About UsThe Decision Factor offers insightful comments and observations on analytics—from views on new technology approaches and market dynamics to the latest industry trends driving demand for faster, smarter information analysis. This blog contains personal views, thoughts, and opinions from SAP employees, mentors, and friends working in the area of analytics. It’s not endorsed by SAP nor does it constitute an official communication of SAP. |
Posted by: Deepa Sankar May 16, 2013  Last time, I discussed how companies can mine their data gold by turning it into insight, which leads to positive impacts on your business, such as increased revenues, reduced costs, managed risks, and capital. These impacts give your business a better competitive advantage. Today, let’s discuss the other details of the other critical factors to make your BI program successful.
Define the Value of BI with KPIs
Defining the value of BI, i.e. assigning a dollar value to BI, is often challenging since this …
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Posted by: Pras Chatterjee May 14, 2013  It should come as no surprise that the next mile of finance is upon us – changes are afoot in the world of budgeting and forecasting. Traditionally, this has entailed the finance organization accumulating information at a high level of aggregation from their business partners (sales, HR, marketing) and other cost and responsibility centers. This information feeds into budgeting, forecasting, and strategic planning models with most of the emphasis on revenues and expenses. But many of these models lack collaboration, clarity, and timeliness. In …
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Posted by: Deepa Sankar May 9, 2013  Previously, I covered the importance of a business intelligence (BI) strategy and how BICC becomes a key element of your organization. This time, I will cover details on the other critical factors to make your BI program successful.
Companies need to recognize that data is “gold”. To mine this gold, you have to turn data into insight, which leads to positive impacts on your business, such as increased revenues, reduced costs, managed risks, and …
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Posted by: Kaan Turnali May 8, 2013  Do you have all three layers of mobile BI security covered: device, app, and data? All of the convenience and benefits of mobile devices provide a particular security risk, complicating matters for the technology managers. When we think about the three layers of security in mobile BI, each layer plays an equally important role. Moreover, each layer represents a specific component of a user’s access profile. Therefore, it’s vital not only to understand how each layer completes the security picture, but also to make sure they work …
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Posted by: Scott Jeffries May 7, 2013  Over the past few weeks, we’ve explored three key activities to driving enterprise value through analytics. In this final installment, we’ll discuss the path forward.
Many times, the immediate need for business insight is scattered around the organization, and the response is addressed in isolation rather than as a company-wide imperative. Employees often perform their analysis in spreadsheets and resort to manual workarounds when existing tools and processes are inadequate.
Today, however, the requirement for financial and operational insight is growing …
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Posted by: Scott Jeffries May 2, 2013  In my last two blogs, we discussed two of the three key activities to drive value through analytics—gaining control of your data and delivering the right information to the right people. Now it’s time to explore the third activity—enabling real-time analysis.
Business issues are on-going. Companies must continuously monitor business performance against established targets to identify areas for appropriate action and further analysis. In addition, business users are bombarded on a daily basis with questions that require quick investigation. And many of these questions …
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Posted by: Markus Schunter April 30, 2013  Yesterday’s Analytics
Until recently, financial analysis-based decision making relied on a historical view of aggregate data –understanding yesterday’s events to influence tomorrow’s performance. Highly skilled data scientists took summary-level information – analytic engines would be quickly overrun by larger or more detailed volumes of data – and analyzed promotion effectiveness, capital ROI, or quarter-end results.
While useful, this approach posed several problems:
Analysis was by definition backward looking. Summary-level analysis could easily mask anomalies that, if identified, would change the …
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Posted by: Patricia Saporito April 29, 2013  Everyone is talking about “Big Data,” but what they really want are “Big Insights.” To realize significant insights requires an effective analytic strategy.
Many companies believe they have an analytic strategy when what they actually have is an architecture, which is important but certainly not all you need. An analytic strategy requires continuous strategic and tactical business alignment, defining and updating your analytic strategy in view of your business goals and objectives, and analyzing and updating your current analytic roles, analytic skills, business processes and …
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Posted by: Lance Holbert April 25, 2013  Business analytics has evolved dramatically from its humble beginnings in core data warehousing more than 30 years ago. It’s evolved from simple, decision support solutions to advancements in business intelligence (BI), enterprise performance management (EPM), and, most recently, intelligent data concepts and predictive analytic applications. Companies have embraced the value of analytics – solutions that combine data and analysis to drive insights – to help them differentiate, become more competitive, and make better business decisions.
A Pervasive Culture of Analytics
Almost everyone in your company can benefit from …
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Posted by: Scott Jeffries April 23, 2013  In the first two blogs of this series, we discussed the three key activities to drive value through analytics—gaining control of your data, delivering the right information to the right people, and enabling real time and predictive analysis. Today, I want to delve deeper into the second activity.
It’s not enough for an organization to simply have consistent data. It also must agree on how to use and deliver that data – preferably at a …
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