Best Demand Planning Software

StockTrim is a self-serve forecasting and order-planning tool for small and mid-sized product companies, sold as one plan priced by annual revenue.

StockTrim: how the forecast is made. StockTrim syncs sales, stock and open purchase orders from a connected system or a CSV and forecasts 24 months ahead. The Demand Analysis screen shows the forecast model (set to auto), a seasonality toggle, the history period, growth and excluded outliers, and the planner can override any month by hand or by template upload. The pages we read name no algorithms, safety stock formula or review period, so ask which model runs on your items.

StockTrim: from forecast to purchase order. The reorder point is lead-time demand plus a safety stock set from your service level. The order quantity is the reorder point minus stock on hand and on order, rounded for minimum order quantity and batch size. On the Order Plan, rows that are short on stock turn red and Create Purchase Orders builds one draft PO per supplier. A planner edits lines against container volume, weight or budget limits, approves, and either sends the PO to a compatible inventory system or downloads a PDF or CSV.

StockTrim: stack and limits. It names Shopify, QuickBooks, NetSuite, Unleashed, Fishbowl, Katana, Zoho Inventory, Odoo, Amazon FBA and others, plus API access. The pages describe no S&OP, promotion modelling or multi-echelon planning, and one Capterra reviewer says work orders and transfers can't sync. Raw-material forecasting with multi-level bills of materials is a paid add-on.

Users like

Easy to use and set up, fast and helpful support, forecasts that stopped over-ordering and cut stock-outs, two-way sync of POs back to the ERP.

Users dislike

Initial navigation and multi-level BOM setup take time, new-product forecasts can feel off for one-offs, SKU codes must be consistent to avoid duplicates, some work orders and transfers cannot sync.

Source: Capterra, 14 reviews

Inventory Planner by Sage connects to your stores, marketplaces and inventory system, forecasts demand per SKU and shows a recommended order quantity and replenish date for each one.

Inventory Planner documents two forecast methods. Last sales averages sales over a set number of days and ignores seasonality. Seasonal uses the same months of earlier years and needs at least 12 months of history. The planner sets one method for the account and overrides it for single variants. Lead time and days of stock can be set per variant, vendor or warehouse, and stockout periods can be left out of sales velocity so a sold-out item doesn't look like a slow seller.

The replenishment report is where a buyer works. It ranks items by forecast lost revenue or by sell-out date, the buyer reviews or edits the forecast and the stockout history, and POs are raised from the recommendations with the supplier's currency, minimum order quantity and payment terms already filled in. That makes it a tool for people who place many small orders across many suppliers.

On the stack side it names Shopify and Shopify Plus, Amazon, WooCommerce, eBay and BigCommerce, plus Brightpearl, Cin7, QuickBooks, Linnworks, NetSuite and Dynamics 365. It is built for retailers, wholesalers and multichannel sellers. The help pages document no statistical safety stock and no material requirements planning, and a reviewer says manufacturing and bill-of-materials workflows need careful configuration.

Users like

Dashboards give shared visibility of demand and purchasing; forecasting picks up seasonality and replaces spreadsheets; support rated 4.6.

Users dislike

Pricing seen as high and revenue-based; reports sometimes need data configuration; forecasting algorithm called improvable by one reviewer; a 2022 review describes slow support during an outage.

Source: Capterra, 82 reviews

Flieber forecasts demand per SKU and channel and turns the forecast into replenishment and transfer plans for brands that sell through several channels.

Flieber corrects its own input before it forecasts. Its False Zero Substitution feature detects periods when an item was out of stock and estimates the true demand, and it adjusts out the spike that follows a restock. The help center describes a custom model built with Nixtla's TimeGPT and blended with a seasonal model at daily and weekly level. Planners review flagged exceptions and override forecasts for promotions, targets and new products at SKU, channel or group level.

The purchasing side is where Flieber stands out. Replenishment recommendations are built from safety stock, target days of cover, lead times and order frequency, which can be set per product, category or channel. In the plan view an AI assistant can rebalance quantities to a target arrival date, a container or pallet type and a cash cap, and shows its reasoning for each edited cell. The result is draft purchase orders grouped by supplier, or an inbound shipment, that respect minimum order quantity and case pack and can be pushed to systems such as NetSuite after approval.

It reads Amazon, Shopify, Walmart, TikTok Shop, eBay, Etsy and BigCommerce, and the help center names Anvyl and NetSuite. Flieber's own page says it isn't a fit for single-channel sellers, for WMS or full ERP needs, or for manufacturing planning.

