Dear Reader.
All is Data. Data is all.
This could have been the shortest blogpost in the short history of this blog. And I probably could leave it at that while all of you would stare at those words - in awe about the awesomeness of this simple statement.
I am of cause joking. I couldn’t do that. Just leaving you like this. Hungry for more. So, behold! This is my last blogpost. ☺
Now, after this little intermezzo of fine words, let us get a little bit more serious. The phrase above is not something I just wrote down for fun. No, certainly not. That, what is going to happen in the next years, the changes that are about to come, will change the world that we know, how we interact with it and how we live our lives in general.
It was not hard to realize that information systems in general, and the collection of data especially, are not only useful but a necessity in today’s day and age. It goes without saying that this includes Business Logistics as well. The importance of the topic is something we will probably never forget, as there was – I think – no lecture or seminar where the two words “information system” were not used or where the importance of the same was not emphasized at least once.
But you see – it is true! Data is everywhere.
When you get up in the morning. The time spent in the bathroom. The kitchen. At breakfast. The moments when you first look at your phone. Looking at your watch. Realizing that you are late for class. Getting into the Metro or using your bike or car to get there. When you open your notebook. When you listen to your teacher. When you write down notes. Using Facebook in class. Googling something. Eating…
With this endless description of everyday situations, I just want to make clear that data exists in a lot of places and situations. According to Wikipedia “data is a set of values of qualitative or quantitative variables”. One very cryptic definition. But fact is that data is something that “is measured, collected and reported, and analyzed, whereupon it can be visualized using graphs, images or other analysis tools”. So, there is data when you brush your teeth. You can measure the time it takes you to finish or the calories you burn while doing so. If this makes sense is another question.
Admittedly, that has nothing to do with Business Logistics. But don’t worry, we will get there. However, first keep in mind one important fact! Data is not equal to information. Data only becomes useful or suitable for making decisions once it has been analyzed in some way. And only when that has happened, it is information that has a meaning.
As for Business Logistics. You have a whole lot of data here as well. Routes, times, destinations, inventories, weights and employees to just mention a few. And all those are only meaningful if you see them in a certain context. When you analyze them.
We talked about Inventory Management. We talked about routing and transportation problems. All those topics are full of data that can be captured. An almost unmeasurable, unbelievably huge pool of data. Humans alone could never dream to take all that data and to process it. To analyze it. To give it meaning, so that it becomes useful information. Information that is crucial for a Business.
The better the information we have, the better can be the decisions we make.
I mean, do you grasp what I am trying to tell you? Imagine, for example, a self-driving vehicle that receives instructions automatically via an 8G internet connection. That “knows” what is happening around it. That “senses” distances. It calculates and optimizes routes in real time, especially within the last mile, avoiding traffic jams. And it, the vehicle, anticipates where the customer will be within the next 15 minutes to receive something he ordered half an hour ago by talking to his smart-phone or smart-whatever! And all that data it automatically analyzed. Maybe even in real time for all deliveries that happen all around the world for an international global player firm, enabling the management to react fast in case it is needed or to make adjustments in the strategy.
Do you already see it? Data is everywhere. And in the last decade we finally found the means to access and analyze this infinite pool of data.
Information Systems.
Combined with the right data IS can make the wildest dreams come true. So, think back. Let your imagination run wild. Think of what becomes possible if you are enabled to access all the data around you.
You remember us talking about the vehicle routing problems? Or the calculation we did regarding the inventory levels and lead times? Just think of anything we did in class. Most likely you will find data there as well. And where data is, we might be able to optimize some processes and functionalities, remove bottlenecks, shorten lead times or just create something wholly new.
This ultimately leads us to one important keyword we actually mentioned in class quite often already.
Big data. Now you might already be able to guess what big data is and how it can be used. We will not be able to get at all deep into the topic as there are whole books just as an introduction. But I can tell you, it is a very interesting topic, even though it takes some time to get into it. But I at least want to give you a general overview by explaining the following definition.
“Big data is data sets that is so voluminous and complex that traditional data processing application software is inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating and information privacy. There are three dimensions to big data known as Volume, Variety and Velocity.”
Definition of Big Data from Wikipedia
The amount of data that was processed in “normal” cases were not a problem for modern computers. But if you think about all the data that could be collected in the future you will certainly will agree on the fact that those data pools are voluminous and complex.
And the software (and partly hardware) that is available in general, is not made for processing data in such huge amounts.
The challenge is to transform this raw data into useful information. How should a computer, for example, analyze and visualize the data of millions of packages that are transported via drones or other futuristic vehicles to the customer?
As for the three Vs. Volume refers to the amount of data, variety refers to the number of types of data and velocity refers to the speed of the data processing.
This so called 3Vs model states, that the challenges arising with big data systems and big data management result not only from the sheer amount of data that must be managed efficiently, but from the expansion of all three properties.
To conclude this post. I think we have interesting times ahead. Not only in Business Logistics. However, as Business Logistics depends heavily on (correct) data, it will be interesting to see and to think about how big data will change for example the process of demand forecasting, the vehicle routing, the inventory management and especially how new ways will change the “business as usual” that predominates at the moment and how it will look like at the end of the next decade.
Thank you so much for reading. As always.
Simon Drews
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