Three Phases of the Big Data Journey

How to Understand the Big Data Journey

According to Christina Kirby of Comcast in a recent blog post here:

“Creating a data-driven culture and the accompanying shift in mindset is not a simple undertaking. This is particularly true for companies that were not built with data in mind. This kind of transformation and adoption must be seen as a journey that may take multiple years.”

At Comcast, working with big data is considered a journey, not an overnighter.

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The Big Data Journey

TDWI contributer Ulrik Pedersen described three phases to becoming a data-driven organization that also map nicely to the phases of a big data journey:

  • Understanding the health of the business
  • Experiencing operational excellence
  • Shaping competitive strategies

Let’s explore these phases in more detail.

Phase 1: Understanding the Health of the Business

In this first phase, organizations use big data and diagnostic analytics to dig deeper into how various aspects of the business are executing.

Think of it like a doctor running tests to make a more accurate diagnosis and define the right treatment.

Most companies have built data warehouses that can answer descriptive questions — telling them what happened. Diagnostic analytics answer the details about the how and why, giving you a detailed diagnosis on the business execution to create an actionable plan for improvement.

By way of example, let’s say a company was looking to improve their customer acquisition. They would use big data analytics for a detailed diagnostic examination of campaigns, costs and conversion across all channels.

Phase 2: Experiencing Operational Excellence

In this next phase, firms build upon the diagnostic analytics to predict events and define the right strategies for those events.

These analytics will add items more data to the mix to identify specific actions to take. As the analytics are operationalized, the data and actions will be driven to the business teams regularly. Regular execution of the analytics will allow the organizations to continuously improve.

To keep with our example of improving customer acquisition, a firm would supplement the diagnostic analytics with more attribute, behavior and offer data.

This data would provide answers about where to most effectively target, what behavior to look for and which offers work best so the marketing team can execute optimal campaigns. The result should be higher conversion and lower customer acquisition costs.

Phase 3: Shaping Competitive Strategies

In this phase, an organization will add even more data to the mix, including external data, and create analytics that create competitive differentiation in the market and drive new strategies.

While the earlier phases help improve execution, this phase takes the streamlined execution and expands the company’s revenue and footprint in the marketplace.

Continuing on our theme of customer acquisition, the expanded analytics add eternal demographic, targeting and channel data to identify new segments to go after. Offers and channels will be aligned via the analytics to create new campaigns to expand the customer base. The result should be increased revenue, larger customer lifetime value and broader set of customers.

The Rewards of Starting With Big Data Analytics

Follow these three steps to each area of the business you need to improve and your journey will bring tremendous value to your business. Big data analytics is truly a journey worth undertaking. Organizations that understand big data analytics is a journey gain much more value out of their efforts, expanding how they use and apply the data to multiple parts of the business.

Ready to start your big data journey? A free trial of Datameer is a great way to kick-start your efforts and learn what big data analytics are all about.

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