Users like

Customer support, ease of use, forecasting accuracy and inventory management (G2 summary tags); reviewers cite one place for sales, stock and supply data and fewer stockouts/overstock

Users dislike

Complexity and a learning curve, plus forecasting limitations (G2 summary tags); one reviewer wants more APIs and channel connections

Source: G2, 30 reviews

Netstock sits on top of your ERP and turns stock, order and sales data into daily-recalculated safety stock, reorder points and supplier-level order recommendations.

Netstock: the order logic is documented. This is the best-documented formula in the group. Reorder point is safety stock plus lead time. The order-up-to level adds the replenishment cycle. The recommended order quantity is the order-up-to level minus net stock when net stock is below the reorder point, and MOQ and order multiples then adjust it upward. Safety stock is recalculated daily from your target fill rate, lead time, supplier risk and forecast risk, and planners can override fill rate per item.

Netstock: how a buyer works in it. The planner reviews forecasts and the Projection tab, opens the Orders screen to generate an order schedule, filters by classification and impact, and uses a Solver to shape orders toward a value, volume or weight target before finalizing. The help center says order status shows whether an order was downloaded to the ERP or exported.

Netstock: forecasting is a separate purchase. The Demand Planning add-on, with top-down, bottom-up and middle-out forecasting by product, channel and customer plus promotions and events, is quoted separately and isn't part of the $900 entry bundle. Netstock names over 60 ERP integrations, including NetSuite, Sage, Acumatica, Microsoft Dynamics, SAP Business One, SYSPRO and Cin7 Core.

Users like

Ease of use (18 mentions), inventory management (17) and forecast accuracy (17), per G2's summary of reviews.

Users dislike

Missing features (10 mentions), data inaccuracy (8) and data management issues (7); one 2/5 review from a Dynamics NAV manufacturer describes a nine-month implementation and lost trust in recommendations.

Source: G2, 182 reviews

GMDH Streamline forecasts demand with time series decomposition, then calculates safety stock and an ordering plan with order-by dates that a buyer previews before creating purchase orders.

The planner imports sales and stock through built-in connections, a database connection or spreadsheets and updates the project on the data cadence, for example monthly. Streamline recommends at least 24 months of sales history so it can pick up seasonality, estimates true demand from stockout information, and lets the planner adjust forecasts manually for promotions and events, including custom holiday calendars.

Replenishment parameters such as supplier lead time are set once and revised when suppliers change. Streamline then calculates safety stock, shows projected stockouts and overstocks, and recommends what to order now. The buyer edits quantities and items in a purchase order preview, creates the POs, and the tool calculates a next order by date. That preview step is the clearest buyer-facing control in this group. The workflow documentation also covers transfers between locations and material requirements from bills of materials.

G2 lists vendor-verified integrations with Acumatica, NetSuite, SAP Business One, SAP S/4HANA Cloud, Microsoft Dynamics 365 and Shopify. One Capterra reviewer without a direct integration needed a manual twice-monthly import.

Users like

Capterra reviewers (4.8 from 11, mostly 2018 to 2020) call projections easy to set up and change, the forecasting models flexible and support strong.

Users dislike

Capterra reviewers say skilled staff are needed to read the output and setup is tedious without a direct integration.

Source: G2, 278 reviews

Slimstock's Slim4 classifies each SKU by demand behavior, applies a fitting forecast model and drives replenishment and multi-echelon inventory optimization across a network of locations.

Slimstock doesn't ask you to choose a forecasting method. Slim4 classifies each SKU by how its demand behaves and applies the model that fits, and the vendor doesn't name the model families. Inventory parameters are recalculated from demand volatility, forecasts, supplier lead times and constraints, and the service levels you set. Planners work from exception alerts where real demand departs from the forecast, and customer stories describe planners working from a to-do list rather than reviewing every SKU. Prodalam, a customer with 40 branches and 3 distribution centers, is the vendor's example of balancing stock across a network.

For purchasing, the replenishment module generates recommendations or can create purchase orders automatically for outstanding and future orders, including transfers between branches. The vendor pages we read don't describe an approval step, safety stock formulas or how minimum order quantities are handled. Slimstock says it works alongside your existing ERP rather than replacing it and names SAP, Oracle, Microsoft and Salesforce.

Users like

Capterra reviewers (4.7, 26 reviews) praise forecasting that accounts for trends and campaigns, support from consultants, centralized purchasing and a to-do list that prioritizes daily work

Users dislike

Capterra reviewers cite need for fuller ERP integration, hard-to-measure forecast accuracy, limited column customization and a clunky campaign module; G2 written themes not readable

Source: G2, 75 reviews

ToolsGroup builds probabilistic forecasts for each SKU and location and uses them for multi-echelon inventory optimization and replenishment recommendations, with a particular strength in intermittent demand.

