Turning numbers into knowledge: 8 key data considerations for the Finance function

eBook

Turning numbers into knowledge 8 key data considerations for the Finance function

Contents The changing role of the CFO

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When it comes to data flows, automate everything

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Don’t underestimate the value of a data fabric

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AI won’t fix garbage data

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The future of finance technology is ecosystems

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Contents Prepare a data foundation that is ready for anything

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Find the narrative in the numbers

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Focus on data security

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Thick subledger, thin general ledger

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Build a digital finance department that can move in real time

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8 key data considerations for the finance function

The changing role of the CFO

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The CFO is being called on to be a change agent who can help drive new initiatives and a storyteller who can paint a meaningful picture of where the organization stands and what lies ahead.

Journal of Accountancy

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The responsibilities of the chief financial leader are broader and more diverse than ever.

McKinsey

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Expanding well beyond their traditional roles in finance and accounting, today’s CFOs have the opportunity to lead by example as a strategic partner and key advisor across the enterprise.

KPMG

There is a clear consensus that the role of the CFO and the Finance function has been expanding over the last few years. The explosion of data, the accelerating rate of business change, inflation, an economy upended by the pandemic and other market pressures are just a few of the reasons the CFO role has expanded in scope and strategic importance.

At the heart of all of this is the ability of Finance to create, manage, visualize and democratize a data foundation that can be used and trusted by the business.

In this guide, we outline key data considerations for CFOs and their teams as they work to deliver a digital finance function and step into their expanded roles.

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8 key data considerations for the finance function

When it comes to data flows, automate everything It is absolutely crucial that Finance is accountable for how data moves through an organization from source to report. The controls put in place are critical to the success of the finance function and need to be very clear and fully automated.

For many finance functions the finance data flow is still very manual and people focused, with an inability to drill back from aggregated balances to transaction detail. This leads to higher operational risk and a high reliance on key people and siloed skills – some of which reside outside the finance function all together!

CFOs need to feel comfortable that their processes and controls are automated and transparent enough that they don’t need to spend extensive amounts of time reviewing and ‘checking’ the numbers.

When the data flow is automated, finance teams are more efficient and have better visibility into the data itself and the controls, rules and processes that are in place.

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8 key data considerations for the finance function

Don’t underestimate the value of a data fabric The amount of data available to today’s finance teams can seem overwhelming. This is especially true in their relatively new role as data stewards within an organization – tasked with providing seamless data access, views and analytics crossdepartmentally to financial and non-financial data.

Enter the data fabric, an emerging data management design that enables augmented data integration and sharing across heterogeneous data sources.

For CFOs who look after complex data and finance IT landscapes, utilizing a data fabric provides business users easy access to data and increased performance and business agility while minimizing the total cost of finance – the ability to operate better, faster and at a lower cost.

The benefits are broad but can include: • Empowering finance – and business users generally – to create data models and consume data without the need for coding experience.

• Flexibility in the choice of database application that can be used to underpin a dataset, removing dependencies and broadening your ability to deliver the highest performance at the lowest cost.

• Reducing the cost of finance through the elimination of redundant storage mechanisms.

• The ability to integrate client or partnerdeveloped IP or applications more easily.

Data fabric is a strategic technology approach that can mean big benefits to CFOs and their teams as they work to ensure data is trusted, detailed and generating business insights. From increasing flexibility and performance to reducing the cost of finance, this is an important strategic technology that will unlock business value.

Gartner recently estimated that data fabrics have the ability to cut data management efforts by up to 70% and accelerate time to value.

This has massive implications for finance departments. From limiting the need to build out point to point integrations between systems to the reduction of repetitive tasks like profiling datasets, discovering and aligning new data sources and addressing ongoing integration issues – finance can reduce time to value.

Gartner, “Gartner Identifies the Top Strategic Technology Trends for 2022”

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8 key data considerations for the finance function

AI won’t fix garbage data Everyone is talking about Artificial Intelligence, Machine Learning and other cognitive computing tools and the benefits they can offer CFOs and their finance teams.

