The news that the relentless progress of AI has also reached the finance function may be welcome to some but worrying for others. How can data as precise, mission-critical and professionally controlled be entrusted to a ‘black box’ in the hope of producing any credible benefits and results? A Gartner survey conducted in 2023 revealed that 61 percent of finance organisations were not currently using AI. While this number has probably improved, it suggests a widespread hesitation about AI among finance leaders.
Well, it’s happening, and the leaders in this area are already generating high quality performance narratives from reports and dashboards for distribution to their colleagues. More significantly they are also improving the accuracy of their forecasts, being able to produce and update them more frequently in a fraction of the time they used to take before.
So what?
The insights from dashboards and their value are not always fully understood by wider operational users, so including an AI-generated narrative will help address this without any additional burden to the finance team. Giving report and dashboard users the ability to interact with them in natural language and receive a fast, intelligent response will likely convert those looking for instant answers and tired of digging down, drilling through and otherwise doing the analysis themselves before they have time to act.
The benefits of better forecasting are well established, from better decisions on the allocation of funds, staff and other resources, to more realistic budgets, better risk assessments, increased stakeholder confidence, improved operational efficiencies and better benchmarks against which to measure and correct actual performance.
The speed of it! We have all been impressed by how immediately well-trained AI responds to our inquiries, and it is not hard to imagine the time we can save if we can set it up correctly.
However, many finance functions in both the public and private sectors are still an important step away from being able to harness this power.
This step comes under the heading of ‘Business Intelligence’, otherwise known as ‘Business Analytics’ with a focus on a single, near real-time, well governed, best version of the truth. Clever as AI is, it cannot be expected to make much sense safely of multiple versions of the truth, disparate data siloes and limited data governance, so we have to get organised.
The good news is that taking this step brings fast and tangible benefits, well before the involvement of AI.
What if there were a way to replace all those complex, single-owner Excel workbooks that fill the reporting, planning, forecasting and analysis gaps left by accounting systems, complement them with automatic data feeds from finance, project, legacy and other systems so that all inputs, updates, plans, forecasts, analysis and reports are driven from the same source with a clear audit trail?
We are not talking about Data Warehouses here. They have a different but complementary role to Business Intelligence, being much larger scale, high-cost historical data stores optimised for high-volume, high-performance, mainly read-only analytics on vast datasets, and AI is already proving its value in mining them for insights.
Business Intelligence systems, like Jedox are much lighter in comparison, lower cost, more agile and interactive (read and write), often including summarised data warehouse information in their blending and management of multiple source data. With all the power of Excel, enhanced with even more flexibility, enterprise level scalability and security, a Business Intelligence toolset like Jedox addresses the known weaknesses of Excel. At the same time it leverages and builds on the widespread Excel skills of data analysts and so reduces the change management and re-training impact, resulting in a smoother adoption cycle.
So, what are the immediate benefits of going down the Business Intelligence route?
First and foremost, it places a carefully governed structure on top of the data gathered and modelled for output, providing the necessary ‘guiderails’ required for consistent and accurate reporting, planning and analysis, without having to embark on a large-scale IT implementation. These guiderails include role-based security access controls, data validation rules, audit trails and change tracking, workflow approvals, version controls, data security and encryption, standardised data definitions, automated policy enforcement, collaboration features and compliance reporting.
Within this framework, different types of users, from administrators to departmental managers and general information consumers are able to work safely on a day-to-day operational basis with an immediate payback in terms of significant time savings, improvements in accuracy, automated and optimised processes, reducing the time investigating errors and managing the system. At the same time, finance and operations users can get the latest information they are authorised to see when they need it, fast, reducing the time required to supply their forecasts, commentaries and budget data, streamlining operations for everyone.
Hopefully it won’t have gone unnoticed that a carefully governed and structured data environment is ideally suited to the leverage that AI can deliver, and therefore it is a relatively small step to implementing it safely, particularly if your choice of Business Intelligence tool includes AI interfaces, like Jedox.
Organisations as diverse as the NHS, Toyota, Linklaters, McDonald’s, Deutsche Telekom and Microsoft are using Jedox to deliver
Timesaving
Efficiency
Accuracy
Is it TEA time for you as well?
