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The Converged Digital Industrial Economy and the Internet of Things

  |  October 21, 2013   |  Comments

If the current IT technology vendors and convergence architects can't deliver the converged technology stacks and processes needed to smelt all of this data together in a strong, durable, yet flexible bond, others will rise to challenge.

At the Gartner Symposium/ITxpo 2013 earlier this month, Gartner Senior VP Head of Research Peter Sondergaard uttered something controversial about the current IT market.

He said, "Many of the vendors on top of the IT world today--namely Cisco, Oracle, and Microsoft--will likely not be the IT leaders of tomorrow in the Digital Industrial Economy."

Sondergaard said the aforementioned companies' antiquated channel strategies, sales force, out of tune partner ecosystems and changing customer business models are the main reasons current leaders are falling behind, and new IT solutions ecosystem emerging.

Gartner might as well have called the "Digital Industrial Economy" (which suggests a new set of revitalized business processes that are fully coordinated and interoperable with digital equivalents) "Convergence Analytics," because it's pretty much the same thing. I believe the efficient use of various converged technologies is crucial to companies' ability to compete. There is so much data to process and understand; often, that data needs to be acted on quickly (which I mentioned in my last article at ClickZ).

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Figure 1: Domo.com 

It's not surprising few organizations have the means (both talent and software/services) to fully "digitize" their business processes into insights (see Figures 4 and 5). Those insights must drive meaningful business development, yet convergence architects are in short supply and most have over 10 years of experience. Simply, we don't have enough people who can build converged technology implementations.

Peter Sondergaard suggests we have already entered the new era, of the "Internet of Things" as an industrial engine of change, because of millions upon millions of new IP addresses assigned to intelligent devices that are communicating structured information. This information needs to be filtered and analyzed in real time to be the most useful. In the new convergence paradigm, business information that can't be directly digitized and acted upon becomes a business liability.

Data is being generated by current and potential customers (even as the nature of business is itself being redefined) who are interacting with brands across different channels. In order to get a 360 degree view of the customer--to understand what generates customer satisfaction and possibly, loyalty--the data needs to be "converged" or "digitized."

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Figure 2: Omni-Channel customer journey in travel industry, IBM

The customer journey is complicated (see Figure 2) and customers have become ever more elusive and fickle (see Figure 3). They easily switch loyalties when a stronger competitor is present in the market, making it vital for brands to be present and proactive in all relevant channels.

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Figure 3: Unruly Media

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Figure 4: Experience level in years of Convergence Analytics Architects, derived from LinkedIn search results.

There are valid reasons why silos exist in most corporations. However, the very same silos have also made it much harder to achieve the digitization of data that Gartner thinks is the most vital factor of all. At the end of the day, many organizations among F1000 aren't ready to act on convergence, nor are the main IP vendors able to deliver it to them, even if they wanted all the data to be converged.

As Gartner pointed out, very soon, most brands will have to converge their data in order to survive and continue to prosper.

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Figure 5: Seniority Level of Convergence Architects in Fortune 1000 corporations, derived from LinkedIn search results.

As the winds of change bring us into the next "industrial age," you can call it whatever you want. The most important point for businesses to understand is that their future--perhaps their survival--lies in tying all the data together to tell intelligent stories that can be acted on quickly.

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Figure 6: Combining Business Intelligence, Analytics and Big Data - Source: isanthosh.com

If the current IT technology vendors and convergence architects can't deliver the converged technology stacks and processes needed to smelt all of this data together in a strong, durable, yet flexible bond, others will rise to challenge. 

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ABOUT THE AUTHOR

Marshall Sponder

For over a decade Marshall Sponder has influenced the development of the digital analytics industry with his WebMetricsGuru writings that focus on social media metrics, analytics and media convergence. He also possesses considerable in-house corporate experience with roles at IBM, Monster.com, Porter Novelli, and WCG while continuing to work with start-ups. Marshall is a Board Member Emeritus at the Web Analytics Association (DAA) and teaches Web Intelligence at Rutgers University and Baruch Business College. Marshall is the author of "Social Media Analytics: Effective Tools for Building, Interpreting, and Using Metrics," published by McGraw-Hill in 2011.

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