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,...
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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). The greatest potential of analytics is in unifying a company around its customers, creating a unified view of what matters most to them, and most importantly, what their expectations are.
This is where analytics and business intelligence really begins to matter, in making an entire business unified and focused on its core set of objectives from the customers' standpoints. The traditional view of analytics and business intelligence is that it is a useful means of automating the rote and mundane work in accounting and finance. Yet in actuality, analytics and business intelligence can also revitalize and re-energize an entire value chain of a business, galvanizing the supply chain to distributed order management, ERP and fulfillment systems (Ranjan, Bhatnagar, 2011).
This is not a revolutionary concept, however taking the necessary steps to re-align a business and make it centered on customers first, not internal measures of performance, is.
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