The Exact Definition of Logistics & Supply Chain Management

Many people tend to associate the logistics term and supply chain management term as synonymous.  But, are they really refer to the same concept?  In response, I try to cite some statements from a handful of academical papers to confirm this issue.  Enjoy!!!

- my kid's version of supply chain management -

"Logistics Management: the process of planning, implementing, and controlling the efficient, cost-effective flow and storage of raw materials, in-process inventory, finished goods, and related information flow from point-of-origin to point-of-consumption for the purpose of conforming to customer requirements" (Cooper et. al. 1997).

"Supply chain management is the integration of business processes from end user through original suppliers that provides products, services, and information that add value for costumers."  (Cooper et. al. 1997).

“SCM represents one of the most significant paradigm shifts of modern business management by recognizing that individual businesses no longer compete as solely autonomous entities, but rather as supply chains (consisting of individual businesses, working together).” (Lambert and Cooper 2000)

“The term SCM [is] used to explain the planning and control of materials and information flows as well as the logistics activities not only internally within a company but also externally between companies” (Chen and Paulraj, 2004).

“Supply chain management (SCM) encompasses the planning and management of all activities involved in sourcing and procurement, conversion, and all logistics management activities.  Importantly, it also includes coordination and collaboration with channel partners, which can be suppliers, intermediaries, third party service providers, and customers.  In essence, supply chain management integrates supply and demand management within and across companies”, according to the Council of SCM Professionals (Moonen 2008).

"A review of the SCM literature reveals that confusion exist in terms of what SCM actually is.  Nevertheless some commonalities do seem to exist:

•  It involves through several stages of increasing intra- and inter-organizational integration and coordination: and in its broadest sense and implementation, it spans the entire chain from initial source to ultimate consumer.
•   It potentially involves many independent organizations.  Thus managing intra- and inter-organizational relationships is of essential importance.
•  It includes the bidirectional flow products (material and services) and information, the associated managerial and operational activities.
• It seeks to fulfill the goals of providing high costumer value with and appropriate use of resources and to build competitive advantages." (Cooper et. al. 1997).

- end of 2013 - may we always be better persons in many years to come  -

 
References

Chen, I., & Paulraj, A. (2004). Towards a Theory of Supply Chain Management: the Constructs and Measurements. Journal of Operations Management, 22(2), 119–150. 

Cooper, M. C., Lambert, D. M., & Pagh, J. D. (1997). Supply Chain Management: More Than a New Name for Logistics. International Journal of Logistics Management, 8(1), 1–14.

Lambert, D. M., Cooper, M. C., & Pagh, J. D. (1998). Supply Chain Management: Implementation Issues and Research Opportunities. International Journal of Logistics Management, 9(2), 1–18.

Moonen, H. (2009). Multi-Agent Systems for Transportation Planning and Coordination. Erasmus University Rotterdam.

Object Oriented VS Agent-Based Software Engineering

Found a nice explanation that points out the difference between object-orientation and agent-based software while I was reading a thesis entitled "Multi-agent Systems for Transportation Planning and Coordination" written by Moonen (2009).  

He wrote, "From a software engineering design perspective, it is good to understand where agent-based approaches differ from traditional Object Orientation (OO) development methods. ...

Jennings (2001) listed the most compelling differences between agent-based and OO: 

•  Objects are generally passive in nature – they need to be send a message before they become active;
• Objects do encapsulate state and behaviour realisation, they do not encapsulate behaviour activation (action choice) – more specifically, an agent can have behaviours which are reactive, proactive, and/or social in nature;
• OO fails to provide an adequate set of concepts and mechanisms for modelling complex systems;
• OO approaches provide minimal support for specifying and managing organisational relationships;
• Agents have at least one thread of control but may have more, whereas Objects have solely one thread of control (Wooldridge, 1999)."  

little robot by annares - source openclipart.org

 

Just exactly what I have been looking for, maybe it is the case for you too ;)

References

Jennings, N. R. (2001). An Agent-based Approach for Building Complex Software Systems. Communications of the ACM, 44(4), 35–41.

