Big Data’s Christmas challenge: Make it merry or go home

As we approach Christmas, every logistical network in the world is being stretched to its maximum. In fact, this week brings the highest volumes and most stress of the year for the companies that move consumer goods and people everywhere in the world. What will appear seamless to us (hopefully) is driven by a remarkable need for predictability and incredibly fast operations. Without these two, it can’t be a merry Christmas for logistics companies or their customers.

And what’s true for the Holiday Season is true for the rest of the year as well. Let’s take a look.

Predicting the unpredictable

Capacity is a significant variable. Having the right capacity means being able to predict what will come through the system at a given moment: Load levels, weather, customs requirements, timelines and, above all, cost affect the need for capacity. Without accurate predictions, logistics networks are are insufficient (too little capacity) or inefficient (too much).

Time and money sensitivity

The ability to predict capacity is the salve for logistics’ extreme sensitivity to time and money. Timeframes for pickup and delivery matter, but not at any cost. Cost matters a great deal, but not at the sacrifice of timely delivery. It ends up being a very delicate balancing act that determines both customer satisfaction and profitability. Time and money are in constant contention.

Time rears its head in the form of guaranteed delivery times and associated penalties when performance doesn’t match the SLA. It gets ugly when routing changes affect any logistics touch point, with some touch points having much more latency than others, like when people or packages are on international flights. And time matters greatly when the system has to deliver location information on any package or person within minutes to meet demands of customers or customs. Time is always top of mind.

Money, in the form of cost, is all about the efficiency of the pickup, the handling phase and delivery of goods and services. In transportation, the yield on perishable inventory like airline seats, means capacity can only be sold until a point, and then unsold goods go unsold forever. Lastly, over- or under-ordering due to lack of real-time visibility into inventory kills efficiency and profitability. These are significant challenges that require really fast data. Cost is likewise top of mind.

Really fast data

TKW-on-the-road_Implico_Shutterstock_rgb_300dpiMaking it work requires very fast operational data. Not just any data, but data that enables organizations to make decisions that fix problems, lower cost and increase revenue. Only very fast operational data can reroute trucks and airplanes or provide real-time supply chain visibility. Only really fast data provides an ability to intercept ‘things’ enroute, whether those things are customers or objects, and change destinations. This is a tall order when you consider that data traditionally moves more slowly than what it describes.

And one way to get that to happen is to uniquely identify components of the supply chain so that data that describes items can be much bigger  and faster than what can go on a tag or manifest. In the old days, labels had to change to reflect changing facts. In today’s world, the barcode or other identifying never changes but the describing data is constantly in flux, managed in back-end systems.

Why does all of this matter? Because customs selections packages to pull, customers call to reroute, weather changes, strikes happen, and ‘hard’ capacity limits are reached resulting in rerouting. We live in a very dynamic world and being competitive means being faster in response than anyone else. As Mike Tyson once said, “Everyone has a plan until they get punched in the face.” He would know.

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Categories: Data Analytics / Big Data, Transport and Logistics

Author:Chris Taylor

Reimagining the way work is done through big data, analytics, and event processing. There's no end to what we can change and improve. I wear myself out...

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2 Comments on “Big Data’s Christmas challenge: Make it merry or go home”

  1. December 11, 2012 at 10:39 am #

    Predictive analytics applied to capacity planning and logistics can produce an immediate and measurable ROI.

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  1. Hadoop: A race car without wheels? | Successful Workplace - December 12, 2012

    […] things that most companies still struggle to get right, Big Data is a research project and not an operational possibility. Insight is fantastic and Big Data technologies certainly help deliver insight, but […]

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