Logistics is a complex and dynamic sector that is evolving with the use of data by gathering valuable insights that promise to benefit corporates and consumers alike
With the advent of e-commerce and increasing globalisation, smooth logistical operations are responsible for the hassle-free running of supply chains and ensuring that consumer demand is met.
The logistics sector has been an ever evolving one to the challenges it faces almost everyday. For instance, efficiency and speed of logistical operations determine if finished products can reach customers on time and maximising their utility. Without this, there may be delays that trickle down to the end consumer and lead to significant price hike or even impact company profitability, similar to what we are witnessing in the post pandemic world today.
Data Analytics can help the logistics industry consolidate heaps of fragmented data and structure them to provide valuable insights that can support the overall economy. Here are few ways data can be used to improve sector productivity.
Performance management
Logistics companies spend millions every year to optimise their operations and solving inefficiencies along their supply chains. Data can help employees with insights that can be converted into actionable results. For instance, optimisation of resource consumption or delivery routes can allow warehouses to be ready for shipment arrival and maintain schedules by reducing wasted time. Data can also flag inefficient nodes in the supply chain to managers to replace or enhance them, thus improving the overall performance of logistical operations.
Order processing
The more orders, the more revenue and profit. However, if order processing is inefficient, the entire revenue process can suffer leading to lower profitability and likely higher prices for products. With Data Analytics, data is integrated into order processing that frees up space for more orders. Such data integration can lead to higher revenues.
Forecasting
A crucial aspect of logistics is forecasting demand and supply to facilitate the movement of goods. An accurate determination of demand and supply is only possible through Data Analytics. Peak demand, supply chain disruption, economic cycles, etc can all be predicted using data. Such insights can massively help inventory management and anticipating and planning shifts by understanding supply and demand. This could lead to significant improvements in profitability of a company.
Digitisation
The endgame for the logistics industry is to become automated such that, digital platforms remove any supply chain inefficiencies, improve demand-supply prediction, increase asset productivity and increase transparency throughout the chain. Such a system can help stakeholders remain connected to the entire supply chain, adopt optimal pricing strategies, improve routes and provide superior customer experience. Moreover, with automation at the core of all operations, internal business processes will simplify the labour-intensive operations and get rid of manual processes and increase overall transparency of operations.
Data Analytics is significantly impacting practically every industry while giving rise to new ones. The logistics industry presents an ideal case for data to transform the industry given its complex nature of operations and the number of nodes present. By creating digital and more automated logistical operations, Data Analytics can innovatively transform the sector to have more robust operations and applications for a more sustainable logistics industry.
