Open source initiatives for Lokad integration

Published on by Joannes Vermorel.

Currently Lokad is essentially an hosted solution relying on closed source software; but this situation is likely to evolve since we have already started to work on various applications that will be released under BSD license (the BSD license is an open source license compatible with closed-source commercial applications).

Integrating Lokad into existing applications

Lokad provides time-series forecasts; in order to leverage most of the added-value of those forecasts, an integration of Lokad within the company systems (ERP, CRM, SCM among other) is usually required. This integration can represent a significant investment for our customers depending on the complexity/extensibility of the existing applications. Thus, we want to lower the costs associated to those integrations.

We are currently planning to release as open source the Lokad integration components; i.e. the piece of software used to integrate Lokad within other applications. Those components will be actively supported by Lokad; yet, the open source license will give more freedom to our customers to customize or to adapt those components without having to wait for next release (if they want to).

Lokad OpenShell project

The first open source integration component to be released will be the Lokad OpenShell (planned for Q1 2007), a MS PowerShell Snap-In that will let you interact with the Lokad Web Services directly from the shell command-line. We have already setup a project space on CodePlex. Feel free to post your requests / suggestions.

 More generally, if you think that your current ERP, CRM, SCM ... application deserve its own open source Lokad integration component, do not hesitate to contact us (or simply post a comment to this post); your feedback will be used to assign the right priorities to the various projects.

Categories: community, open source, partners Tags: No Comments

Web Services Tutorial in C#

Published on by Joannes Vermorel.

The Lokad Web Services provide a programmatic access to all the Lokad features. Accessing the Lokad Web Services is easy and straighforward. We have just released a 100 lines .Net project that illustrates how to perform a full round-trip with our Web Services; first uploading some time-series data and finally retrieving forecasted time-series.

The source-code is available on CodePlex under a BSD license 

An extensive tutorial explaining every line of this project is under way.

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Upcoming Lokad User Guide

Published on by Joannes Vermorel.

I have almost finished to write the Lokad User Guide. In case you might be interested, I have pasted below the table of content of this guide. Stay tuned for the release. Meantime you can contact us directly, we will do our best to answer your questions.

Lokad, User guide

  • Preface
    • Who should read this guide?
    • What is the content of this guide?
  • Table of contents
  • Time-series forecasting applied to business
    • What is a time-series?
    • Profitability through time-series forecasting
  • The Lokad services
    • Big picture
    • Time-series data
    • Forecasting tasks
    • Forecasted time-series retrieval
    • Lokad business network

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Upcoming documentation

Published on by Joannes Vermorel.

 Update: New documents mentioned below have been released 2006-12-09.

We know that documentation is still a weak point of Lokad, but we are already working on it. We will soon release a series of short documents

  • In a nutshell: Forecast, Why and How?
  • Top 10 benefits of Lokad
  • Lokad vs. the Competition
Plus, we are also working on extensive (and printable) guides for Lokad. Stay tuned. Meantime the email support will do its best to answer all your questions.

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Do not make a sum with your forecasts

Published on by Joannes Vermorel.

Although we have tried to make Lokad as simple and intuitive as possible, statistical forecasting is a counter-intuitive science with many traps. In this post, I am going to describe one of the most frequent mistakes that I have encountered within many companies. In a nutshell, it is wrong to make a sum of forecasted values. Since the problem is quite hard to grasp, let's start with an example.

Let's say that you have 3 shops; and that those 3 shops are selling coconuts. Being in charge of the supply chain, let's say that you need to forecast how much coconuts must be re-ordered next week. The coconuts will not be delivered to the shops directly but to a single warehouse. Thus there is only a single coconuts replenishment order for the 3 shops.

In order to perform your replenishment forecast, it is natural to rely on your historical coconuts sales data. In the present situation, you have 3 time-series representing the daily coconuts sales for each one of the 3 shops. How can we perform a single replenishment forecast based on those 3 time-series?

A naive method would consist of making one coconuts' sales forecast for each time-series (one forecast per shop), and then to make the sum of those 3 forecasted values in order to compute the replenishment order. Unfortunately, this method is wrong. A much more accurate approach consists of aggregating first the 3 time-series into one (i.e. summing the 3 time-series) and then performing a forecast directly on the aggregated time-series.

You are probably wondering what difference it makes between the two methods: forecasting first and then making the sum OR making the sum first then forecasting. Well, the true explanation requires some statistics that are totally beyond the scope of the post, thus I will try to give an intuitive explanation of the phenomenon. Summing forecasts does not improve the accuracy whereas making a forecast based one a single smoother time-series does improve the accuracy (the sum of 3 time-series is smoother than the initial time-series).

Categories: accuracy, forecasting, tips Tags: No Comments