This is the first of four related blog entries that will look at the post-2015 development agenda and its implications. This entry describes the process of setting that agenda.
In theory, the origins of the post-2015 process could be traced back many years to the setting of the Millennium Development Goal deadline. It was obvious then that there would be a post-MDG world from 2015. However, it seems more appropriate to date the timeline (see Figure 1 below, and more detailed timeline in Table 1 at the end) from September 2011, with the formation of the UN System Task Team: the body charged with overseeing the post-2015 process.
Figure 1: Post-2015 Process Outline Timeline
The MDGs were an integration in 2001 of two rather separate processes: the OECD Development Assistance Committee’s work on International Development Goals, and the UN’s work to develop the Millennium Declaration. This added to the time and effort required to produce the MDGs, yet the same is happening again with the post-2015 process, as summarised in Figure 2 below (adapted from an original by Claire Hickson).
Figure 2: Post-2015 Development Agenda and Sustainable Development Goals Process Map
The timeline shown is therefore a single representation of multiple strands. The post-2015 development agenda process is relatively well-advanced. Following the UN System Task Team’s formation, a series of thematic and national consultations on the agenda have already been conducted, with two key reports produced in 2012 (“Realizing the Future We Want for All”) and 2013 (“A Renewed Global Partnership for Development”). A High-Level Panel was set up by UN Secretary-General Ban Ki-moon. Chaired by the Presidents of Indonesia and Liberia and the UK Prime Minister and involving 24 other “eminent persons”, this produced its report mid-way through 2013. These documents were placed before the UN General Assembly when its 68th session began in September 2013; a session which included special meetings and events on the MDGs and after.
At the time of writing, the sustainable development goals (SDGs) process was not quite so well developed. Emerging from the 2012 UN Conference on Sustainable Development (“Rio+20”) and its General Assembly resolution in July 2012, this led to formation of a UN Open Working Group. The Group has been supported by a UN System Technical Support Team, which provides a link to the post-2015 activity since it works under the UN System Task Team. It has also been supported by an “Intergovernmental Committee of Experts on Sustainable Development Financing” and a “High-Level Political Forum” that provides political momentum for the process. The Open Working Group has a series of eight sessions being run during 2013-2014, and structured along thematic lines. This will report towards the end of 2014.
At that point – during 2015 – an integration of the two processes and political negotiation of the final post-2015 agenda should occur, leading to a new post-MDG framework to run from the start of 2016. It is worth just asking whether such a framework might not emerge. Present signs are that this would be extremely unlikely: process, timeline and structures are all in place; and significant political capital – plus other resources – has already been invested. It would take something huge and unexpected to derail the process. We can therefore work on the assumption that there will be a post-2015 agenda.
Table 1: The Post-2015 Process Schedule
Sourced largely from Hickson (2013)
|Sep 2010||UN MDG Summit|
|Sep 2011||UN System Task Team established to lead post-2015 process|
|May 2012-Apr 2013||Post-2015 thematic global consultations|
|Jun 2012||Rio+20 summit; working group on Sustainable Development Goals (SDGs) set up|
|Jun 2012||UN System Task Team “Realizing the Future for All” report|
|Jun 2012||National post-2015 consultations begin|
|Jul 2012||Rio+20 “The Future We Want” resolution to UN General Assembly|
|Aug 2012||High-Level Panel (HLP) set up by Ban Ki-moon|
|Sep 2012||HLP convened|
|Nov 2012||HLP first substantive meeting (London)|
|Jan 2013||SDG Open Working Group created|
|Feb 2013||HLP second meeting (Monrovia)|
|Feb 2013||EU post-2015 communication “A Decent Life for All”|
|Mar 2013||UN System Task Team “A Renewed Global Partnership for Development” report|
|Mar 2013||HLP third meeting (Bali)|
|Mar 2013-Feb 2014||Eight sessions of SDG Open Working Group|
|May 2013||Draft SDG report|
|May 2013||HLP “A New Global Partnership” report|
|Jul 2013||Progress report of SDG Open Working Group to UN General Assembly|
|Sep/Oct 2013||New UN General Assembly session and MDG Review Summit|
|Sep 2013||First session of High-Level Political Forum on sustainable development|
|Sep 2014||SDG Open Working Group to report to UN General Assembly|
|Jan 2015||MDG deadline|
|Jan-Dec 2015||Intergovernmental negotiations via UN General Assembly on Post-2015 Agenda|
|Sep 2015||High-Level Political Forum Meeting|
|c.Jul-Sep 2015||UN General Assembly Post-2015/MDG Review Summit|
|Jan 2016||New Post-2015 framework in place|
 Hulme, D. (2009) The Millennium Development Goals (MDGs): A Short History of the World’s Biggest Promise, BWPI Working Paper 100, Brooks World Poverty Institute, University of Manchester, UK http://www.bwpi.manchester.ac.uk/resources/Working-Papers/bwpi-wp-10009.pdf
 Hickson, C. (2013) Post-2015 development goals process and timeline, Trio Policy, 11 Jul http://www.triopolicy.com/post-2015-development-goals-process-and-timeline/
If you work on technology, you need to understand innovation. If you work on technology and development, you need to understand inclusive innovation.
