How Search Engines technology can solve Africa’s mass-transit mess
Mass Transit seems to be an unsolvable problem in emerging markets. Every city has its inglorious stories of informal transport struggles and endless traffic jams. This exceptional post by Greg Lindsay perfectly described this reality:“First hacked together more than 70 years ago and manufactured nowhere else outside the Philippines, the ageless, endlessly patched jeepney is both an icon of national ingenuity and testament to its utterly dysfunctional public transportation”. Beyond South-Asia, urban citizen from Nairobi will recognize their Matatus, from Dakar their “car rapides”, from Douala their “bendskins” etc…
Public transport operators have failed and myriads of informal buses, mini buses, shared taxis, motorbikes, tuktuks have taken over, without being able to fully meet this ever growing urban demand.
Depending on whom you ask, suggested solutions range from more regulation, more roads/infrastructure, imported BRTs with GPS tracking, to cashless fares. A couple of years back, some players (including Safaricom, Equity Bank and Google) engaged in a battle against cash in the mass transit sector in Kenya. Despite the incredible penetration of Mobile Money and strong government support, the “cashless matatu” initiative did not really take off. Paying or getting paid by mobile does not seem to be the key problem that keeps the Public Service Vehicle (PSV) sector up at nights.
The Matatu Driver is the most critical player
The trouble with typical suggestions, is they ignore one of the most critical players in this ecosystem: Matatu drivers. Every bad ride experience story or road incident news seem to point to the irrational drivers. Strangely, none tries to understand the root causes of their behaviors. Why do they keep riders waiting for hours inside the bus before departing? Why do they stop every few miles to pick riders along the road or force riders into another bus in the middle of the journey? Why do they race between some stops, sometimes causing accidents?
The reality is that drivers are “blind” when it comes to assessing demand. They have no idea about the demand accross the route. Therefore, they guess and try any tactic to meet their daily earning target at the expense of riders’ experience”. Before adding more roads, regulations or cashless just because mobile money is available, the solution to the mass-transit in Africa, should start from leveraging actual demand data. By analogy, this is exactly what Search Engines are all about.
Lessons for Matatus from Google’s Search Engine
Today, search engines look more like a commodity. A blank box on any browser, that provides speedy and relevant answers to queries, without ever failing. A lot has been written about Google since the 2000’s, but no link has yet been established between web search and mass transit.
The “portal wars” few decades back, between Yahoo, Lycos, AOL etc …did not consider search as a key weapon. All what mattered was keeping web users in one’s portal and feeding them with private content (almost like social networks today). Displaying search results and links that routed them out was out of question. As the sprawling web continued its exponential growth, finding accurate results started to become a major issue. Many portals such as Yahoo! started building curated directories, organized in themes to cover more and more sectors. When you searched on Yahoo!, hundreds or thousand answers would be displayed in no particular order. Additionally, the directory was very far from being comprehensive (some search engines could not even find their own names as a keyword).
What later became Google started from an attempt to search the entire web (not just private directories) and display the results with some priorities (relevance dimension). In scientific research and publications, the importance of a paper is directly derived from its citations (number of times the paper has been cited by other scientist papers). Google founders mimicked this approach and started ranking each website based on the number of other websites linking back to it. This is how PageRank started, along with BackRub, the search engine derived from this ranking method. The rest is history!
The early BackRub approach applies to real world mass-transit. Just like the web, cities are dynamic collections of millions of more or less busy places (hotspots). The “importance” of a place is directly related to the number of trips heading to it. Some places get trendy over time while other fade to irrelevance, as the city evolves and grows. Just like web back-links, for a given place: school, stadium, airport … it is possible to determine the top departing places that are “feeding” it in traffic.
Urban planning & regulations, road & infrastructure design, real-estate development and mass-transit dispatch should actually be built from the ground up, from this data
In the trendy ride hailing sector, this is the primary why taxi drivers are paying 25% to Uber: ability to find riders quickly, at proximity vs randomly wandering across the streets to find riders.
In reality, transport has its own complexities but in general, the chaotic mass transit in emerging markets can be “solved with a dispatch” inspired from Search Engines’ original ranking, itself derived from scientific paper citations.
Keep with us for the next steps at -> aywamarkets.com
