The New Breed of Supply Chain Software incorporating Big Data

Big DataTo remain current, supply chain software must constantly evolve. This evolution must reflect the changes that occur in industries and markets around the world, and must also react to new innovations in IT with particular regard to data processing.

Early usage of Big Data

So called “Big Data” is not a new innovation as such, but its accessibility is. Big data is just what it sounds like – it is data on a huge scale. Until 2 or 3 years ago, Big data remained the province of large corporations; businesses that were large enough to have huge premises where they could keep the hardware to store and process colossal quantities of data, and who also had pockets deep enough to be able to afford the hardware. These commercial giants could not only take advantage of the opportunities that big data brings to the table in terms of marketing, but could also integrate it into their supply chain software as a fundamental part of demand forecasting.

The advent of computing in The Cloud has now brought Big Data into the reach of most sizes of companies, which means that with the right supply chain management software, it can be put to good use in terms of picking up trends, applying the information to inventory, sampling lead times, and triggering purchases.

Harnessing Big Data to Predict Demand across the Supply Chain

Just recently, the Automotive Aftermarket Suppliers Association (AASA) Technology Council (ATC), having looked into incorporating Big Data into their supply chain software, published a special report during its spring meeting in March. The report entitled “Harnessing Big Data to Predict Demand across the Supply Chain,” was compiled via by Epicore Software Corporation, and it focuses on employing Big Data to analyze and predict demand across the entire supply chain. You can click on this link to download a copy of the report in PDF format.

Facilitating the balancing of stock at a macro level

The report looks into the industry’s potential for forecasting demand down at store level. The findings indicate that the next important step in terms of the industry “aftermarket” is predicting demand across the whole supply chain. It will be of assistance to suppliers in terms of pulling slow-moving and/or redundant stock off the shelves, and replacing it with current, faster moving stock of higher demand where appropriate, thereby facilitating the balancing of stock at a macro level.

The significant impact of big data in supply chain software

Incorporating big data to forecast demand in supply chain software will result in leaner practices across the entire supply chain. This includes manufacturers producing a more accurate number of components, and suppliers and distributors keeping the right amount of stock on the shelves. According to Chris Gardner, the Vice President of the AASA; by collaborating throughout the industry and being able to forecast future demand throughout the life cycle of any product, this new supply chain software will have a significant impact.

Replacing analytics with predictive analytics

The industry is in a good position to think about taking the next step. The vice president of Epicore, Scott Thompson, is reported as saying that There now exists a broad-based understanding of the enormity of the data among leading suppliers and distributors.” He went on to say that it was Epicore’s aim to assist the industry through this new breed of supply chain software, to progress beyond mere analytics and incorporate predictive analytics; moving from the micro viewpoint into the macro viewpoint.

Harnessing the power of data storage and analytics in the cloud

It’s not just the AASA who can benefit from the new breed of supply chain software that incorporates Big Data via computing the cloud. By striking up the right deals with cloud data storage and analytical service providers, all sizes of businesses can take advantage of this methodology.


What other aspects of supply chain software (apart from forecasting) can Big Data impact on? Have your say at the feedback section below.

Leave a Reply

Your email address will not be published. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>