In simple terms, inclusive innovation is the means by which new goods and services are developed for and/or by those who have been excluded from the development mainstream; particularly the billions living on lowest incomes. So new technologies for the base of the pyramid – mobile phones, mobile services, telecentres, better seed varieties, vaccines, etc – can all be included.
We can chart the rapid rise of interest in inclusive innovation in various spheres. In the past few years, the World Bank, IDRC, GIZ, OECD and other development agencies have all launched inclusive innovation actions. India, Thailand, China, South Africa, Indonesia and other national governments have added inclusive innovation elements into their policies. And – as shown in Figure 1 below – academic publications related to the topic have been growing fast.
Figure 1: Google Scholar Academic Publications for “Inclusive Innovation”
But what exactly is “inclusive innovation”?
The growth in publications means an increasing diversity of views, which now demand some overall conceptualisation. This has two key aspects: firstly who, secondly what.
Inclusive innovation means someone is being included. But who? It must be some group that is typically marginalised within or excluded from mainstream processes of development. Sometimes this may be women or youth or the disabled or the elderly. But dominant attention has been on “the poor”; those on lowest incomes which may typically be defined as some small number of US dollars – US$1, US$1.25, US$2, US$2.50, etc – per day. (There is also the issue of who, within this group, is then to be included via the innovation: will it be the whole group or just some part: perhaps the less-poor, or the men, or the adults? This raises further questions about representation and heterogeneity and inequalities within the excluded group.)
And if (some of) this group are now being included in some way, in what are they being included?
It seems most helpful to understand the different views as a “ladder of inclusive innovation” (see Figure 2 below): a set of steps, with each succeeding step representing a greater notion of inclusivity in relation to innovation. In more detail these are:
- Level 1/Intention: an innovation is inclusive if the intention of that innovation is to address the needs or wants or problems of the excluded group. This does not relate to any concrete activity but merely the abstract motivation behind the innovation.
- Level 2/Consumption: an innovation is inclusive if it is adopted and used by the excluded group. This requires that innovation be developed into concrete goods or services; that these can be accessed and afforded by the excluded group; and that the group has the motivation and capabilities to absorb the innovation. All of those stages could be seen as sub-elements of this level of the inclusive innovation ladder, though all will be required for consumption so they are not hierarchical sub-steps (as appear in later levels).
- Level 3/Impact: an innovation is inclusive if it has a positive impact on the livelihoods of the excluded group. That positive impact may be understood in different ways. More quantitative, economic perspectives would define this in terms of greater productivity and/or greater welfare/utility (e.g. greater ability to consume). Other perspectives would define the impact of innovation in terms of well-being, livelihood assets, capabilities (in a Senian sense), or many other foundational understandings of what development is. For those with concerns about inequality, this could include a condition that the benefits were restricted to the excluded group, or were greater than those achieved by ‘included’ groups using the innovation. One can therefore differentiate an absolute vs. relative notion of inclusive impact of innovation, the latter being a sub-step above the former.
- Level 4/Process: an innovation is inclusive if the excluded group is involved in the development of the innovation. It is highly unlikely that the entire group could be involved so – as noted above – this immediately shrinks down to “members of the excluded group”. This level needs to be broken down according to the sub-processes of innovation: invention, design, development, production, distribution. These would create a set of sub-steps with, for example, an assumption of greater value of inclusion in the upstream elements than the downstream elements. Further complicating matters, the extent of involvement is equated with different levels of inclusion. Again, there would be sub-steps akin to those seen when discussing participation in development, with higher sub-steps representing deeper involvement. Borrowing from Arnstein’s ladder of participation, sub-steps can include: being informed, being consulted, collaborating, being empowered, controlling.
