Should we have a “95:5 rule” for ICTs and development?
Typical consumption-related uses of ICTs touch 95% of people but make only a 5% difference to their livelihoods. This covers “intensive” application of ICTs: their use to intensify an existing livelihood. Examples include use of mobiles to bring market information to farmers; access to e-government at a local kiosk, substituting a journey to district headquarters; use of a website helping handicraft producers sell their goods; or use of email by a retailer in a low-income community.
Typical production-related uses of ICTs touch 5% of people but make a 95% difference to their livelihood. This covers “extensive” application of ICTs: their use to extend the range of possible livelihoods, by created a new ICT-based livelihood. Examples include the umbrella people selling mobile phone calls by the street; or a worker from a poor community undertaking data entry work; or a mobile money service agent. So extensive ICT livelihoods only exist because of ICT and they fall into the ICT sector, broadly defined.
A classic example is the comparison of two studies from Kerala, India. The arrival of mobile phones in one fishing area led to an average 9% increase in profits for fishermen[1]. Given 75% of income in South Indian fishing households comes from fishing[2], that suggests ICT consumption increased household income by 7% on average. Simultaneous to this, the Keralan government was engaged in setting up an IT impact sourcing initiative, outsourcing data entry and digitisation work to groups of women from below-poverty-line families[3]. These new ICT jobs led to an average 75% increase in household income.
As with most quantitative findings, these specific figures don’t exactly match 5% or 95% but an overall average may get closer.
Let’s first take evidence on intensive use. Consumption-related evidence sometimes reports more than a 5% income increase[4]. But this must be set against other work that shows a less than 5% income increase[5] or no increase[6] or questions the limited time-scales or scope of studies that demonstrate income increases[7]. And it must also be set against the occasional study showing an exact match: “Internet users reported an increase of US$ 51.86 in labor income … 5.01% per year”[8].
Can we say that 95% of those living in the global South are digital ICT consumers? We are certainly close to that point. There were just over 90 mobile subscriptions per 100 citizens in developing countries in 2014[9]. We need to bump that down to take account of individuals with multiple subscriptions but bump it up again to take account of shared access[10]. The end result will be in the neighbourhood of 95%.
Turning to evidence on extensive use, many of those working in the ICT sector derive 100% of their income from their employment. We could shade that down overall given some with ICT-based livelihoods will have other income sources. The proportion of those working in the ICT sector is growing but typically less than 5% (e.g. 5.7% of employment in OECD countries[11] but generally much lower in less-wealthy countries[12]). As an example, India’s ICT sector represents less than 1% of India’s workforce[13] but that must be multiplied by three given the estimate that two-thirds of India’s ICT jobs lie outside the formal ICT sector[14]. But that estimate may exclude a number of ICT-based livelihoods, so the result may at least be heading for 5%. It is certainly increasing year-on-year.
Given these pulls in various different directions, an endpoint of 95%:5% is not unreasonable, and certainly all the evidence points to some form of strong Pareto-type distribution.
So what?
Mathematically, 5% of 95% has the same development effect as 95% of 5%. That means these two uses of ICTs should be given equal emphasis by governments, development agencies, development informatics researchers, ICT4D practitioners, etc.
But at present they are not. Intensive, consumption-related ICT application is given far, far more attention. In future that needs to be rectified, with equal emphasis given to digital inclusion by improving existing livelihoods; and to digital inclusion by creating new ICT-based livelihoods.
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[2] Sivasubramaniam, K. (1991) Kattumaram Fisheries and Fisherfolk, FAO, Bay of Bengal Programme, Madras
[3] Heeks, R. & Arun, S. (2010) Social outsourcing as a development tool: the impact of outsourcing IT services to women’s social enterprises in Kerala, Journal of International Development, 22(4), 441-454
[4] E.g. Aker, J.C. (2008) Does Digital Divide or Provide? The Impact of Cell Phones on Grain Markets in Niger, BREAD Working Papers (177), Bureau for Research and Economic Analysis of Development, Duke University, Durham, NC; Rizvi, S.M.H. (2011) LifeLines: livelihood solutions through mobile technology in India, in: Strengthening Rural Livelihoods, D.J. Grimshaw & S. Kala (eds), Practical Action Publishing, Rugby, UK, 53-70
[5] E.g. May, J., Dutton, V. & Munyakazi, L. (2011) Information and Communication Technologies as an Escape from Poverty Traps, PICTURE Africa Research Project, Nairobi; cited in Diga, K. (2013) Access and usage of ICTs by the poor, in: Connecting ICTs to Development, L. Elder, H. Emdon, R. Fuchs & B. Petrazzini (eds), Anthem Press, London, 117-136
[6] E.g. Aker, J.C. & Fafchamps, M. (2013) Mobile Phone Coverage and Producer Markets: Evidence from West Africa, Discussion Paper 9491, Centre for Economic Policy Research, London, UK
[7] E.g. Srinivasan, J. & Burrell, J. (2013) Revisiting the fishers of Kerala, India, in: ICTD2013: Proceedings of the Sixth International Conference on Information and Communication Technologies and Development, J. Donner & T. Parikh (eds), 56-66
[8] Galperin, H., Mariscal, J. & Barrantes, R. (2014) The Internet and Poverty: Opening the Black Box, IDRC, Ottawa
[9] ITU (2014) ICT-Eye, International Telecommunication Union, Geneva
[10] Heeks, R. (2009) Beyond subscriptions: actual ownerships, use and non-use of mobiles in developing countries, ICT4DBlog, 22 Mar
[11] OECD (2014) ICT Employment (indicator), OECD, Paris
[12] OECD (2011) Size of the ICTsector, in: OECD Factbook 2011-2012, OECD, Paris; EC (2012) Information and Communications Technology (ICT) Sector, EU Skills Panorama, European Commission, Brussels
[13] NSSO (2013) Key Indicators of Employment and Unemployment in India, 2011-2012, National Sample Survey Office, Government of India, New Delhi; Nasscom (2014) India IT-BPM Overview, Nasscom, New Delhi.
[14] Nandi, R. (2014) Decent work and low-end IT occupation workers in Delhi, The Journal of Social Science and Humanity Research, 2(1), 9-23
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