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Cambridge Cognition Holdings (LSE:COG) Inventory Turnover : 6.66 (As of Dec. 2023)


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What is Cambridge Cognition Holdings 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. Cambridge Cognition Holdings's Cost of Goods Sold for the six months ended in Dec. 2023 was £1.44 Mil. Cambridge Cognition Holdings's Average Total Inventories for the quarter that ended in Dec. 2023 was £0.22 Mil. Cambridge Cognition Holdings's Inventory Turnover for the quarter that ended in Dec. 2023 was 6.66.

Days Inventory indicates the number of days of goods in sales that a company has in the inventory. Cambridge Cognition Holdings's Days Inventory for the six months ended in Dec. 2023 was 27.39.

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. Cambridge Cognition Holdings's Inventory-to-Revenue for the quarter that ended in Dec. 2023 was 0.03.


Cambridge Cognition Holdings Inventory Turnover Historical Data

The historical data trend for Cambridge Cognition Holdings'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.

Cambridge Cognition Holdings Inventory Turnover Chart

Cambridge Cognition Holdings 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 29.09 25.46 27.22 19.25 13.48

Cambridge Cognition Holdings 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 11.55 7.42 7.97 5.57 6.66

Cambridge Cognition Holdings Inventory Turnover Calculation

Cambridge Cognition Holdings'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 )
=2.717 / ((0.216 + 0.187) / 2 )
=2.717 / 0.2015
=13.48

Cambridge Cognition Holdings'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 )
=1.436 / ((0.244 + 0.187) / 2 )
=1.436 / 0.2155
=6.66

* 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.


Cambridge Cognition Holdings  (LSE:COG) 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.

Cambridge Cognition Holdings'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
=0.2155/1.436*365 / 2
=27.39

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.

Cambridge Cognition Holdings'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 )
=0.2155 / 7.476
=0.03

* 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.


Cambridge Cognition Holdings Inventory Turnover Related Terms

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Cambridge Cognition Holdings (LSE:COG) Business Description

Traded in Other Exchanges
Address
Tunbridge Court, Tunbridge Lane, Bottisham, Cambridge, GBR, CB25 9TU
Cambridge Cognition Holdings PLC is a neuroscience digital health company specializing in the precise measurement of clinical outcomes in neurological disorders. The company product segments include Software, Services, and Hardware. It generates maximum revenue from the Software segment. Geographically, it derives majority of its revenue from the United States of America and also has a presence in the United Kingdom, European Union, and Rest of world. The company services include Neuroscience consultancy, Technical consultancy, Study design, Data analysis, Study management, Data management, and Reports and interpretation.

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