And rightfully so!

These new technology solutions are unleashing exciting capabilities from personalizing customer experiences and sophisticated fraud detection to process automation.

Finance teams need to be mindful of overlaying these innovative new technologies on finance data architectures that are decades old. Siloed, legacy systems can mean data flows require manual intervention or contain incomplete information.

In order to meet current and future regulatory and management reporting requirements, Finance functions need an efficient, automated data flow that can be enriched with non-financial data to improve analytics and insight generation.

Listen now ​

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8 key data considerations for the finance function

The future of finance technology is ecosystems Thanks to cloud computing, open source, and other innovations, technology vendors are building out ecosystems that are greater than the sum of their parts and benefit both customers and the vendors themselves.

As a recent Forbes article summarized, “The walled garden of monolithic, enterprise offerings is simply too siloed in this environment of broad choices. The future of business belongs to ecosystems.”

By utilizing open-source approaches or integration with other vendors, ecosystems are enabling companies to leverage existing technologies faster and preventing vendors from having to provide expertise in areas outside their core competencies.

This ultimately encourages quicker advancements in technology, drives higher quality standards and supports the growth of both existing and emerging industries.

For finance teams, technology ecosystems can improve speed to value and quicker access to new capabilities, cross-functional value and collaboration and the flexibility that comes from modular design.

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Ecosystems are particularly attractive when consumers’ needs and tastes are heterogeneous or unpredictable or when technological trajectories are dynamic or uncertain.

Boston Consulting Group, “Do you need a business ecosystem?”

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8 key data considerations for the finance function

Prepare a data foundation that is ready for anything CFOs are being asked to create a finance data architecture that is performant today while remaining flexible enough to react to tomorrow’s requirements. This can be easier said than done.

To start, CFOs can establish a finance data foundation with the ability to hold significant amounts of detailed data – ensuring they can retain key data attributes if and when they are needed for new regulatory or management reporting requirements. This can be done with a finance management platform that can support data granularity separate from the General Ledger and ERP environment.

Additionally, an open, modular architecture can help provide finance teams the ability to integrate with specialist solutions from niche providers. For example, ESG data models, calculation engines, or AI tools should be able to easily integrate with an established data foundation to ensure consistency in reporting.

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Many of the traditional finance vendors are demonstrating ESG use cases or adapting their offering to support ESG reporting.

Listen now ​

10 8 key data considerations for the finance function

Find the narrative in the numbers Data points are just numbers until they are analyzed for patterns and trends and made consumable to stakeholders to drive action. Today’s CFOs and finance executives must go beyond analyzing data and shift to storytelling – finding the narrative in the numbers.

From the article, “Finding the narrative in the numbers” by Carlinde Kallianiotis, Partner and Leadership Coach at Ginger Communications.

On the surface, finance and storytelling might seem to be polar opposites: one is about numbers, the other about language. However, if finance teams can uncover the narrative in the numbers, they have at their disposal a powerful tool that provides context to facts and figures. It allows the C-suite, Board and other stakeholders to connect with a message on an emotional level and understand the financial impact on the business.

Here are a few quick tips to start you on your data storytelling journey: • Look at the data the way a detective examines a crime scene. Then present your evidence and build your case in the form of a narrative. Don’t forget there’s a human story behind every data point, so start to see data as a huge set of tiny stories.

• What’s the strategic narrative of your company?

Think about where your customers/clients are right now. Where do you want to take them and how are you going to get them there? What has to happen?

What obstacles need to be overcome? How can you bring them with you? Start by identifying the change you want to create and reverse engineer your story from there.

• Start and end with a story rather than a graph or bar chart. Data visualizations can be effective, but you still need to wrap them in a narrative – and make it personal if you can. Don’t forget that people buy people, not numbers.

