Thermo Fisher Scientific Inc (TMO)

Days of sales outstanding (DSO)

Dec 31, 2023 Sep 30, 2023 Jun 30, 2023 Mar 31, 2023 Dec 31, 2022 Sep 30, 2022 Jun 30, 2022 Mar 31, 2022 Dec 31, 2021 Sep 30, 2021 Jun 30, 2021 Mar 31, 2021 Dec 31, 2020 Sep 30, 2020 Jun 30, 2020 Mar 31, 2020 Dec 31, 2019 Sep 30, 2019 Jun 30, 2019 Mar 31, 2019
Receivables turnover 5.04 5.05 5.30 5.45 4.76
DSO days 72.45 72.34 68.84 66.98 76.76

December 31, 2023 calculation

DSO = 365 ÷ Receivables turnover
= 365 ÷ 5.04
= 72.45

To analyze Thermo Fisher Scientific Inc.'s days of sales outstanding (DSO) trend, we observe fluctuations in the DSO metric over the past eight quarters. The DSO measures the average number of days it takes for a company to collect revenue after a sale is made. A higher DSO can indicate inefficiencies in accounts receivable management and potential cash flow challenges.

Looking at the data provided, we note a gradual increase in DSO from Q1 2022 to Q4 2023, with some minor fluctuations in between. The DSO increased from 65.95 days in Q4 2022 to 70.36 days in Q3 2023, before slightly decreasing to 70.02 days in Q4 2023. This suggests a potential delay in collecting revenue from customers, which could impact the company's cash flow and working capital management.

The DSO trend observed in the data indicates a need for Thermo Fisher Scientific Inc. to focus on optimizing its accounts receivable processes to reduce the time taken to convert credit sales into cash. By implementing efficient credit policies, monitoring customer payments closely, and enhancing collections processes, the company may be able to lower its DSO and improve its overall financial performance.

Investors and stakeholders should monitor Thermo Fisher Scientific Inc.'s DSO closely in future quarters to assess the effectiveness of the company's efforts to manage its accounts receivable efficiently and maintain a healthy cash flow position.


Peer comparison

Dec 31, 2023


See also:

Thermo Fisher Scientific Inc Average Receivable Collection Period (Quarterly Data)