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RSS 2020 Predictions: Too Much IIoT Failure Forces Industrial Businesses to Get Smarter About Data

VMblog Predictions 2020 

Industry executives and experts share their predictions for 2020.  Read them in this 12th annual series exclusive.

By Syed Hoda, Chief Commercial Officer at

Too Much IIoT Failure Forces Industrial Businesses to Get Smarter About Data

The IIoT offers no shortage of promise for manufacturers and other industrial enterprises eager to introduce new production efficiencies and oversight into their (often globally-distributed) operations. That isn't news - however, this promise has remained a mirage for those lacking the foundational data infrastructure necessary for IIoT implementations to actually function successfully. I foresee 2020 to really be the year that these organizations execute the data technology digital transformations required to ensure tangible IIoT results.

Here are my specific predictions for the IIoT, and related data technologies, in 2020:

1) Industrial businesses launching IIoT transformations without compatible data infrastructures will continue to fail throughout 2020

IIoT implementations have proven to be a Mount Everest for many: a rewarding challenge and achievement to pursue, and yet brutally unforgiving to those who venture out ill-prepared. Cisco has reported that, in fact, close to three-fourths of IoT projects are failing. Research by Microsoft has further determined that 30% of IoT projects fail at the proof of concept stage.

I believe this stark reality is perpetuated by three factors. First, industrial organizations face shortages in acquiring personnel capable of successfully utilizing machine data - these are skillsets which remain in limited supply given the relative youth of the technology. Second, while properly utilizing the IIoT requires full corporate cultural support and tremendous agility, it's all too common for siloed and resistant corporate cultures to hold back implementations and prevent more efficient and effective practices from ever reaching the factory floor.

However, the third and most fatal factor for IIoT initiatives has been the limitations of organizations' existing data and IT infrastructures. The industrial sector in particular has struggled to adopt the "data first" practices and mindset that IIoT solutions require to thrive, largely because the traditional databases and infrastructure technologies they have in place were never designed to handle machine data, or any data at IoT scales. In 2020, expect businesses introducing IIoT implementations to continue to face a steep and perilous climb if they don't first address these underlying obstacles.

2) With increasing urgency, legacy data stacks will be replaced with technologies better able to unlock the IIoT's potential

While I believe that my first prediction will unfortunately hold true for those organizations that introduce IIoT applications under the same conditions proven to result in high rates of failure, I'm also quite optimistic that 2020 will actually be the year that more manufacturers and industrial businesses find their footing with data strategies more congruent with IIoT success. These businesses are coming to realize that the extreme data volumes inherent to IIoT implementations call for a new kind of digital transformation; there aren't any shortcuts.

For IIoT deployments to succeed (both quickly and over the long haul), businesses must adopt databases and data infrastructure built to handle billions of data sets arriving from device sensors, often positioned within linked factories across the globe. These 24/7 firehoses of data - representing myriad data formats - must be acquired and processed with millisecond reaction time in order to achieve the real-time analysis at the heart of the IIoT's value proposition. Therefore, appropriate data technologies must simultaneously provide the scalability, flexibility, availability, and cost efficiency required to support deployment across both dispersed geographies and local and cloud systems.

I anticipate that 2020 will witness a sharp increase in industrial enterprises that truly understand the role of data technologies as it pertains to their lofty IIoT ambitions. Expect these businesses to get their acts together from a data solution perspective, driven forward by the marked advantages of IIoT implementations and a clarified focus on how to realize them.

3) In 2020, IIoT data requirements will continue to outpace the established database industry

Just as past leaps in database technology introduced increasingly effective relational databases and then more modern NoSQL platforms, the high volume, velocity, and data variety intrinsic to IIoT data requires an entirely new category of data technologies. While this need has largely left the mainstream database industry playing catch up, newer solutions built for industrial time-series use cases (such as our own, CrateDB) expect 2020 growth to continue by combining the structure and simplicity familiar to relational databases with NoSQL's flexibility and scalability.

IIoT-ready time-series databases allow for processing any data type regardless of data structure, and can store images or geospatial data while scaling indefinitely and processing complex SQL queries in real-time. Considering that optimized time-series databases can process queries 20-30 times faster than traditional databases and reduce cloud costs by 50-75%, expect industrial enterprises pursuing IIoT implementations to accelerate their adoption of such solutions throughout 2020.


About the Author

Syed Hoda 

Syed Hoda is the Chief Commercial Officer at, which develops data management solutions for machine data and IIoT applications. Syed is based in Silicon Valley.

Published Monday, January 13, 2020 7:34 AM by David Marshall
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