Big Data Breakdown in Logistics
Big data is a popular buzz word right now – many companies are talking about it but very few have adopted a strategy around it. By definition, big data is a very large collection of structured and unstructured data that may be difficult to understand as individual parts, but is useful when centrally located and supported accurately. Big data gives companies the opportunity analyze massive amounts of information from various sources. In some cases, when big data is compiled sufficiently and there are resources to analyze, it can produce powerful insights regarding customers or target audiences, and it can improve business strategies.
Big data is an easy concept to sell, but not necessarily an easy concept to implement. When considering a big data strategy, it is pertinent to identify what is in your scope. It is important to determine the:
- …volume of transactions or scale of the data
- According to IBM Consulting, most companies in the US have at least 100 Terabytes of data stored
- …velocity of transactions or streaming/real-time data
- Examples are sensor information, social media or GPS tracking & traffic
- …variety of information or different forms of data
- Everything within the digital world can be a source of data, from traditional structured databases to unstructured data. For example, on-time performance statistics are structured data, whereas carrier failure reasons or exception management comments are unstructured data
- …veracity of information or uncertainty of data
- Big data is only meaningful and actionable if the data input sources are accurate
Data from hundreds to thousands of locations are captured in a data lake – a large warehouse that stores and processes data – and is reduced to use within analytical applications to provide easy to consume data. This insight can be provided to engagement systems for decision making purposes. Typically, the levels of insight can be broken down into four buckets.
- Descriptive Analytics (Hindsight) –What happened?
- Diagnostic Analytics (Insight) – Why did it happen?
- Predictive Analytics (Foresight) – What will happen?
- Prescriptive Analytics (Foresight) – How can we make it happen?
There are many ways that Unyson is looking into big data and the impacts it has on our overall network. One of our initiatives is to combine several sources of data to develop proactive winter plans. We are pulling in weather conditions, traffic, GPS sensor information, carrier exceptions, service failures and shipment patterns to provide a comprehensive forecast and anticipate predictive behaviors for critical shipments during the winter season.
The ability to use big data as a resource is an exciting opportunity that will continue to grow and unfold over the years. We are just scratching the surface with the value it provides. We will continue to remain at the forefront of the industry with this new tool, and I welcome any questions you may have about this exciting game changer. Please feel free to reach out to me with any questions, I’d love to hear from you and learn from your insights. If you would like to subscribe to our Executive Vice President’s newsletter, please email email@example.com and you will be added to the monthly distribution.
Talk data to me!
Senior Director, Solution Services