from a technology perspective, but the real story for big data is how organizations of different sizes are leveraging data and analytics to power their business models. Big data has the potential to uncover new customer, product, and operational insights that organizations can use to optimize key business processes, improve customer engagement, uncover new monetization opportunities, and re-wire the organization's value creation processes.
As discussed in this chapter, organizations need to understand that big data is about business transformation and business model disruption. There will be winners and there will be losers, and having business leadership sit back and wait for IT to solve the big data problems for them quickly classifies into which group your organization will likely fall. Senior business leadership needs to determine where and how to leverage data and analytics to power your business models before a more nimble competitor or a hungrier competitor disintermediates your business.
To realize the financial potential of big data, business leadership must make big data a top business priority, not just a top IT priority. Business leadership must actively participate in determining where and how big data can deliver business value, and the business leaders must be front and center in leading the integration of the resulting analytic insights into the organization's value creation processes.
For leading organizations, big data provides a once-in-a-lifetime business opportunity to build key capabilities, skills, and applications that optimize key business processes, drive a more compelling customer experience, uncover new monetization opportunities, and drive competitive differentiation. Remember: buy for parity, but build for competitive differentiation.
At its core, big data is about economic transformation. Big data should not be treated like just another technology science experiment. History is full of lessons of how organizations have been able to capitalize on economics-driven business transformations. Big data provides one of those economic “Forrest Gump” moments where organizations are fortunate to be at the right place at the right time. Don't miss this opportunity.
Finally, organizations have been taught to think cheaper, smaller, and faster, but they have not been taught to think differently, and that's exactly what's required if you want to exploit the big data opportunity. Many of the data and analytics best practices that have been taught over the past several decades no longer hold true. Understand what has changed and learn to think differently about how your organization leverages data and analytics to deliver compelling business value.
In summary, business leadership needs to lead the big data initiative, to step up and make big data a top business mandate. If your business leaders don't take the lead in identifying where and how to integrate big data into your business models, then you risk being disintermediated in a marketplace where more agile, hungrier competitors are learning that data and analytics can yield compelling competitive differentiation.
Homework Assignment
Use the following exercises to apply what you learned in this chapter.
Exercise #1: Identify a key business initiative for your organization, something the business is trying to accomplish over the next 9 to 12 months. It might be something like improve customer retention, optimize customer acquisition, reduce customer churn, optimize predictive maintenance, reduce revenue theft, and so on.
Exercise #2: Brainstorm and write down what (1) customer, (2) product, and (3) operational insights your organization would like to uncover in order to support the targeted business initiative. Start by capturing the different types of descriptive, predictive, and prescriptive questions you'd like to answer about the targeted business initiative. Tip: Don't worry about whether or not you have the data sources you need to derive the insights you want (yet).
Exercise #3: Brainstorm and write down data sources that might be useful in uncovering those key insights. Look both internally and externally for interesting data sources that might be useful. Tip: Think outside the box and imagine that you could access any data source in the world.
Chapter 2
Big Data Business Model Maturity Index
Organizations do not understand how far big data can take them from a business transformation perspective. Organizations don't have a way of understanding what the ultimate big data end state would or could look like or answering questions such as:
• Where and how should I start my big data journey?
• How can I create new revenue or monetization opportunities?
• How do I compare to others with respect to my organization's adoption of big data as a business enabler?
• How far can I push big data to power – even transform – my business models?
To help address these types of questions, I've created the Big Data Business Model Maturity Index. Not only can organizations can use this index to understand where they sit with respect to other organizations in exploiting big data and advanced analytics to power their business models, but the index provides a road map to help organizations accelerate the integration of data and analytics into their business models.
The Big Data Business Model Maturity Index is a critical foundational concept supporting the Big Data MBA and will be referenced regularly throughout the book. It's important to lay a strong base foundation in how organizations can use the Big Data Business Model Maturity Index to answer this fundamental big data business question: “How effective is my organization at integrating data and analytics into our business models?”
Chapter 2 Objectives
• Introduce the Big Data Business Model Maturity Index as a framework for organizations to measure how effective they are at leveraging data and analytics to power their business models
• Discuss the objectives and characteristics of each of the five phases of the Big Data Business Model Maturity Index: Business Monitoring, Business Insights, Business Optimization, Data Monetization, and Business Metamorphosis
• Discuss how the economics of big data and the four big data value drivers can enable organizations to cross the analytics chasm and advance past the Business Monitoring phase into the Business Insights and Business Optimization phases
• Review lessons learned that help organizations advance through the phases of the Big Data Business Model Maturity Index
Introducing the Big Data Business Model Maturity Index
Organizations are moving at different paces with respect to where and how they are adopting big data and advanced analytics to create business value. Some organizations are moving very cautiously, as they are unclear as to where and how to start and which of the bevy of new technology innovations they need to deploy in order to start their big data journeys. Others are moving at a more aggressive pace by acquiring and assembling a big data technology foundation built on many new big data technologies such as Hadoop, Spark, MapReduce, YARN, Mahout, Hive, HBase, and more.
However, a select few are looking beyond just the technology to identify where and how they should be integrating big data into their existing business processes. These organizations are aggressively looking to identify and exploit opportunities to optimize key business processes. And these organizations are seeking new monetization opportunities; that is, seeking out business opportunities where they can
• Package and sell their analytic insights to others
• Integrate advanced analytics into their products and services to create
