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Human Extract, Transform, and Load

HETL (Human Extract, Transform, and Load)

Definition:  When an employee in the field captures data with a pen or pencil & paper, drives back to the office at the end of the workday, and manually transcribes the data into a back-end computer system.

You’re probably thinking this is an antiquated phenomenon that disappeared decades ago with the advent of mobile devices and wireless data networks.  I’m here to tell you that this productivity killer is alive and well in 2012!  Large and small companies all over the world are still wasting time, fuel, money, and accuracy of data.  They’re also misappropriating valuable resources by turning field personnel into data-entry clerks like you used to see in the 1970’s and 80’s.

Luckily, this widespread problem is easily solvable:

  1. Build a native or HTML5 mobile app that’s capable of retrieving data, capturing new data from the employee, saving the data offline, and sending that data back to HQ.
  2. Give employees working in the field a wireless mobile phone/tablet capable of running the app you’ve built.
  3. If the device has 2G/3G/4G capabilities, the data captured in the field can be sent to HQ as soon the employee is in a coverage area.
  4. If the device only has Wi-Fi, the employee can send that data on it’s way by driving to the nearest hotspot or uploading it from home.

That’s it!  Don’t make it harder than it has to be.  Yes, data at rest and data in transit has to be secured but that’s easy to do these days.  Please do your part to but an end to Human Extract, Transform, and Load and convert your organization into a real-time enterprise.

– Rob

Sharing my knowledge and helping others never stops, so connect with me on my blog at http://robtiffany.com , follow me on Twitter at https://twitter.com/RobTiffany and on LinkedIn at https://www.linkedin.com/in/robtiffany

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Rob is a writer, teacher, speaker, world traveller and undersea explorer. He's also a thought leader in the areas of enterprise mobility and the Internet of Things.

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