Data Analytics empowers decision-makers with real-time visual analytics using spatiotemporal data streams. Through an immersive logistics analytics dashboard, transportation & shipping companies can optimise routing, identify bottlenecks, and mitigate maintenance risks, helping in the logistics industry growth
Importance of Analytics in Logistic Industry
Analytics continues transforming many industries, and logistics industry is one of them. The heterogeneous and complex nature of the logistics industry, along with the dependence on many pieces of machinery, can create bottlenecks at any spot in the supply chain. Data analytics has proved to be the most effective tool one can use to deal with them.
The logistics industry, until recently, was burdened with decades-old equipment, machines, and procedures. This not only hampered the efficiency but also became the primary reason behind its falling. In a detailed study on supply chain firms,
More than one-third of executives reported being engaged in serious conversations to implement analytics in the supply chain, and three out of 10 already have an initiative in place to implement analytics
The arrival and spread of big data usage dramatically changed the way businesses use to work with their analytics. Companies can now anticipate slow and busy periods, potential future supply shortages, and act accordingly. Integrating the supply chain data streams from various logistics providers could reduce prevailing market fragmentation, allowing powerful new partnerships and services. Many logistic players recognise that data analytics is a landscape-changing trend for the industry.
Although the data that needs to be processed and managed is highly complex, it’s worth the effort to adopt the data culture as advanced data analytics helps consolidate an industry that has been traditionally fragmented.
Data captured by Logistic Businesses
Logistics industries today, regulate a massive flow of goods and simultaneously generate extensive data sets. For millions of consignments every day, origin source and destination, quantity, size, weight, content, nature of product and location are all tracked across global transportation and distribution networks.
Big data analytics requires a substantial number of high-quality and structured information sources to work adequately. What can be a reliable source of data points? Following are a selection of possible data sources:
Operational data from traditional systems
Easily available real-time Weather & Traffic data
Driving patterns, and location information
Business financial numbers
With all said and done, there remains huge scope for improving the outcomes based on tracking the data. Most likely there remains an immense untapped potential for enhancing operational productivity and customer experience and building valuable new market models.
However, the journey for competitive edge begins with the identification of effective big data adoption cases. Benefiting from the value of information assets is a distinct strategic goal for most businesses and corporations. Apart from Internet giants, which have successfully stabilized data-driven business models, most of the companies in other divisions are typically in the initial stages of examining how to benefit from their expanding inventory of data and use it to their advantage.
Benefits from Logistics Analytics
In times of heightened competitiveness with a demanding customer base, managing and understanding all your logistics data will impact your daily business exercises positively. Also, logistics analytics tools will empower you to take complete command of your business or organisation.
Key Performance Index Tracking
You can't improve what you can't measure. Monitor performance in real-time and identify inefficiencies before its too late. As soon as data indicates errors in picking rates, delays in picking procedures or that shipping lacks some items; managers have the information they need to intervene immediately.
Using real-time GPS data, weather data, road maintenance data, fleet, and personnel schedules, the most optimised routes can be easily identified for delivery. This can also lead to better customer experience with more accurate delivery times.
Supply chain inefficiencies can be removed by introducing new digital platforms. It will help solve the problems associated with asset underutilisation, demand-supply matching, visibility and connectivity across systems. The use of analytical solutions will enhance operational clarity and connectivity between previously siloed systems; enabling stakeholders to connect throughout the supply chain.
Unleashing new business opportunities
With an improved understanding of the strengths and weaknesses of their business, decision-makers will be empowered to expand their current revenue streams. With strategic business partnerships, made successful by playing on each other's strengths, the industry as a whole can see a phenomenal growth.
The goal is to build a value-driven logistics network aligning supply and demand, along with some updates in organizational practices and tools. The industry is growing and sooner or later a time will come when the entire ecosystem will rely on data for business operations and management decision-making.