True data confidence shifts finance teams into a world of analysis and educated decision-making, as opposed to data entry which is how most businesses still operate due to their insistence on sticking to age-old manual- and spreadsheet-driven processes.
Source: Supplied. Ivan Jardim, sales account manager at Insight Consulting.
At its most simple definition, data confidence is the degree to which an organisation's leaders and decision makers trust the data with which they work, and beyond this, the ability of this data to realise business value. In other words, it is accurate, reliable and timely, and it results in actionable insights.
In practice though, and despite technological advances, despite software that can quite literally shift the paradigm, most finance departments are trapped in an endless cycle of data reporting as opposed to data analysis. This means that in the endless rush to report, the absence of deep analysis most likely results in them missing critical opportunities for strategic insights.
Let’s be clear from the outset. This is not a problem exclusive to small businesses. Even large organisations have teams that are drowning in manual interventions. This is a world where spreadsheets reign supreme, creating a minefield of manual interventions with potential errors.
It is inefficient because entire teams are spending countless hours inputting and reconciling data to create reports, as opposed to understanding – deeply understanding – the strategic implications of those numbers.
Beyond that, factor in manual inputting, formatting, fatigue and versions, doubt – to varying degrees – creeps in, and affects the organisation’s data confidence.
Checklist for change
With the best intentions, finance professionals who sit at the beating heart of organisations are traditionally “numbers people” who may not be entirely comfortable with technology.
This is no fault of their own, this is a culture that has been passed down from generation to generation. Balancing the books is the driver, while the transformative potential of data analytics is not fully appreciated. Unfortunately, in 2025 and beyond, this presents a significant barrier to achieving genuine data confidence and organisational growth.
Digital transformation is no longer a buzzword; it is a strategic imperative and organisations would do well to understand whether they are data-ready. A good starting point is to conduct a transformation checklist assessing manual processes, data literacy and scenario planning. This could take the following form:
Manual process audit: How long does it take my organisation to generate reports? Are we still using spreadsheets as our primary tool? Can we quickly identify anomalies in our financial data?
Data literacy assessment: Does the finance team understand data beyond numbers? Can it interpret trends and generate strategic insights? Are they equipped to use advanced analytical tools?
Scenario planning capability: Can we simulate the financial impacts of unexpected events? Do we have the ability to model different business scenarios quickly? Is the organisation prepared for potential disruptions?
The path towards true data confidence requires a multidimensional approach:
Clean, accurate data. Specialist data partners can take organisations from a state of data chaos to clean, usable and valuable data.
Education: There is no way around the fact that finance teams need comprehensive training in data analytics. The goal is to transform a team that works with, balances and reports on numbers into strategic insight generators. In order to get there, the team needs to move beyond traditional accounting skills towards understanding data visualisation, predictive analytics and strategic interpretation.
Technology: Organisations need to invest in the right tools that automate mundane tasks, freeing up financial professionals to focus on analysis and not data entry. The best platforms clean data, create dashboards and provide real-time insights for users.
Partnership: There is no substitute for collaborating with specialist partners who understand both finance and data. This expertise is non-negotiable if an organisation is to bridge the two worlds. A good partner will help an organisation discover hidden opportunities, transform inefficient processes and enable more strategic decision-making.
Analytics in action
So what does the desired end-state look like?
A transformed finance team that does not just report the numbers. It has full data confidence, enabling it to tell a story. A transformed finance team with the peace of mind of full data confidence, provides real-time insights, conducts sophisticated scenario planning, predicts financial trends and contributes strategic recommendations to the organisation’s leadership.
Forward-looking businesses are increasingly treating their data as an intangible asset. Just like a building, equipment or vehicle fleet, data has become a critical resource that, if compromised or stolen, can halt or severely disrupt business operations.
As finance teams walk on their digital transformation journeys, investment in robust data security is non-negotiable. Of course, it is paramount to protect information, but it is also about protecting the integrity of your most valuable strategic resource.
Finally, one of the biggest fears around increased use of technology is around what happens to professionals. Let’s be honest, technology has advanced to unprecedented levels, yet despite this, not even the most sophisticated AI can replace a well-trained, experienced finance professional who understands analytics.
Why? Because the experienced human, when freed from mundane tasks, can ask the right questions, at the right times, and then interpret complex data landscapes with the kind of context that only humans understand.
Achieving true data confidence in finance is no longer optional or something to defer to a later stage. It is existential. The longer an organisation, or its finance teams, resist it, the more they will find themselves losing relevance and competitiveness in a data-driven business environment.
The journey begins with a simple question: Are you reporting data, or are you analysing it?