- Level 5/Structure: an innovation is inclusive if it is created within a structure that is itself inclusive. The argument here is that inclusive processes may be temporary or shallow in what they achieve. Deep inclusion requires that the underlying institutions, organisations and relations that make up an innovation system are inclusive. This might require either significant structural reform of existing innovation systems, or the creation of alternative innovation systems.
- Level 6/Post-Structure: an innovation is inclusive if it is created within a frame of knowledge and discourse that is itself inclusive. (Some) post-structuralists would argue that our underlying frames of knowledge – even our very language – are the foundations of power which determine societal outcomes. Only if the framings of key actors involved in the innovation allow for inclusion of the excluded; only then can an innovation be truly inclusive.
Figure 2: Understanding the Different Levels of Inclusive Innovation
The levels are akin to steps on a ladder because each level involves a gradual deepening and/or broadening of the extent of inclusion of the excluded group in relation to innovation. In general each level accepts the inclusion of the levels below, but pushes the extent of inclusion further. Thus, for example, those concerned with inclusion of impact accept – necessarily – the value and actuality of inclusivity of intention and consumption, but feel this is not sufficient to fully justify the label of ‘inclusive innovation’.
The corollary is that a commentator standing at any particular step of the ladder would not regard views or practice at lower levels to represent true inclusive innovation. Taking the example of those at the base-of-the-pyramid as the excluded group, commentators at Level 4 would feel innovation is only inclusive if those on low incomes somehow participate in the innovation process; perhaps typically in the development of the new good or service. A new good or service which benefited the poor without this (i.e. an innovation at Level 3 developed non-participatively by a large firm or by government) would not be regarded as an inclusive innovation.
One may also detect a move from the positive towards the normative in ascending the ladder, with a decreasing number of real-world examples as one ascends. Thus there are many examples of new goods and services which are developed and consumed by excluded groups, some of which have a beneficial impact. Involvement of excluded groups in innovation processes is not frequent but it does occur. However, one may be harder-pressed to find examples of structures let alone widely-shared knowledge frames in practice: these levels may represent aspirations more than realities at present.
Armed with the ladder model, we will find that dialogue, research, policy-making, practice, etc. are easier to achieve because all parties have the basis for framing their own understanding of inclusive innovation, and that of others.
However, this is just a first attempt. So comments or pointers to other conceptualisations of inclusive innovation are welcome.
(This model and related text are extracted from “Inclusive Innovation: Definition, Conceptualisation and Future Research Priorities” by Richard Heeks, Mirta Amalia, Robert Kintu & Nishant Shah; a conference paper for AIE 2013 which can be found at: http://bit.ly/IncInnov)Follow @CDIManchester
 Arnstein, S.R. (1969) A ladder of citizen participation, Journal of the American Institute of Planners, 35(4), 216-224
 For further details on the relation between innovation systems and inclusive innovation, see: Foster, C. & Heeks, R. (2013) Conceptualising inclusive innovation: modifying systems of innovation frameworks to understand diffusion of new technology to low-income consumers, European Journal of Development Research, 25(3), 333-355 [see also: https://www.escholar.manchester.ac.uk/uk-ac-man-scw:198318]
The dominant narrative within ICT4D associates digital technologies with positive impacts, and has tended to underplay negative impacts. What are the implications for development informatics research?
There has been a recent cluster of global evidence about negative impacts:
- Economic: online retail models are precipitating closure of high street shops. This may be more economically efficient but it is also more ‘efficient’ in terms of employment numbers, it erodes both the sense and reality of community, and large ICT-based firms have been adept at avoiding paying corporation tax. (See attached ‘thank you’ note posted by staff of closed UK photographic retail chain, Jessops.)
- Political: the excitement of the Arab Spring and its supposed twitter revolutions has given way to a situation in which the autocrats have colonised cyberspace. Moving on from the simplicities of blocking and filtering, regimes are now monitoring online communications in order to identify and then arrest, intimidate or attack opponents. Paid commentators are spreading misinformation and pro-regime messages.
- Military: killing by drone is on the increase as are the concerns about autonomy, civil use, and accountability. It is now possible to manufacture your own gun using a 3D-printer. An undeclared cyberwar is already underway between global powers.
- Social: ICTs have propelled a hypersexualisation of young people and pornification of sexual relations.
We can begin to understand this via the ICT impact/cause perspectives diagram shown below.
Unless we adopt an extreme perspective, we can recognise that in terms of impacts, it would have been equally easy to pull out a set of positive evidence about ICT. But it is positive and negative together that tell the whole story. And in terms of causes, there is no simple relationship between the technology and the impacts identified above but, instead, a socio-technical foundation.
