Stock Demand Trends and Forecastby Odoo Tools
If you knew stock demand trends per warehouses, you would have a clue to decrease keeping costs and to have a flawless supply chain. Regretfully, you can't know the future. However, you can predict it with a certain reliability. This is the tool for that goal. The app let you construct stock demand per periods and forecast further demand.
The tool is compatible with both Odoo Enterprise and Odoo Community.
It is the simplest but still widely used statistical method for time series forecast. Using the method you consider stock demand trends being linear without seasonal effects, without a purely defined trend, and without smoothing abnormal observation.
Moving Average (MA) and Autoregressive Moving Average (ARMA)
The moving average method takes into account 'errors' in previous observations, and in comparison to the AR method smooths abnormal data.
The autoregressive moving average method is a combination of both AR and MA methods. To apply the ARMA method use the MA method with auto regression coefficient (P coefficient) as 2
Autoregressive Integrated Moving Average (ARIMA)
The method which also combines the methods AR and MA, but also tries to make data stationary. It is appropriate to use for historical data with pure trend but without seasonal changes.
Seasonal Autoregressive Integrated Moving-Average (SARIMA)
The SARIMA method enriches the ARIMA method with considering seasonal changes. It is one of the most complex and wide spread methods utilized for forecasting time series now
Simple Exponential Smoothing (SES)
The SES model usage is similar to the AR method, but instead of relying upon linear function, it exploits exponential one
Holt Winter’s Exponential Smoothing (HWES)
The HWES method enriches the SES method to work with time series trends and seasonal effects.
When this tool should be used
- You have enough historical stock demand data (per location or company), since it is senseless to make forecast based on last 5 days of operations
- Stock demand is regular and is not chaotic, meaning that your decisions do not have 100% impact and there is at least some correlation between market demand and your WMS operations
- You have some seasonal and from period to period trends, which you noticed but can't fully analyse
The tool to search, select and update product templates in batch€ 92
The tool to make inventory data essential and comfortable for elaboration€ 36
The tool to configure variant prices based on attributes coefficients and surpluses€ 96
The tool to restrict rights for create, edit and delete products€ 28
The tool to always know how much our production may promise€ 36
The tool to restrict users' access to stocks, locations and warehouse operations
The tool to build deep and structured knowledge base for internal and external use€ 228
The tool to automatically synchronize Odoo attachments with OneDrive files in both ways€ 394
The tool to automatically synchronize Odoo attachments with OwnCloud / NextCloud files in both ways€ 394
To guarantee tool correct work you would need a number of Python libraries: pandas, numpy, statsmodels, scipy, xlsxwriter. To install those packages execute the command:
pip install pandas numpy statsmodels scipy xlsxwriter
Default valuesIn the most cases you apply the same statistical model and forecast the same number of periods. To save time you can assign default values to the report wizard. Go to Inventory > Settings and find the section 'Sales Trends and Forecast'
OdooTools is the team of developers and business analysts to help you extend Odoo potential. We have been communicating with end users to whom the software became the main business tool since 2012. As a result, we are proud of dozens of successful Odoo apps developed. We are open for new ideas and challenges to create the best Odoo tools for business needs all over the world.
Odoo Proprietary License v1.0 This software and associated files (the "Software") may only be used (executed, modified, executed after modifications) if you have purchased a valid license from the authors, typically via Odoo Apps, or if you have received a written agreement from the authors of the Software (see the COPYRIGHT file). You may develop Odoo modules that use the Software as a library (typically by depending on it, importing it and using its resources), but without copying any source code or material from the Software. You may distribute those modules under the license of your choice, provided that this license is compatible with the terms of the Odoo Proprietary License (For example: LGPL, MIT, or proprietary licenses similar to this one). It is forbidden to publish, distribute, sublicense, or sell copies of the Software or modified copies of the Software. The above copyright notice and this permission notice must be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Please log in to comment on this module
- The author can leave a single reply to each comment.
- This section is meant to ask simple questions or leave a rating. Every report of a problem experienced while using the module should be addressed to the author directly (refer to the following point).
- If you want to start a discussion with the author or have a question related to your purchase, please use the support page.