The treasurer and data
| 13-12-2016 | Lionel Pavey |
Treasurers are confronted with new data every day – just think of the daily download from the bank statements. As this is a constant process, treasurers need to able to perform real-time financial analysis.
This analysis has to be performed with various internal data management sources, together with external data such as foreign exchange and interest rates. Originally this was done with rather large static data like annual budgets, but nowadays there appears to be a change in sentiment towards more proactive rolling forecasts.
The treasurer has a multitude of tasks including cash flow forecasting, hedging of foreign exchange and interest rates, investing excess funds, acquiring funding, advising on liquidity and financial risks, maintaining relationships with financial institutions. To be able to do all this requires a good continuous flow of internal data, together with an understanding of data analysis.
Treasurers need to be more proactive and interact and understand the requirements of all departments and divisions within the company. They need to be able to zoom in and out between the macro and micro levels and gain a better understanding of the business fundamentals through the whole scope from procurement to sales.
The 5 biggest challenges
- Receiving timely and accurate data
- Recognizing and acting on data – both structured and unstructured
- Keeping abreast with the constant changes in data technology – blockchain
- Becoming truly proficient at data analytics
- Continuous feedback to data providers to show how their data has been incorporated and used
So, just a few extra activities on top of the normal roles of forecasting, negotiating, risk management, and people management.
It is clear that the duties of a treasurer are many and that the job is a very special one requiring both proactive and reactive skills. For all of this to work, companies have to get all relevant staff to think the same way and understand the importance of continuous, timely and accurate data. Good structured data analysis can transform a company’s understanding of its business and provide important insight into its workings. This can lead to better knowledge of customers’ requirements, working capital flows, comparing internal data to industry or sector trends, changes to strategic thinking etc.
There are 2 sorts of data scientists: First those who can extrapolate from incomplete data….
Cash Management and Treasury Specialist – Flex Treasurer
