Product details are displayed in English. Translations coming soon.
Quick facts
- Price
- $499.00 USD
- ERPNext versions
- —
- Setup time
- 30 min
- License
- One-time perpetual
- Languages
- 11 languages
ایک بار کی خریداری
Demand Forecasting & MRP Optimizer for ERPNext
A build-to-order ERPNext app that adds statistical demand forecasting, safety-stock and reorder-point optimization, and MAPE accuracy tracking, then feeds the results straight into ERPNext's Production Plan and reorder engine. ECOSIRE scopes, builds, installs, and supports it for your instance.
$499.00USD
ابھی کوئی ادائیگی نہیں۔ یہ ہماری ٹیم کو قیمت کی درخواست بھیجتا ہے — ہم قیمت اور اگلے اقدامات کے ساتھ ای میل کے ذریعے رابطہ کریں گے۔
اہم خصوصیات
`Demand Forecast` and `Forecast Item` DocTypes storing per-item, per-period projected demand with a versioned, approvable document workflow
Configurable forecasting methods per item or item group: simple/weighted moving average, single and double (Holt) exponential smoothing, and seasonal Holt-Winters for items with recurring seasonality
Safety-stock computation from demand standard deviation, lead-time variability, and a target service level (z-score), replacing hand-typed static values
Reorder-point optimization that writes back to each Item's native `reorder_level` / `reorder_qty` via a `hooks.py` `doc_events` handler so ERPNext's built-in reorder engine fires on optimized thresholds
Whitelisted server method to generate a draft ERPNext `Production Plan` directly from an approved forecast, respecting BOMs and existing open orders
Auto-creation of draft Material Requests and Purchase Orders from forecasted net requirements, left in draft for planner review
ABC classification by revenue contribution and XYZ classification by demand-variability (coefficient of variation), stored on the item for filtering and policy defaults
Forecast-vs-actual accuracy tracking with per-item and aggregate MAPE plus forecast bias, retained each cycle for trend analysis
Scheduler events registered in `hooks.py` (nightly/weekly) that recompute forecasts and reorder policies from `Stock Ledger Entry` and `Sales Invoice Item` history
Server Scripts and a dedicated `Forecast Model Config` DocType so smoothing factors, seasonal periods, and horizons are tunable without redeploying code
Client Scripts on the Item and Forecast forms for inline what-if of service level and lead time before committing a policy
Dedicated `Demand Planner` Role and Role Profile with DocType- and field-level permissions plus optional User Permission scoping by warehouse or item group
Planner dashboard and report views (Query/Script Report) for MAPE, bias, stockout-risk items, and slow-moving/dead XYZ-C stock
Full Frappe REST API and whitelisted endpoints exposing forecasts, policies, and accuracy metrics for Power BI or an external planning tool
Built and tested against Frappe/ERPNext v15 and v16, packaged as a standard installable app with migration-safe fixtures
اس مصنوع کے بارے میں
Most manufacturers and distributors running ERPNext hit the same wall: the platform plans supply beautifully once you tell it what demand will be, but it has almost no opinion about the demand itself. ERPNext's Production Plan pulls from open Sales Orders and Material Requests, and the reorder engine relies on static reorder_level / reorder_qty values you type into the Item master by hand. There is no moving average, no exponential smoothing, no seasonality, no safety stock derived from demand variability and lead-time risk, and no feedback loop telling you whether last month's plan was any good. Planners end up maintaining forecasts in spreadsheets and re-keying reorder points quarterly, which is exactly where stockouts and dead inventory come from.
Demand Forecasting & MRP Optimizer for ERPNext کیوں منتخب کریں
`Demand Forecast` and `Forecast Item` DocTypes storing per-item, per-period projected demand with a versioned, approvable document workflow
Configurable forecasting methods per item or item group: simple/weighted moving average, single and double (Holt) exponential smoothing, and seasonal Holt-Winters for items with recurring seasonality
Safety-stock computation from demand standard deviation, lead-time variability, and a target service level (z-score), replacing hand-typed static values
Reorder-point optimization that writes back to each Item's native `reorder_level` / `reorder_qty` via a `hooks.py` `doc_events` handler so ERPNext's built-in reorder engine fires on optimized thresholds
Whitelisted server method to generate a draft ERPNext `Production Plan` directly from an approved forecast, respecting BOMs and existing open orders
Auto-creation of draft Material Requests and Purchase Orders from forecasted net requirements, left in draft for planner review
This is a proper Frappe app (demand_forecasting_mrp) that ECOSIRE builds for your instance, not a theme or a set of custom fields bolted onto stock ERPNext. It ships a Demand Forecast DocType and per-period Forecast Item child rows, a Forecast Model Config DocType where you choose the method (moving average, single/double exponential smoothing / Holt, or seasonal Holt-Winters) and its parameters per item or item group, and a Reorder Policy DocType that computes safety stock and reorder point from demand standard deviation, lead time, and a target service level (z-score) rather than a fixed number. A scheduler event registered in hooks.py recomputes forecasts on your chosen cadence (nightly or weekly) by reading historical consumption from Stock Ledger Entry and Sales Invoice Item, so the numbers stay current without anyone touching a spreadsheet.
