A part of the GIGA map explaining the waiting scenario at the AMTS bus stop. Some interesting insights have been mapped in the given section. Let’s take one case: It starts with visibility of the bus number. As the size of the number is small, the visibility is low. As a result the commuters waiting at the bus stop end up standing in the bus bay area instead of the bus stop structure itself, as it helps them read the number within the few seconds of visibility. This now makes the approaching bus, stop on the road instead of nearer to the footpath, creating obstruction for other traffic, leading to chaos. Another factor related is the Autos standing near the bus stop. They also end up obstructing the smooth passage of the bus. Now one additional factor – the poorly maintained bus stop structure adds more reasons to standing on the road.
Now what has been explained above is a complex interconnection of different factors leading to discomfort and inconvenience. These became our insights. These were the issues which we understood when we GIGA mapped and zoomed out to get the bigger picture. This is where systems thinking was sinking in.
Finally after a lot of editing and refinement we were ready with our final Giga map. A 7-foot long map with all the information along with the statistics we had. The map was a linear time based map with the commuter journey mapped from left to right. At every point in the journey, the different insights we gained over the weeks were noted down and put in the final Giga map.
Link for zoomable version: http://prezi.com/ewzsmq6gsdje/?utm_campaign=share&utm_medium=copy&rc=ex0share
Active and disguised waiting are two different kinds of waiting types we came across. Active waiting is, simply put, when you ‘experience time’. When you are waiting for the bus at the stop, when you are waiting in a line to get a ticket, you are waiting and feel impatient. This is usually the waiting that we experience and identify the most. However another kind of waiting is ‘Disguised waiting’, where you are usually in transition from one place to another. The difference is clear with an example – say you are in an elevator going to the 12th floor. You are waiting – ‘waiting to get to 12th floor’. However you don’t identify this usually as waiting as you are moving and getting somewhere. Another example is travelling in a bus, when you are moving fro one stop to another.
Some general trends were observed around the different active and disguised waiting times all throughout the journey of the commuter and represented as shown.
We mapped the different actions against the different elements of a bus system. This helped us see the different mash-ups which can give us some interesting ideas. For example – when you take any 2 terms in the map, say ‘Ticket/Token’ + ‘Footpath’ you can come up with interesting options – say if we have the ticketing station on the footpath instead in the BRTS bus stop (which is in the middle of the road), it will help people to enquire/decide without crossing the road, making the experience much better.
Another example – ‘headphones’ + ‘seating’ – here we are looking at one common activity in the bus during the commute- people listening to music via headphones and one integral element – the seat. What if the seats had headphone jacks which play different local radio channels with recurring announcements about the coming stops and other info like connecting routes. Such ideas came up after this map helped to see these connections.
The linear mapping done earlier was extended to the complete timeline with more interconnections and insights. The original mini map became the starting point and the second map was built around it.
The entire journey of the commuter gets covered from left to right. Different aspects like belongings, active waiting, card/tickets, signage, BRTS/ AMTS are all factored into the map. Basic differences between AMTS and BRTS due to the on and off bus ticketing led to separate parts on the map for each.
All the information we had was quite scattered – it was a collection of observations and some insights. We then were explained the concept of Giga mapping – GIGA-mapping is super extensive mapping across multiple layers and scales, investigating relations between seemingly separated categories and so implementing boundary critique to the conception and framing of systems. Source:
some interesting examples of Giga mapping –
So then we decided to sit down and make different connections with all the information we had. For this, we had to pull out all the observations, waiting psychology notes, the Indian scenario notes, online research and then put it all together in one map. When we started the first decision came easy – deciding the format of the map – a linear time based map – as both waiting and bus systems are well represented.
However then making the giga map was not at all a simple task. Here is the first rough draft of the same –
Four of us were by now well aware of the experience of typical Ahmedabad AMTS & BRTS commuter. Ideas and different approaches to the issues had slowly started coming to our minds. So we simply put all these down on a sheet. We simply put all the things that came to us, as we can then refine any idea as we go ahead.
Different approaches – Gamification – further led to many ideas and solutions. We also started to diversify a little by also looking to issues related indirectly to the waiting scenario like – Appeal higher classes, Utilization of road exclusivity, Driver training. However it all at the end had to lead to a better commuter waiting experience.