Improving Supply Chain with Free and Open Source Software

With the help of supply chain software, leading companies can analyze supply chain, obtain valuable information and make sound decision to streamline supply chain operations to the next level. Anyway, supply chain software is not always the option for small and medium enterprises.

Free and Open Source software (FOSS) has provided unprecedented opportunities for small companies to enhance their analytic capabilities. In addition, FOSS help to bring people closer to theories. Experimenting with FOSS also help large business enterprises to determine if certain functionalities are right for them so they can make better business case.

The purpose of this post is to establish the collection of high quality FOSS that supply chain practitioners can use to improve supply chain performance. It's centered around common supply chain problem solving techniques such as statistics, process analysis, performance measurement, modeling and optimization. Comments and suggestions from readers are very welcome, linking back to this post will be highly appreciated.

Bass Model for New Product Forecasting
New product forecasting is the special class of forecasting technique but it's often not discussed in most textbooks. One of the most prominent method was developed by Professor Frank M. Bass in 1963. The logic is to determine how products are adopted by consumers and apply the same growth rate to similar new products. It's very suitable for products with long life cycle. He also provides ready-to-use excel spreadsheet and you can download here.



Zaitun for Artificial Neural Networks Forecasting
When it comes to time series analysis, I believe Microsoft Excel is the best option for most forecasters because it's simple to use and manipulate data. Anyway, if level of demand fluctuation is high, basic time series analysis won't yield good results.

Artificial Neural Networks (ANN) is a kind of algorithm that can recognize patterns and improve prediction over times. In order to implement ANN, you need to learn programming. Anyway, Zaitun makes it easier for busy executives to take advantage of capability of ANN. The image below demonstrates how this software recognizes demand pattern and it keeps finding solution until target MSE is reached. The software is available to download here.



R-Project for Statistical Computing
Statistical method is the bread and butter of people working in marketing, economics and quality engineering. Most people rely on Microsoft Excel to perform simple statistical analysis. For more complex problems, people usually turn to SPSS. Anyway, these software are pretty expensive.

In 1991, Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand developed the first version of R. Later, it's become the open source statistical software and it's gained significant acceptance from academic communities. The reasons are that it's free and there are many add-ons to handle broad range of statistical analysis. Native R uses command line interface but graphic user interface is available here. Other useful add-ons are also available here.


In this post, Pairach who is the Ph.D. candidate at Logistics Systems Dynamics Group, Cardiff University demonstrates how to use R to measure transaction cost for supply chain relationship. He also compares the performance of R against other commercial software.


YAWL for Workflow System
Information flow enables various members in supply chain to achieve better planning to reduce costs and increase service level. ERP implementation seems to be number one priority for most companies. What if you want to improve information flow on the budget?

Workflow system is the use of information technology to streamline manual process and it is the integral part of major ERP software. You don't really have to make big investment to get this kind of functionality becuase YAWL or "Yet Another Workflow Language" is the open source software. In this example, YAWL is used to improve order fulfillment process. As you can see, modeling method is very intuitive and it looks very much like traditional flowchart. YAWL is available here.



Analytic Hierarchy Process for Multi Criteria Decision Making
The most common decision making technique is Linear Weighting Model. The concept is to multiply each decision criterion with certain weight. Anyway, obtaining weight can be subjective. Moreover, in complex decision making which consists of more than 10 criteria, Linear Weighting Model won't yield good result because people tend to focus too much on specific criterion.

Analytic Hierarchy Process (AHP) was developed by Thomas Saaty in 1977. This method establishes the goal, selects criteria, makes pairwise comparison between each criterion then checks for consistency.

In this example, AHP can be done in Microsoft Excel. However, I just found good AHP software by S. Anders Brandt. Only citation in report "Brandt, S.A. 2006, AHP v. 2.0. Analytic hierarchy process software" is required if you want to use this software. This software also comes with step-by-step guide as below,


MaxDEAfor Performance Evaluation
In supplier performance evaluation, you evaluate suppliers based on 4 basic type of measurement (cost / quality / delivery / service). The difficulty is that each type of measurement has different unit ($, quality level, % on time delivery, service quality score). Then how to evaluate different measurement units at the same time?

Data Envelopment Analysis (DEA) was developed by Charnes, Cooper and Rhodes in 1978. It's based on linear programming and it's capable of handing different type of measurements and different type of measurement units. In this Wikipedia page, there is the example how to formulate and solve basic DAE problem. To make it easier, you can use this DEA software. It's developed and implemented in Microsoft Access by CHENG Gang and QIAN Zhenhua. Basically, you prepare raw data in Excle file, import into this software, select category of each data, select DEA model and let the software do the trick. 


Warehouse Optimizer for Manual Warehouse Design
This software was developed by Professor Kees Jan Roodbergen at University of Groningen. The objective is to determine optimal number of warehouse shelves and block that minimizes average order picking distance in manual warehouse. It's based on this paper "Roodbergen, K.J., Sharp, G.P., and Vis, I.F.A. (2008), Designing the layout structure of manual order picking areas in warehouses. IIE Transactions 40(11), 1032-1045".

After downloading this software, you only input minimal design parameters and the software will suggest best possible layout. This is particularly useful if you wan to evaluate your current warehouse layout and to evaluate different design scenario.



ASDN for Supply Chain Modeling
It usually takes months to implement supply chain modeling project. Anyway, with ASDN software, you'll see how quick supply chain modeling can be. This software was developed by Professor Petri Helo at University of Vaasa in Finland. The software is available here with example files and quick user guide.



To start testing this software, double click the software file (in Java) then open one example file. Then you will see sample supply chain network as above. When you click on any supply chain node, you'll see basic input data on the left hand side. This means this software requires very minimal data input and that's the reason why ASDN is a rapid modeling tool.

When you input all required data for all supply chain nodes, the software will calculate system performance measurement such as total order lead-time, average inventory level in unit / $ and capacity constraint node.

You can develop test scenario by changing some supply chain nodes and the software will capture system performance for you. Or you can select Tools->Goal Seek function and this software will rearrange new decoupling points that minimize inventory level and reduce overall lead-time.

Time to market is crucial for many retail and apparel products. So this software is the ideal way to create supply chain improvement ideas.
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