Trends in Business Analytics for 2011: Alberto's Predictions

There are three main trends that we can see occurring in 2011 across all industries and regardless of company size: (a) a large increase in volume of work, (b) utilization of social media as a key data source, and (c) challenges in implementation and innovation. First, the year 2011 will bring a tremendous increase in the volume of work in business analytics. Specifically, the area of predictive analytics had an increased momentum in the last half of 2010 that will carry to 2011 without any abatement in sight. My prediction is that companies will increase their 2011 appetite for predictive analytics by over 200% from 2010.


The need for more efficient ways to do work and adapt to swift changes in the economic environment will be feeding the craving for companies to use business analytics. Some of the accompanying challenges that this increased appetite for predictive analytics will include the following:

1. Prioritization of analytics projects to align with corporate strategic and tactical objectives
2. Analytic resources identification - the profiling of individuals that know predictive modeling technique
3. Institutionalization of budgeting for analytics projects , or no more unplanned budget for analytics projects

Whether business analytics resides in the IT or business organization, companies will need to modify their business models to reflect the contributions and needs of an analytics organization. Companies need to decide whether they will bring analytics talent by acquisitions, hiring, or by outsourcing. Offshoring will be substantially different for IT than for analytics (rate cards, project management, and resources). Adjustments on delivery expectations for analytics projects may be needed since the analytics portion of a project can be a short-term exercise, but the enterprise implementation for the same project could be a long-term project.

Social media will become an even more important key data source. It will be used to reduce the time that it takes to predict trends affecting companies and their competitors. Companies that successfully leverage analytics in social media to detect future trends, and make changes to their strategy, will differentiate in the marketplace by using “swift insights” to quickly adapt to changing market conditions. The best example to understand the importance of swift insights is the experience of Coca-Cola vis-à-vis Gap. In 1985 Coca-Cola introduced a new coke formula, and it took them nearly three months to return to their original formula after a public outcry. On the other hand, Gap introduced its new logo, and the public backlash was so pronounced in the social media that one week later they returned to their original logo. In mathematical terms this mean that social media accelerated the identification of the need for change by eleven times (11x). In other words, if an average car ran at 50 miles in 1985, it will run at 550 miles in 2010.

The involvement of business personnel from companies will become essential in defining the social media analytics strategy, and for testing the results of any analytics project. This involves additional time commitments that must be managed both strategically and operationally. A combination of savvy, innovative, and experienced staff in consulting, technology, finance, and analytics skills will become critical in 2011 for companies to successfully integrate social media analytics into their business models. Any licensed driver can drive a car at 50 miles per hour, but only skilled experts can maneuver a car at 550 miles per hour.

The areas of innovation and implementation are connected by a combination of best practices and repeatable processes in best of breed companies. Enterprise analytics implementation requires a combination of a knowledge of statistics, analytical tools, and optimization techniques. Companies must guard against unwise investments in analytics by following best practices: references, due diligence, proof of value, pilot or POC, evaluation, budgeting, project planning, and implementation. Once the analytic problems have been defined and aligned with strategic goals, companies should look at their internal project planning process to ensure the availability of right resources, skills, and budget.

Planning a phased approach is recommended in all analytic analytics projects. This allows for the evaluation of the business lift, in addition it gives time for improvements and modifications that are department and geographically specific. The key for planning analytics capabilities within a company is to build a small but strong foundation of business, technical, and analytics skills and then move from small projects to larger projects.

The integration of technology innovations with analytics will be a crucial test for many companies in 2011 and beyond. There are three main technologies that will make an impact in the way we do business in 2011: mobile devices, visualization, and speech technologies. The delivery of predictive analytics results using mobile devices, like the iPad, tablets, and smart phones, allows executives and field personnel to have access to swift insights. Those insights will allow decision makers at all levels of a company to know the impact of their decisions in revenues, costs, and profitability.

The ability to use analytics and mobile devices to deliver filtered and ready to act information (converting data into information) will depend on innovative visualization techniques. The screen space in mobile devices is smaller than laptops and PCs, hence the need for smarter visualizations. The use of spreadsheets is not efficient in smart phones. For companies that have hundreds of products, the representation of multiple dimensions or variables (i.e., predicted revenues, profits, and commissions), the use of line or bar charts also have a limited use. The use of interactive 3D visualizations in mobile devices to represent analytics outcomes will become a new breakthrough in the business world. 3D visualizations and predictions are common practice in web-based games, and those algorithms will be integrated into the business world in 2011.

Speech technology is another innovation that will be making its mark in 2011 and beyond. In December 2010 two high school students won a price at the Siemens Competition by developing a speech recognition algorithm that can detect a speaker’s emotion better than any current technology. Imagine how many errors individuals make when they are in a hurry, or otherwise distracted. The business impact of preventable errors could be billions of dollars annually using a combination of this speech recognition technology and predictive analytics outcomes, all delivered through mobile devices.

Finally, my last prediction: in order to flourish and quickly adapt to changes in these rapidly changing economic times, we need to carefully listen to those that are our future. The examples from Siemens Competition (speech recognition technology), Gap (social media), and visualizations (web-based games) are common technologies used by the 9-to-30-year-old population. One of my main roles as an innovator is to listen to those voices and use my experience to provide guidance in implementing those new technologies and methodologies for businesses. A warning and advice to companies: listen carefully to those that represent our future. The future belongs to them, and our job is to provide guidance based on our experience.

My wish to companies for the year 2011: be the future not the past. Companies need to be open to new ideas and new ways to do business using analytics. Learn from the Blockbuster-Netflix proposed partnership in 2000. Blockbuster laughed Netflix out of their office thinking that the online subscribe service model would not be successful in the movie rental business. Now Netflix is a thriving business with 16 million members, while Blockbuster is in bankruptcy with $900 million in debt.