This leads to a number of implications for the academic field of development informatics:
Balance: are we balanced enough in terms of the impacts we associate with ICTs in our work? Pushing a largely positive narrative can have the effect of making our work seem like hype; a relentless monotone buzz to which those working in development become habituated, and start to ignore.
Preparation: are the policy makers and practitioners who use our work prepared for what’s coming? Development informatics research needs to engage with the negative impacts, providing research users with an understanding of those impacts and, where possible, some strategies for amelioration.
Analytical Tools: do we understand what is behind these ICT trajectories? ICTs are not the direct cause of the impacts outlined above; they are an enabler of particular economic and political interests. Development informatics needs to ask the age-old question: cui bono? Who benefits when high street shops close? Who benefits from cyber-repression? Who benefits from printed guns? Who benefits from pornography? Cui bono is answered by the analytical tools of political economy. We need to be answering those questions and using these tools a whole lot more in development informatics.
Advocacy: how do we engage with ICT4D innovation trajectories? Even as it becomes more open and more decentralised, the trajectory of innovation can still be shaped by debate, by advocacy and by activism. Development informatics has always been an engaged area of academic endeavour, not stuck in the ivory tower. We have often worked with those seeking to deliver the positive impacts of ICT4D. The challenge now is to work more with those seeking to avoid the negative impacts of ICT4D.
If you see other implications, then let us know . . .Follow @CDIManchester
Why has M-Pesa been so successful in Kenya, yet mobile money initiatives in other developing countries much less so? Recent Centre for Development Informatics research can help provide a systematic response.
M-money services have two core functionalities. Registered customers can convert between e-cash and real cash (typically at the physical premises of an m-money agent), and can transfer e-cash from their account to that of another account holder via SMS. They might use this to send money to family members or friends, or to pay a provider – anyone from a taxi driver to a local school – for goods and services.
M-Pesa was launched in Kenya in 2007. It has grown spectacularly: in mid-2012, there were 19.5 million m-money users in Kenya (83% of the adult population), transferring nearly US$8 billion per year (equivalent to 24% of GDP) – M-Pesa is responsible for more than 90% of these transfers. Transfers are growing at nearly 40% per year.
It’s not that m-money initiatives in other developing countries have failed: there are an estimated 250m users of m-money services in emerging markets. Just that they have not – yet – succeeded on anything like the scale of M-Pesa, with Kenya accounting for 30% of all emerging market m-money transactions in 2011. For example, a recent survey in South Africa found only 16% of respondents with a mobile money account. In Nigeria, only 3% of adults use mobile money. And Africa is the lead continent: outside the Phillipines, m-money has been very slow to catch on in Asia. In India, for example, Nokia quit the m-money business in 2012 after two years of failing to build a critical mass.
How do we explain the differences? University of Manchester research, based on six months of primary fieldwork conducted by Chris Foster, analysed the reasons M-Pesa has grown so fast in Kenya; reasons summarised in the model shown below:
Ongoing support from government – liberalisation of the mobile market; investment in infrastructure; light-touch regulation; facilitation of the initial pilot, etc – combined with strong consumer demand across all strata of society (itself partly fed by the instability and disruption following the disputed 2007 elections). These drove a virtuous circle:
- Competition between mobile sector firms pushed them to seek profits beyond the traditional middle-of-the-pyramid; answering the demand from the majority market of the country’s poor.
- The service was delivered via atomised distribution networks that reached right down into poor urban and rural communities; a network of nearly 50,000 agents by 2012.
- Those embedded intermediaries – essential in scaling any innovation to reach the base-of-the-pyramid – were given the flexibility to adapt business models, retailing patterns and service offerings so they met the specific and heterogeneous needs of their local customers. Effective knowledge channels allowed these innovations to filter back up to the lead firms, which then scaled those they found most useful; fuelling yet further growth.
Armed with this model, we can analyse the m-money weaknesses in other emerging markets. For example:
- Much lower levels of customer demand (put down to both culturo-institutional factors and more effective functioning of and access to existing financial services) combined with a more stringent regulatory regime are behind the slow growth rates in India.
- A much smaller number of intermediaries (agents) and a lack of innovation (e.g. to address cash float problems) is restricting growth of m-money in Uganda and Tanzania.
- Tighter regulation and the much small number of intermediaries has held back expansion of mobile money services in South Africa.
We are not the first to try to understand the different performance of M-Pesa vs. other countries (see e.g. Wolfgang Fengler, Amaka Okechukwu who both also note the value of Safaricom’s market domination). However, we hope that our model provides a clear and transferable framework for comparison, that can be used alongside more in-depth evidence from other countries to help understand their relative success or failure in mobile money.
