How logistics is been used in business applications?
Answers
Business intelligence (BI) has revolutionized logistics and transportation, and the rate of change is only increasing. Before we look at where the industry is headed, though, let’s take a moment to look at how far it’s come.
The concepts of logistics and transportation are as old as trade itself. The term logistics was first used in the early 1800’s to describe the calculated movement of troops during conflict and from there the idea was transferred to business as the management of the movement of raw materials to production and finished goods from production to market. Logistics and transportation have always been focused on the best means of moving people and goods from origin to destination, but prior to BI the emphasis was on geography and available infrastructure. Clearly things have changed since those humble origins.
Early applications of BI in logistics and transportation relied on descriptive analytics to provide information about past performance in the business. Any predictive analysis required high level data analysts who would scrutinize historical data and use the information gleaned to make projections on future trends, business needs, and long-term strategies. This type of investigation required significant capital investment in hardware as well as personnel trained to use that equipment and interpret the information produced. The results were only an educated prediction on the best course forward. Similarly, diagnostic analytics were used to scrutinize past failures, determine a cause, and recommend a solution to avoid future losses. While these means of analysis still hold relevance in the current environment, they simply look at past data and thus miss what is happening right now. Decision makers can only respond reactively in this scenario, not proactively.
Significant advances in technology have allowed for the automation of predictive analysis, but still based on retrospective data. But with the rise of operational intelligence (OI) and the internet of things (IoT) the type and amount of information available continues to expand. The cost of data storage has dramatically decreased, and cloud computing allows smaller operations a means to join the “big data” revolution without significant capital investment. Pair these factors with better tools that more efficiently interpret the vast quantity of available information, and the implications for logistics and transportation are dramatic. Businesses are now able to employ predictive and prescriptive analysis based on current operations.
