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Imagine trying to predict the future of your business based on outdated or incomplete information. For many finance teams, this is a daily challenge. When decisions worth millions rely on flawed data, the consequences can be costly. High-quality data is the backbone of financial planning and analysis (FP&A). Without it, even the best strategic plans, budgets, and forecasts are built on shaky ground.
For FP&A teams, these challenges can manifest in several ways. Unreliable data complicates everything from daily decision-making to long-term strategic planning. According to Gartner, 85% of FP&A teams struggle to meet the complex needs of their organizations due to poor data quality. Whether it’s managing cash flow, forecasting expenses, or planning for headcount changes, data issues erode the very foundation of effective financial management.
The saying “Garbage In, Garbage Out” (GIGO) couldn’t be more relevant in FP&A. When inaccurate or inconsistent data enters the system—whether due to manual errors, outdated records, or disconnected platforms—the resulting insights are flawed. For instance, if a company’s Human Resources Information System (HRIS) isn’t synced with its Applicant Tracking System (ATS), headcount forecasts can be wildly off, leading to skewed budget plans.
These data issues don’t just obscure the financial picture—they lead to bad decisions. Companies may underinvest in growth opportunities, overlook critical cost-saving measures, or misallocate resources, resulting in lost competitiveness and missed targets.
At the heart of FP&A is forecasting—the ability to predict future trends, expenses, and revenue based on current and historical data. But when the data is unreliable, it becomes nearly impossible to produce accurate forecasts. Common culprits include manual data entry errors, discrepancies between systems, outdated records, and poorly integrated data sources.
These inaccuracies lead to forecasts that don’t reflect the true state of the business, which can cause organizations to make misguided decisions. Overestimating revenue because of inflated data can lead to overspending, while underestimating costs due to overlooked expenses can result in budget shortfalls and missed targets.
Companies that can access up-to-date data are better equipped to respond quickly to market changes and internal shifts - having real-time financial insights is not a luxury—it’s a necessity.. Unfortunately, for many organizations, this remains a challenge due to siloed data, poor integration between systems, and time-consuming manual processes.
By the time finance teams generate reports, the data they contain is often outdated, limiting their ability to make timely and informed decisions. This lag in financial reporting can hamper a company’s agility, delaying critical decisions and reducing its ability to seize new opportunities or address risks in real time.
AI offers a powerful solution to these persistent data challenges, helping organizations automate data integration, cleansing, and analysis. With AI-driven platforms like Precanto, companies can significantly reduce the reliance on error-prone manual processes and ensure their data is always ready for analysis.
Precanto’s AI-powered platform enables real-time anomaly detection and data cleansing, ensuring that finance teams have access to accurate and consistent data at all times. For instance, Pulmonx, a leading medical technology company, was able to uncover a $6M overstatement in stock-based compensation by using Precanto to identify data anomalies in real time. This allowed the company to correct its financial plan and avoid costly missteps.
By continuously learning from historical data patterns, AI enhances its predictive capabilities, providing finance teams with real-time insights that traditional systems simply cannot match.
Once data quality issues are resolved, AI-driven insights can transform how FP&A teams operate, offering a range of powerful benefits:
Overcoming data challenges is not just about fixing short-term issues—it’s about positioning your company for long-term success. Investing in data quality and leveraging AI-driven financial solutions allows FP&A teams to build more accurate forecasts, make better decisions, and maintain a competitive edge.
How Precanto Helps Overcome Data Challenges
At Precanto, we tackle data challenges head-on with our AI-powered financial intelligence platform. Precanto automates data integration from systems like ATS, HRIS, ERP, and planning tools through secure APIs, file uploads, or SFTP transfers. Once the data is ingested, it undergoes comprehensive cleaning and optimization, including standardizing data formats, imputing missing values, and applying machine learning for anomaly detection and error handling. By centralizing this data into a unified model, Precanto provides real-time insights and empowers finance teams to run accurate forecasts, conduct variance analysis, and simulate “what-if” scenarios.
Our platform’s error-handling features allow users to resolve data inconsistencies through proactive notifications and an intuitive interface, ensuring that all data is accurate and actionable. With Precanto, finance teams can confidently rely on a single source of truth, make data-driven decisions faster, and focus on strategic financial planning.
About Precanto
Precanto is committed to transforming FP&A through advanced AI and machine learning technologies. Our solutions address common data challenges, providing finance teams with the solutions they need to succeed. By ensuring your data is clean, consistent, and ready for analysis, Precanto empowers you to make informed decisions, achieve accurate forecasting, and unlock the full potential of AI in your financial processes.
Schedule a demo to learn how Precanto can help your organization.