If you see ways in which you think the model should be modified – based either on experiences in Kenya or elsewhere; then let us know . . .Follow @CDIManchester
If you don’t already know it, Raspberry Pi is not a low-cost computer. It’s an ultra-low-cost computer (see photo below). And it was the subject of a recent demonstration and discussion workshop (see links for video) for CDI members in Manchester. This focused on the development-related potential of Pi and its add-on interface ”Pi-Face”, which is being developed at the University of Manchester by Andrew Robinson.
Although credit card-sized, Pi is a fully-functioning computer. Hook up a keyboard, mouse and monitor and away you can go with Linux and, for example, OpenOffice. And, as noted, it is ultra-low-cost. The actual production costs will depend on scale, with the economics catching even Raspberry Pi Foundation – the non-profit creators – by surprise. Expecting they might eventually ship around 10,000 Pis, they have already shipped more than one million.
At those sorts of production scales, costs for Pi could be reduced to around the US$15-20 mark. Adding a keyboard, mouse and Pi-Face will stack less than US$2 on top, and looking at similar products it is likely that a small screen can be produced for US$15. Of course, cost is not the same as price but we are talking of a complete computer system that will likely cost less than US$35 to produce and perhaps US$50-60 to buy. Just the Pi-plus-Pi-Face combination could be supplied to developing countries for as little as US$25.
In many ways, its key attributes are those of a mobile phone (not surprising since it runs with the same ARM chipset you’ll find in many mobiles):
- Very low cost puts it into the category of “semi-disposable” device, and a ready addition to many other innovations without breaking the bank.
- Its robustness and low maintenance requirements make it particularly suitable to harsh developing country environments.
- Its small size and portability make it suitable for applications that other computers can’t reach.
- It has very low power consumption, so can work more easily in electrical off-grid environrments.
But it’s not a mobile phone, and you can’t use it for calls and text. What it does do is connect readily to a host of other devices. And, unlike a mobile phone, it is easy to customise, using common open source software and “tinker-able” hardware components. All run by a .org not a .com organisation.
Raspberry Pi may just fizzle and die, without much effect on international development. But the potential is certainly there for it to paradigm shift ICT4D. The mobile phone explosion has shifted ICT4D’s emphasis towards the “C”, with widespread acceptance that “m-development” models will dominate. Raspberry Pi could shift us back towards the “I”; towards the computing and data processing and automation that were the origins of ICT4D in the 1970s and 1980s but which have fallen by the wayside.
At present, Pi is a solution looking for development problems, but three application areas spring to mind:
a) Micro-enterprise and household computing: providing access to standard computing applications not for the community but for the individual enterprise and household. Add an Internet connection and we might call it not OLPC (the One Laptop per Child initiative) but OTPH: a one telecentre per household approach that moves us beyond community computing models.
b) Technical education: the prime motivation behind Pi was to reignite interest in computing as a subject among schoolchildren. There’s a great thirst for IT education in schools, colleges and universities in developing countries but budgetary constraints are a major barrier (see earlier blog entry on revising computing curricula in Africa). Pi can help to overcome those – the possibility is that it could do all the OLPC does at half the price, and allow kids to open the box and play about much more, learning how IT works.
c) Data collection and automation applications: there’s a trickle of new electronic applications for development – smart motor controllers that save power and extend motor life, low-cost health monitors, water quality and climate change measurement devices, field-based agricultural sensors. Raspberry Pi could turn that trickle into at least a stream if not a flood.
The promise of Pi, at root, is to enable a new ICT4D innovation paradigm: one in which Pis are widely used and understood within developing countries, and in which grassroots innovation is really possible for the first time in the ICT4D domain (see earlier blog entry on grassroots ICT4D innovation). There’s no reason the same informal sector micro-entrepreneurs who now fix mobile phones can’t also work with Raspberry Pi. But they can customise and adapt this technology much more than they can a mobile phone. It can therefore be appropriated far more by the base of the pyramid.
Pi also allows a new model of collaborative innovation: that done working alongside base-of-the-pyramid consumers. Large firms, university departments, social enterprises can now afford rapid, mass prototyping – trying out and iterating quickly through many different models until they find one that works.
As yet, of course, this is promise not reality, and one can foresee plenty of issues around everything from distribution through support and training to growth in e-waste. But the international development impact of Raspberry Pi – good or bad, large or small, paradigm-shifting or incremental – is up for grabs. Over to you.