The output is wired back into ERPNext's own planning, not a parallel report. Whitelisted server-side methods generate a draft Production Plan (and, where relevant, Material Requests and draft Purchase Orders) directly from the approved forecast, and a hooks.py doc_events handler keeps each Item's reorder_level and reorder_qty in sync with the latest computed policy so the native reorder engine fires on optimized thresholds. An ABC/XYZ classification job segments items by revenue contribution (ABC) and demand variability (XYZ) so planners spend attention where it matters, and every forecast cycle stores forecast-vs-actual so a dashboard can track MAPE and bias over time. All of it respects Frappe permissions — a dedicated "Demand Planner" Role and Role Profile, DocType-level and (where needed) User Permission scoping so planners see only their responsibility area — and every number is reachable through the standard Frappe REST API for BI tools or an external planning workbench.
Because this is build-to-order, nothing is pre-listed for instant download. We start with a short scoping call, confirm which forecasting methods, service levels, and MRP hand-off behavior fit your operation, and then build against that signed-off scope. Typical delivery is 2-4 weeks from confirmed scope. You get the installable app source for your version of Frappe/ERPNext (v15 or v16), installation and configuration on your instance, UAT on a staging bench with a documented rollback plan, training for your planners, and a post-go-live support window. The git repository is handed to you at the end, so you own the code.
What you get
- Installable Frappe app source (`demand_forecasting_mrp`) built for your Frappe/ERPNext v15 or v16 instance
- Installation and configuration on your bench, including scheduler-event setup, Role Profile creation, and initial model calibration
- Technical documentation: DocType reference, hooks.py events, whitelisted methods, and REST API endpoints
- User guide plus a live training session for your demand planners and supply-chain team
- UAT on a staging bench with a documented, tested rollback plan before production cutover
- Post-go-live support window for defect fixes and questions after deployment
- Handover of the complete git repository so you own and can extend the code
- Data-mapping notes covering which historical sources (Stock Ledger, Sales Invoice) feed each forecast and how MRP hand-off behaves
Who this is for
Demand planner
Owns the forecast and wants ERPNext to produce statistically grounded projections (moving average, smoothing, seasonality) with MAPE and bias tracking, instead of maintaining forecasts in a spreadsheet and re-keying reorder points every quarter.
Supply-chain / inventory manager
Needs safety stock and reorder points derived from demand variability, lead time, and a target service level, plus ABC/XYZ segmentation to cut stockouts on A-items while releasing cash trapped in slow-moving C-items.
Production / MRP planner
Wants forecast-driven Production Plans, Material Requests, and draft POs generated automatically inside ERPNext, with BOM explosion and existing open orders respected, so planning starts from a defensible demand number.
ERP / operations lead
Responsible for the ERPNext instance and wants a properly built Frappe app with clean DocTypes, permission-scoped roles, REST API access for BI, and v15/v16 support — not brittle custom fields and manual scripts.
Installation overview
Download from ECOSIRE
Buy the license on ecosire.com and download the Demand Forecasting & MRP Optimizer for ERPNext app ZIP from your account dashboard.
Add the app to your bench
Extract the ZIP into your bench's apps folder, or run `bench get-app` with the path to the extracted app.
Install on your site
Run `bench --site SITE_NAME install-app APP_NAME` followed by `bench migrate` to install Demand Forecasting & MRP Optimizer for ERPNext and apply its schema.
Activate your license
Open the ECOSIRE License settings on your site and activate your license key. Requires the free ecosire_connect and ecosire_license_client apps.
