A convoy of truck recently traveled in Europe as part of the European Truck Platooning Challenge. One of the convoys traveled more than 2,000 KMs platooning where ever possible with all driverless trucks following the lead truck with a driver inside.
The driverless trucks open up several possibilities including higher utilization of inventory, lower fuel consumption (which is a bug cost) and less human errors leading to overall safety and better efficiency in the system.
This week as part of Kista Mobility Week Program, Ericsson is offering test rides of driverless buses from and to Kista Galleria in Sweden.This is a very interesting demonstration of what is possible around future transport.
The transportation industry is huge both in volume and financial terms. And it is witnessing massive disruption that will change the way people and goods get transported. I am very excited about the kind of technology, intelligence and innovation that it will require to build such a system and operate at a scale.
I am a frequent Uber customer but I always find it difficult to book an Uber cab from the Bangalore airport. The reason is simple – poor internet connectivity at the airport arrival area. Since the app does not behave well with the limited connectivity, I always end up using an alternative. This must be a problem for many other passengers as well and lost customer opportunities for Uber.
On the flip side, if I am an Uber cab driver, I will prefer not to pick passengers for airport drop-off because I will find it difficult to get a return trip from the airport. Double whammy.
What if Uber builds an airport button that can fast-track the entire booking process? Why does it need to find so many vehicles that are available, then show it on the map and then allow the booking process? That just uses lot of bandwidth and takes time. I really don’t care to see which cab I am booking. I just want to know if there is a cab that gets booked and I can head home as fast as possible. Uber can always build intelligence on the cab inventory at the airport and use it while booking.
Less internet usage with faster booking process!
For many of us Internet is all pervasive. It is essentially a medium without which we cannot imagine our present day lives. What started as a mechanism to connect several machines has grown to break political and social boundaries of the physical world that we live in.
And it has a profound impact in India too. The impact can be seen in all walks of life – banking, travel, social, politics, entertainment etc. The list is endless. However, the reach and penetration of internet is still limited to the big cities. Not surprisingly, lot of new application development is biased towards places where internet usage is already dense.
At Rivigo, we are changing that. Our business model involves thousands of people who are part of the logistics value chain to deliver business benefits to our customers. These people are connected to Rivigo technology platform from many remote places in India. Learning, understanding and using new age technology is how they go about doing their day’s job. And that is mandatory. Rivigo is making technology accessible to people in such remote places and creating a real need for them to be part of the internet.
This is what I believe is the future of internet – connecting people who are already not connected! And Rivigo is just doing that with its technology platform.
Happy new year to all friends, family and Rivigoans. Wishing Rivigo continue the disruption in the logistics industry with technology & business innovation!
Rivigo has raised $30 million in a Series B round from existing investor venture capital firm SAIF Partners. Read the detail story here
On November 11, Alibaba posted a record $14.3 billion in sales on Singles’ day passing every record that any company have ever posted. And this is just the beginning of what it means for future of logistics.
According to the Bloomberg post, Alibaba quoted
“Alibaba estimated that 1.7 million deliverymen, 400,000 vehicles and 200 airplanes would be deployed to handle packages holding everything from iPhones to underwear. Mobile devices accounted for 69 percent of Wednesday’s transactions.”
This is significant in many ways. The technology needed for building such kind of reliable logistics has to provide intelligence at another level. Imagine a constant stream of geo-location data from half a million trucks.
How will you place such large number of trucks every day? What will be the placement algorithm that will be used?
How will the technology churn data at this large scale on a low latency system? How will you design technology for such low latency?
What about the memory and server farms that will be setup? What about the failure points in the system? The system cannot go down under any circumstances because there is no way to find something missing manually – a needle in haystack!
How will you monitor performance? Nobody can watch the normal performance of 400,000 trucks. Just imagine if looking at a truck takes 1 minute, you need 400,000 minutes or around 6,666 hours or cool 277 days to monitor these trucks. What kind of user interactivity that needs to be provided with the use of technology that will make 277 days job to a less than few minutes job.
There is a disruption in the logistic industry that requires another level of technology and it is inevitable!
Image courtesy – altronshpg
At Rivigo Labs, we are building the next generation of data acquisition, processing and visualization tools that will drive changes in the logistics industry. This essentially means building a data architecture that can cater to the needs of this complex system. Here are some of the considerations that I have for data architecture that we are building –
1. Scalability – Can handle growing amount of works
2. High availability – Allows continuity of work
3. Performance – Responsive within reasonable time
4. Maintainability – Ease of making future changes
5. Comprehendible – Easy to understand
Now, there are several technology that can fit the bill for any type of architectural considerations. But how do you select the right technology?
And, I believe this is a wrong question to ask at the initial stages of designing the data architecture. The right questions to ask are – What are the requirements? How the information and data will flow through the system? What are the events in the system and how they will be generated? Who are the consumer of the data?
The idea is to be able to draw a simple diagram that represents answers to the above questions. This will help understand the functionality and complexity of the system. And at this stage, it is essential to introduce discussions on the scalability of the system. I feel this approach is extremely cost effective because the cost of changing anything is as good as changing a diagram to represent new assumptions and flow.
Once this stage is hashed out after considering exceptions and important edge cases, the time is right to think about what is the right technology to be used to build this system?
This way you are not forcing yourself to adopt to a particular technology but opening up to evaluate multiple technology that meets the design.
At Rivigo, data meets logistics and magic follows. We are transforming the antiquated logistic industry and bringing it into the 21st century with process automation, driver analytics and data science.
Rivigo is re-envisioning the truck as a Internet of Things (IoT) platform with intelligent sensors that constantly interact with a real-time responsive logistics network. We use the IoT to assist in integration of communications, control, and information processing across logistics networks that focus on all elements including the vehicle, the infrastructure, and the driver.
The charter of Rivigo Labs is to create the next generation of data acquisition, processing and visualization tools that will drive change in the logistics industry. Some of the problems we work on includes network optimization, recommendations systems, end-to-end automation, human factor design, smart trucking systems and beautiful visualizations, all at tremendous scale. We are not only pushing the envelop in the logistics industry, but we are also generating cutting edge tools in IoT, data science and people analytics.
In nutshell, we are building next generation transportation data science!
[The post is late by a month nevertheless here it goes…]
After 11 years with Adobe, it is time for me to look at new beginning with newer opportunities outside Adobe. Today, the technology is evolving to become a mainstream driver for new business model that were not possible in the past. I am very keen to get into that space, where you are not just selling technology but using it to bring about a change at a very fundamental level – change in people’s behaviour, disrupting the way things happen while creating a great business opportunity.
Unfortunately, this also mean an end to my long journey with Adobe. I will miss all the great things that I have accomplished with my team, the great friendship that I have built and building something long lasting and helping customers being successful. I appreciate having had the opportunity to work with many smart people outside and @Adobe and wish ColdFusion and Adobe all the best!
I have joined Rivigo and excited about leading logistics innovation at Rivigo. More on that later!
As mentioned in my earlier post about support hiring, one of my tasks was to get the support team off the ground for one of our products.
There are some key differences in how different functional teams like development, quality engineering and support team operate and go about doing their day-to-day tasks.
This is not an exhaustive list but this understanding has several advantages that a manager can leverage for managing the team, collaborating with others, build a rewards and appreciation strategy that can result in building highly successful teams. Managers can also leverage this core knowledge to remove any biases if they are coming from different background and have more empathy towards employee behavior and develop risk assessment strategies.