Stock Demand Trends and Forecast v.17
The tool to calculate stock demand trends and make predictions for future demand statistically
If you knew the stock demand trends of your warehouses, you would have a clue to decrease keeping costs and have a flawless supply chain. Regretfully, you can't know the future. However, you can predict it with a certain reliability. This is an Odoo tool for that goal. The app lets you construct stock demand by periods and forecast scientifically further demand based on the Python library statsmodels.
The scientific approach to forecasting
The app assumes applying statistical methods to calculate historical trends and make a forecast. Experiment with statistical models and parameters to achieve the most reliable prediction. Leverage the proven statsmodels methods
Innovative data analysis interface
The tool introduces a special interface to instantly calculate series. Flexibly switch between different reports and update settings in a few clicks. Control data in pivot, graph, or chart views. Export series as an Excel tabled
Focused analysis
Shrink considered stock operations flexibly or analyze global company inventory demand. Group data into various series
Topical data
Apply time frames for historical data and work with intervals that are of interest to your industry. Work with past and future periods.
Flexible report configuration
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Introduce as many analytic reports as you need. Each report is based on Odoo's stock moves' data
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Keep reports to re-use them, instantly switch between reports, or experiment with real-time changes without saving those
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Show historical and forecast series as a table, line graph, or bar chart, or export data as an Excel table
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Apply as many and as different statistical models as you want to check. Each stats model will peer its own data series and prediction if the latter is possible. See also the section "Statistical models"
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Define the data periods under analysis by entering a start and end. Only inventory data within this interval will be included in the series
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Split data series into years, quarters, months, weeks, and days depending on seasons assumed in your industry or business area
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Select an unlimited number of periods to predict future periods or check hypotheses
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Grant the right to forecast tools for any WMS user (the group Inventory > Stock Demand Forecast)
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Filter stock data by product variants, product templates, product categories, units of measurement, source or destination locations, warehouses, operation/picking types, stock rules, and companies (for multi-company regimes). Introduce your own criteria based on Odoo's dynamic domain constructor, so shrink analysis by any stock move storable fields
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Introduce a few data series simultaneously with grouping by a product variant, a unit of measurement, a source or destination location, a warehouse, a stock move state, an operation type, a stock rule, or a company. Take into that if the report assumes products with different units of measurement, the grouping will be possible only by the units or by variants
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Hide/show general statistical measurement of series: count, mean, standard deviation, minimum, maximum, 25%, 50%, and 75% factors
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Optionally compare predicted values to real historical data if any. See also the section "Hypothesis Testing"
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Make figures human readable (e.g. 192,217 as 200k) or show them precisely.
Statistical models
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The tool allows calculating inventory demand trends based on predefined statistical models introduced by the Python package statsmodels
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Methods have different complexity, and their own unique parameters, and might be suitable for a definite market or a specific business. The final choice of the model and related statistical parameters is only up to you. Nobody except you can better understand tendencies in your company inventory demand, and hence which methods and factors should be applied
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Available statistical models are Autoregression (AutoReg), Autoregressive Distributed Lag (ARDR), Autoregressive Integrated Moving Average (ARIMA), Seasonal Autoregressive Integrated Moving-Average (SARIMAX), Holt Winter's Exponential Smoothing (HWES), Simple Exponential Smoothing (SES)
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For deep details about what each stats model means and which parameters might be applied, look through the tab "Help" on the stats model form
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Keep and use an unlimited number of stats models with various parameters. Check, compare, and update those flexibly through the forecast manager interface
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Often models with specific parameters will not result in any prediction or the prediction will be unrealistic. This is normal, only a deep understating of trends and much experimenting might give a viable forecast for your specific case.
Hypothesis Testing
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To get a proper prediction, it is usually needed to experiment a lot with statistical models and introduced parameters. To check the results, the app allows compare forecast data with real values
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To check a certain assumption with historical values, you may make an analysis and prediction for some past periods, and turn on the setting "Hypothesis testing"
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For example, you have stock moves from 2017 to 2022. Then, you can get report historical data for 2017-2021, and make the forecast for 12 months of 2022. In this way, you will get the prediction for the interval for which you already have actual values. By comparing forecast and actual values, you can decide whether a chosen model and factors are good enough
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The app allows checking the hypotheses for a few stats models simultaneously. In this way, it is possible to reveal what is actually the most appropriate, or whether experimenting should be continued.
Usage requirements
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To reveal trends, there should be enough historical stock moves data. It is senseless to make a forecast based on the last 5 days of operations since no trend cannot be retrieved. Take into account that data should be enough for the chosen filters and for each grouped series
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There should be not only enough stock moves but also there should be some actual trends. Chaotic data will not result in reliable predictions. To use the app, you should understand which assumptions (e.g. seasonal changes) you check
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To use the app, you either should have a clear understanding of how statistics works or a will to understand that. Regretfully, there is no way to make a "general" analysis, each specific case is unique and requires its own elaboration.
Savjeti za konfiguraciju i instalaciju za Stock Demand Trends and Forecast Odoo v.17
Python dependencies
To guarantee the tool works correctly, a number of Python libraries are required: pandas, numpy, statsmodels, scipy, xlsxwriter. To install those packages execute the command:
pip3 install pandas numpy statsmodels scipy xlsxwriter
If you run Odoo on Python prior to or equal to version 3.7, please install the following versions of the packages pandas==1.3.5, statsmodels==0.13.1
Server memory limits
Running the statistical analysis and making the forecast is quite a resource-demanding operation. If users face the hanging interface, make sure that server memory limits and timeouts are enough. Otherwise, increase those settings.
