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What this blog covers:

  • FP&A teams deal with increasing data volumes, scale and complexity to answer critical business questions.
  • Finance leaders need a comprehensive data stack to manage their workloads without speed, cost, and scalability issues.
  • Kyvos offers its patented smart pre-aggregation technology backed by a universal semantic layer, data mesh capabilities and cost optimization to make their lives easy.
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In the search for the Goldilocks or ‘just right’ tech stack to boost FP&A (Financial Planning and Analysis) functions, most CFOs are caught between two extreme ends—legacy systems with the associated skill base they have invested in over the years and enterprise tech solutions that can modernize their existing ecosystem. Modern FP&A tools are poised to win this battle, but at what cost? Let’s find out more.

The Future of FP&A: Moving from Intuition to Data-Driven Insights

With many finance leaders pivoting toward data and analytics innovations, FP&A reporting covers around one-third of total finance spending in most organizations. However, not all these investments deliver the expected ROI, mostly due to delayed insights, exploding data volumes, and inaccurate predictions.

To top that, one-fourth of stakeholders still do not factor financial analysis into their decision-making processes, making the adoption lower than expected. Plus, these decision-makers don’t always trust the source data as legacy systems often lead to fragmented analysis. Almost 73% of finance leaders want to implement centralized data governance protocols to eliminate dispersed and outdated information.

Hence, designing FP&A of the future requires a well-balanced framework backed by the right technology stack. At the same time, increasing enterprise data volumes, complexities and scale rely on faster and more consolidated query responses to build powerful insights. Kyvos can help take FP&A functions to the next level, where intuitions turn into data-derived analytics. Here’s how:

#1 Analyze as Much Data as You Have or Need

Global financial institutions gather, process and analyze billions of transactions every day. With data volumes growing at approximately 61% annually, imagine the challenges of analyzing this information overload.

Organizations use one or more analytical tools to analyze and visualize all their data. But after a certain limit, reports get clunky and slow because these tools may need to process millions or even billions of rows with hundreds of dimensions and millions of cardinalities to return a single query. This causes undue delays in query responses. Delayed reports become useless for time-sensitive decisions, like calculating the outstanding loan figures before submitting a risk compliance report.

Kyvos offers a patented smart pre-aggregation technology to handle massive datasets– both historical and streaming. It creates scalable data models for various combinations relevant for business users, encompassing frequently asked queries. This minimizes redundant calculations and returns query responses across multiple dimensions and measures in split seconds.

#2 Get Faster Insights at Any Scale

Legacy systems – with their cumbersome and static spreadsheets – cannot refresh data when the inflow of information grows exponentially, with hundreds of attributes for multiple asset classes. If users fire complex queries on this data, responses may sometimes take hours to return, particularly when they want access to the lowest, transaction-level granularity.

Data engineers need to create multiple extracts to run these queries, which further slows down the performance. In addition, extracts limit the depth and breadth of the data, affecting the accuracy and quality of insights drawn from it.

Kyvos enables live connection between any existing analytical tool and data platform for exponentially faster query responses. The platform also offers incremental data refresh capabilities without manual processing or custom codes. Users get interactive, fast and uninterrupted access to the entirety of their data with Kyvos’ intelligent query engines and analytics servers.

#3 Do Complex Calculations with Ease

FP&A teams need to analyze months or weeks of transaction history to answer queries like – how to improve revenues from partner merchants in a specific region or what were the profits generated by the loans department in a specific year.

Queries run on such current and past Y-o-Y data are complex and involve multiple joins to deliver accurate results. Traditional systems aggregate this data and run two queries in parallel. All this happens during the run time, leading to higher costs and sluggish performance. Kyvos offers an innovative solution using aggregate varying measures and different formulas for time-period analysis. Advanced hierarchies within the datasets reduce complexities in attributes and allow drill-down to the lowest levels.

With custom roll-ups, Kyvos users can control member values rolling up into parent values within a parent-child hierarchy, especially when dealing with values like asset depreciation. The platform delivers an updated, comprehensive and accurate view of all the data to explore complex KPIs. Also, the platform offers extreme decimal support for up to 13 decimal points with a precision of up to 38 digits.

#4 Augment Analytics with Other Data Products

Centralized data management entrusted to a single FP&A team can lead to a logjam of data requests, analytics backlogs and scalability issues. A data mesh architecture proposes a decentralized approach that treats data as a product and departments can manage their individual datasets while collaborating on different operations to conduct deeper, multidimensional analytics.

Kyvos helps create such department-owned data models that function as robust data products. Users can also share these assets to reduce data duplication while maintaining complete data protection and access controls.

#5 Bring FP&A on the Cloud

The legacy OLAP systems – Essbase, SSAS and TM1 – have been integral to FP&A functions. But they use an antiquated scale-up architecture installed on costly servers and additional human resources to keep pace with an enterprise’s growing demands for data-driven insights. In addition, scalability becomes a major pushback with these systems when analytical needs go up or down.

A 2021 survey stated that organizations using cloud-native solutions witnessed a 6% increase in data-driven decision-making and 49% of users could also get more accurate and faster insights with this move. Needless to say, it’s high time for organizations to take their FP&A functions to the cloud.

Kyvos is built purposefully for the cloud to offer its scale-out capabilities, where analytics can scale limitlessly with underlying cloud data warehouses or platforms. Pre-processing massive datasets leverages the computing capacity of existing cloud data platforms without any in-memory constraints.

#6 Make It All Self-Serve with a Universal Semantic Layer

Due to the complex application landscape in most organizations, FP&A analysts deal with inconsistent reporting, siloed information and a lack of common business logic to maintain consistency of information across the board. Kyvos creates a universal semantic layer between analytics tools and data platforms to bridge these data gaps.

By defining all business logic in a single location, the semantic layer standardizes key financial terms and metrics to deliver consistent query results, even at high user concurrency. Kyvos uses advanced data modeling features to build this abstraction layer while ensuring complete data protection, thanks to a three-tiered security architecture.

Kyvos enables non-technical business users to get unified views for any number of queries as the platform hides the physical complexity of the data even when using multiple tools for data visualization.

Looking Ahead

Beyond predictable spreadsheets and reports, financial planning and analytics experts need to analyze data more deeply and find insights quickly to take advantage of every growth opportunity. New-age solutions like Kyvos optimize their financial performance and help build an FP&A function for the future. For more information, please get in touch with our experts and let us take your data analytics to the next level.

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What is FP&A?

Financial Planning and Analysis, or FP&A functions in modern organizations involve budgeting, data analytics and forecasting to make strategic financial decisions and steer the organization towards its objectives. It includes quantitative and qualitative analytics covering financial performance factors in a company to anticipate obstacles, streamline operations and predict future growth.

What are the basic concepts of FP&A?

FP&A teams combine operational, external and financial data to uncover deeper insights into the company’s profitability and cash flows. The main underlying concepts of FP&A are financial planning based on comprehensive risk analytics, budgeting, scenario planning to consider all what-ifs, performance reporting and predictive analytics.

What is reporting in FP&A?

FP&A professionals prepare several reports to map the present and historical data to actual performances and predictable results. FP&A reporting helps make business-critical decisions based on the company’s financial position, solvency and liquidity. The key reports are budget variance analysis, cash flow forecasting, operational reviews, balance sheets and income statements.

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