Big Data And The Success Of The Supply Chain

Big Data And The Success Of The Supply Chain

Big data is broadly defined as a massive volume of information that is not structured and that needs to be processed by special means like specialized software or detailed database strategies in order to be utilized for specific purposes. The importance of Big Data cannot be overstated so it comes as no surprise that it is becoming more influential and relevant as a defining factor in the way business strategies operate nowadays.

Technology today makes it possible to analyze patterns, correlations and insights better than ever before, and that is why this idea is no longer a concept to be imagined, but instead a reality we must not just deal with, but also take advantage of in order to remain competitive and to stay ahead of the competition by embracing evolving trends.

In order to have an idea of just how much data we are talking about when we get involved with Big Data, consider the fact that in the last two years, more data has been created than in the entire history of the human race. With that being said, supply chain managers and logistics experts now have the tools to process this information in order to make the best decisions to affect the business and anticipate the needs of the industry and their customers, sometimes even before those agents are even able to identify said needs as such. Supply chains are not more complex than ever and the management of data is allowing also for the management of the difficulties that inevitably come along with enhancing complexity.

Big data is not a new concept to the industry, but it seems like only marketing and manufacturing are truly ahead of the game when it comes not only to managing the information but actually putting it to good use. The funny thing is, that with so many variables that affect transportation, warehousing, and management, it only makes sense that logistics seriously adopts Big Data as a game-changing strategy in order to enhance efficiency and productivity. Something that we can already see working is the use of automated alerts in order to replenish low stocks in inventory management. These applications sometimes work completely on their own without the input of operations to create the new orders, as they are needed.

It is important to differentiate between what we call structured and unstructured data as well. Structured data deals with what we call “hard numbers”, meaning the quantity of products that are ordered or stores in a warehouse, while unstructured data deals with more intangible things like the allocation of display space, and the impact of visibility dealing with product brands and such. Unstructured data cannot be measured by regular means such as database entries and it comes from places like social media in the forms of text, audio and video in some cases.

Historically, supply has always been easier to predict than demand, but the study, gathering, and utilization of unstructured data is one of the things that is allowing for the demand component to be broken down and used as the source information for making big decisions.

Image courtesy of Pixabay at

Data comes from many places and sometimes something as simple as a cash transaction can give those who can use the information wisely, a great deal of insight into the nature of customer preferences and the way they go about purchasing and using products. Another great example is finding ways to maximize fuel efficiency by choosing the best routes and general conditions in order to get the most out of your input. In order to make decisions concerning this factor, one has to gather information about octane ratings, general fuel usage depending on specific vehicles, weather and road conditions and even how the tires of the vehicles interact with the different types of streets and highways that must be traveled. All of these ingredients are necessary to paint a bigger picture and make the right adjustments in order to transform data into measurable improvements.

The harsh reality is that the omnipotent and omnipresence nature of Big Data makes so that businesses can no longer look at it as a nice alternative they forgo due to their own technical limitations, and instead get on board Big Data as the real transformation of business strategy and embrace it as the way business is done period. Information is power and now that statement is truer than ever in a world where information is being created, distributed and analyzed at such rate. Those who do not adapt will inevitably be left behind, as they will no longer be able to compete in a market that anticipates, adjusts, plans and executes based on the ebb and flow of the industry and the choices of their customers. Big Data will become even more instrumental in the management of the supply chain and the direction of logistics planning

If you want to read more great articles about Big Data, data analysis, analytics and general topics on logistics, check out our publications at David Kiger’s Blog.

* Featured Image courtesy of Kevin Ku at

Sorry, comments are closed for this post.