I went to a conference provided
by one of the Big Data platform leaders last week, and I was struck by the lack
of persuasive reasons presented for aggressively moving forward with broad
scale Big Data projects. There were a couple of customers discussing their
experiences but their focus was architectural and operational rather than
business minded. Instead of tangible use case, vertical application, and ROI
successes and proof points, there was an implicit assumption that skyrocketing
growth in data volumes meant that Big Data deployments would soon take over the
IT world, and that by inference, this early-to-market vendor would necessarily
be a market leader.
I call
this rationale the "Chicken Little approach" because we can't
validate a technology movement just because an industry or a vendor makes a lot
of noise. (In this case, the Big Data technology boom is implicitly assumed to
be valid because start-ups and chunks of data are falling from the sky!) And as
far as the vendor is concerned, we can't ordain it a long-term industry leader
just because it is early to market with a Big Data platform.
Customers
will not bet their jobs on unproven business assumptions and the promise of
higher performing computing. At the
very least, Big Data vendors must demonstrate better business results for their
customers, offer value or cost benefits that far outshine current alternatives,
and provide some hard assurances that any departure from a customer's existing
infrastructure would be in sync with the industry and would be fully supported
for the foreseeable future.
As a
Marketing guy, there are several directions I’d take to prove the advantages of Big Data solutions to the business community including characterizing the opportunity by
industry vertical, identifying key use cases that resonate with the market, and
providing vendor specific unique proof points and value propositions. I'd first
identify the key verticals to approach because use cases and
value propositions become more tangible and persuasive when they are
validated by vertical. The rest of this blog focuses on one of
several approaches that could be used to identify the most likely
vertical targets for Big Data vendor offers.
The chart below is from the October 2011 McKinsey Quarterly. It's two years old but still relevant. I like the McKinsey analysis because it suggests near-term opportunities, e.g., finance and insurance, and promising verticals in the mid to long-term, e.g., the real estate market. This chart also forecasts the economic impact (GDP) that should occur as these industries take advantage of Big Data technologies. For instance, Big Data is predicted to provide an enormous lift for the Real Estate business.
The chart below is from the October 2011 McKinsey Quarterly. It's two years old but still relevant. I like the McKinsey analysis because it suggests near-term opportunities, e.g., finance and insurance, and promising verticals in the mid to long-term, e.g., the real estate market. This chart also forecasts the economic impact (GDP) that should occur as these industries take advantage of Big Data technologies. For instance, Big Data is predicted to provide an enormous lift for the Real Estate business.
This McKinsey analysis provides a comparative view of the many potential verticals that could be considered. The vendor who takes the more targeted vertical approach to market is far more likely to persuade business decision makers to get serious about Big Data and to include that vendor in their Big Data IT deployment plans.
Look for my next blog which will explore the key use cases driving Big Data today.
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