Često postavljana pitanja o Stock Demand Trends and Forecast Odoo v.17
Koje su politike ažuriranja vaših alata?
Prema važećim pravilima Odoo Apps Store:
- Svaki modul kupljen za verziju 12.0 i stariju daje pristup svim verzijama do 12.0.
- Od verzije 13.0 svaku verziju modula treba kupiti zasebno.
- Bez obzira na verziju, kupnja daje pravo na sva ažuriranja i ispravke unutar glavne verzije.
Imajte na umu da tim faOtools ne kontrolira ta pravila. Za pitanja obratite se izravno predstavnicima Odoo Apps Store.
Kako mogu instalirati vašu aplikaciju na Odoo.sh?
Najizravniji je pristup koristiti ugrađeni tijek rada Odoo trgovine:
1. Otvorite stranicu modula i kliknite gumb Deploy on odoo.sh
2. Nakon toga bit ćete preusmjereni na GitHub stranicu. Prijavite se na račun, zatim kliknite 'Create a new repo' ili upotrijebite postojeći. Provjerite da je spremište privatno. Nije dopušteno objavljivati aplikacije pod licencijom OPL-1. Ako treba, stvorite novi repo za Odoo.sh projekt
3. Zatim idite na odoo.sh i kliknite gumb Deploy. U skočnom prozoru potvrdite odluku i kliknite 'Continue.' Time se pokreće instalacija.
Ovi koraci instalirat će aplikaciju na produkcijsku granu projekta. Ako želite postaviti aplikacije na druge grane ili ažurirati modul, poduzmite sljedeće:
1. Prenesite izvorni kod aplikacije iz Odoo trgovine
2. Napravite commit modula u potrebni GitHub repozitorij. Provjerite da nijedna mapa/datoteka aplikacije nije ignorirana (tj. nije u .gitignore repozitorija). Repozitorije automatski stvara odoo.sh i po zadanim postavkama mogu sadržavati važne stavke (npr. /lib). Prenesite sve direktorije, poddirektorije i datoteke modula bez iznimaka
3. Postavite ciljnu granu odoo.sh projekta ili, ako to pretpostavljaju postavke, pričekajte dok se automatski izgradi.
Kako trebam instalirati vašu aplikaciju na vlastiti poslužitelj?
2. Ponovno pokrenite Odoo poslužitelj;
3. Uključite način za razvoj (tehničke postavke);
4. Ažurirajte popis aplikacija (izbornik aplikacija);
5. Pronađite aplikaciju i pritisnite „Activate“/„Install“;
6. Slijedite smjernice na stranici aplikacije ako postoje.
Primijetio sam da vaša aplikacija ima dodatne dodatke. Mogu li ih kupiti naknadno?
Da, naravno. Istodobno Odoo automatski dodaje sve ovisnosti u košaricu, pa prethodno kupljene alate treba isključiti da ne platite dvaput.
Postavio sam vašu aplikaciju na Odoo.sh i u testovima vidim upozorenje/pogrešku
Crveno/narančasto upozorenje ne utječe na značajke aplikacije. Nažalost, naši moduli ponekad ne prođu standardne automatske testove jer oni pretpostavljaju ponašanje koje je u sukobu s ciljevima aplikacije. Npr. mijenjamo izračun cijene, a testovi standardnog Odoo modula uspoređuju konačnu cijenu sa standardnim algoritmom.
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Ako i dalje smatrate da upozorenje utječe na stvarne značajke, javite nam i pošaljite potpune zapisnike instalacije i potpuni popis postavljenih modula (uključujući jezgru i treće strane).
Mogu li kupiti aplikaciju izravno od vaše tvrtke?
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Želio bih dobiti popust
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Mogu li instalirati aplikaciju u svoju bazu Odoo Online (SaaS)?
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Vaš alat ovisi o drugim aplikacijama. Trebam li ih kupiti?
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Koja je cijena modula u američkim dolarima? Zašto se promijenila?
Cijena naših modula je u eurima. Odoo trgovina pretvara cijene u druge valute prema internom tečaju. Stoga se cijena u američkim dolarima može promijeniti kad se tečaj ažurira.
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Odoo demonstracijske baze (pregledi uživo)
Za ovu aplikaciju možemo osigurati besplatnu personaliziranu demo bazu.
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Prijava grešaka
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Javni zahtjevi za značajke i ideje modula (besplatan razvoj)
Snažno smo motivirani poboljšati svoje alate i zahvalni smo na svakoj povratnoj informaciji. Ako su vaši zahtjevi od javne koristi i mogu se učinkovito provesti, tim će ih uvrstiti na naš popis zadataka.
Takav popis zadataka obrađuje se redovito i ne podrazumijeva dodatne naknade. Iako ne možemo obećati rokove i konačni dizajn, to može biti dobar način da dobijete željene značajke bez ulaganja i rizika.
Za kontakt nije potreban broj telefona ni kreditna kartica. Potrebna je samo kratka prijava e-poštom koja ne traje više od 30 sekundi.
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