The Power of Data: How Analytics Improves Logistics Performance and Efficiency
Data analytics is a cool way to make sense of data and use it to make smart decisions. Data analytics can help us in many areas and fields, but one of the most exciting and tough ones is logistics.
Logistics is all about moving stuff and people from one place to another. Logistics involves planning, doing, checking and improving different things like transportation, storage, inventory, delivery and customer service.
Logistics is a hard and fast-changing field that has many problems like high customer demands, rising costs, environmental rules, global competition and new technologies. To solve these problems and beat the competition, logistics companies need to use data analytics in their work.
Data analytics can help logistics companies do their work better by:
Finding the best routes and times based on traffic, weather,fuel and customer likes (Datumize, 2020).
Seeing everything that happens in the supply chain by tracking goods and machines in real-time (Logistics Tech Outlook, 2021a; 2021b).
Guessing demand and supply changes based on past data, market situations and customer actions (Datumize, 2020).
Spotting weird things and stopping errors by looking at machine patterns (Logistics Tech Outlook, 2021a; 2021b).
Making customers happy by giving them what they want based on preferences, reviews and loyalty (Datumize, 2020).
Data analytics can also help logistics companies create new ways of doing business by:
Building smart warehouses that use sensors to watch temperature,wetness and inventory levels (Discover Data Science,n.d.).
Making self-driving vehicles that can go through complex places without human help (Discover Data Science,n.d.).
Using blockchain technology that can make sure security, tracking and responsibility in deals (Trade Finance Global,n.d.).
Using artificial intelligence that can do things like predicting, planning and deciding for us (Discover Data Science,n.d.).
Data analytics is not just a tool but also a secret weapon for logistics companies. According to a study by Logistics Tech Outlook magazine(Logistics Tech Outlook, 2020),most shippers(companies that send stuff)and third-party logistics companies(companies that give logistics services)think that data analytics is very important to make smart decisions. Most of them also think that big data(lots of complex data)makes quality and performance better.
But,data analytics also has some challenges for logistics companies like:
Getting good,data from many sources,such as sensors,GPS,cameras,social media,and databases.
Working on,cleaning,and joining,data into one format that can be easily used,and analyzed.
Analyzing,data using the right methods,such as describing,predicting,and prescribing analytics.
Showing,and telling,data insights using clear,and fun dashboards,and reports.
Doing,data-driven actions,and solutions that match with business goals,and values.
To overcome these challenges,data analytics needs not only technical skills,but also field knowledge,business sense,and thinking skills. Data analysts,data scientists,data engineers,and data managers are some of the key people involved in data analytics projects for logistics.
To sum up,data analytics is an awesome way to change logistics into a more good,effective,and new field. Data analytics can help logistics companies do their work better,give their customers more value,and create new things. Data analytics is not only important,but necessary for logistics companies to live,and grow in today’s tough,and dynamic market.
Datumize.(2020).How is data analytics changing logistics business? Retrieved from https://blog.datumize.com/how-is-data-analytics-changing-logistics-business
Discover Data Science.(n.d.).Data Science in Logistics.Retrieved from https://www.discoverdatascience.org/industries/logistics/
Logistics Tech Outlook.(2020).What is the Importance of Data Analytics in Logistics Business.Retrieved from https://www.logisticstechoutlook.com/news/what-is-the-importance-of-data-analytics-in-logistics-business–nid-751.html
Logistics Tech Outlook.(2021a).Top Examples of Data Analytics for Logistics.Retrieved from https://www.logisticstechoutlook.com/news/top-examples-of-data-analytics-for-logistics–nid-1055.html
Logistics Tech Outlook.(2021b).Ways Data Analytics is Used in the Logistics Industry.Retrieved from https://www.logisticstechoutlook.com/news/ways-data-analytics-is-used-in-the-logistics