Moonen, H. (2009). Multi-Agent Systems for Transportation Planning and Coordination. Erasmus University Rotterdam.

Wooldridge, M. J., & Jennings, N. R. (1995). Intelligent Agents: Theory and Practice. Knowledge Engineering Review, 10(2), 115–152.

Say It with Plots

Credits to R, GGPlot2, and Cookbook for R Blog.

Photo Blog: Neural Network Prediction Model

Documenting some old notes about the formalization of the neural nets prediction model.

I think the note about the "classic" Levenberg-Marquadt rule for dataset decomposition (into into the training, the validation, and the testing sets) also deserves some highlight.

Reviewing the results of the notes documentation I did with my scanner (Canon Pixma MP 540) (see the software release management blog) and my camera (Nikon D 5100) (see this blog),
I think I will go on using the camera instead of the scanner due to the picture quality, practicality, and blog aesthetic issues :)

9 Minutes Introduction Video to Agile Scrum Method

Brilliant compact explanation about agile scrum software engineering method by Hamid Shojaee.



note: I do not own the video for sure ;)

The Innovation of Loneliness - Vimeo Video

I find that this great video by Shimi Cohen below has some truth in it.  Many modern people, especially the youngsters, have lost the sense of real life social interaction in exchange for the convenience that digital artificial social media offers.

Come on people, meet real people, and interact with them.  Spend less time in interacting with your PC/ laptop/ smart-phone which gives the sensation of artificial connectivity :p

Software Release Management - Scanned Notes

Conserving some knowledge from my old note book should not be a bad idea...

 

... for some notes, it's better than throwing them directly to the trash can.

Reviewing Machine Learning (Prediction Model) Diagnostics

Suppose, you've done all you need to do to build a prediction model.  Despite your hard work and high expectation, the prediction model you've designed performs poorly.

What to do next then?

After having a discussion with a good friend, he suggested me to review Andrew Ng's advices for debugging predictive analytic (machine learning) model.  He referred me to the video series below:



Having all the videos in the series (Advice for Applying Machine Learning - What to Do Next 1-7) reviewed , I learned about the machine learning diagnostic issue.  To Andries Ng's words, machine learning diagnostics is defined as: "a test that you can run to gain insight what is/isn't working with a learning algorithm and gain guidance as to how best to improve its (predictive) performance." 

Machine learning diagnostics is built on the identification of "bias" and "variance" symptoms of predictive models.  Based on the symptom's identification process, we can then define the prospective measures that will likely lead to better result.

So, what to do next then?
Based on the advice from lecture sets, the alternative measures are:

 ... and back to work, for sure :p 

Free Statistical Machine Learning Books and Lecture Slides

Statistical Machine Learning - Data Mining - Business Intelligence Books.

Inspired by recent David Smith's blog post about the possibility to downloading free Statistical Machine Learning e-book, I try to "re-echo" and "re-package" the exciting news.  Thanks to the generous researchers who make their valuable works freely available, we can download free digital copy of their books (either whole or as subsections) and the accompanying lecture slides.  Herewith, I list the URLs for downloading some data mining/ predictive analytic/ statistical machine learning resources

1.  "Elements of Statistical Learning (Full Book)" by  Trevor Hastie, Robert Tibshirani, and Jerome Friedman.

2.  "Information Theory, Inference, and Learning Algorithm (Full Book)" by David MacKay.

3.  "Forecasting: Principles and Practices (Full Book)" by Rob J Hyndman and George Athanasopoulos.

4.  "Introduction to Data Mining (3 Chapters of the Full Book and Complete Lecture Slides)" by Pang-Ning Tan, Michael Steinbach, and Vipin Kumar.

5.  "Machine Learning (Lecture Slides)" by Tom Mitchell.

6.  "Pattern Recognition and Machine Learning (one Sample Chapter and Some Lecture Slides)" by Christopher Bishop.

7.  "Data Mining for Business Intelligence (Instructor Materials)" by Galit Shmuelli, Nitin Patel, and Peter Bruce.

