GURUFOCUS.COM » STOCK LIST » Technology » Software » Neurones (XPAR:NRO) » Definitions » Inventory Turnover

Neurones (XPAR:NRO) Inventory Turnover : 140.42 (As of Dec. 2023)


View and export this data going back to 2000. Start your Free Trial

What is Neurones Inventory Turnover?

Inventory Turnover measures how fast the company turns over its inventory within a year. It is calculated as Cost of Goods Sold divided by Total Inventories. Neurones's Cost of Goods Sold for the six months ended in Dec. 2023 was €140.4 Mil. Neurones's Average Total Inventories for the quarter that ended in Dec. 2023 was €1.0 Mil. Neurones's Inventory Turnover for the quarter that ended in Dec. 2023 was 140.42.

Days Inventory indicates the number of days of goods in sales that a company has in the inventory. Neurones's Days Inventory for the six months ended in Dec. 2023 was 1.30.

Inventory-to-Revenue determines the ability of a company to manage their inventory levels. It measures the percentage of Inventories the company currently has on hand to support the current amount of Revenue. Neurones's Inventory-to-Revenue for the quarter that ended in Dec. 2023 was 0.00.


Neurones Inventory Turnover Historical Data

The historical data trend for Neurones's Inventory Turnover can be seen below:

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.

* Premium members only.

Neurones Inventory Turnover Chart

Neurones Annual Data
Trend Dec14 Dec15 Dec16 Dec17 Dec18 Dec19 Dec20 Dec21 Dec22 Dec23
Inventory Turnover
Get a 7-Day Free Trial Premium Member Only Premium Member Only 631.75 415.78 303.88 412.36 534.21

Neurones Semi-Annual Data
Jun14 Dec14 Jun15 Dec15 Jun16 Dec16 Jun17 Dec17 Jun18 Dec18 Jun19 Dec19 Jun20 Dec20 Jun21 Dec21 Jun22 Dec22 Jun23 Dec23
Inventory Turnover Get a 7-Day Free Trial Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only 87.68 115.51 157.00 174.26 140.42

Neurones Inventory Turnover Calculation

Neurones's Inventory Turnover for the fiscal year that ended in Dec. 2023 is calculated as

Inventory Turnover (A: Dec. 2023 )
=Cost of Goods Sold / Average Total Inventories
=Cost of Goods Sold (A: Dec. 2023 ) / ((Total Inventories (A: Dec. 2022 ) + Total Inventories (A: Dec. 2023 )) / count )
=283.665 / ((0.353 + 0.709) / 2 )
=283.665 / 0.531
=534.21

Neurones's Inventory Turnover for the quarter that ended in Dec. 2023 is calculated as

Inventory Turnover (Q: Dec. 2023 )
=Cost of Goods Sold / Average Total Inventories
=Cost of Goods Sold (Q: Dec. 2023 ) / ((Total Inventories (Q: Jun. 2023 ) + Total Inventories (Q: Dec. 2023 )) / count )
=140.423 / ((1.291 + 0.709) / 2 )
=140.423 / 1
=140.42

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.


Neurones  (XPAR:NRO) Inventory Turnover Explanation

Inventory Turnover measures how fast the company turns over its inventory within a year. A higher Inventory Turnover means the company has light inventory. Therefore the company spends less money on storage, write downs, and obsolete inventory. If the inventory is too light, it may affect sales because the company may not have enough to meet demand.

1. Days Inventory indicates the number of days of goods in sales that a company has in the inventory.

Neurones's Days Inventory for the six months ended in Dec. 2023 is calculated as:

Days Inventory =Average Total Inventories (Q: Dec. 2023 )/Cost of Goods Sold (Q: Dec. 2023 )*Days in Period
=1/140.423*365 / 2
=1.30

2. Inventory-to-Revenue determines the ability of a company to manage their inventory levels. It measures the percentage of Inventories the company currently has on hand to support the current amount of Revenue.

Neurones's Inventory to Revenue for the quarter that ended in Dec. 2023 is calculated as

Inventory-to-Revenue=Average Total Inventories (Q: Dec. 2023 ) / Revenue (Q: Dec. 2023 )
=1 / 372.483
=0.00

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.


Be Aware

Usually retailers pile up their inventories at holiday seasons to meet the stronger demand. Therefore, the inventory of a particular quarter of a year should not be used to calculate Inventory Turnover. An average inventory is a better indication.


Neurones Inventory Turnover Related Terms

Thank you for viewing the detailed overview of Neurones's Inventory Turnover provided by GuruFocus.com. Please click on the following links to see related term pages.


Neurones (XPAR:NRO) Business Description

Traded in Other Exchanges
Address
Immeuble Le Clemenceau 1 - 205, Avenue Georges Clemenceau, Nanterre Cedex, Paris, FRA, 92024
Neurones SA is a France-based technology sector company. Its core business involves the provision of Information Technology (IT) services catering to the needs of hardware, software, and consulting. Its operations are thereby divided into three segments: Infrastructure Services, Application Services, and Consulting. The Infrastructure segment is the strongest revenue driver through the provision of such services as IT operations, IT service management, systems and network, server, application, and workstation outsourcing. Its second most profitable business is carried out through the Application segment, which entails SAP, Web and decision support, social media, data analysis.