In data management, the history is the future

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Curated from infoworld.com →

Two-thirds of today’s businesses have digitized, and the rest are moving in that direction. While right now this is happening in lockstep with rapid, global growth in spaces like mobile e-commerce and the internet of things (IoT), in the near future it will go beyond internet-based and -connected businesses to mean augmented reality. No longer is digital a cost of business; it isbusiness.

Yet obstacles stand in the way. Fear prevents some companies from embracing digital transformation, though a more quantifiable barrier is lack of skills. Only 15 percent of executives think their companies have the skills to complete that transformation—a percentage that hasn’t budged in two years.

How will companies compete if they can’t close the skills gap? The answer has less to do with skills than with mindset.

As reams of raw letters and numbers stream through systems literally every second, managing the onslaught of information becomes the determining factor in whether a business grows or stagnates.

Bu the mindset surrounding data management hasn’t kept pace. Digital technology has created the need for it to be sleek and agile, something that can only happen when it’s iterative. Yet too often software is developed definitively, rendering the product clunky and obtuse. This happens because of a lack of creativity and conceptualization. A solution for agile data management begins with its history.

A century before American companies were pioneering computing technology, they were revolutionizing industrial technology. Henry Ford and his production boss, Charlie Sorensen, realized that by creating a line of employees, each charged with a specific assembly task, whose parts arrived on a conveyor belt, they could reduce assembly time, increase output, and control the workflow.

They began implementing their plan in April 1913. The results were immediately apparent. Engine assembly time was cut from ten hours to less than four; chassis from 12 to six and, by the end of the year, to 2.3. The number of cars produced, which had steadily risen to nearly 69,000 by 1912, skyrocketed to more than 170,000. Company profits rose, worker wages doubled, and market prices halved.

This ingenious feat of engineering, otherwise known as “waterfall design” for its largely irreversible downward flow, kept the American economy humming through two world wars and the ensuing decades.

In the meantime, the new industry of information technology, built on advances in computing and telecommunication systems, was speeding up business practices and daily life. Mechanical tasks that had forever been completed by people—like filing and accounting—were starting to be done by machines.

The machines, “hardware,” ran on “software,” lines of code that packed tons of transmissible information onto tiny chips. In the 1970s and ’80s, the major software used by businesses was enterprise resource management (ERP), a monster that could integrate supply chain management (SCM), customer relationship management (CRM), and business intelligence (BI).

ERP was borne out of, and created to facilitate the waterfall design.

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Yves Mulkers

Yves Mulkers is the founder of 7wData and a widely followed voice in the data and AI community. He curates the 7wData and AI Beat newsletters, reaching hundreds of thousands of data and AI professionals, and writes on data strategy, analytics, AI, and the evolving data ecosystem.