Other parts of this series:
- Making intelligent automation happen in finance
- Making better decisions in finance with analytics
- Making the business case for cloud technology in the finance function
- Increasing benefits from cloud technology
- The benefits of agile platforms in financial services
- Confronting the challenges of agile platform implementation in financial services
- Artificial Intelligence in Finance: Five opportunities to take the leap
“Properly used, analytics can help finance partner with the business, enhance performance and improve bottom-line results.”
In the first blog in this Digitizing Finance series we looked at intelligent automation and its potential impact on the finance function. We now consider how CFOs can best harness the power of analytics. Properly used, analytics can help finance partner with the business, enhance performance and improve bottom-line results.
Finance continues to evolve from a transactional back-office function — reporting on historic results – to an integrated, forward-looking partner with the business. The deployment of intelligent analytic tools is critical to this transformation.
Digital technologies continue to automate and simplify finance processes. But it is the analytic tools connecting and processing the new streams of digital data that can really help drive value, including efficiency improvements. We are fast approaching a time when queries can be managed by cognitive agents, reporting commentary can be automatically generated, and executives can run scenario analysis with a voice command.
There are two key areas in which analytics can deliver distinct benefits, both to finance and to the wider organization:
1) Intelligent Analytics
Data is the underlying fuel for analytics and is being stored in exponentially growing quantities. New tools create a digital engine, combining the computing power required to process millions of lines of data with analytics and artificial intelligence (AI) to deliver insights comparable to those developed through thousands of hours of traditional analysis.
Automated machine learning techniques can help improve predictions of the future based on learnings from the past. Just as meteorologists have improved the reliability of their weather forecasts, finance teams can apply similar techniques to the prediction of future business performance.
While finance teams’ time has traditionally been spent on reporting historic data, new technology allows finance to focus on the future. Forward-looking analytics tools provide predictive insights and facilitate preventative or opportunistic action as needed.
Advances in natural language processing (NLP) continue to improve the capabilities of cognitive agents, allowing such agents to answer questions and provide immediate insight.
2) Insight Delivery
Having a rich set of data is only part of the equation. Data for data’s sake is meaningless unless the data can be accessed and displayed effectively to permit informed decision making. Defining the right metrics and indicators to measure performance is another critical component in an effective finance analytics program.
Clear, easy-to-understand dashboards and the ability to quickly drill down through different dimensions are essential for time strapped executives. Dashboards can also facilitate self-service reporting, reducing the burden of report production on finance teams, and helping finance support business users in accessing the data most relevant to them. Maps, for example, can now effectively depict intercompany transactions and flows across regions. Users can zoom into different geographies for additional detail.
In addition to innovative visualization techniques, analytic software tools provide multiple options for improved access to data. Moving beyond traditional spreadsheets and slides, data can now be accessed and displayed on multiple devices. Mobile reporting through phones and tablets allows access to data on the move and with more interactive interfaces. Such data is stored, not locally, but in the cloud, improving data security and reducing the risk of a data leak if a device is lost.
Many cloud-based analytic tools also provide access to third party-transactional, market or reference data. Merging these data sets with an organization’s own data creates the potential for more advanced and richer analytics.
As finance evolves from transactional activities and historic reporting towards providing greater business insight, CFOs should look to develop their analytics capability, thus providing the front-line business with the right insights in a user-friendly fashion.
AI provides huge potential for analytics, both in the ability to spot additional insights beyond the capabilities of the human mind, and in transforming the end user experience with automated reporting and commentary. However, technology is not the only facilitator. To increase the benefit of analytics, companies’ source data should be of the right quality and employees’ skills should be adapted to new demands faced by organizations. Data science and other emerging skills can play central roles in the finance teams of the future.
In the next blog in this series, we will look at the role of cloud technology in digitizing the finance function. In the meantime, learn more about Accenture’s finance analytics capabilities.