The benefits of strengthening the finance department’s relationship with data

As organisations grapple with a constantly rising tide of digital data, many are finding their traditional methods of managing it are no longer up to the task. They're finding that, unless they have a data management software platform and automation in place, they'll eventually drown.

Looking to the future, the problem of managing data at scale will only increase as businesses create new customer experience touchpoints, explore avenues to reach new audiences, follow new trends, and become more invested in customer success. These activities require mountains of data, and this data only works if it's catalogued, processed, and applied appropriately.

Without the right systems in place, it's possible that an organisation will use the wrong metrics to measure outcomes, or metrics that are simply wrong, and this challenge is particularly acute for the finance department.

Finance professionals need absolute certainty that their data can stand the test of investors, public auditors, and regulators. A massive amount of energy and work is put into establishing a suitable level of control for reported financials and metrics, but often what's overlooked are leading indicators that guide strategy and capital allocation. This can lead to lost opportunities and reduced profits.

The challenge of data quality

Senior management often struggles to derive business value from data, and it's easy to group all kinds of challenges under the vague umbrella of 'data quality'. Yet it's important to look a layer deeper than just trust of data.

There are many different ways to think about data trust. These include completeness, accuracy, accessibility, traceability, recency and relevancy. Until you unpack which aspects of business data are problematic, it's hard to facilitate a conversation about why a decision-maker feels hesitation, reluctance or indecision about a particular analysis.

In many cases, Chief Financial Officers and their teams don't feel as though they are getting enough return on investment for their IT spend. They perceive that they're investing a lot and not seeing tangible results.

From IT's perspective, looking at an organisation-wide data strategy, it's challenging to apply the right degree of quality for these situation-specific needs. Perfection is often the enemy of good, but at a minimum, there should be enough insight to calibrate expectations and make active trade-offs.

Assessing value

Generally, no single system or vendor can claim to be a cure-all for this data culture disconnect. Metrics themselves aren't enough, as they can only be successful when coupled with strong process, commitment, and organisational buy-in to ensuring sound maintenance of the data. That's why enterprises in every industry must embrace the idea of governance and common data standards.

Success often depends on a central effort and combination of the software with the processes and systems that ensure data health. Once you can do that, you can demonstrate the business value of your data. Suddenly the disconnect between investment and return vanishes.

Focusing on data health

As organisations become flooded with more and more data, it's important to remember that the context and usability of data is paramount. By systematising context in a way that allows a larger audience to consume and interpret it, you supercharge the business value of the data. The right data systems and data-driven culture grant people the ability to understand the 'why' as well as the 'what', which means that the data isn't just there — it's decision-ready.

Strong data governance is critical to teasing apart the actual challenges of working with data and solving them at a human level. Democratising data with appropriate governance and universal quality standards ensures that you're putting safe data in the hands of the people who need it to make decisions and that those people understand the life history and quality of the data they work with.

This can be achieved by taking a data health approach to the challenge. Corporate data is no longer viewed as a collection of assets that people share with particular tools. Rather, it's seen as a living thing that requires care and feeding, a common language, and common understanding. Everyone who works with data needs to have access to its context to understand the data itself and its value to the business, and consequently shares responsibility for maintaining the visibility and reliability of that data.

By following a strategy of data health, the finance team and the IT department can achieve trust in their data processes and agree on what ROI should be achieved. In this way, the full value of an organisation's data assets can be realised.