Recently, EMC shared its views on critical stages of the Big Data Business Model Maturity Index in a blog post by Bill Schmarzo, Chief Technology Officer and EMC's Dean of Big Data.
Essentially, EMC developed the Big Data Business Model Maturity Index to help organizations measure how effective they were at leveraging data and business analytics to power their business models.
According to EMC's Schmarzo, the vast majority of organizations he meets currently leverage Business Intelligence (BI) and data warehousing tools to monitor business - ultimately providing a retrospective, batch view of what the business has accomplished. And while this is a critical foundation upon which to build big data capabilities, organizations have learned that they cannot become a real-time, predictive and prescriptive data-driven organization using these BI and data warehouse tools.
Organizations need something more, which is where the Big Data Business Model Maturity Index comes into play.
So, what are the steps that an organization needs to accomplish in order to advance itself through the Big Data Business Model Maturity Index?
To progress through the Big Data Business Model Maturity Index - and become more effective at leveraging data and analytics to power their business models - Schmarzo shares that organizations must progress through four stages.
- The Insights stage is about coupling the wealth of internal and external data with predictive analytics to uncover insights about the organization’s key (internal) business processes, product and service attributes, and/or customer behaviors and sentiments. Key actions of the insights stage include: Identifying and understanding the decisions that the key business stakeholders need to make to support an organization’s key business initiatives
- The Optimization stage applies prescriptive analytics to the customer, product, operational and market insights to deliver recommendations to front-line employees, partners and customers to improve effectiveness of the organization’s key (internal) business processes. Key actions required to transition from the Insights to the Optimization stage include: Evaluating insights and deploying prescriptive analytics.
- The Monetization stage leverages the approach from the Optimization phase to identify and execute on new (external) business opportunities within the context of the organization’s existing business strategy. Key actions required to transition from the Optimization to the Monetization stage include: Catagorizing analytic insights, proving ROI and validating business relevance and business potential for insights.
- The Metamorphosis stage leverages the organization’s cumulative insights, data and analytics to create net new components of the business strategy – new business models, new consumption models, new corporate goals! Key actions required to transition from the Monetization stage to the Metamorphosis stage include: Creating new customer consumption models, creating an analytics platform to incorporate customer-facing interactivity and determining how to enable, scale and secure the analytics platform so that third-party application developers can develop, market, sell and support new value-added applications - think Apple App Store or Google Play.
Big Data Dreams
As EMC's Schmarzo cautions, organizations do not need a big data strategy as much as they need a business strategy that incorporates big data. Organizations don’t fail at big data because of a lack of business opportunities; they fail because they have too many. Additionally, business and IT leaders must co-lead the big data journey starting with identifying, brainstorming, and prioritizing the big data business opportunities or analytics use cases. Business leaders need to be committed to treating analytics as a business discipline, in the same way they treat accounting, finance, marketing and organizational sciences. Last, organizations culturally need to embrace data and analytics in order to optimize their key business processes, uncover new monetization opportunities and deliver a more compelling customer experience.