Less speculative is the cost to the operator of sending an SMS.  I have written previously on the egregiously high cost of sending SMSes in Africa.  However, to add insult to injury, in at least 17 African countries, operators charge an interconnect fee for connecting with other operators nationally.  In many cases they are doubling even tripling the cost of sending an SMS.  The argument for levying an interconnect charge is based on the need of the operator to recover the costs of terminating a call or in this case an SMS on their network.  But let’s face it, the incremental cost of terminating an SMS on an operator’s network is effectively zero or near enough to zero to as to make no difference.  In many countries, including South Africa, there are no internal interconnect fees for text messages.  So here is a list of the most egregious offenders:

Mobile Costs

In order to relate mobile charges directly to income, I needed data that hadn’t already been converted into USD or similar.  This mean going to the operator’s websites for data.  Obviously there are hundreds of different rates and packages for mobile access.  I started by choosing the operator with the largest market share in the country.  From that operator, I chose one minute of air time during the day i.e. prime time and outside of the mobile network.  I was in some doubt as to whether to choose outside to the fixed line operator or outside to other mobile operators and went with the latter assuming it would represent the widest possible access.  I deliberately chose off-net calls to bring in the issue of interconnect fees.  This represents about the most expensive local call you can make in a country.

Minimum Wage

As I mentioned, the ILO were kind enough to point me at a spreadsheet they maintain which has a fair amount of data on minimum wage in African countries.  They have up-to-date data from 24 countries.  However, as we start to unpack things, there is some complexity here that I haven’t fully processed yet.  For instance, when I looked for data for Kenya (which was absent from the ILO data), I found this article which mentions two minimum wages, one for urban and one for rural agricultural workers.  In South Africa I know there is a specific minimum wage for domestic workers.  I would like to focus on the lowest wage earners but it is challenging to try to pick something that is consistent across countries.  I also thought of nurses wages or a day labourer’s wage.

Another assumption I made was that people work five days a week.  The ILO data gave a monthly wage but I  wanted a daily wage for the index so I divided by the average number of working days in a month (22).  I’m not sure whether this is a fair assumption at the bottom of the pyramid.

Needless to say, I welcome corrections and insights here.

Number of SMSes a days work will earn you at minimum wage

Number of call minutes a days work will earn you at minimum wage

Magazines like The Economist have embraced the miracle of mobiles (see their recent special report “Mobile Marvels”) and among development agencies, adding the letter “m” for mobile to existing initiatives e.g. m-health, m-governance, m-learning, etc has become the latest in tech-savvy development.  Unfortunately not enough attention has been paid to two significant downsides to the current status of mobile infrastructure in Africa, namely uncompetitive telecommunications markets and walled garden practices by mobile operators.

1.  Uncompetitive Markets

Mobile markets are dominated by incumbent operators and are typically uncompetitive and overpriced.  Telecommunications regulatory expert Ewan Sutherland neatly summarises the issue:

A very small number of market players, protected by high politico-regulatory barriers to market entry, can easily result in price shadowing and even in collusion. Analyses of the markets for mobile call origination in France, Ireland and Spain have illustrated this problem, despite operators competing on the market for some years. In the case of France there has been shown to be collusion between the three operators, resulting in heavy fines (Conseil de la Concurrence 2005). To date, there has not been detailed analysis of markets in Africa, nor the regulatory action to remedy the lack of effective competition.i”

African countries still lack detailed market analyses that could lead to regulatory action but we know enough to suggest that such analyses are needed if prices are to be brought down.  By any standard, mobile markets in Africa are uncompetitive.  Vodafone and MTN, two of the largest operators in Africa, command on average more than 50% of the market in the nearly 20 African countries in which they operateii.  Safaricom, the largest operator in East Africa, holds more than 80% of the mobile market in Kenya.

Evidence from the pan-African research network, ResearchICTAfrica, points to a remarkably high percentage of income being spent by the poor on mobile services.  For low income earners across 17 countries studied, the average African is paying more than 50% of their disposable income on mobile services.

At the same time, mobile operators are posting impressive profits.  Kenyan operator Safaricom generated over 900 million USD in revenue last year of which a staggering 40% was Earnings before Interest, Taxes, Depreciation, and Amortization (EBITDA).  Other operators are also posting impressive profits with most operators on the continent announcing year on year increases in revenue.

The startling contrast between the remarkable benefits of mobile infrastructure and the high price being paid for mobile services in Africa while mobile operators post record profits leads to the conclusion that more competitive mobile markets in Africa would lead to even greater social and economic benefit for all but especially the poor.

