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In many cases, the end of the year gives you time to step back and take stock of the last 12 months. This is when many of us take a hard look at what worked and what did not, complete performance reviews, and formulate plans for the coming year. For me, it is all of those things plus a time when I u...
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A Harsh Big Data Message | @ExpoDX #BigData #IoT #Analytics #SmartCities #DigitalTransformation
The real opportunity for Big Data vendors is to focus on this issue: ‘Determine how to get value from Big Data’

This is a short blog with a harsh message for Big Data vendors.

Camera fades in to Pastor Schmarzo heading to the pulpit…

What does the future hold for today’s Big Data vendors?  Hundreds of startups are rushing into the Big Data market to stake their claim to a market that IDC predicts will reach $187 billion by 2019.  Dang, that’s a big market, especially considering that the Global Business Intelligence market will only reach a trifling $20.8 billion by 2018 or the long-running ERP applications market is expected to reach a trivial $84.1 billion by 2020.  Yes, the big data market opportunity is very exciting indeed!

However, there is one little, teeny-weeny challenge for big data vendors trying to realize this financial bounty. The Gartner chart below summarizes this challenge very nicely (see Figure 1).

Figure 1 Source: Gartner

Many Big Data vendors are focused on selling “Infrastructure and/or architecture” because that’s the traditional way for software and hardware companies to “break the bank,” establish competitive differentiation (otherwise known as “architectural lock-in”, and make lots and lots of money.  They want to sell a “platform” that their customers and partners can use to solve any of a multitude of Information Technology (IT) needs. Since the days of IBM 360 mainframes and Microsoft DOS/Windows, selling a platform upon which others can build applications is the fastest way to untold riches.

Unfortunately with respect to Big Data, vendors selling “infrastructure and/or architecture” are selling to the wrong part of the organization. They are selling to the part of the organization where data is a cost to be minimized (and consequently, these vendors end up in one-sided battles with procurement on pricing and margin).  It’s a slippery slope that leads to burning through lots of investor money and without a happy ending.

Focus on “Make Me More Money”
The real opportunity for Big Data vendors is to focus on the #1 issue on the Gartner chart: “Determine how to get value from Big Data.”  This requires the Big Data vendors to talk to both IT (who owns the data and the technology infrastructure) AND the Business leaders (who are the ones trying to determine how to get value from Big Data).  You will start having conversations about helping organizations improve customer retention or reduce fraud or improve the quality of care or optimize network performance or expand predictive maintenance. This is not a conversation that ends with “oh, just buy my product.”

We tell our customers that Big Data requires a “think differently” approach where organizations need to “think differently” about how they are using data and analytics to power their business models, as embodied by the Big Data Business Model Maturity Index in Figure 2.

Figure 2: Big Data Business Model Maturity Index

Well, vendors need to experience this same “think differently” moment. Big Data vendors need to realize that to be successful, they need to work with their customers to help them become more effective at leveraging data and analytics to power their business models.  To be successful, Big Data vendors need to be able to drive a business value conversation in order to help organizations determine how to get value from Big Data.

Unfortunately, many Big Data vendors seem unwilling to invest in these types of conversations.  They just want to sell you a platform that solves all your problems and move onto the next opportunity.

And ultimately, this will lead to their demise.

“Thus ends today’s sermon.” Camera fades out to a light at the end of the tunnel – the Big Data Vision Workshop.

The post A Harsh Message for Big Data Vendors appeared first on InFocus.

Read the original blog entry...

About William Schmarzo
Bill Schmarzo, author of “Big Data: Understanding How Data Powers Big Business” and “Big Data MBA: Driving Business Strategies with Data Science”, is responsible for setting strategy and defining the Big Data service offerings for Hitachi Vantara as CTO, IoT and Analytics.

Previously, as a CTO within Dell EMC’s 2,000+ person consulting organization, he works with organizations to identify where and how to start their big data journeys. He’s written white papers, is an avid blogger and is a frequent speaker on the use of Big Data and data science to power an organization’s key business initiatives. He is a University of San Francisco School of Management (SOM) Executive Fellow where he teaches the “Big Data MBA” course. Bill also just completed a research paper on “Determining The Economic Value of Data”. Onalytica recently ranked Bill as #4 Big Data Influencer worldwide.

Bill has over three decades of experience in data warehousing, BI and analytics. Bill authored the Vision Workshop methodology that links an organization’s strategic business initiatives with their supporting data and analytic requirements. Bill serves on the City of San Jose’s Technology Innovation Board, and on the faculties of The Data Warehouse Institute and Strata.

Previously, Bill was vice president of Analytics at Yahoo where he was responsible for the development of Yahoo’s Advertiser and Website analytics products, including the delivery of “actionable insights” through a holistic user experience. Before that, Bill oversaw the Analytic Applications business unit at Business Objects, including the development, marketing and sales of their industry-defining analytic applications.

Bill holds a Masters Business Administration from University of Iowa and a Bachelor of Science degree in Mathematics, Computer Science and Business Administration from Coe College.

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