Moving data analytics forward in a treasury function is rewarding but challenging, requiring considerable planning. Several distinct challenges should be expected and addressed.
Data is likely to exist in a multitude of silos around an organisation, and it is important to understand where these silos are, who owns them, and how they can be broken down. A key aim for any treasury data strategy should be the creation of a golden source of data.
But the quality of that data is likely to vary, which makes it important to have comprehensive policies in place around data governance and control.
Then there’s quantity: already overwhelming, and becoming more so by the day. Too many inputs create a recipe for confusion. A key lesson here is not to deviate too far from treasury strategy, and to remember what that strategy is intended to achieve: less can sometimes be more.
Finally, it’s important to have clarity on an organisation’s data resources, both in terms of technology and personnel. Treasurers must understand what they need from technology, so they can work out the tools they need to bring in to achieve their goals; and must upskill existing staff while hiring the right data-centric skills into an organisation.
The challenges are considerable, and the preparation that goes into surmounting them is wide-ranging and onerous. But the potential outcomes more than justify the work that is put in. Data is one of the most powerful resources in the modern treasury world, and the only thing that can be said with certainty about the future is that data’s importance will only increase.