February 2013

The Future of Business Analytics

By Dan Rachlis

Dan Rachlis

Business analytics--What is it? Where is it going? These are questions we will be discussing in this article.


Business analytics is the practice of using data to drive business strategy and performance. It is undergoing massive, disruptive changes that will radically transform the way the industry and customers think about analytics. The exponential growth in data is a key driver of this change. In addition, the mainstream adoption of cloud computing across the enterprise continues to put pressure on the capabilities of businesses to incorporate all relevant data from multiple data sources to enable users to make more timely, comprehensive, insightful business decisions. All this adds up to business analytics demand by companies for new tools and processes to quickly and easily collect all types of data, and to store, manage, manipulate, aggregate, analyze and integrate all that data into useful ways that positively impact their businesses.

Data is the heart of business analytics. It is what companies rely upon for their competitive advantage and it is becoming more important as technology and analytical tools are now available, from hardware to software to data collection to collective intelligence. What is collective intelligence? In my view it is accessing the untapped knowledge of your network, in other words the aggregated knowledge, insight and expertise of a diverse set of data. Can an organization that chooses to ignore the insights and data of employees, customers and business partners expect to thrive? For many, the answer is no. Fortunately, the opportunity to more effectively apply collective intelligence has become a reality. As individuals become more adept and comfortable sharing thoughts and ideas in virtual spaces, companies can use these insights to address critical business challenges. Harnessing collective intelligence can play an important role in generating new ideas, solving problems, disaggregating and distributing work in new and innovative ways, and making better, more informed decisions about the future.

Business analytics is moving from looking at reports generated by a business intelligence (BI) system to an algorithm that will make decisions for you. The trend is toward delivering massive amounts of data right here right now. How many widgets do we need next week delivered to our store in Chicago? And databases in the sky delivering real-time information to devices, like Shazam, telling us what song that is or Yelp finding the best steakhouse in Chicago, to a mapping application using GPS to tell Yelp what my location is and the weather applications to see if it is going to rain tonight so eating al-fresco is not an option. Companies need to collect all this information and develop sophisticated algorithms and use predictive modeling to assist with their decision making.

Where do we go from here? By combining data, statistical analysis and predictive modeling, business analytics enables more accurate, objective and economical decision making. It includes a range of approaches and solutions, from looking backwards to evaluate what happened in the past, to forward-looking scenarios that include planning and predictive modeling. The model below shows the hierarchy of data analytics. The higher you go up the pyramid the more value and competitive advantage a business gets from the underlying data. To maximize the benefit of analytics, organizations need to go from the base of the pyramid to the top by combining the collective intelligence from all available sources available.

To View Image Click Here.

The amount of data that is generated in the business world is doubling every year. Information from devices, machines and social media creates an entirely new set of challenges, and reinforces the fact that data will continue to grow exponentially for the foreseeable future. Naturally, the demand for tools that help organizations access, analyze, govern and share information is seemingly insatiable. The trick is combining the data warehouses with the transactional data and the non-traditional external data (around the transaction such as web server logs, Internet clickstream data, social media activity reports, mobile phone records and information captured by sensors) into a source to develop useful information for sophisticated modeling and business analytics.

Dan Rachlis, ASA, MAAA, is a specialist master in the Chicago office of Deloitte Consulting LLP. He can be reached at drachlis@deloitte.com or at 312.486.5631.