How Demand Forecasting & MRP Optimizer for ERPNext Compares
| Criterion | ECOSIRE | Custom Build | Competitor | Odoo Native |
|---|---|---|---|---|
| Statistical forecasting (smoothing, seasonality) | Built in: moving average, Holt, Holt-Winters, configurable per item | Whatever you scope and can build in-house | Often basic moving average only, if any | |
| Safety stock & reorder optimization | Computed from demand variance, lead time, service level | Possible but you design the model | Varies; frequently static thresholds | |
| Forecast accuracy (MAPE / bias) | Tracked every cycle, per-item and aggregate | Only if you build the tracking | Rarely included | |
| ABC/XYZ classification | Automated by revenue and demand variability | Buildable with effort | Sometimes ABC, XYZ uncommon | |
| MRP / Production Plan hand-off | Draft Production Plans + POs generated from forecast | You wire the integration | Often exports, not native hand-off | |
| Fit to your ERPNext instance | Scoped to your data, roles, and v15/v16 bench | Fully bespoke but you own delivery risk | Generic; take-it-or-leave-it config | |
| Ownership & extensibility | Full git repo handover, standard Frappe app | You own it; you also maintain it | Vendor-controlled; limited source access | |
| Support & delivery model | Build-to-order, UAT, training, post-go-live window | Depends on your team's bandwidth | Ticket support, generic docs |
Frequently Asked Questions about Demand Forecasting & MRP Optimizer for ERPNext
+How long does delivery take?
This is a build-to-order app, so nothing is downloaded instantly. After a short scoping call we confirm the forecasting methods, service levels, and MRP hand-off behavior you need, then build against that signed-off scope. Typical delivery is 2-4 weeks from confirmed scope, depending on how many forecasting methods and integrations are in scope.
+Does this replace ERPNext's Production Plan and reorder engine?
No — it feeds them. We keep ERPNext's native planning and reorder logic and make it smarter: the app computes optimized reorder points and safety stock and writes them back to each Item's `reorder_level` / `reorder_qty`, and generates draft Production Plans and Material Requests from approved forecasts. Your team keeps working in standard ERPNext screens.
+Which Frappe/ERPNext versions are supported?
We build and test against Frappe/ERPNext v15 and v16. Tell us your exact version and bench setup during scoping and we target that; the deliverable is packaged as a standard installable Frappe app so it fits your existing bench and migration flow.
+What forecasting methods do you support?
Moving average (simple and weighted), single and double (Holt) exponential smoothing, and seasonal Holt-Winters for items with recurring seasonality. Method and parameters are configurable per item or item group via a `Forecast Model Config` DocType, and accuracy is tracked with MAPE and bias so you can compare methods on your own data.
+How does support and updates work after go-live?
Every engagement includes a post-go-live support window for defect fixes and questions. Because you receive the full git repository, your team can extend the app themselves, and we offer ongoing support or enhancement work — including compatibility updates when you upgrade Frappe/ERPNext — as a separate arrangement after the initial window.
+Will it deploy safely on our production instance?
Yes. We install and validate on a staging bench first, run UAT against your data, and prepare a documented rollback plan before any production cutover. The app uses migration-safe fixtures and standard Frappe install mechanics, and scheduler events are configured to run on a cadence that suits your data volume.
+Can we access the forecast data from Power BI or another tool?
Yes. Forecasts, reorder policies, and accuracy metrics are stored in proper DocTypes and exposed through the standard Frappe REST API and dedicated whitelisted methods, so Power BI, a data warehouse, or an external planning workbench can read them with role-scoped API keys.
Related Modules
قیمت کا تخمینہ طلب کریں
Demand Forecasting & MRP Optimizer for ERPNext
A build-to-order ERPNext app that adds statistical demand forecasting, safety-stock and reorder-point optimization, and MAPE accuracy tracking, then feeds the results straight into ERPNext's Production Plan and reorder engine. ECOSIRE scopes, builds, installs, and supports it for your instance.
- `Demand Forecast` and `Forecast Item` DocTypes storing per-item, per-period projected demand with a versioned, approvable document workflow
- Configurable forecasting methods per item or item group: simple/weighted moving average, single and double (Holt) exponential smoothing, and seasonal Holt-Winters for items with recurring seasonality
- Safety-stock computation from demand standard deviation, lead-time variability, and a target service level (z-score), replacing hand-typed static values
- Reorder-point optimization that writes back to each Item's native `reorder_level` / `reorder_qty` via a `hooks.py` `doc_events` handler so ERPNext's built-in reorder engine fires on optimized thresholds