Still not convinced about Business Intelligence? Here’s how we did it.

About 9 months ago our company implemented a LOB application that allowed us to track activities, tickets, projects, sales initiatives, agreements, timesheets and billing. This tool had a dramatic and positive effect on our ability to manage our processes and to increase our organizational efficiency. Many of our staff have since developed a high level of comfort with it and are constantly finding new ways to leverage its capabilities. To be honest, I no longer understand how we could have ever operated without this tool. That being said, the logical next step for us, now that we are accumulating important operational and sales data, is to leverage this data to better understand our business. We believe the insight that can be obtained by understanding this data will help us identify areas for improvement, opportunities for growth, and improve our ability to forecast, budget and estimate.

Our LOB application ships with a series of reports that allow us to draw data related to certain aspects of our business. Albeit a good starting point, we quickly realized we weren’t gaining true intelligence from these reports. This is by no fault of the application vendor but rather the reality of standard out-of-the-box reporting. Such reports are static entities that provide point-in-time views of data. They lack the ability to pivot, perform train-of-thought querying, and cannot be expanded to support statistical modeling to assist with forecasting. Moreover, perhaps the most significant limitation was the inability to intersect data with that of other data sources. For instance, utilization data would be significantly more useful if it were combined with financial data to provide real revenue and cost figures against each metric.

Ultimately, our objective was to avoid having to involve staff from multiple departments to generate various reports, which then had to be manually merged to generate management reports. Additionally, we wanted to build advanced analytics to improve our ability to forecast. There are significant challenges in building such a reporting solution. We embarked on a journey to define the performance metrics and statistical models we needed to better run our business and to implement a solution on the Microsoft Business Intelligence platform (using SQL Server, SQL Analysis Services, SQL Integration Services, and SharePoint Server 2010 – PerformancePoint Services). Over the coming weeks, I intend on journaling the approach we took and the challenges we faced in implementing our solution. Stay Tuned!

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