A connected world — How IoT and Data- Driven decision making are changing the logistics landscape in India
Imagine a world where your living room mirror shows you your open chats, calendar events and weather updates, where your online purchases get delivered to your vehicle or where you can text your car and ask it how much fuel it has left. Innovations such as these are not scenes from your favourite science fiction show but are in fact real life products that harness the power of an increasingly connected world.
The network of physical objects connected via sensors ranges from household appliances to vehicles and even heart rate monitors. While the Internet of Things is capable of amazing advances and innovations for the common man, the stream of ambient data and related insights that businesses can achieve is what really excites us here at Shipsy.
With the massive increase in penetration of smartphones and availability of cheap hardware such as GPS modules, RFID sensors etc, organizations now have a multitude of sources generating data 24*7. Making sense of all this data, deriving insights and analyzing this makes up a huge component of another buzzword — Big Data.
The inclusive power of data driven decision making
Contrary to popular perception, big data and analytics are not tools solely to be used by big tech names. By studying historical trends, value can be created even for the smallest of businesses. A lot of decisions taken by small & medium businesses are based on intuition — who is the best employee? Which kind of tyre works best for your trucks? Which vendor is the most effective? This is where the power of data driven decision making comes into play. What small organisations have may not necessarily qualify as big data but that’s not a bad thing! It makes it even simpler for them to use their data, however the more data, the better (statistically significant) the models become.
Logistics and data driven decision making
The supply chain and logistics industries are unique because of the sheer number of moving parts and stakeholders. Across the different stages of first mile, middle miles and last mile a single shipment changes hands dozens of times and this happens for millions of shipments. Keeping track of all these shipments, ensuring that they are delivered on time while simultaneously keeping an eye on efficiency and costs is a logistical nightmare (no pun intended). With the rise of ecommerce, new challenges such as next day delivery, reverse logistics etc have entered the equation.
Any big challenge, however, carries with it big opportunities. Favourable macro factors have driven Indian logistics companies to take up a slew of initiatives to organize themselves and increase efficiencies. As customer expectations have risen, Indian companies have taken initiatives to serve them and retain market share.
India’s logistics sector is highly fragmented with a large number of small and unorganised players. Some bigger Indian logistics firms have taken steps along the path to digitization where all their systems are online and have functioning ERP systems. However, not many companies have taken initiatives to leverage the data that these processes creates. They generate vast amounts of data but often do not learn from past trends.
That being said, a few players are taking active initiatives to connect themselves and their resources to the IoT and reap the benefits. GPS sensors on trucks provide much needed in-transit visibility, real time tracking, route deviations etc and allow people downstream in the supply chain plan for delays. They are able to manage inventory better when they have full visibility on the arrival times of further stock.
A leading logistics company has linked its GPS systems to its ERP so that it can track its shipments through a single software. Sensors in the weighing machines for shipments have also been connected and feed directly to the software. Western practices such as Geo-fencing have been implemented, where an alert is sent when a truck enters into the geo-fenced area around a warehouse.
However, there is a growing problem of cognitive overload. With so many devices and sensors generating data constantly, there are just too many things to look at. The really important thing now is to look at the most important aspects first. Data visualisation techniques or actually even AI can make it simpler and serve the most relevant data to generate insights. Just like gmail gives out the most important emails on top or how its inbox bundles promotion emails.Not many people talk about it but this is a big problem of big data, IBM has even added the 4th V in big data (apart from volume, velocity, variety) i.e., visualisation.
How UPS harnessed the potential of big data
While trying to optimizing UPS’ strategy for deliveries — by reducing idle time spent in traffic, finding routes with least amount of stoplights etc, UPS researchers designed a system called Orion. Orion — On-Road Integrated Optimization and Navigation used 1,000 pages of code to analyze 200,000 possibilities for each route in real time. One of their major findings was the inefficiency of left turns. By essentially going against the flow of traffic in the US, UPS vehicles were wasting time and fuel money from idling. This led them to make one simple rule — to minimize, or if possible, eliminate left turns. Even though this meant drivers would often travel a greater distance, results showed that more packages could be delivered in less time with a reduced amount of emissions by driving in a series of right-hand loops.
As a result, between 2004 and 2012, UPS saved 10 million gallons of gas and carbon emissions were reduced by 100,000 metric tons (the equivalent of pulling 5,300 cars off the road annually). It also saved the company 98 million idle minutes or about $25 million worth of labor cost each year. In other words, this one simple change increased profits, met customer demands, improved safety and positively affected the environment.
Conclusion
While Big Data must not be interpreted as a magic cure, data driven decision making holds the potential to create lasting value for companies. The adoption of analytics is steadily increasing but companies must be patient before they can reap the whole return on their investment. It is after all no coincidence that five of the biggest companies in the world (Amazon, Google, LinkedIn, Microsoft, Apple) share the common traits of large-scale network effects, highly data-centric company cultures, and new economic value-added services built atop sophisticated analytics.
Source:
UPS Case Study
http://businessintelligence.com/big-data-case-studies/ups-uses-big-data-every-delivery/
DHL trend report on IoT
http://www.kdnuggets.com/2015/01/debunking-big-data-myths-again.html
