Analytics 3.0

Analytics 3.0

1. In the new era, big data will power consumer products and services.

2. The Evolution of Analytics

   • Analytics 1.0—The era of “business intelligence.
     • time of real progress in gaining an objective, deep understanding of important business phenomena and giving managers the fact-based comprehension to go beyond intuition when making decisions.
   • Analytics 2.0—The era of big data
     • the need for powerful new tools and the opportunity to profit by providing them quickly became apparent. Companies rushed to build new capabilities and acquire customers.
     • When internet-based and social network firms primarily in Silicon Valley: Google, eBay, and so on began to amass and analyze new kinds of information.
   • Analytics 3.0—The era of data-enriched offerings.
     • Marks the point when other large organizations started to follow suit. Today it’s not just information firms and online companies that can create products and services from analyses of data.
     • You have the ability to analyze those sets of data for the benefit of customers and markets.
     • You have the ability to embed analytics and optimization into every business decision made at the front lines of your operations.

3. Today it isn’t just online and information firms that can create products and services from analyses of data. It’s every firm in every industry.

4. One of the most dramatic conversions to data and analytics offerings is taking place at General Electric, a company that’s more than 120 years old.

5. Organizations will need to integrate large and small volumes of data from internal and external sources and in structured and unstructured formats to yield new insights in predictive and prescriptive models

6. Consistent with the increased speed of data processing and analysis, models in Analytics 3.0 are often embedded into operational and decision processes, dramatically increasing their speed and impact.

   • Procter & Gamble is integrating analytics in day-to-day management decision making through more than 50 “business sphere” decision rooms and more than 50,000 “decision cockpits” on employee computers.

7. To develop products and services on the basis of data, companies need a capable discovery platform for data exploration along with the requisite skills and processes

8. Analytics 3.0 provides an opportunity to scale those processes to industrial strength. Creating many more models through machine learning can let an organization become much more granular and precise in its predictions.

   • IBM
     • Formerly used 150 models in its annual “demand generation” process, which assesses which customer accounts are worth greater investments of salesperson time and energy.

9. Companies that want to prosper in the new data economy must once again fundamentally rethink how the analysis of data can create value for themselves and their customers.

   • Analytics 3.0 is the direction of change and the new model for competing on analytics.