Businesses need agile tools to quickly identify and communicate actionable insights for more informed decision-making. Facing uncertainty like never before, businesses worldwide have placed newfound importance on data analytics as they try to realign their operations in the midst of a global pandemic. The impact of COVID-19 on financial planning analysis (FP&A) professionals is especially significant, forcing chief financial officers (CFO) to implement new forecasting models as well as incorporate new data as they adapt to the “new normal.” When finance leaders were asked in a recent Deloitte Dbriefs, “What are the biggest challenges to plan for the future/next year?,” almost a quarter cited the lack of advanced capabilities to respond to the external environment. With neither current and accurate data, nor the tools for extracting actionable insight from vast datasets, FP&A teams will inevitably struggle to achieve the necessary levels of agility to continuously adapt forecasts as new information becomes available. A recent edition of Deloitte’s also highlighted several factors that has corporate leaders challenging the status quo of traditional business planning processes. Such factors include the need for constant scenario development and modeling; a lack of confidence in future projections; the urgent need for decisions about courses of action; an unclear decision-making framework, particularly around capital allocation; and time- and resource consuming manual iteration. CFO Insights Sharon Daniels, CEO of , stated in a recent announcement that, “For data to have value, enterprises must be able to extract meaningful insights that lead to positive business outcomes - they need to reduce the time it takes to get to those insights, and take action." Arria NLG Enterprises are already swimming in data that they can’t analyze, much less communicate actionable insights in real-time. Even if FP&A teams can somehow assemble relevant data for ad hoc analyses on desktops,this is too often done by brute force using spreadsheets, which can take an inordinate amount of time. As such, they must overcome barriers to standardizing, systematizing, and operationalizing the data-gathering and analysis process. Historical financial information and performance indicators are housed, manipulated and analyzed in Microsoft Excel spreadsheets. Since hitting the market in 1985, Excel has become one the most widely utilized computer application in workplaces worldwide. Fast forward 35 years to present day where 1.2 billion users worldwide rely on the robust functionality and intuitive design of Microsoft Excel to help them analyze and understand data.  As the audiences currently consuming these insights has multiplied exponentially, so too has the need for augmented analytics and data storytelling. Integrated data visualization capabilities are one way to help decision-makers see and manage by exception more rapidly, iterate scenarios faster, and understand likely impacts more quickly to support decision-making. However, businesses that generate analysis and reports with basic tables and charts lacking advanced language analytics are competitively disadvantaged. AI-powered applications like the just-introduced Add-In, bring data understanding to the masses by leveraging natural language generation technology for report automation. A subset of artificial intelligence that turns structured data into text or spoken narratives, Natural language generation (NLG) technology automatically analyzes data, producing written summaries that are nearly indistinguishable from analyses authored by human subject matter experts. Excel remains entrenched as the most widely adopted business analytics tool for FP&A professionals and is every analysts' tried-and-true tool for decision and reporting support. Arria for Excel adds natural-language functionality and report automation within worksheets, which instantly turns volumes of data into contextual narratives. Streamlined financial auditing, accelerated clinical safety reporting, fraud mitigation, and myriad other use-cases are bi-products of NLG's ability to automate reporting within the ubiquitous Excel. This will save countless man-hours (and costs), reduce human errors and erroneous reporting, ensure fiduciary transparency, and extend the reach and utility of data analytics. For effective analysis and planning, financial reports and forecast models must be available in time to inform decision making and as such, should be published as soon as possible after the end of the reporting period. In addition, with volumes of data changing at a pace like never before, insightful information delivery across the enterprise provides clarity, transparency and confidence in times of uncertainty. Businesses and governments can simplify and operationalize what was previously complex and time-consuming using AI like natural language generation that augments analytics with data storytelling. Empowered with such agile resources, FP&A teams can produce dynamic, actionable intelligence from petabytes of underlying data in real-time.

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