What is VidiStock?
Every business that holds stock lives with the same trade-off: too little stock loses sales, too much ties up cash. VidiStock helps you strike that balance with data.
What it does
Section titled “What it does”- Takes your data. Products, daily sales and current stock, from CSV files or an ERP connector.
- Forecasts demand. For every product and warehouse it tests several methods on past data and keeps the one with the lowest error.
- Calculates safety stock and reorder points. It accounts for forecast error and supplier lead time.
- Suggests orders. It lists the products that need ordering, with quantity and value, and shows the calculation behind each suggestion.
- Alerts and analyses. Stockout risk, overstock, supplier problems; cash tied up in stock and turnover.
What it does not do
Section titled “What it does not do”- It does not send orders to suppliers; it produces a list of suggestions.
- It does not replace your ERP or accounting system; it works alongside it.
- It does not do production planning, capacity planning or work order management.
See FAQ and limitations for the full list.
Who it is for
Section titled “Who it is for”Wholesalers, distributors, retailers and e-commerce businesses with hundreds or thousands of products, supplier lead times of days or weeks, and possibly several warehouses or branches.
How a suggestion is calculated
Section titled “How a suggestion is calculated”Take a product that sells 10 units a day on average, with a supplier that delivers in 14 days (±3 days). There are 150 units on hand.
| Step | Result |
|---|---|
| Expected demand over the lead time | 140 units |
| Safety stock (95% service level; from forecast error and delivery variation) | 83 units |
| Reorder point | 223 units |
| 150 on hand is below the reorder point | Order needed |
| Target stock (reorder point + economic order quantity) | 827 units |
| Suggested order (rounded to cases of 50) | 700 units |
The example uses the classic EOQ with constant demand; when an ordering cost is set, the application finds the quantity with the optimal plan (Wagner–Whitin), which also accounts for seasonality. In the application every suggestion has this breakdown with the product’s own figures. Formulas: Methods and accuracy.
What data does it need?
Section titled “What data does it need?”| Data | Required | For |
|---|---|---|
| Products (code, name, unit cost, lead time) | Yes | Plan and values |
| Daily sales and returns (product, warehouse, day) | Yes | Demand forecast |
| Stock balance and open orders (product, warehouse) | Yes | Stock position |
| Customer code (on sales) | No | Customer concentration |
| Purchase orders | No | Supplier scorecard, lead time alerts |
| Sales prices and currencies | No | Gross margin, return on stock, FX risk |
Data comes from a CSV file or an ERP connection (Netsis, Logo Tiger / Go, Mikro, DİA; beta). At least two years of sales history is recommended for forecasting; only then can seasonality be captured.
How is it deployed?
Section titled “How is it deployed?”- Cloud: hosted by VidiStock; used in the browser.
- Your own server: installed directly on Windows Server or with Docker on a Linux server; data does not leave your network. See On-premise installation.
What does it do differently?
Section titled “What does it do differently?”- Shows its calculation: every order suggestion has a step-by-step breakdown; the answer to “why this much?” is on screen.
- A method for each product: a steadily selling product and a rarely selling spare part are forecast with different methods; the choice is made by backtesting and the forecast error is reported.
- Turkish ERPs: reads directly from Netsis, Logo, Mikro and DİA.
- Multiple currencies: foreign-currency buying and selling with central bank rates; break-even rate and FX scenario.
- Money made visible: capital tied up in stock, excess and dead stock, turnover, holding cost.