Big Data and the Supply Chain

Contribution by Dennis Weir – Marketing Executive at Barloworld Supply Chain Software

 

The Supply Chain is Big Data

It comes as no surprise to you as a veteran of the Supply Chain. Ever since the first trade routes from point A to point B were opened at the dawn of civilization, Big Data has been an issue in the Supply Chain. Long before the vendor du jour with sufficient marketing panache swayed an entire industry to believe that Big Data is the next big thing.

It isn’t the next big thing. It is the persistent big thing and what they pay you the big bucks to manage. Hey vendor du jour, way to show up to the party late and spend the night talking about how you organized the party.

It is Actually Quite Small

After an early morning meeting out of the office I stopped by Subway for a breakfast sandwich before I headed in to do a day’s work. As the woman behind the counter built my sandwich to my preference I could see the inventory shifting from RM/WIP to a Finished Good. Other than realizing I spend too much time thinking about supply chains it reminded me that all of the little transactions are what make the data Big.

Some Things Might be too Small

From a process efficiency standpoint, how that woman was able to make my meal was fantastic. It wouldn’t make sense for Subway, or the franchise owner as the case may be, to install a tracking system that counts the number of spinach leaves she put on my sandwich. Not only would it take longer than most customers would want to wait and/or raise the cost of my sandwich; unless the technology was ultra violet I don’t want to be reminded that the sandwich I’m going to eat is part of a multi-step, multi-vendor transaction.

Small Things have Tremendous Value

So perhaps the number of leaves of spinach that were on my sandwich is too small to track in your Supply Chain/Big Data. But, I would be ecstatic to know that the box that the spinach came in was tracked with a serial number that associates the lot, expiration date and unique manufacturer. That way when a recall is issued for that product, it is easier to track it down. However, this is an example of small data (i.e. scanning the serial number of the spinach upon receipt and upon disposal) to know that the inventory in question is in my supply chain. So the issue you must first consider to improve the overall performance of your Supply Chain/Big Data is:

[list][item icon=”fa-download” ]what data/information do I already have;[/item][/list]

[list][item icon=”fa-download” ]where is my existing information found/available;[/item][/list]

[list][item icon=”fa-download” ]what new data/information would I like to have;[/item][/list]

[list][item icon=”fa-download” ]where can you get the new data/information.[/item][/list]

Building from the Bottom-Up

There are various ‘levels’ of data in your Supply Chain. To simplify the discussion let’s use three simple categories: Transaction, Position, and Status.

Transaction level data pertains to a particular task in your supply chain such as scanning product upon receipt. This data can exist in your own business systems as well as those of your customers and vendors. Transaction level data impacts the Position and Status level data related to the Transaction.

Position level data refers to a specific quantity of unique inventory or assets found in your supply chain. This data is tracking the inventory and supplies your company consumes as it provides value to your customers. This data can exist in your own business systems as well as those of your customers and vendors. Position level data directly impacts your ability to progress Status level data to a financial conclusion.

Status level data refers to the status of orders. These orders could be of various types including transfer, purchase, manufacturing, sales or service orders. When you buy or sell, there is an order than represents the financial impact of the order. It could increase or decrease your Position and requires Transactions to complete the work. This data can exist in your own business systems, and should, but may include data from your customers and suppliers.

The more granular the information you can obtain, the larger the Big Data set of your Supply Chain is going to be. Don’t fret. The old adage of what can be measured can be improved holds true for Big Data in the Supply Chain. If you can see it then you can learn from it and make significant, competitive advantage improvements to your business.

Building from the Past-Forward

Being able to see down into the various levels of data in your Supply Chain shows you what’s happening currently in your Supply Chain. Similarly, you need to look into the Past as well. Because, in spite of various protestations, the past is a great indicator of the future. When looking in the past you want to gather as much Position and Status level data you can. How much inventory did you have during a period of time for a particular item? Which vendors did you buy from, which products did you manufacture/make and which customers did you sell to during that same period?

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Conclusion

The Supply Chain is inherently Big Data. Your job is to know which data is relevant and what it means to your business. In subsequent blogs we will explore specific uses of Big Data in the Supply Chain. The first of which will be Big Data and the Supply Chain: Dynamic Targeting. Going forward, we would enjoy hearing your ideas for blogs on Supply Chain/Big Data.If you’d like to spend time discussing your Supply Chain and the types of data you have or want and how you’d like to transform your company; please reach out. Instead of watching Subway build my sandwich and thinking about supply chains we can instead talk about yours. If you are in the Chicago area; lunch is on me and it doesn’t have to be Subway.[/blockquote]