ToolsGroup produces a full probability distribution of demand per SKU and location instead of a single number, and the vendor's case studies show where that matters. Aston Martin plans around 80,000 spare part SKUs with safety stock re-tuned daily, and reports safety stock value down 18% on clustered items while the service measure in the case study reached 97.1%. Safety stock comes from demand, supply and lead-time uncertainty together, which suits slow-moving, long-tail and service parts demand.

For purchasing, the output is purchase, replenishment and production recommendations that planners work mainly by exception. In the fischer Italia case the company runs a monthly consensus forecast and S&OP cycle, adjusts the statistical forecast with commercial input and executes the purchase recommendations through SAP MRP. The pages describe recommendations and ERP execution, and don't document supplier-facing PO transmission. The vendor now markets the platform as Decion, while G2 files its reviews under Service Optimizer 99+.

Users like

Forecasting and forecast accuracy, inventory management, ease of use, ease of implementation (G2 pros summary).

Users dislike

'Improvement needed', lacking features, poor interface design / UX, complex implementation (G2 cons summary).

Source: G2, 49 reviews

RELEX is a retail and supply chain planning platform with machine learning forecasts at product, store and day level, probabilistic inventory planning and daily automatic replenishment.

Sales, inventory and master data arrive from the ERP, point of sale and warehouse systems by batch, the Data API or the SAP connector. The forecast runs per product, location and day and weighs demand drivers such as weekday, price, promotions, cannibalization, holidays, local events and weather. Planners work from dashboards that show how each driver moved a forecast, and correct exceptions rather than every line.

The inventory module sets safety stock, replenishment frequency and order cycles from the forecast and lead times, and the replenishment engine then creates store and distribution center order proposals every day. An AI agent explains the logic behind each order, and the proposals are written back to the ERP through the connector. The SAP connector is documented for S/4HANA on-premise and private cloud and for ECC 6.0 EHP8, with Oracle, Microsoft Dynamics, Visma, IFS and AS400 also named.

Users like

Ease of use, features, dashboard and interface design (G2 pros summary).

Users dislike

Lacking or missing features, usage challenges, data inaccuracy, data management issues (G2 cons summary).

Source: G2, 40 reviews

Kinaxis Maestro runs demand, supply and inventory planning on one data model, so a change in demand recalculates the supply plan and its scenarios without a batch run.

The Kinaxis demand planning brochure we read, a 2018 document from the RapidResponse era, so product names have changed since, lays out six steps. Planners condition sales history for outliers and promotions, collect finance, sales and marketing inputs, generate and publish a statistical forecast, define new product introductions and end of life, build a consensus plan and get it approved. The demand dashboard shows forecast value add against a naive forecast, volume error, mean absolute error and bias, which gives you a way to check the forecast later.

The approved unconstrained plan goes to aggregate supply planning in the same platform, which returns a constrained plan to balance. Kinaxis says customers that use demand planning also subscribe to its S&OP application. The material doesn't show how a purchase order or requisition is created from the plan, and Capterra's listing says Maestro doesn't include inventory replenishment. Purchasing teams meet it through the supply applications. Vendor pages name no ERP, and a G2 reviewer at a company with over 1,000 employees says it bridges several ERPs.

Users like

Real-time visibility linking demand, supply, inventory and capacity; flexible planning workbooks and alerts; scenario planning; strong reporting.

Users dislike

Steep learning curve; can be slow; complex workbooks and configuration to maintain; one reviewer reports data not real-time or consistent.

Source: G2, 14 reviews

SAP Integrated Business Planning combines statistical forecasting, demand sensing and consensus demand with S&OP and supply planning, and returns the plan to SAP ECC or S/4HANA.

In SAP's documentation an administrator builds forecast models, history is loaded from SAP ECC, S/4HANA or another system, and the planner maps reference items for new products, brings in promotion data, segments items by ABC and XYZ class and runs time-series analysis with change-point detection. The statistical forecast runs interactively in the Excel add-in or in planner workspaces, or as a scheduled background job. The plan feeds consensus demand in IBP or goes to ECC or S/4HANA as planned independent requirements, and demand sensing then refines the near-term forecast.

Forecast error alerts need SAP Supply Chain Control Tower and AI analysis needs Joule Premium, so ask which products your quote includes. A G2 community answer notes there is no built-in automatic replenishment, which fits the handoff above: purchasing gets planned requirements through SAP, not supplier orders from IBP.

Users like

Forecast accuracy (42 mentions), ease of use (37), real-time data and supply chain management (28), unified platform (27), visibility (26).

Users dislike

Complexity and difficult setup with heavy training needs (35 mentions); steep learning curve (28, 21); complex setup needing time and expertise (18).

Source: G2, 301 reviews