Brian's Blog


The concept of Big Data is getting a lot of attention these days. There is even a blog in the Harvard Business Review examining “What a Big-Data Business Model Looks Like”.

The fact of the matter is, similar to the dot-com business model – that was never actually a stand-alone business model – big data is not a business model. Big data is an enabling phenomenon. As I have described in previous blogs, when big data is combined with advanced analytics, it is an enabler for new ways of conducting business. By looking at big data as a business model, big data is sold short in terms of how it can greatly impact core, traditional business models.

To make this point, I’ll briefly highlight a few videos that demonstrate how traditional business models maximize their effectiveness via the use of big data and advanced analytics:

  • Healthcare: In this healthcare example, one of the largest insurers in the United States demonstrates to use big data and advanced analytics to analyze staggering volumes of unstructured data to find the bit of information that help the healthcare professional make more informed decisions for individual patient-specific diagnostics. Note that this is not a new business model, it is just a better way of doing business.
  • Utilities: In this public utility example, the city of DC discusses how they use big data and advanced analytics to increase the efficiency and effectiveness of maintaining and upgrading the infrastructure and service of the water utility infrastructure – which is nearly 200 years old. DC Water collects information related the city water infrastructure throughout the city, including soil type, pipe age, break frequency, and pressure issues. They use this information to inform their proactive repair maintenance and repair schedule. Using this data, they have save 20 percent, over $1 million, on their repair truck fuel costs, by optimizing their repair truck schedule. Public utilities are a business model that is thousands of years old. Nonetheless, this old business model can be augmented via the use of big data and advanced analytics.
  • Manufacturing: In this manufacturing supply chain example, the manufacturing supply chain is evaluated and a few best practices are highlighted. These best practices boil down to supply chains being instrumented, interconnected, and intelligent. When these best practices are integrated in to the traditional manufacturing business model, the business model itself does not change. The traditional business model is enabled. Additional details can be found here in the full study.
  • Government: This final video on New York’s experience integrating analytics into its collection processes illustrates the potency of the “big data”/advanced analytics combination. New York was able to stop over $1 billion in refunds going to tax payers.

My colleagues and I at IBM have developed a methodology to help public sector organizations evaluate their strategy and business models and develop a roadmap as to how that business model can be made more efficient and effective through the use of big data and advanced analytics. Please feel free to contact me for more details.

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