2. Walled Gardens

Most of the discussion of the benefits of mobile infrastructure focuses on the increase in efficiencies that access to communication can provide.  What is not often discussed is the environment for innovation and entrepreneurship that mobile infrastructure can provide.

There have been some significant innovations with mobile services in Africa.  The most significant one is the development of mobile banking and money services such as mPesa in Kenya.  This and other similar innovations are largely top-down from the operator and have been slow to evolve in spite of the obvious demand.  What is missing on the continent is end-user innovation of the sort that leads to serendipitous discovery of social and commercial services.

In Africa, mobiles are too expensive too encourage the kind of experimentation that leads to innovation. Consider that in Rwanda, 4 minutes of local mobile communication or 10 SMSes constitutes an entire day’s wage for a labourer.  While this is expensive, it is obviously useful enough to spend a significant proportion of income on its use for essential calls.  What will never happen in this context is the kind of playful use that happens when one doesn’t have to consider the cost of each call and each SMS.

The cost of SMSes in particular are a barrier to innovation because they represent a gateway to the Internet for every mobile phone no matter how simple.  Because an SMS message carries data, it offers the opportunity to extend the reach of Internet applications whether for data collection, commerce, social networks or other innovative services.  Yet SMS services represents the most profitable aspect of mobile operator networks.  SMS charges are estimated to be between 80 and 90% profit.

However, it is not just cost that is a barrier to innovation.  Mobile operators jealously protect their mobile services and use them to help lock users on to their network.  It is impossible to launch a mobile service across mobile networks without negotiating access with every mobile network involved.

This is in stark contrast to the generative environment of the Internet which has spawned what are now some of the largest companies in the world (Google, Facebook, et al) from the minds of individuals who developed these services without huge corporate backing and in markets that did not exist until they created them.

If we were able to drive down the barriers to mobile voice and SMS use through reduced cost and more Open Access style networks, individual and small-business innovation in the delivery of novel voice and data services would very likely blossom on the continent.

So What Can We Do?

When I initially chatted with Katrin about Fair Mobile, what I had in my mind was an index of how fair mobile markets are in various countries.  Now the ITU already maintain an excellent ICT Development Index but I was thinking of something simpler and more focused, something like the Economist’s Big Mac index which uses the cost of a McDonald’s hamburger as a proxy for purchasing power parity (PPP) but perhaps even closer might be the Alternative Big Mac Index which measures how long one has to labour in a given country to earn the price of a Big Mac.

So what would that look like?  Well, what initially sent me down this path was Nathan Eagle’s description of nurses in Kenya and how they refused to send SMS updates to an online blood bank database simply because the cost of an SMS represented too significant a proportion of their daily wage.  Since then Katrin and I have discussed various indicators and metrics that might best make up a Fair Mobile Index.  Armed with these ideas, I went off a couple of weeks ago to the IDRC’s Acacia Research and Learning Forum 2009 in Dakar and had the opportunity to organise an OpenSpace session on Fair Mobile at the event.  About a dozen people attended the event, including among others, Alison Gillwald, Christoph Stork, and Godfred Frempong of the ResearchICTAfrica network as well as Willie Currie from the Association for Progressive Communications (APC).

We discussed the basic dilemma of the high cost and closed nature of mobile networks and brainstormed a number of factors that affect equity in mobile access, including:

• transparency and market complexity
• number portability
• tariff complexity and transparency
• issue of quality of service:  dropped calls, network coverage, voice quality, etc
• demand perspectives – cultural influences on usage
• taxation issues both on handsets and on usage
• the need to establish mobiles as a generative platform for innovation
• foreign ownership
• interconnection rates

A Simple Ratio

In the end, Alison suggested that it might be simpler to start with something very basic such as the ratio of basic mobile costs to the national minimum wage in a country.  Discussion followed on how to get the average cost of mobile and the suggestion was made to take a minute of peak time use on the largest operator in the country.  In the end, I propose to take 2 minutes of air time and 4 SMSes as the proxy which hopefully represents what might be a typical day’s phone use.

Obviously this simple ratio of mobile usage cost to minimum wage only begins to scratch the surface of Fair Mobile but it seems to me now that it is better to start with something simple and easily understood and refine it over time rather than try to come up with the perfect basket of indicators.

The next thing I think I would like to add is the percentage EBITDA of the largest operator in the country.  This would add a sense of proportion or disproportion between what people are paying and what sort of profit the operators are making.  More complex will be developing a metric around the “thickness” of the walled gardens.

So stand by for more as I start to compile some of this data.  I’m hoping that AfricanSignals will prove an ongoing useful resource on mobile pricing.

Finally, I should emphasise that these are just emerging thoughts on Fair Mobile.  I reserve the right to recant, adapt, and evolve rapidly.