The world has woken up to the fact that Data Analytics has the answers to plaguing questions in every industry. Businesses seek the relationships and dependencies between seemingly independent entities. This helps business strategists optimize costs and improve efficiency. The shipping industry has major interdependencies and the outcome requires a lot of organizations working in tandem. Right from the moment the consignment is booked through a shipping carrier, it changes hands, changes places and times to reach the destination. So, Big Data Analytics is of much use in this industry.
Strategists now study logistics industry and individual companies, from modelling, optimizing rail, truck and cargo movements across places to greater visibility of freight movements, improved freight connectivity and of course, the pricing strategies. Shipping carriers have floating price schemes based on their optimization parameters. Data analytics helps you decide how to optimise shipping budgets from your end based on fluctuating costs.
Shipping costs fluctuate seasonally according to several factors. Demand is high during December holiday season when e-commerce organizations run pillar to post with their order fulfilment. Demand is very low during summers when people vacation outside their homes. So, if you run an ecommerce platform, you can strategize your operations for the peak season or the lull season well in advance with the help of Data Analytics. Remember that Big Data, true to its name, analyses everything from transit times, fuel costs, insurance and weather conditions to non traditional data like traffic delays, manmade delays, unexpected repairs, GPS relays, sensor relays and traffic management.
While Big Data helps you see problems, you can make use of it from your end to pre-empt problems. For example, if Data points to bottlenecks during the peak season, you can strategize and probably deal with it somehow from your end. You can decide on when to run your discount sales and free shipping offers from your site based on what you study. Do you want to figure out when to offer fixed shipping rates, free shipping or actual shipping rates? Learn to optimise that from studying big data.
You can reduce errors effectively with data analytics. Several packages are lost, redirected or damaged when in transit. Past data and conditions that led to such situations can greatly help you reduce the incidence of such errors. While you, as an end user of a shipping carrier cannot do much to eliminate package losses directly, you can get to know when to insure your packages and when not to. Also, refer this blog on How to get a handle on your lost packages?
So, like with most other industries, shipping and logistics organizations are looking at big data to ease out their pain points and they are traveling in the right direction with this move.
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