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On this page you will learn how to analyze inventory flows and their impact on your business. We explain how our automated analysis works and show you how to use the Net flow metric to identify potential issues with recipes, inventory management, or even fraud.

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Understanding Net Flow

Net flow measures the difference between the inflow (items delivered) and outflow (items sold, returned and depreciated) of your stores. This analysis requires tracking:
  • Delivered Items: Both raw materials and finished products
  • Outgoing Items: Sales, returns, and depreciation
  • Recipe Conversions: How raw materials convert to final products

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Why Net Flow Analysis is Complex

Traditionally, tracking inventory flows requires extensive manual effort and deep operational knowledge. Key challenges include:
  • Recipe Conversions: Raw materials transform into multiple products (e.g., 1kg coffee beans → many cups of coffee)
  • Multi-Step Processing: Items may go through several stages before final sale (e.g., frozen → thawed → baked)
  • Timing Differences: Deliveries and sales happen at different times, often spanning multiple days

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Estimating Net Flow

Here’s how we calculate the Net flow metric:
1

Calculate Inflow

For each order we calculate the inflow as the Delivered amount.
We are not including starting inventory levels in this logic, but when evaluating Net flow over longer time periods this does not present an issue as the impact of starting and ending inventory becomes negligible.
2

Calculate Outflows

Until the next order arrives, track:
  • Sales No.
  • Return amount
  • Depreciation amount
This includes the delivered item and all composites with their recipe conversions (e.g., coffee beans → coffee cups).
The tracking period for the outflows starts with an order and ends when the next order arrives. This ensures we capture all movements related to a specific delivery.
3

Calculate Net Flow

Subtract total outflows from inflow:
Net Flow = Inflow - Total Outflows
Relative Net Flow = (Net Flow / Inflow) * 100%
Net flow analysis is most reliable when analyzed over longer periods (weeks to months) as it ignores day-to-day inventory fluctuations.

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Example: Coffee Bean Net Flow

Let’s see how this works for coffee beans:
  1. Inflow
    • On December 4th, store receives 1 bag (1kg) of coffee beans
    • Inflow = 1 bag
  2. Outflows (until next delivery)
    • 50 small coffees (12g × 50 = 600g = 0.6 bags)
    • 10 large coffees (20g × 10 = 200g = 0.2 bags)
    • Total outflows = 0.8 bags
  3. Net Flow 
    Net Flow = 1 bag - 0.8 bags = 0.2 bags
Relative Net Flow = (0.2 bags / 1 bag) × 100% = 20%
A 20% net flow means less coffee was used than delivered, which is not problematic at all as long as it doesn’t continue over weeks and months. Therefore, net flow patterns become much more interesting when analyzed across bigger time periods.

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Understanding Net Flow Results

The Net flow metric helps identify three key scenarios:
  • Balanced Flow (≈ 0%): Items are being used as expected
  • Positive Flow (> 0%): More items enter than leave, suggesting:
    • Recipe quantities aren’t being followed
    • Outflow of items isnt’t being properly tracked (missing returns or depreciations)
    • Potential fraud in sales recording (e.g. large coffee is handed out but small coffee booked in the POS)
  • Negative Flow (< 0%): More items leave than enter, indicating:
    • Recipe quantities may be too generous
    • Deliveries aren’t being recorded
Always compare net flow across different stores to establish what’s normal for your business. Perfect zero net flow is rare - focus on identifying significant deviations from your baseline.
As Net flow is calculated for each order instead of each day, it can sometimes look weird when visualized over a timeseries if there were some zero orders. For example if an item is orderable every day and has a shelf live of a week, it is conceivable that it is only ordered once per week and sold on all the other days. In this example when looking at the net flow for the week everything looks in order but looking at it on a daily basis shows a positive net flow for the day with the order and negative net flow on the other days where the orders where 0 but there were outflows.

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Common Use Cases

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Recipe Compliance

Net flow helps identify if stores follow recipes correctly. For example:
  • If a recipe requires 100g of coffee per cup
  • But staff consistently uses 90g
  • You’ll see a positive net flow for coffee beans

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Fraud Detection

Net flow can reveal potential fraud patterns. For example:
  • Staff books a small coffee but serves a large one
  • Keeps the price difference
  • Results in unexpectedly positive net flow for coffee beans

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Analyzing Net Flow

The true value of net flow analysis comes from comparing patterns across locations and time periods. Here’s an example comparing net flow for coffee beans across different stores:
You can also visualize net flow trends over time to spot patterns:
When analyzing net flow, group by Location, Location-Tag, Item, Item Groups, or Item-Tag to identify patterns. You can analyze data at a daily level.