(the following URLs do not really fits in the data analytics topic, but they're useful information to share anyway:D).

8.  "Multiagent Systems - Algorithmic, Game-Theoric, and Logical Foundations (Full Book)" by Yoav Shoham and Kevin Leyton Brown.

9.  "Fundamentals of Multiagent Systems with NetLogo Examples" by Jose M Vidal.

10.  "Essential of Metaheuristics (Full Book)" by Sean Luke.


Hopefully the URLs will still work in the future,  Enjoy then.. :)

Knowing Extra Data Analytic Tools can be Handy

In the last period, I have been using R for preparing and analyzing big sized data.  It has been a reliable tool for many of my needs.  The existence of numerous blogs (e.g. r-bloggers) that share many useful tips makes trouble shooting can be done reasonably fast.

Memory Allocation Notification - R

Not without flaw, I just realized that R does have its limit.  At the moment, it can not allocate working memory more than 2.2 GB regardless how powerful your computer is (see the description picture above).  Although you have 8 GB RAM, R will send an exception when the utilized memory reaches the allowed limit.  To solve this issue (i.e. coping with "big data" analysis using R) Ryan Rosario's video can stand as a good reference.

EM Clustering - Weka

I haven't really experimented with what the video has suggested (I am not in the mood for learning new package :p).  In exchange, for my problem at the time (doing EM clustering for ~25,000 records data), I just used my old "fellow" Weka, and solve the problem within 30 minutes or so.

Because a tool's limitation can be explored at unexpected time, it is always handy to know more than one statistical learning tools (e.g. R, Weka, Rapidminer, etc).  Happy data crunching then :).  

Network Plot with Gephi - My 1st Trial

After quite sometime from my initial blog about Gephi, finally I took some time to learn using it.  Actually, for few days I've been trying to find some available network plot packages that can be developed within R environment.  However I can't find one that can produce appealing visualization better than Gephi (at least for now).  For those of you who'd love to learn making network plots using R, I do recommend Dai Shizuka's blog for clear starter tutorials.  For those who want to learn Gephi, it will take you about one or two days to make descent graphs.  Gephi is quite easy to learn for a beginner.  In principle, I only need to read two guides (i.e. the quick start guide and the supported input files) to start.  For making a try out plot (below) I spent most of the time in preparing the edge list input file.  So give some time to try it yourself then... :)     

My First Gephi Plot.

Schiphol Airport's Luggage Logistics

When I was clearing up some old magazines and papers,  I realized an interesting information was hiding in one of the magazines.   I ripped some of the pages and scanned them to "conserve" the insight about how the Schiphol Airport (one of the world's busiest airports) handle an important issue of any traveler, the luggage business (can you imagine if you arrive in another continent without finding your luggage at the picking belt? surely it will be disastrous!!!).   Investing one or two minutes to understand how they handle our precious bags won't hurt.   Anyway its better to keep the insight in this blog rather than junk it directly to the trash can for sure.

The information source is the Schiphol Magazine - September 2011,  I think I intentionally brought the magazine with me along the traveling to scan the luggage operation description.   After more than a year, I did scan them today..  better late than never huh.. :p

Click on the picture for better viewing and enjoy!!!

Luggage Logistics Operation - Page 1

Luggage Logistics Operation - Page 2

Luggage Logistics Operation - Page 3

Luggage Logistics Operation - Page 4

2012 Berganti 2013: Kliping Foto Kalender Belanda

2012 beranjak pergi, 2013 menghampiri tak terhindari..  semoga dalam setiap periode waktu, entah itu detik baru, menit baru, jam baru, hari baru, minggu baru, bulan baru, ataupun tahun baru, kita selalu belajar dan berada dalam derajat kebaikan yang lebih bagus dari masa-masa yang telah lampau.. (amin :p)

Kelender 2012

Seru-seruan nge-scan kalender 2012 yang dikasih gratis dari yang punya kontrakan, sayang juga kalau harus berakhir di tempat sampah gambar-gambar bagusnya.  Seru juga untuk ngehias blog di awal tahun ini :D

Negeri Belanda