• Rather than rattling off figures, think of more inventive and relatable ways to contextualize them – for example, rather than saying, “We sold 1.5 million units,” you could say, “The number of units sold would fill an Olympic-sized stadium.”

• Experiment with one of the basic tenets of effective storytelling – show, don’t tell. For example, a global newspaper recently wrote an article about the wealth position of the richest person on earth ($185 billion USD). To make this number imaginable for the reader, they explained that this money could

buy you 400,000 modern town houses in the US. Not everyone is a familiar with financial numbers and these storytelling tricks are effective.

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8 key data considerations for the finance function

Focus on data security Data security is a critical concern for any finance director. Financial information is highly sensitive and a breach of data can have severe consequences for both the organization and its clients.

As such, data security should be an integral part of any finance director’s job. It is essential to take measures to prevent unauthorized access, theft, or loss of data.

To maintain data security, finance directors should establish clear policies and procedures for data access, storage, and sharing. These policies should be communicated to all employees, and regular training sessions should be conducted to ensure that everyone is aware of the importance of data security. It is also essential to limit access to sensitive data only to those who need it and to monitor who has access to what information.

Another critical aspect of data security is ensuring that all systems and software used by the organization are up to date with the latest security patches and protocols and have strong access controls in place to limit data access based on roles. Finance directors should regularly review and audit their security measures to ensure they are effective and up to date with the latest security standards.

Finally, AI is revolutionizing fraud detection for finance teams by leveraging advanced analytics and automation. It enables real-time monitoring of transactions, detects anomalies and patterns indicative of fraud and utilizes natural language processing to analyze unstructured data sources.

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8 key data considerations for the finance function

Thick subledger, thin general ledger Finance teams are seeing the value of using a ‘thick’ subledger to hold detailed data and data attributes while maintaining a ‘thin’ general ledger free of unnecessary detail and customizations.

This target state allows finance functions to establish a single integration point for accounting, finance and reference data coming into the architecture while maintaining the original transaction level detail. This allows for greater drill back capabilities from aggregated balances in the GL back to the original transaction details stored in the subledger.

Subledgers can also de-risk and support a cloud general ledger migration or the rationalization of multiple GLs as a result of merger and acquisition activity. For example, a Financial Services company likely has many legacy IT systems that are not designed to work in a cloud environment, making data compatibility a challenge. This may require companies to manually recreate data which introduces cost and risk.

A cloud GL may also have specifications around certain data formats or the application of a data model or accounting rule.

Additionally, it may not be possible or cost-effective to store detailed transaction data in a cloud general ledger. Many of today’s GLs are overburdened with too much data. Making the move to a cloud GL can offer the chance to rethink your data strategy and commit to using the GL as it was intended, supporting by an integrated accounting hub and subledger to maintain detailed transaction data.

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8 key data considerations for the finance function

Build a digital finance department that can move in real time Our finance transformation solutions use new and emerging digital technologies to maximize efficiency and impact through process automation. They deliver a single source of accurate data that can support real-time, strategic analytics and insights.

Fynapse is Aptitude’s next-generation, automated, cloud-native finance management platform. Fynapse is built on a composable architecture providing an ecosystem of modules that can operate as standalone or be easily connected to meet specific use cases.

The Aptitude Accounting Hub (AAH) is a cloud-ready, accounting engine and subledger solution. AAH is purpose-built to centralize and automate finance, accounting, and reporting. It empowers finance teams with total control of accounting rules and processes, all managed from a single location and designed with finance users in mind.

Key business benefits of finance digitalization • Shift finance towards a value-adding, guidance role within the organization • Use improvements in cloud computing, scalability and process automation to drive down the cost and risk of the finance function • React with agility to market challenges, opportunities and new regulations • Reduce the financial close to near real time, ensuring the business has the data it needs to be competitive • Empower your team with solutions designed to be easily configured by finance users resulting in faster onboarding and a more self-sufficient team

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