor collaboration. This could be improved immediately without the need for external input and with very
limited resources — meetups, community events and workshops bringing together dierent actors would all be a
great way to start. Longer term, there is a need for stronger community leadership and guidance and better-designed
pipelines between dierent activities, but for the moment, simply getting people together regularly is likely to have a
strong positive impact.
2. Adopting known good practices where feasible
Funding and external pressures limit the degree to which things like adaptive management and human-centred
design can be implemented right now. However, there is no reason why they cannot be adopted as far as is possible,
and with wider discussion and training –adoption will inevitably improve. A good starting point might be to simply
ensure everyone in the ecosystem is aware of the support that already exists — e.g. Lean Impact for Social Good, the
Principles for Digital Development and the extensive array of useful social-tech blogs such as ICT Works.
3. Creating a shared voice — for advocacy, lobbying and telling the Kenyan story
Many of the suggestions outlined in Section 4 involve changes on the part of the bigger actors — government,
funders, investors and other international organisations. Coming together to lobby for these changes more coher-
ently increases the likelihood of people listening and acting. Bringing these actors into the same room as the smaller
players in the ecosystem would help and could be done with a more active and vibrant local community scene.
4. Experimenting to create models that others can adopt and adapt
There are many ideas outlined in earlier sections — some may work, others inevitably won’t but would provide useful
lessons. As a sector, we often worry too much about getting the upfront design right and planning ahead when, if
we embraced the spirit of iterative and adaptive approaches more, we could start to trial some of these ideas, see
which ones work, then focus on those. It would be great to see more experiments that generate useful data through
actually trying to address some of these challenges, and to work with the instigators to help them evolve and adapt
as they learn.
5. Further research
Lastly, there are key areas where further, more robust, research would help; for example, on dierent models for tech
hubs and gathering hard data on funding and investment successes/failures14.
If any of these suggestions stir you into action, please contact me to discuss how I can support your work. I would enjoy
working with anyone experimenting with new ideas or approaches - helping you to draw out learnings, to adapt and
evolve as you continue to iterate. Please get in touch.
14 A recent piece of research which is extremely relevant to anyone involved in the Kenyan innovation and tech ecosystem read is Scale Up!
Entrepreneurs’ Guide to Investment in Kenya (https://make-it-initiative.org/africa/activities/guides-investment/) which includes rich observations,
good practice guidance and a directory of investors currently active in supporting Kenyan technology startups.
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Appendix A: Interviewees
Interviewee Organisation/Aliation
Alejandro Espinosa-llano Computer Aid
Angela Oduor Lungati Ushahidi
Annina Wersun Plan International
Boris Maguire Echo Mobile
Britone Mwasaru Swahilipot Hub
Catherine Gicheru Code for Kenya
David Lemaiyan Code for Africa
David Spencer VSO
Declan Ottaro Ushahidi
Dennis Gichangi Dew CIS Solutions/CodePamoja
DJ Koeman Poa! internet
Dorothy Muroki FHI 360
Dunstan Machoka BTI Millman/CodePamoja
Enock Kavingwa Keya Nakala Analytics
Esther Gathiji Digital Opportunity Trust
Farida Bascha Practical Action
George Anyiko K’Ouma SADA Kenya
George Marrows Echo Mobile
Geraint Tudor-Jones DFID Kenya
Jack Kaburu Catholic Relief Services (CRS)
Jessica Musila Mzalendo
Joseph Wangondu Kariuki Plan International Kenya
Judith Owigar JuaKali
Kevin Barasa ICT4D Entrepreneur
Kirui Kenned iHub Software Consulting / Tanasuk Technologies Africa
Linda Kamau AkiraChix
Magdalene Wanjugu NairoBits Trust
Mativo Jonathan ICT4D Kenya
Mick Larson Tunapanda Institute
Peter Njuguna Plan International Kenya
Rita Zagoni Africa’s Voices Foundation
Robert Magori Practical Action
Roy Ombatti/Mwangi AB3D (African Born 3D Printing)
Sasha Kinney Independent consultant
Sean Blaschke UNICEF Innovation
Sebastiaan Tan Caspar Coding
Sheilah Birgen iHub
Tess Wandia iHub Research
Tim Kelly World Bank
Yves Niyiragira Fahamu
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  • Conference Paper
    Full-text available
    Summary Several early technology developments put Kenya on the map as the ‘tech capital’ of East Africa, and during the past decade, Kenya went through a period of overabundant funding for information and communications technology (ICT) solutions related to governance or development challenges. But ICT specialists, staff from non-governmental organisations / civil society organisations (CSOs) and donors tend to agree that not many applications (apps) and platforms developed at that time yielded results. This has led to a refocusing on different types of governance and development programmes. • Too many of Kenya’s Making All Voices Count grantees repeated the same mistakes, which have been documented as well-known challenges for technology for transparency and accountability (Tech4T&A) initiatives: commissioning the design of custom-made tech platforms; overestimating smartphone use among their community members; and not engaging their communities in the design, piloting or testing of the tech product (de Lanerolle, Walker and Kinney 2016; Sika, Sambuli, Orwa and Salim 2014). Despite the fact that the implementing CSOs are in Kenya, not every organisation has sufficient in-house tech knowledge to be able to choose and implement a tech-based solution. • When the tech component was slow in delivering results, Making All Voices Count grantees in Kenya worked hard to achieve governance improvements, and often managed to add in the tech component towards the end of the programme. • In Kenya, the focus has shifted towards governance issues at the county level, and several proofs of concept developed with Making All Voices Count funding are suitable for adaptation and scaling up in accountability programmes at this level.