FinTechA treasurer’s guide to business intelligence (and how to get it right)

A treasurer’s guide to business intelligence (and how to get it right)

Business intelligence capability empowers an organisation to crunch big data and leverage dynamic insights in order to support improved decision-making. Yet while there are now a number of increasingly innovative and accessible business intelligence solutions corporates are able to implement, treasurers have got to plan and develop BI with care.

Like it or not, the global treasury ecosystem is constantly evolving. Between regulatory divergence, rising interest rates and unprecedented levels of socio-political uncertainty, corporates are increasingly reliant upon treasury teams to take a lead and make sense of shifting markets in order to unlock organisational value. Yet before treasurers are able to build strategic insights and make meaningful contributions at the C-level, they must first learn to develop, deploy and leverage dynamic tech solutions, tools and processes that enable them to collect and crunch big data.

That’s where business intelligence comes in.

Business intelligence (BI) is a pretty far-reaching umbrella term that’s used to describe any number of apps, tools, infrastructure or best practices that enhance an organisation’s level of access to data – as well as its ability to analyse that data in order to optimise decision-making and, ultimately, financial performance. BI models empower otherwise non-technical business users with the innate ability to interact with much bigger and substantially deeper data sets, which is why business intelligence solutions are often considered one of the most accessible and effective types of decision support systems. They assist with and totally streamline planning, budgeting, performance evaluation and the communication of management information.

It’s worth pointing out that business intelligence isn’t just about white label apps and modulated software structures. BI will inherently mean different things to different organisations, and it manifests itself through data analysation techniques, processes and systems that are often unique to a particular company or sector. That being said, enterprising fintechs and software vendors have made considerable leaps in recent years in order to spot common gaps in service and provide surprisingly comprehensive BI solutions which can then be applied and modified to fit existing information systems within a dizzying range of departments, sectors and global markets.

But even with the right tools in place, achieving success and unlocking chartable growth potential within an organisation through business intelligence isn’t always a walk in the park. Before implementing a new BI solution or infrastructure, treasurer teams have got to ensure there’s adequate support in place from particular service areas – and more important still, that they know what it is they’re actually trying to achieve.

What does BI look like?

Before delving into the keys to BI success, it’s worth first taking a look at what the solutions and services claiming to unlock business intelligence actually look like.

Demand for real-time insights and a desire to collect, crunch and understand big data have totally redefined the way fintechs and software developers approach business intelligence – which is why a number of leading treasury management systems providers have begun to rollout their own dynamic white label BI solutions that are able to fully integrate with existing TMS or ERP systems as bolt-on modules supported by a common cloud infrastructure. BI modules supported by wider TMS cloud integrations not only enable team collaboration for those practitioners working remotely, but also include segregated data workflows that are totally invaluable for larger multinationals with a decentralised or regionalised treasury function.

These modules all vary in functionality and design, yet the vast majority do focus on the shared provision of on-demand analysis that allows treasury teams to generate targeted projections and reports based on bespoke scenarios in real-time. More important still, any business intelligence tool worth its salt empowers corporates with the ability to uncover data trends and relationships via smart visualisations that are generated automatically and are incredibly simple for non-technical users to grasp and act upon.

As fragmented treasury teams continue to be stretched and pushed to make bigger strategic contributions at the managerial level, the ease-of-use and automation of these BI solutions are becoming more important than ever – which is why there’s been a huge push in 2019 to equip business intelligence with the power of AI and machine learning.

Leading solutions providers like SAP have already deployed AI tools in order to enhance BI capability. Its HANA cloud platform is designed to leverage automated algorithms that replicate and ingest structured financial data strands from a number of sources before identifying patterns and highlighting any irregularities unprompted. American start-up Domo offers a similar AI-powered BI solution that utilises a scalable cloud dashboard to collect data from all available third-party sources in order to offer treasurers unprompted strategic recommendations based on identified patterns or quandaries.

This latest crop of corporate BI solutions also work to create a two-way data dialogue for teams using natural language processing (NLP). NLP is designed to amalgamate coding and linguistics in order to better understand human language before presenting that language in an actionable, business reporting context. This added translative power now only allows business users to better understand data strands, but it also enables them to actually interact with that data and have meaningful, analytical conversations with their BI system.

Bearing in mind just how much that could assist treasurers in simplifying big data and translating patterns into tangible business decisions, it’s little wonder demand for NLP-enabled solutions has skyrocketed. According to research conducted by Tableau, the NLP market is forecasted to be worth more than $825m by 2023. Many BI vendors have already pre-empted this surge by integrating NLP within their own existing cloud and SaaS solutions.

Tools like Microsoft Power BI support natural language queries so that clients can navigate their data sets just by asking simple questions – thus saving treasurers valuable time and making the analysation process more casual and conversational. These increasingly powerful BI tools are not only armed with the power of AI, machine learning and NLP, but they’re also fairly simple to integrate with existing infrastructure. Yet for those organisations that have not yet laid out any of the necessary groundwork required for BI, there are a few critical steps that must be taken care of before diving headfirst into a new project.

How to get business intelligence right

In order to start things off on the right foot, any new BI project requires full support from top management. After all, if an organisation is starting from scratch where BI is concerned, they’ll require people, time and money to get things off the ground.

Bearing that in mind, a total buy-in from the C-level is absolutely critical in order to deliver on any business intelligence project. Likewise, the automation that business intelligence modules will subsequently go on to facilitate requires sufficient buy-in and support from any available IT resource from the project outset – as BI solutions require constant supervision in terms of database and server connectivity, a module’s ability to pass through firewalls and authentication processes.

After securing adequate buy-in and support from the C-level as well as from IT, business intelligence projects or the integration of new solutions require a clearly planned outline. Before pitching a BI solution and kickstarting implementation, treasury teams must develop a roadmap from inception that firmly frames data origins and collection in relation to the system’s final users. The foundation of any successful BI project is built upon a corporate’s understanding of where raw data is supposed to originate from, who will be consuming the reports that data goes on to feed and what sort of actionable analysis a business hopes to generate.

By addressing these objectives and parameters early on, practitioners should be able to manage expectations in terms of ownership over the solution, the way in which it will be used and its forecasted impact upon business.

Finally, successful BI implementation is all about knowledge and continuous development and education. Providers are constantly upgrading capability and improving functionality in line with industry trends and tech capability – but a BI solution is only as good as the team of users accessing it. Without a clear understanding of a solution’s dashboard, a system of processes in place and defined objectives with which to utilise a business intelligence module, corporates will be unable to leverage the insights that BI is designed to provide. Teams must constantly be working to advance and push forward alongside its BI capability.

Business intelligence isn’t a single lane highway. There are a range of options, objectives and solutions that are designed to service very different organisations operating across a diverse range of sectors and market conditions. Yet by exploring what’s out there, understanding the potential of BI and demonstrating a willingness to take things slow and get business intelligence right, these solutions have the power to unlock a world of potential.

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