Analytics and Business Intelligence Assessing the Impact

Analytics and Business Intelligence

Assessing the Impact of Analytics and Business Intelligence

The pervasive adoption of analytics to mitigate risk has accelerated due to greater uncertainties in economic conditions, the accelerating pace of change in markets, and a reliance on quantified measurements of performance vs. qualitatively based (Hopkins, LaValle, Balboni, Shockley, Kruschwitz, 2010). The intent of this analysis is to look at how analytics and business intelligence can be used for automating the more mundane analytical and reporting tasks while also looking into how analytics and business intelligence are making finance and accounting systems more real-time and responsive to market conditions.

Automating Routine Tasks with Analytics

Computing variances between actual and forecasted amounts by account, defining financial ratios and calculating them over a multi-year timeframes and across multiple divisions is how analytics is most often used in accounting and financial reporting today. These are relatively mundane tasks that often require accountants and financial analysts to work weeks in some cases to complete analyses and create Balanced Scorecards for comparing performance of product lines, product divisions and sales territories (Mohanty, 2011). Without question, business intelligence and analytics have streamlined these tasks, freeing up analysts' time to concentrate on problems that are more complex, completing more insightful analysis to guide their businesses to greater growth. Analytics are a powerful series of technologies and in many companies, entire enterprise suites of software that can streamline the development of reporting systems that reflect market conditions, financial status of the business, and the real-time costs of managing the supply chain so that the best possible decisions can be made (Hopkins, LaValle, Balboni, Shockley, Kruschwitz, 2010). To minimize analytics as only one of many tools used for automating accounting and finance however is to completely miss the point of how powerful these technologies are when used for finding insights into customers and their purchasing behavior (Ranjan, Bhatnagar, 2011).