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5 Ways Big Data is Redefining Supply Chain

January 23, 2019 | By River Logic

Big data incorporates data-sets on the order of terabytes and petabytes. Self-correcting and self-monitoring, big data systems make outlier data more noticeable and allow development of statistical models and trends. This facilitates predictions from supply chains to human resources and everywhere in between. Machines "learn" to operate from inductive and predictive analyses. Savvy industries worldwide have caught on and employed such inductive statistical analysis in order to diminish operation costs. Following are five ways big data has changed supply chains.

1. The Effect of Trend/Outcome Prediction

With enough data, businesses can inspect outlier spikes in cost and operation, then trim the fat. Such examination need not be limited to supply chains, but using it to streamline supply chains is very cost-effective (hence, this is a regular application).

The valuable elements of a supply chain will stand out statistically, as will the detrimental ones. This means the good can be polished and the bad can be cut. Big data makes this prediction possible, and businesses are quickly using such analysis to codify operations. If all the data from several years' sales is gathered and cross-referenced digitally through a big data application, certain supply chain redundancies can be easily identified and cut.

As an example: if the cost of running a supply of product to a certain region ends up being higher than the returns on that product, but just thirty miles east consumption is booming, big data could help an organization identify such a redundant supply line and cut / reapportion it to the successful one. 

Coca Cola specifically used big data to consolidate resources and more efficiency conduct their supply chains across seventeen different plants throughout Europe. A good indicator of the reality behind big data changes throughout businesses worldwide is that the most well-established agencies are using it to effect efficiency. If those with the most resources are finding benefit, assuredly there's value.

2. Big Data Implementation in Real Time

Quick changes can be made with proper application of data, giving organizations a strategic advantage over competition. Hypothetically, a line of shoes isn't selling in a particular market because some media involvement threw off statistical projections. The supply chain can be alerted and units saved.

Big data streamlines production, distribution, manufacturing, and development. As terabytes and petabytes of information become like the megabytes and kilobytes of yesteryear, it becomes easier to nix extraneous purchases, practices, and technological developments. Furthermore, this can be done at the very moment the inefficiency is discovered.

Certainly there are supply chains that require more time in restructuring. However, with big data the ability exists to catch these events and stop the financial hemorrhaging before it starts. It's the difference between telephones and the internet; and another reason savvy managers looking to efficiently streamline supply chains are quickly adopting big data analytics.

3. Extension of Perspective

Via strategic optimization, continuous analysis provides continual enhancement of supply chains. When numbers are crunched, relationships between suppliers, manufacturers, distributors and consumers are enhanced. Big Data provides more numbers in real time, inducing expanded perspective.

Since big data is burgeoning, early involvement will provide more advantages and larger perspective. Soon the perspective big data affords will be available to any business that has sufficient financial mass to absorb it. Obviously the ma-and-pop general store on the corner won't be utilizing big data techniques any time soon, but the new MMJ dispensaries across Colorado, Washington and Oregon will jump at such innovations as corporations seize on a lucrative opportunity.

Consumer goods companies will all have this technology in a matter of time, because it offers such an efficient means of consolidating resources over time. Especially as the current economy struggles, businesses are going to be looking for big data to provide solutions. For all these reasons, it only makes sense to get involved with analytical applications of such data options as soon as possible.

4. Optimized Delivery and Supply Networks

Big data specifically optimizes desired areas. Changing a supply route could save time, money, or both. When the entire picture beyond the "micro" level can be seen, suddenly obvious changes present themselves that were otherwise hidden.

It's not uncommon for two chains of supply to service stores which are reasonably near and could be serviced by a single chain. If you imagine the supply chain as a two-dimensional tree divested of its leaves, then those areas where branches are gnarled and knotted can be pruned. This means the resources sent out from the roots can be curbed, or sent to buff up already fruitful branches.

Via scientific application of big data, expansion of business is facilitated as resources can be reapportioned to successful areas. Such enterprise optimizationTM has streamlined supply chains across world, again as a direct result of big data's technological convenience. Ironically, technology can make such supply chains work more organically.

5. Excising Lag

One of the best ways to effectively manage a supply chain is to get rid of the time lag. According to Forbes, supply chain efficiency is boosted 2.6 times via big data analytical implementation. Expert scientists or outside contractors can be used to manage the data and find where lag can be destroyed.

Industry leaders also help discover leverage points. It's easy enough to see that doubling supply efficiency is an absolute windfall. It's been touched on throughout the article, but let's consider some numbers. If it cost twenty million dollars to distribute a certain commodity like single-serving potato chips throughout a metropolis, that number can be divided by 2.6. It comes out to a little under 7.7 million dollars, instead of 20 million. Now you've got a little over 12.3 million dollars to devote to another network.

That's almost a doubling of your revenue in that area! Imagine you've got a line of chips or what-have-you being distributed throughout Seattle. Now you can afford to distribute throughout Portland and maybe even the Tri-Cities area (as they've got a smaller population base) for the same price it took you to supply Portland alone.

Obviously, finding all the areas where supply chains can be made more efficient isn't a process that happens overnight. And as this reality becomes more attainable, the more companies will take advantage. Eventually, the big data route will become a must, causing the competitive advantage to dwindle. For this reason, it's crucial larger enterprises begin to leverage big data now while gaining the maximum competitive advantage is possible. 

Closing Remarks

The big data trend is still expanding, and savings involved in efficiently re-structuring supply chains are likely to be enough for not only substantial additional profit, but for streamlined, efficient outreach efforts that capitalize on the knowledge an increased statistical perspective yields. I.E., when you establish new supply chains, you'll save money through big data — you'll know what works and what doesn't work. Simply put, why wouldn't a company take advantage of this technology?

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