First let me start off by defining Business Intelligence as defined by Business Journal International Weekly. “Business Intelligence is a set of theories, methodologies, processes, architectures and technologies that transform raw data into meaningful and useful information for business purposes.” Over the past 10 years business intelligence has soured in popularity to what is now, a $15.8B a year business, with an estimated 55 percent of companies today using some form of Business Intelligence or Business Analytics solutions. According to Gartner, “by the year 2020 researchers show an estimated 75% of companies globally will rely on Business Intelligence to run their companies.” Who would have thought this number would get so high? Continue reading this post>>
Data analysis is considered to be a core component in business intelligence systems. The importance of data analysis pushes some company leadership to opt for outsourced data analysis while other business leadership prefers to stick with in-house data analysis. Let’s first take a look at the role of data analysis in business intelligence. Data analysis converts raw data gathered using different tools into meaningful data, which is usually presented to managers through reporting tools, and will aid managers in decision making. Ultimately, good data analysis leads to good decision making and successful business practices.
In past articles I’ve written here on arcplan’s BI Blog, I explored the role of spreadsheets in the planning, budgeting, and forecasting process and the importance of agility and accuracy. Today I would like to talk about the benefits of business analytics in the planning process when it comes to providing agility and accuracy.
When forecasts are consistently accurate, business leaders can have more confidence when making decisions and investments to guide the organization, as they have a good idea of how the organization will perform in the coming months. Agility is essential because volatile markets make it difficult for forecasts to reflect current business conditions. Therefore, Best-in-Class organizations are more likely than All Others to implement technology to enable both data access and the ability to utilize data to make predictive decisions (Figure 1). Fifty percent (50%) of Best-in-Class organizations have implemented an enterprise-level BI solution in comparison to 28% of All Others. These tools provide data in an easily consumable format so employees can find and utilize the data they need to make decisions. The Best-in-Class are also over twice as likely as All Others to have implemented predictive analytics. This technology helps to convert BI data into forward-looking forecasts.
Figure 1: Best-in-Class Technology Adoption
Source: Aberdeen Group, January 2013